'n Wasige beheerder vir 'n elektriese hooflynlokomotief
- Authors: Mors, Winfried
- Date: 2012-08-16
- Subjects: Fuzzy systems , Fuzzy logic , Automatic control , Electric locomotives
- Type: Thesis
- Identifier: uj:9497 , http://hdl.handle.net/10210/5927
- Description: M.Ing. , The principal reasons for the development of a prototype improved control system are the high maintenance costs and unreliability of Spoomet's fleet of class 6E/6E1 resistor technology electric main line locomotives. These factors may largely be attributed to two fundamental shortcomings of the existing locomotive control systems, namely the lack of inherent feedback and application of inconsequent control practices during acceleration from standstill. The improved control system features the application of a rule based fuzzy controller, implementing human skill and experience to control tractive effort of a resistor technology main line locomotive. The aim of the fuzzy controller is to accelerate the train from standstill to approximately 35 km/h, smoothly and safely. The prototype fuzzy controller was implemented with a personal computer using an advanced fuzzy logic development system. A simulation model was developed for the locomotive and the load. This model was used to first test the structure of the controller and the initial rule blocks. Following the verification of the fuzzy rules on the simulation model, a relay interface was developed to implement the operation of the control system in coupled mode with the existing control system on a locomotive. The interactive fine-tuning and evaluation of the fuzzy rules were performed during this phase of the development. The test results include the successful evaluation of the prototype fuzzy controller under a variety of typical and "worst case" operating conditions, as well as under conditions of wheel slip. The industrialisation and long term considerations for continued development of the fuzzy logic controller are described in the conclusion.
- Full Text:
- Authors: Mors, Winfried
- Date: 2012-08-16
- Subjects: Fuzzy systems , Fuzzy logic , Automatic control , Electric locomotives
- Type: Thesis
- Identifier: uj:9497 , http://hdl.handle.net/10210/5927
- Description: M.Ing. , The principal reasons for the development of a prototype improved control system are the high maintenance costs and unreliability of Spoomet's fleet of class 6E/6E1 resistor technology electric main line locomotives. These factors may largely be attributed to two fundamental shortcomings of the existing locomotive control systems, namely the lack of inherent feedback and application of inconsequent control practices during acceleration from standstill. The improved control system features the application of a rule based fuzzy controller, implementing human skill and experience to control tractive effort of a resistor technology main line locomotive. The aim of the fuzzy controller is to accelerate the train from standstill to approximately 35 km/h, smoothly and safely. The prototype fuzzy controller was implemented with a personal computer using an advanced fuzzy logic development system. A simulation model was developed for the locomotive and the load. This model was used to first test the structure of the controller and the initial rule blocks. Following the verification of the fuzzy rules on the simulation model, a relay interface was developed to implement the operation of the control system in coupled mode with the existing control system on a locomotive. The interactive fine-tuning and evaluation of the fuzzy rules were performed during this phase of the development. The test results include the successful evaluation of the prototype fuzzy controller under a variety of typical and "worst case" operating conditions, as well as under conditions of wheel slip. The industrialisation and long term considerations for continued development of the fuzzy logic controller are described in the conclusion.
- Full Text:
Adaptive fuzzy logic steering controller for a Steckel mill
- Authors: Ferreira, Arno Barry
- Date: 2009-02-26T12:19:09Z
- Subjects: Fuzzy logic , Fuzzy systems , Stainless steel industry , Neural networks (Computer science)
- Type: Thesis
- Identifier: uj:8158 , http://hdl.handle.net/10210/2164
- Description: M.Ing. , Columbus Stainless, a subsidiary of Acerinox, manufactures stainless steel in their plant located in Middelburg, South Africa. During the hot rolling operation the steel is rolled on a 4-high finishing mill where strip movement perpendicular to the rolling direction occurs. This movement is undesirable because it causes inferior product quality and may also lead to downtime if the strip moves past the edge of the rolls. In the past the operator made adjustments to the relative alignment of the rolls in the mill in an attempt to limit the sideways movement of the strip. In order to improve product quality and production throughput, the manual action of adjusting the parallelism of the rolls was replaced with an automatic steering control system. Analysis of the process revealed that several variables have an impact on the way the strip reacts to changes in the alignment of rolls in the mill. An adaptive fuzzy logic control system was designed and implemented in the real time control system of the mill. During commissioning the system did not have an adverse effect on production and all initial project criteria were met, as was stipulated in Section 1.4 of this document. The control system improved the strip movement by an average of 11% on various products rolled. Based on production data, the system potentially prevented two coils from leaving the rolls during the month long evaluation period and saved 40 minutes of production time. If the savings in material losses and the potential gain in production time are added the possible anticipated monetary saving is estimated to be about 24 million Rand a year.
- Full Text:
- Authors: Ferreira, Arno Barry
- Date: 2009-02-26T12:19:09Z
- Subjects: Fuzzy logic , Fuzzy systems , Stainless steel industry , Neural networks (Computer science)
- Type: Thesis
- Identifier: uj:8158 , http://hdl.handle.net/10210/2164
- Description: M.Ing. , Columbus Stainless, a subsidiary of Acerinox, manufactures stainless steel in their plant located in Middelburg, South Africa. During the hot rolling operation the steel is rolled on a 4-high finishing mill where strip movement perpendicular to the rolling direction occurs. This movement is undesirable because it causes inferior product quality and may also lead to downtime if the strip moves past the edge of the rolls. In the past the operator made adjustments to the relative alignment of the rolls in the mill in an attempt to limit the sideways movement of the strip. In order to improve product quality and production throughput, the manual action of adjusting the parallelism of the rolls was replaced with an automatic steering control system. Analysis of the process revealed that several variables have an impact on the way the strip reacts to changes in the alignment of rolls in the mill. An adaptive fuzzy logic control system was designed and implemented in the real time control system of the mill. During commissioning the system did not have an adverse effect on production and all initial project criteria were met, as was stipulated in Section 1.4 of this document. The control system improved the strip movement by an average of 11% on various products rolled. Based on production data, the system potentially prevented two coils from leaving the rolls during the month long evaluation period and saved 40 minutes of production time. If the savings in material losses and the potential gain in production time are added the possible anticipated monetary saving is estimated to be about 24 million Rand a year.
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An integrated systems approach to risk management within a technology driven industry using the design structure matrix and fuzzy logic
- Authors: Barkhuizen, Willem Frederik
- Date: 2012-08-01
- Subjects: Value analysis (Cost control) , Risk management , Artificial intelligence , Fuzzy logic
- Type: Thesis
- Identifier: uj:8904 , http://hdl.handle.net/10210/5376
- Description: D.Ing. , “Innovation is the act of introducing something new” (Byrd & Brown, 2003). When companies are competing on the technology “playground” they need to be innovative. By analysis according to Byrd & Brown (Byrd & Brown, 2003) the “act of introducing”, relates to risk taking, and the “new” relates to creativity, and therefore these concepts, creativity and risk taking, in combination, are what innovation is all about. Risk management has become one of the greatest challenges of the 21st century, and one of the main components in innovation and the technology driven industry, intensifying the need for a systematic approach to managing uncertainties. During the development and design of complex engineering products, the input and teamwork of multiple participants from various backgrounds are required resulting in complex interactions. Risk interactions exist between the functional and physical elements within such a system and its sub-systems in various dimensions such as spatial interaction, information interaction etc. The relationships are of a multi-dimensional complexity that cannot be simplified using the standard task management tools (Yassine A. A., 2004). To find a meaningful starting point for the seemingly boundless subject of risk management the research takes a step back into the basic definition of risk management and follows an exploratory research methodology to explore each of the risk management processes (risk assessment, risk identification, risk analysis, risk evaluation, risk treatment and risk monitoring and review) and how these processes can be enhanced using the design structure matrix (DSM) and fuzzy logic thinking. The approach to risk management within an organisation should be seen as a holistic approach similar to the total quality management process, providing the ii opportunity to incorporated risk management during the design process as a concurrent task. The risk management model is then developed concurrently (during the design phase) using product development methodologies such as conceptual modeling and prototyping, and ultimately the prototype is tested using a case study. Finally resulting in a clustered DSM providing a visual representation of the system risk areas similar to the methodology used in Finite Element Analysis (FEA). The research combines alternative system representation and analysis techniques (Warfield, 2005), in particular the design structure matrix, and fuzzy logic to quantify the risk management effort neccessary to deal with uncertain and imprecise interactions between system elements.
- Full Text:
- Authors: Barkhuizen, Willem Frederik
- Date: 2012-08-01
- Subjects: Value analysis (Cost control) , Risk management , Artificial intelligence , Fuzzy logic
- Type: Thesis
- Identifier: uj:8904 , http://hdl.handle.net/10210/5376
- Description: D.Ing. , “Innovation is the act of introducing something new” (Byrd & Brown, 2003). When companies are competing on the technology “playground” they need to be innovative. By analysis according to Byrd & Brown (Byrd & Brown, 2003) the “act of introducing”, relates to risk taking, and the “new” relates to creativity, and therefore these concepts, creativity and risk taking, in combination, are what innovation is all about. Risk management has become one of the greatest challenges of the 21st century, and one of the main components in innovation and the technology driven industry, intensifying the need for a systematic approach to managing uncertainties. During the development and design of complex engineering products, the input and teamwork of multiple participants from various backgrounds are required resulting in complex interactions. Risk interactions exist between the functional and physical elements within such a system and its sub-systems in various dimensions such as spatial interaction, information interaction etc. The relationships are of a multi-dimensional complexity that cannot be simplified using the standard task management tools (Yassine A. A., 2004). To find a meaningful starting point for the seemingly boundless subject of risk management the research takes a step back into the basic definition of risk management and follows an exploratory research methodology to explore each of the risk management processes (risk assessment, risk identification, risk analysis, risk evaluation, risk treatment and risk monitoring and review) and how these processes can be enhanced using the design structure matrix (DSM) and fuzzy logic thinking. The approach to risk management within an organisation should be seen as a holistic approach similar to the total quality management process, providing the ii opportunity to incorporated risk management during the design process as a concurrent task. The risk management model is then developed concurrently (during the design phase) using product development methodologies such as conceptual modeling and prototyping, and ultimately the prototype is tested using a case study. Finally resulting in a clustered DSM providing a visual representation of the system risk areas similar to the methodology used in Finite Element Analysis (FEA). The research combines alternative system representation and analysis techniques (Warfield, 2005), in particular the design structure matrix, and fuzzy logic to quantify the risk management effort neccessary to deal with uncertain and imprecise interactions between system elements.
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Condition based maintenance monitoring of gear box using fuzzy logic systems
- Mushiri, Tawanda, Mbohwa, Charles
- Authors: Mushiri, Tawanda , Mbohwa, Charles
- Date: 2014
- Subjects: Fuzzy logic , Krones machinery , Condition based maintenance , Gearboxes
- Type: Article
- Identifier: http://ujcontent.uj.ac.za8080/10210/372086 , uj:4983 , http://hdl.handle.net/10210/13115
- Description: The purpose of this research was to come up with an intelligent monitoring tool to reduce the number of breakdowns of a beverage company bottle washer. The Fuzzy Logic system was derived among other artificial intelligent systems to be best appropriate to solve the breakdown challenges of the bottle washer. A gearbox is always jamming and it’s not easy to troubleshoot the breakdown cause and fuzzy logic is a tool that was used for monitoring. The researchers carried out a company audit, interviews and administered questionnaires in order to gather relevant data. The results were used in intelligent condition-based-maintenance modelling to solve the problem using fuzzy logic system and it was found that oil level should be always above 40% otherwise the gearbox will be made to stop. Torque is supposed to have a range of values accepted from 0-8 000Nm beyond that we consider the stoppage of the gearbox.
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- Authors: Mushiri, Tawanda , Mbohwa, Charles
- Date: 2014
- Subjects: Fuzzy logic , Krones machinery , Condition based maintenance , Gearboxes
- Type: Article
- Identifier: http://ujcontent.uj.ac.za8080/10210/372086 , uj:4983 , http://hdl.handle.net/10210/13115
- Description: The purpose of this research was to come up with an intelligent monitoring tool to reduce the number of breakdowns of a beverage company bottle washer. The Fuzzy Logic system was derived among other artificial intelligent systems to be best appropriate to solve the breakdown challenges of the bottle washer. A gearbox is always jamming and it’s not easy to troubleshoot the breakdown cause and fuzzy logic is a tool that was used for monitoring. The researchers carried out a company audit, interviews and administered questionnaires in order to gather relevant data. The results were used in intelligent condition-based-maintenance modelling to solve the problem using fuzzy logic system and it was found that oil level should be always above 40% otherwise the gearbox will be made to stop. Torque is supposed to have a range of values accepted from 0-8 000Nm beyond that we consider the stoppage of the gearbox.
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Design of a fuzzy logic control system for monitoring gearbox jamming in a bottle washer machine
- Mushiri, Tawanda, Mbohwa, Charles
- Authors: Mushiri, Tawanda , Mbohwa, Charles
- Date: 2015-03-03
- Subjects: Fuzzy logic , Gearbox jamming
- Type: Article
- Identifier: uj:5154 , http://hdl.handle.net/10210/14286
- Description: The purpose of this research was to come up with an intelligent monitoring tool to reduce the number of breakdowns of a beverage company bottle washer. The Fuzzy Logic system was derived among other artificial intelligent systems to be best appropriate to solve the breakdown challenges of the bottle washer. A gearbox is always jamming and it is not easy to troubleshoot the breakdown cause and fuzzy logic is a tool that was used for monitoring. The researchers carried out a company audit, interviews and administered questionnaires in order to gather relevant data. The results were used in intelligent condition-based-maintenance modelling to solve the problem using fuzzy logic system and it was found that oil level should be always above 40% otherwise the gearbox will be made to stop. Torque is supposed to have a range of values accepted from 0-8 000Nm beyond that we consider the stoppage of the gearbox. Very higher torques above 10000Nm damages the machinery.
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- Authors: Mushiri, Tawanda , Mbohwa, Charles
- Date: 2015-03-03
- Subjects: Fuzzy logic , Gearbox jamming
- Type: Article
- Identifier: uj:5154 , http://hdl.handle.net/10210/14286
- Description: The purpose of this research was to come up with an intelligent monitoring tool to reduce the number of breakdowns of a beverage company bottle washer. The Fuzzy Logic system was derived among other artificial intelligent systems to be best appropriate to solve the breakdown challenges of the bottle washer. A gearbox is always jamming and it is not easy to troubleshoot the breakdown cause and fuzzy logic is a tool that was used for monitoring. The researchers carried out a company audit, interviews and administered questionnaires in order to gather relevant data. The results were used in intelligent condition-based-maintenance modelling to solve the problem using fuzzy logic system and it was found that oil level should be always above 40% otherwise the gearbox will be made to stop. Torque is supposed to have a range of values accepted from 0-8 000Nm beyond that we consider the stoppage of the gearbox. Very higher torques above 10000Nm damages the machinery.
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Designing of an intelligent fuzzy logic system for accretion prevention in Sponge iron SL/RN rotary KILN based 100TPD DRI process
- Garikayi, T., Nyanga, L., Mushiri, T., Mhlanga, S., Kuipa, P.K.
- Authors: Garikayi, T. , Nyanga, L. , Mushiri, T. , Mhlanga, S. , Kuipa, P.K.
- Date: 2013
- Subjects: Sponge iron , Fuzzy logic , Kiln shell temperatures
- Type: Article
- Identifier: uj:4971 , http://hdl.handle.net/10210/13072
- Description: Sponge iron is an intermediate product of steel formed during direct reduction of iron ore with aid of regulated temperatures and pressures within a rotary kiln. The greatest challenge is the direct measurement of kiln shell temperatures due to the catastrophic accumulation of sintered particles of solid bed which form rings at places along the length of the kiln thus hindering material flow. The accretion reduces productivity, damage kiln lining and reduces the production period as well as reduction in product quality. This process requires a controller which will be able to control with imprecise and partial data input; and be able to achieve the desired product quality under dynamic process conditions thus a Fuzzy Controller was used for the proposed design. The main goal of the research was to predict the rate of accretion build up within the kiln and minimize it with aid of a Fuzzy Control System cascaded to an already existing Programmable Logic Controller. A 16.2% build up rate was achieved as compared to the most appreciated 27% thus nearly a 10% decrease, a result which can improve the campaign period by approximately 48 hours which will be a 200 tons of sponge iron.
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- Authors: Garikayi, T. , Nyanga, L. , Mushiri, T. , Mhlanga, S. , Kuipa, P.K.
- Date: 2013
- Subjects: Sponge iron , Fuzzy logic , Kiln shell temperatures
- Type: Article
- Identifier: uj:4971 , http://hdl.handle.net/10210/13072
- Description: Sponge iron is an intermediate product of steel formed during direct reduction of iron ore with aid of regulated temperatures and pressures within a rotary kiln. The greatest challenge is the direct measurement of kiln shell temperatures due to the catastrophic accumulation of sintered particles of solid bed which form rings at places along the length of the kiln thus hindering material flow. The accretion reduces productivity, damage kiln lining and reduces the production period as well as reduction in product quality. This process requires a controller which will be able to control with imprecise and partial data input; and be able to achieve the desired product quality under dynamic process conditions thus a Fuzzy Controller was used for the proposed design. The main goal of the research was to predict the rate of accretion build up within the kiln and minimize it with aid of a Fuzzy Control System cascaded to an already existing Programmable Logic Controller. A 16.2% build up rate was achieved as compared to the most appreciated 27% thus nearly a 10% decrease, a result which can improve the campaign period by approximately 48 hours which will be a 200 tons of sponge iron.
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Development of an intelligent electronic load controller for stand-alone micro-hydropower systems
- Authors: Nel, Guilliam Johannes
- Date: 2019
- Subjects: Small scale hydropower , Small power production facilities , Induction generators , Interconnected electric utility systems - Automation , Fuzzy logic , Electronic load controllers
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/293715 , uj:31943
- Description: M.Phil. (Electrical Engineering) , Abstract: People living in rural and remote areas of Sub-Saharan Africa generally lack access to electricity due to their geographical location and the costs associated with connecting these areas to the national electrical grid. A viable technology to supply electricity to some of these areas are stand-alone micro-hydropower systems which harnesses energy from flowing water. Self-excited induction generators (SEIGs) are commonly used for the generation of electricity in stand-alone micro-hydropower systems. The electricity supplied by a SEIG to the demand side i.e. the load needs to be maintained stable under various consumer load conditions. This can be accomplished with the use of an Electronic Load Controller (ELC). This dissertation presents the design and development of an intelligent ELC that can maintain a stable voltage on the demand side of a 3-phase SEIG supplying varying single-phase consumer loads. The intelligent ELC consist of an uncontrolled bridge rectifier, filtering capacitor, chopper switch (IGBT), voltage sensor, current sensor, optocoupler, Arduino microcontrollers and a ballast load or storage, depending on site-specific requirements and economic viability. A fuzzy logic control method is implemented to maintain stable and reliable voltage supply. Hardware-inthe- loop simulations were carried out under various consumer load conditions using MATLAB/SIMULINK to analyse and test the efficiency of the system in real-time. Laboratory experiments were carried out and it was found that the Intelligent Electronic Load Controller was able to respond quickly and efficiently to changes in the consumer load to maintain the voltage on the demand side of the three-phase self-excited induction generator very stable and close to the set point voltage value. The intelligent ELC will contribute towards providing reliable and cost-effective means of enhancing the proliferation of micro-hydropower particularly in rural and remote applications in Sub-Saharan Africa.
- Full Text:
- Authors: Nel, Guilliam Johannes
- Date: 2019
- Subjects: Small scale hydropower , Small power production facilities , Induction generators , Interconnected electric utility systems - Automation , Fuzzy logic , Electronic load controllers
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/293715 , uj:31943
- Description: M.Phil. (Electrical Engineering) , Abstract: People living in rural and remote areas of Sub-Saharan Africa generally lack access to electricity due to their geographical location and the costs associated with connecting these areas to the national electrical grid. A viable technology to supply electricity to some of these areas are stand-alone micro-hydropower systems which harnesses energy from flowing water. Self-excited induction generators (SEIGs) are commonly used for the generation of electricity in stand-alone micro-hydropower systems. The electricity supplied by a SEIG to the demand side i.e. the load needs to be maintained stable under various consumer load conditions. This can be accomplished with the use of an Electronic Load Controller (ELC). This dissertation presents the design and development of an intelligent ELC that can maintain a stable voltage on the demand side of a 3-phase SEIG supplying varying single-phase consumer loads. The intelligent ELC consist of an uncontrolled bridge rectifier, filtering capacitor, chopper switch (IGBT), voltage sensor, current sensor, optocoupler, Arduino microcontrollers and a ballast load or storage, depending on site-specific requirements and economic viability. A fuzzy logic control method is implemented to maintain stable and reliable voltage supply. Hardware-inthe- loop simulations were carried out under various consumer load conditions using MATLAB/SIMULINK to analyse and test the efficiency of the system in real-time. Laboratory experiments were carried out and it was found that the Intelligent Electronic Load Controller was able to respond quickly and efficiently to changes in the consumer load to maintain the voltage on the demand side of the three-phase self-excited induction generator very stable and close to the set point voltage value. The intelligent ELC will contribute towards providing reliable and cost-effective means of enhancing the proliferation of micro-hydropower particularly in rural and remote applications in Sub-Saharan Africa.
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Development of an intelligent electronic load controller for stand-alone micro-hydropower systems
- Nel, Guilliam Johannes, Doorsamy, Wesley
- Authors: Nel, Guilliam Johannes , Doorsamy, Wesley
- Date: 2018
- Subjects: Electronic load controllers , Fuzzy logic , Small scale hydropower , Induction generators , Small scale power production facilities , Interconnected electric utility systems - Automation
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/276284 , uj:29561 , Citation: Nel, G. & Doorsamy, W. 2018. Development of an intelligent electronic load controller for stand-alone micro-hydropower systems.
- Description: Abstract: People living in rural and remote areas of Sub- Saharan Africa generally lack access to electricity due to their geographical location and the costs associated with connecting these areas to the national electrical grid. A viable technology to supply electricity to some of these areas are stand-alone microhydropower systems which harnesses energy from flowing water. Self-excited induction generators (SEIGs) are commonly used for the generation of electricity in stand-alone micro-hydropower systems. The electricity supplied by a SEIG to the demand side i.e. the load needs to be maintained stable under various consumer load conditions. This is accomplished through the use of an electronic load controller (ELC). This paper presents the design and development of an intelligent ELC that is able to maintain stable voltage on the demand side of a 3-phase SEIG supplying varying single-phase consumer loads. The proposed intelligent ELC consists of an uncontrolled bridge rectifier, filtering capacitor, chopper switch, voltage sensor, optocoupler, Arduino microcontroller and a ballast load or storage, depending on site-specific requirements and economic viability. The fuzzy logic control method is implemented to maintain stable and reliable voltage. The ELC is designed and simulated under various consumer load conditions in Matlab/Simulink. Simulation results of the ELC model are verified experimentally in a laboratory setting. The proposed intelligent ELC will contribute towards providing reliable and cost-effective means of enhancing the proliferation of micro-hydropower particularly in rural and remote applications in Sub-Saharan Africa.
- Full Text:
- Authors: Nel, Guilliam Johannes , Doorsamy, Wesley
- Date: 2018
- Subjects: Electronic load controllers , Fuzzy logic , Small scale hydropower , Induction generators , Small scale power production facilities , Interconnected electric utility systems - Automation
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/276284 , uj:29561 , Citation: Nel, G. & Doorsamy, W. 2018. Development of an intelligent electronic load controller for stand-alone micro-hydropower systems.
- Description: Abstract: People living in rural and remote areas of Sub- Saharan Africa generally lack access to electricity due to their geographical location and the costs associated with connecting these areas to the national electrical grid. A viable technology to supply electricity to some of these areas are stand-alone microhydropower systems which harnesses energy from flowing water. Self-excited induction generators (SEIGs) are commonly used for the generation of electricity in stand-alone micro-hydropower systems. The electricity supplied by a SEIG to the demand side i.e. the load needs to be maintained stable under various consumer load conditions. This is accomplished through the use of an electronic load controller (ELC). This paper presents the design and development of an intelligent ELC that is able to maintain stable voltage on the demand side of a 3-phase SEIG supplying varying single-phase consumer loads. The proposed intelligent ELC consists of an uncontrolled bridge rectifier, filtering capacitor, chopper switch, voltage sensor, optocoupler, Arduino microcontroller and a ballast load or storage, depending on site-specific requirements and economic viability. The fuzzy logic control method is implemented to maintain stable and reliable voltage. The ELC is designed and simulated under various consumer load conditions in Matlab/Simulink. Simulation results of the ELC model are verified experimentally in a laboratory setting. The proposed intelligent ELC will contribute towards providing reliable and cost-effective means of enhancing the proliferation of micro-hydropower particularly in rural and remote applications in Sub-Saharan Africa.
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Fuzzy logic and condition-based maintenance approaches to machine failure analysis
- Authors: Mushiri, Tawanda
- Date: 2017
- Subjects: Fuzzy logic , Fuzzy systems - Industrial applications , System failures (Engineering) , Reliability (Engineering)
- Language: English
- Type: Doctoral (Thesis)
- Identifier: http://hdl.handle.net/10210/243068 , uj:25088
- Description: D.Ing. (Engineering Management) , Abstract: When the complexity of the controller plant is a non-linear system, the production process cannot be fulfilled by the control effect and it is not easy to manipulate the parameters on Proportional-Integral-Derivative Controller. The major objective under study is simulating and modelling machinery then come up with a suitable intelligent Condition Based Maintenance system (i.e to develop a suitable intelligent system using fuzzy logic and artificial intelligence). The area under study of Fuzzy Logic came as a concern of nonlinear systems which fail to give correct information since machines use conventional Proportional-Integral-Derivative and hence this is for linear systems. Considering vibrations and continuous failure of machines, this will cause incorrect data portraying. Three companies were done in this thesis and all were analysed using fuzzy logic and some finite element analysis of components to monitor the parameters. Root cause analysis was also done to determine what was failing on different equipments. Three companies in a developing country were used as case studies for testing fuzzy logic approaches and models to machinery failure analysis. The three companies are designated as follows: Beverages Production Company, Hydro Power Generating Company and Water Distributing Company. The overall effectiveness of the companies were heavily affected due to many breakdowns. The main problem was found to be resulting from failure to monitor nonlinear systems that naturally exist in such environments. On the bottle washer at Beverages Production Company, fuzzy logic with Model Reference Adaptive Control to prevent failure on the bottle washer and introduce an intelligent Condition Based Maintenance program was done, a solution to come up with a control system that monitors water in the dam as well as protecting the equipment from failure and do stability control of machinery for Water Distributing Company as well as apply the concept of Maintenance Free Operating Period reliability metric to determine maintenance intervals as opposed to Mean Time Between Failure to the Hydro-Power Generation Company and also do a Simulink control on the governor. The results of the simulation of the control strategy of Fuzzy Logic Proportional-Integral-Derivative Controller have much preferred performance as compared to the general Proportional-Integral-Derivative Controller. This was done in the Simulink/Matlab simulation environment. The innovations behind this thesis at Beverages Production Company, the pneumatic valve of the bottle washer which controls the discharge of clean bottles was occasionally sticking or failing resulting in significant loss of production in the plant since all the other processes which follow depend on the bottle washer. The main causes of failure were caused by poor control of temperature and pressure. Excessive moisture and abrasive particles also caused failures. In order to solve this problem a Model Reference Adaptive Fuzzy Controller was designed for the pneumatic valve using the Matlab software. The error resulting from the difference between the actual system output and that of the reference model was executed by the Fuzzy Logic Controller. At company Hydro-Power Generation Company, the administering system of a 150 Megawatts Francis Turbine was developed using fuzzy logic. The representative framework parameters were mirrored with the real information accessible in the power plant. At Water Distributing Company the problem of corroding gates and failure was solved using solid works, Matlab, Programmable Logic Controller and Simulink. The sluice gate valve was controlled and done stability by Matlab to avoid failure. After fuzzy logic is applied in each and every company under study, the breakdowns will be less and machinery can be diagnosed and prognosis is easy to foresee the failures. A new gate was designed by the researcher. The research has shown that fuzzy logic being intelligent, machinery can last longer and production is high. The limitations are that although it is good in monitoring but in some machinery and companies may not work well because of environment like in the water gates. It is also expensive to implement and difficult to convince management to do the research for a start.
- Full Text:
- Authors: Mushiri, Tawanda
- Date: 2017
- Subjects: Fuzzy logic , Fuzzy systems - Industrial applications , System failures (Engineering) , Reliability (Engineering)
- Language: English
- Type: Doctoral (Thesis)
- Identifier: http://hdl.handle.net/10210/243068 , uj:25088
- Description: D.Ing. (Engineering Management) , Abstract: When the complexity of the controller plant is a non-linear system, the production process cannot be fulfilled by the control effect and it is not easy to manipulate the parameters on Proportional-Integral-Derivative Controller. The major objective under study is simulating and modelling machinery then come up with a suitable intelligent Condition Based Maintenance system (i.e to develop a suitable intelligent system using fuzzy logic and artificial intelligence). The area under study of Fuzzy Logic came as a concern of nonlinear systems which fail to give correct information since machines use conventional Proportional-Integral-Derivative and hence this is for linear systems. Considering vibrations and continuous failure of machines, this will cause incorrect data portraying. Three companies were done in this thesis and all were analysed using fuzzy logic and some finite element analysis of components to monitor the parameters. Root cause analysis was also done to determine what was failing on different equipments. Three companies in a developing country were used as case studies for testing fuzzy logic approaches and models to machinery failure analysis. The three companies are designated as follows: Beverages Production Company, Hydro Power Generating Company and Water Distributing Company. The overall effectiveness of the companies were heavily affected due to many breakdowns. The main problem was found to be resulting from failure to monitor nonlinear systems that naturally exist in such environments. On the bottle washer at Beverages Production Company, fuzzy logic with Model Reference Adaptive Control to prevent failure on the bottle washer and introduce an intelligent Condition Based Maintenance program was done, a solution to come up with a control system that monitors water in the dam as well as protecting the equipment from failure and do stability control of machinery for Water Distributing Company as well as apply the concept of Maintenance Free Operating Period reliability metric to determine maintenance intervals as opposed to Mean Time Between Failure to the Hydro-Power Generation Company and also do a Simulink control on the governor. The results of the simulation of the control strategy of Fuzzy Logic Proportional-Integral-Derivative Controller have much preferred performance as compared to the general Proportional-Integral-Derivative Controller. This was done in the Simulink/Matlab simulation environment. The innovations behind this thesis at Beverages Production Company, the pneumatic valve of the bottle washer which controls the discharge of clean bottles was occasionally sticking or failing resulting in significant loss of production in the plant since all the other processes which follow depend on the bottle washer. The main causes of failure were caused by poor control of temperature and pressure. Excessive moisture and abrasive particles also caused failures. In order to solve this problem a Model Reference Adaptive Fuzzy Controller was designed for the pneumatic valve using the Matlab software. The error resulting from the difference between the actual system output and that of the reference model was executed by the Fuzzy Logic Controller. At company Hydro-Power Generation Company, the administering system of a 150 Megawatts Francis Turbine was developed using fuzzy logic. The representative framework parameters were mirrored with the real information accessible in the power plant. At Water Distributing Company the problem of corroding gates and failure was solved using solid works, Matlab, Programmable Logic Controller and Simulink. The sluice gate valve was controlled and done stability by Matlab to avoid failure. After fuzzy logic is applied in each and every company under study, the breakdowns will be less and machinery can be diagnosed and prognosis is easy to foresee the failures. A new gate was designed by the researcher. The research has shown that fuzzy logic being intelligent, machinery can last longer and production is high. The limitations are that although it is good in monitoring but in some machinery and companies may not work well because of environment like in the water gates. It is also expensive to implement and difficult to convince management to do the research for a start.
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Fuzzy logic modelling and management strategy for packet-switched networks
- Authors: Scheffer, Marten F.
- Date: 2012-09-11
- Subjects: Fuzzy logic , Fuzzy systems , Packet switching (Data transmission) , Asynchronous transfer mode , Traffic flow - Simulation methods , Traffic engineering - Simulation methods
- Type: Thesis
- Identifier: uj:9959 , http://hdl.handle.net/10210/7355
- Description: D.Ing. , Conventional traffic models used for the analysis of packet-switched data are Markovian in nature and are based on assumptions, such as Poissonian arrivals. The introduction of packet oriented networks has resulted in an influx of information highlighting numerous discrepancies from these assumptions. Several studies have shown that traffic patterns from diverse packet-switched networks and services exhibit the presence of properties such as self-similarity, long-range dependencies, slowly decaying variances, "heavy tailed" or power law distributions, and fractal structures. Heavy Tailed distributions decay slower than predicted by conventional exponential assumptions and lead to significant underestimation of network traffic variables. Furthermore, it was shown that the statistical multiplexing of multiple packet-switched sources do not give rise to a more homogenous aggregate, but that properties such as burstiness are conserved. The results of the above mentioned studies have shown that none of the commonly used traffic models and assumptions are able to completely capture the bursty behaviour of packet- and cellbased networks. Artificial Intelligent methods provide the capability to extract the inherent characteristics of a system and include soft decision-making approaches such as Fuzzy Logic. Adaptive methods such as Fuzzy Logic Self-learning algorithms have the potential to solve some of the most pressing problems of traffic Modelling and Management in modern packet-switched networks. This dissertation is concerned with providing alternative solutions to the mentioned problems, in the following three sub-sections; the Description of Heavy Tailed Arrival Distributions, Timeseries Forecasting of bursty Traffic Intensities, and Management related Soft Decision-Making. Although several alternative methods, such as Kalman Filters, Bayesian Distributions, Fractal Analysis and Neural Networks are considered, the main emphasis of this work is on Fuzzy Logic applications.
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- Authors: Scheffer, Marten F.
- Date: 2012-09-11
- Subjects: Fuzzy logic , Fuzzy systems , Packet switching (Data transmission) , Asynchronous transfer mode , Traffic flow - Simulation methods , Traffic engineering - Simulation methods
- Type: Thesis
- Identifier: uj:9959 , http://hdl.handle.net/10210/7355
- Description: D.Ing. , Conventional traffic models used for the analysis of packet-switched data are Markovian in nature and are based on assumptions, such as Poissonian arrivals. The introduction of packet oriented networks has resulted in an influx of information highlighting numerous discrepancies from these assumptions. Several studies have shown that traffic patterns from diverse packet-switched networks and services exhibit the presence of properties such as self-similarity, long-range dependencies, slowly decaying variances, "heavy tailed" or power law distributions, and fractal structures. Heavy Tailed distributions decay slower than predicted by conventional exponential assumptions and lead to significant underestimation of network traffic variables. Furthermore, it was shown that the statistical multiplexing of multiple packet-switched sources do not give rise to a more homogenous aggregate, but that properties such as burstiness are conserved. The results of the above mentioned studies have shown that none of the commonly used traffic models and assumptions are able to completely capture the bursty behaviour of packet- and cellbased networks. Artificial Intelligent methods provide the capability to extract the inherent characteristics of a system and include soft decision-making approaches such as Fuzzy Logic. Adaptive methods such as Fuzzy Logic Self-learning algorithms have the potential to solve some of the most pressing problems of traffic Modelling and Management in modern packet-switched networks. This dissertation is concerned with providing alternative solutions to the mentioned problems, in the following three sub-sections; the Description of Heavy Tailed Arrival Distributions, Timeseries Forecasting of bursty Traffic Intensities, and Management related Soft Decision-Making. Although several alternative methods, such as Kalman Filters, Bayesian Distributions, Fractal Analysis and Neural Networks are considered, the main emphasis of this work is on Fuzzy Logic applications.
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Measuring water utility efficiency using fuzzy logic
- Eldidy, Nezar Abdelfattah Mohamed
- Authors: Eldidy, Nezar Abdelfattah Mohamed
- Date: 2012-11-06
- Subjects: Fuzzy logic , Water utilities - Evaluation , Fuzzy systems , Water quality measurement , Water quality management
- Type: Thesis
- Identifier: uj:7361 , http://hdl.handle.net/10210/8117
- Description: D.Ing. , Measuring the efficiency of water utilities has been a constant challenge to various stakeholders in the water sector. There are several factors that influence the efficiency of utilities. The following study examines the different factors and establishes a model to quantify the efficiency of water utilities using limited number of variables. It utilises Fuzzy Logic to develop the measurement model. The developed method can also be used to configure a new water utility for efficiency. In addition, the research highlights some possible imperfections in the water policies that can result in an inherent inefficiency of a water utility. The developed model can assist in setting ceiling levels for utility's water assets and labour, to ensure efficiency. The model is generic and can be applied to any country or community, and can be used to configure water utilities for the poor. The Model utilised "Matlab Fuzzy Tool Box student version 2009a" software as a tool to develop the Fuzzy Inference Engine for Utility Efficiency. The study is a contribution to the domain of knowledge of water engineering science.
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- Authors: Eldidy, Nezar Abdelfattah Mohamed
- Date: 2012-11-06
- Subjects: Fuzzy logic , Water utilities - Evaluation , Fuzzy systems , Water quality measurement , Water quality management
- Type: Thesis
- Identifier: uj:7361 , http://hdl.handle.net/10210/8117
- Description: D.Ing. , Measuring the efficiency of water utilities has been a constant challenge to various stakeholders in the water sector. There are several factors that influence the efficiency of utilities. The following study examines the different factors and establishes a model to quantify the efficiency of water utilities using limited number of variables. It utilises Fuzzy Logic to develop the measurement model. The developed method can also be used to configure a new water utility for efficiency. In addition, the research highlights some possible imperfections in the water policies that can result in an inherent inefficiency of a water utility. The developed model can assist in setting ceiling levels for utility's water assets and labour, to ensure efficiency. The model is generic and can be applied to any country or community, and can be used to configure water utilities for the poor. The Model utilised "Matlab Fuzzy Tool Box student version 2009a" software as a tool to develop the Fuzzy Inference Engine for Utility Efficiency. The study is a contribution to the domain of knowledge of water engineering science.
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Production planning and control of a master churn mixer for the manufacture of margarine using fuzzy logic at an oil company in Zimbabwe
- Nyemba, Wilson R., Mushiri, Tawanda, Mugwindiri, Kumbi, Mushonga, Roy, Mbohwa, Charles
- Authors: Nyemba, Wilson R. , Mushiri, Tawanda , Mugwindiri, Kumbi , Mushonga, Roy , Mbohwa, Charles
- Date: 2018
- Subjects: Fuzzy logic , Master churn mixer , Production planning and control
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/270488 , uj:28751 , Citation: Nyemba, W.R. 2018. Production planning and control of a master churn mixer for the manufacture of margarine using fuzzy logic at an oil company in Zimbabwe. 2017 ACRID European Alliance for Innovation (EAI) Conference. DOI 10.4108/eai.20-6-2017.2270631 , ISBN: 9781631901607
- Description: Abstract: Process and chemical companies have to continually monitor and control their mixing equipment to ensure that production matches requirements and meets recommended standards especially in food processing. The oil company in this research faced challenges in meeting required specifications in some of their batches, prompting the need to look at more efficient ways to control and monitor the master churn mixer. This paper looks at how intelligent fuzzy logic was used to automate the production planning and control of the master churn mixer of the margarine plant. MATLAB 7.12 was used in developing the control algorithm that enabled all the inputs to be monitored closely before they entered the master churn, while maintaining vegetable oil at 80%, water at 20% and operating temperature at 38oC. This was enabled by sensors and programmable logic controllers which monitored all parameters using fuzzy logic to produce margarine of acceptable quality and standards.
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- Authors: Nyemba, Wilson R. , Mushiri, Tawanda , Mugwindiri, Kumbi , Mushonga, Roy , Mbohwa, Charles
- Date: 2018
- Subjects: Fuzzy logic , Master churn mixer , Production planning and control
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/270488 , uj:28751 , Citation: Nyemba, W.R. 2018. Production planning and control of a master churn mixer for the manufacture of margarine using fuzzy logic at an oil company in Zimbabwe. 2017 ACRID European Alliance for Innovation (EAI) Conference. DOI 10.4108/eai.20-6-2017.2270631 , ISBN: 9781631901607
- Description: Abstract: Process and chemical companies have to continually monitor and control their mixing equipment to ensure that production matches requirements and meets recommended standards especially in food processing. The oil company in this research faced challenges in meeting required specifications in some of their batches, prompting the need to look at more efficient ways to control and monitor the master churn mixer. This paper looks at how intelligent fuzzy logic was used to automate the production planning and control of the master churn mixer of the margarine plant. MATLAB 7.12 was used in developing the control algorithm that enabled all the inputs to be monitored closely before they entered the master churn, while maintaining vegetable oil at 80%, water at 20% and operating temperature at 38oC. This was enabled by sensors and programmable logic controllers which monitored all parameters using fuzzy logic to produce margarine of acceptable quality and standards.
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The application of artificial intelligence within information security.
- Authors: De Ru, Willem Gerhardus
- Date: 2012-08-17
- Subjects: Artificial intelligence , Computer security , Fuzzy logic , Information resources management , Electronic data processing departments - Security measures
- Type: Thesis
- Identifier: uj:2641 , http://hdl.handle.net/10210/6087
- Description: D.Phil. , Computer-based information systems will probably always have to contend with security issues. Much research have already gone into the field of information security. These research results have yielded some very sophisticated and effective security mechanisms and procedures. However, due to the ever increasing sophistication of criminals, combined with the ever changing and evolving information technology environment, some limitations still exist within the field of information security. Recent years have seen the proliferation of products embracing so-called artificial intelligence technologies. These products are in fields as diverse as engineering, business and medicine. The successes achieved in these fields pose the question whether artificial intelligence has a role to play within the field of information security. This thesis discusses limitations within information security and proposes ways in which artificial intelligence can be effectively applied to address these limitations. Specifically, the fields of authentication and risk analysis are identified as research fields where artificial intelligence has much to offer. These fields are explored in the context of their limitations and ways in which artificial intelligence can be applied to address these limitations. This thesis identifies two mainstream approaches in the attainment of artificial intelligence. These mainstream approaches are referred to as the "traditional" approach and the "non-traditional" approach. The traditional approach is based on symbolic processing, as opposed to the non-traditional approach, which is based on an abstraction of human reasoning. A representative technology from each of these mainstream approaches is selected to research their applicability within information security. Actual working prototypes of artificial intelligence techniques were developed to substantiate the results obtained in this research.
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- Authors: De Ru, Willem Gerhardus
- Date: 2012-08-17
- Subjects: Artificial intelligence , Computer security , Fuzzy logic , Information resources management , Electronic data processing departments - Security measures
- Type: Thesis
- Identifier: uj:2641 , http://hdl.handle.net/10210/6087
- Description: D.Phil. , Computer-based information systems will probably always have to contend with security issues. Much research have already gone into the field of information security. These research results have yielded some very sophisticated and effective security mechanisms and procedures. However, due to the ever increasing sophistication of criminals, combined with the ever changing and evolving information technology environment, some limitations still exist within the field of information security. Recent years have seen the proliferation of products embracing so-called artificial intelligence technologies. These products are in fields as diverse as engineering, business and medicine. The successes achieved in these fields pose the question whether artificial intelligence has a role to play within the field of information security. This thesis discusses limitations within information security and proposes ways in which artificial intelligence can be effectively applied to address these limitations. Specifically, the fields of authentication and risk analysis are identified as research fields where artificial intelligence has much to offer. These fields are explored in the context of their limitations and ways in which artificial intelligence can be applied to address these limitations. This thesis identifies two mainstream approaches in the attainment of artificial intelligence. These mainstream approaches are referred to as the "traditional" approach and the "non-traditional" approach. The traditional approach is based on symbolic processing, as opposed to the non-traditional approach, which is based on an abstraction of human reasoning. A representative technology from each of these mainstream approaches is selected to research their applicability within information security. Actual working prototypes of artificial intelligence techniques were developed to substantiate the results obtained in this research.
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The development of a multi-input-single-output fuzzy logic greenhouse controller
- Authors: Schepers, Gideon Gustaf
- Date: 2012-09-10
- Subjects: Feedback control systems , Control systems , Fuzzy systems , Fuzzy logic
- Type: Thesis
- Identifier: uj:9872 , http://hdl.handle.net/10210/7272
- Description: M.Ing. , Fuzzy controllers are increasingly being accepted by engineers and scientists alike as a viable alternative for classical controllers. The processes involved in fuzzy controllers closely imitate human control processes. Human responses to stimuli are not governed by transfer functions and neither are those from fuzzy controllers. The fuzzy approach is of course not the answer to all problems, but it can clearly be very successful, and can also be helpful to anyone involved in developing control systems. This study however is devoted to the environmental control task within greenhouses and the fuzzy approach is proposed in order to fulfil this task. To create near optimal conditions within a greenhouse for plant growth two environmental factors are proposed to be controlled namely the temperature and relative humidity. These factors are interdependent and they make the environmental control within a greenhouse a multi-variable control problem. Furthermore, the non-linear physical phenomena governing the dynamics of temperature and relative humidity in such a process makes it very difficult to model and to control using traditional techniques. Thus, it can be said that the environmental control in greenhouses is an art, that only expert growers bring to near perfection. The central theme of this study is the development of a multi-input-single-output heuristic rule-based fuzzy logic control algorithm, for environmental control within a greenhouse. This study is intended to improve existing environmental control systems by implementing this control technique. The control algorithm is tested in an experimental greenhouse and the results obtained indicate that fuzzy logic control is viable for environmental control within greenhouses.
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- Authors: Schepers, Gideon Gustaf
- Date: 2012-09-10
- Subjects: Feedback control systems , Control systems , Fuzzy systems , Fuzzy logic
- Type: Thesis
- Identifier: uj:9872 , http://hdl.handle.net/10210/7272
- Description: M.Ing. , Fuzzy controllers are increasingly being accepted by engineers and scientists alike as a viable alternative for classical controllers. The processes involved in fuzzy controllers closely imitate human control processes. Human responses to stimuli are not governed by transfer functions and neither are those from fuzzy controllers. The fuzzy approach is of course not the answer to all problems, but it can clearly be very successful, and can also be helpful to anyone involved in developing control systems. This study however is devoted to the environmental control task within greenhouses and the fuzzy approach is proposed in order to fulfil this task. To create near optimal conditions within a greenhouse for plant growth two environmental factors are proposed to be controlled namely the temperature and relative humidity. These factors are interdependent and they make the environmental control within a greenhouse a multi-variable control problem. Furthermore, the non-linear physical phenomena governing the dynamics of temperature and relative humidity in such a process makes it very difficult to model and to control using traditional techniques. Thus, it can be said that the environmental control in greenhouses is an art, that only expert growers bring to near perfection. The central theme of this study is the development of a multi-input-single-output heuristic rule-based fuzzy logic control algorithm, for environmental control within a greenhouse. This study is intended to improve existing environmental control systems by implementing this control technique. The control algorithm is tested in an experimental greenhouse and the results obtained indicate that fuzzy logic control is viable for environmental control within greenhouses.
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The quantification of information security risk using fuzzy logic and Monte Carlo simulation.
- Authors: Vorster, Anita
- Date: 2008-06-04T11:27:02Z
- Subjects: Risk assessment , Monte Carlo method , Fuzzy logic , Computer security , Information technology risk assessment
- Type: Thesis
- Identifier: uj:8851 , http://hdl.handle.net/10210/527
- Description: The quantification of information security risks is currently highly subjective. Values for information such as impact and probability, which are estimated during risk analysis, are mostly estimated by people or experts internal or external to the organization. Because the estimation of these values is done by people, all with different backgrounds and personalities, the values are exposed to subjectivity. The chance of any two people estimating the same value for risk analysis information is rare. There will always be a degree of uncertainty and imprecision in the values estimated. It is therefore during the data-gathering phase of risk analysis that the problem of subjectivity lies. To address the problem of subjectivity, techniques that mathematically deal with and present uncertainty and imprecision are used to estimate values for probability and impact. During this research a model for the objective estimation of probability was developed. The model uses mostly input values that are entirely objective, but also a small number of subjective input values. It is in these subjective input values that fuzzy logic and Monte Carlo simulation come into play. Fuzzy logic takes a qualitative subjective value and gives it an objective value, and Monte Carlo simulation complements fuzzy logic by giving a cumulative distribution function to the uncertain, imprecise input variable. In this way subjectivity is dealt with and the result of the model is a probability value that is estimated objectively. The same model that was used for the objective estimation of probability was used to estimate impact objectively. The end result of the research is the combination of the models to use the objective impact and probability values in a formula that calculates risk. The risk factors are then calculated objectively. A prototype was developed as proof that the process of objective information security risk quantification can be implemented in practice. , Prof. L. Labuschagne
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- Authors: Vorster, Anita
- Date: 2008-06-04T11:27:02Z
- Subjects: Risk assessment , Monte Carlo method , Fuzzy logic , Computer security , Information technology risk assessment
- Type: Thesis
- Identifier: uj:8851 , http://hdl.handle.net/10210/527
- Description: The quantification of information security risks is currently highly subjective. Values for information such as impact and probability, which are estimated during risk analysis, are mostly estimated by people or experts internal or external to the organization. Because the estimation of these values is done by people, all with different backgrounds and personalities, the values are exposed to subjectivity. The chance of any two people estimating the same value for risk analysis information is rare. There will always be a degree of uncertainty and imprecision in the values estimated. It is therefore during the data-gathering phase of risk analysis that the problem of subjectivity lies. To address the problem of subjectivity, techniques that mathematically deal with and present uncertainty and imprecision are used to estimate values for probability and impact. During this research a model for the objective estimation of probability was developed. The model uses mostly input values that are entirely objective, but also a small number of subjective input values. It is in these subjective input values that fuzzy logic and Monte Carlo simulation come into play. Fuzzy logic takes a qualitative subjective value and gives it an objective value, and Monte Carlo simulation complements fuzzy logic by giving a cumulative distribution function to the uncertain, imprecise input variable. In this way subjectivity is dealt with and the result of the model is a probability value that is estimated objectively. The same model that was used for the objective estimation of probability was used to estimate impact objectively. The end result of the research is the combination of the models to use the objective impact and probability values in a formula that calculates risk. The risk factors are then calculated objectively. A prototype was developed as proof that the process of objective information security risk quantification can be implemented in practice. , Prof. L. Labuschagne
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Vibration based condition monitoring of rotating machinery using fuzzy logic
- Mushiri, Tawanda, Mbohwa, Charles
- Authors: Mushiri, Tawanda , Mbohwa, Charles
- Date: 2016
- Subjects: Fuzzy logic , Machinery - Vibration
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/217259 , uj:21618 , Citation: Mushiri, T. & Mbohwa, C. 2016. Vibration based condition monitoring of rotating machinery using fuzzy logic. Proceedings of the World Congress on Engineering and Computer Science 2016, Vol. II, WCECS October 19-21 2016, San Francisco, USA , ISBN: 978-988-14048-2-4 , ISSN:2078-0958(Print) , 2078-0966(Online)
- Description: Abstract: Monitoring machinery with an eye or sound is a thing of the past, with the emergency of Next Generation Manufacturing Systems (NGMS) like fuzzy logic is making life easier in automation. By the second if a fault occurs on machinery it can be noticed there and there and rectified. In this case the rotation of machinery in vibrations was explained and done using fuzzy logic.
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- Authors: Mushiri, Tawanda , Mbohwa, Charles
- Date: 2016
- Subjects: Fuzzy logic , Machinery - Vibration
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/217259 , uj:21618 , Citation: Mushiri, T. & Mbohwa, C. 2016. Vibration based condition monitoring of rotating machinery using fuzzy logic. Proceedings of the World Congress on Engineering and Computer Science 2016, Vol. II, WCECS October 19-21 2016, San Francisco, USA , ISBN: 978-988-14048-2-4 , ISSN:2078-0958(Print) , 2078-0966(Online)
- Description: Abstract: Monitoring machinery with an eye or sound is a thing of the past, with the emergency of Next Generation Manufacturing Systems (NGMS) like fuzzy logic is making life easier in automation. By the second if a fault occurs on machinery it can be noticed there and there and rectified. In this case the rotation of machinery in vibrations was explained and done using fuzzy logic.
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