Human beings used to use their own senses and experience to monitor the condition of machinery, but they have a habit of forming labor unions, so a substitute is being sought in computer intelligence. Wang (production and quality engineering, Norwegian U. of Science and Technology), describes one approach to using advanced instrumentation to quantify the health or condition of industrial equipment, so that problems can be diagnosed early in their development and corrected by suitable maintenance, before they become serious enough to cause plant breakdown. His example is an intelligent monitoring system for a centrifugal pump system using multiple layered feed forward artificial neural networks, which effectively avoids the necessity for manually setting up accurate mathematical descriptions. Annotation ©2004 Book News, Inc., Portland, OR (booknews.com)
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Written as a result of a several-year research project using Computational Intelligence techniques for solving condition monitoring and diagnosis problems of machineries at the Norwegian University of Science and Technology, this book is about intelligent system development. In order to survive in an uncertain and complex environment, it is necessary to bring Artificial Neural Networks, Fuzzy Logic Systems, Genetic Algorithms and Expert systems together to make a condition monitoring and diagnosis system more effective, reliable, and cost effective than the traditional one. The focus of Intelligent Condition Monitoring and Diagnosis System is on practical applications of intelligent techniques. It provides practicing engineers and scientists with the information they need to solve the problems in both industry and academia.
Written as a result of a several-year research project using Computational Intelligence techniques for solving condition monitoring and diagnosis problems of machineries at the Norwegian University of Science and Technology, this book is about intelligent system development. In order to survive in an uncertain and complex environment, it is necessary to bring Artificial Neural Networks, Fuzzy Logic Systems, Genetic Algorithms and Expert systems together to make a condition monitoring and diagnosis system more effective, reliable, and cost effective than the traditional one. The focus of Intelligent Condition Monitoring and Diagnosis System is on practical applications of intelligent techniques. It provides practicing engineers and scientists with the information they need to solve the problems in both industry and academia.
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