Intelligent techniques for fault diagnosis of pneumatic valve

Abstract

The detection and diagnosis of faults in technical plants is of great practical significance and paramount importance for the safe operation of the plant The early detection of fault can help avoid system breakdown and catastrophe involving human fatalities and material damage Usually the technical personnel are assigned the job of monitoring the plant for the safe operation They may require to monitor a number of variables to identify the abnormal conditions Since the operator cannot monitor all variables simultaneously an automated approach is needed for the real time monitoring and diagnosis of the system newlineIn process industry there is a crucial need for checking and monitoring the equipment condition precisely since they are mostly subject to hazardous environments such as severe shocks vibration heat friction dust etc The problem of detecting faults in pneumatic valve used in cooler water spray system in cement industry is strategically important because of its various implications like avoiding major plant breakdowns and catastrophes This thesis explores the application of intelligent techniques like Fuzzy logic Neural networks and Neuro fuzzy system for fault diagnosis of pneumatic valve newline