Study On Fault Diagnostic Of Equipments Based On Extension Theory

With the development of science and technology on production, the fault diagnosis has becomean important part of the repair and maintenance of machinery products. When the Equipmentbreakdown, the lose of production and people’s life is difficult to estimate. The traditional faultdiagnosis method can not meet the increasingly complex equipments’ normal running and theintelligent fault diagnosis technology has become the new fault diagnosis hot spots. Conditionmonitoring is an important part of the fault diagnosis. It can increases the reliability, safety andeffectiveness of the machine running. Due to the lack of condition monitoring and health analysis ofthe equipments in the daily operations, serious Accident happened and it caused the incorrect resultsof fault diagnosis.This paper is about the fault prediction and diagnosis using extension theory. It described theresearch of fault diagnostic technology abroad and pointed out the existing problems. For theextension theory has the characteristics of formal, logical and mathematical, it provides a method todeal with problems qualitatively and quantitatively. We propose a method of condition monitoring andfault prediction based on extension theory. The method established a matter element mode to give theformal description on the state of the equipment. It used the dependent function to do thequalitative and quantitative analysis of the equipments state. Through the method, we can change themodel of maintenance which is always done after fault occurred. We use the method on the exampleof turbines to prove the feasibility and effectiveness of it. In order to prevent the occurrence of majoraccidents, we use the method which connects the extension theory with the grey system. It can makefault diagnosis more precise and do a good job in monitoring to keep the machine running well. TheMonitoring data is Formal described by the principle of extension to set up a matter element for theresearch. Then we build up a new method with gray correlation analysis and finally use the exampleof the aircraft engine to prove the feasibility and effectiveness of the method. Based on the abovetheoretical research, we designed a mechanical fault diagnosis system and realized the computer-aideddesign of mechanical fault diagnosis.