Engine fuel-injection quantity abnormal fault diagnosis method based on information fusion

Abstract

An engine fuel-injection quantity abnormal fault diagnosis method based on information fusion mainly requires a data collecting system, a fuzzy processing system and a neural network system. The data collecting system collects and fuses air flow sensor signal waveform characteristics of an engine and storage battery voltage waveform characteristics, and the characteristics are introduced into the fuzzy processing system. The fuzzy processing system fuzzifies the characteristics and enables characteristic values to be distributed in a range of [0,1], and the data is applied to the neural network system. The neural network system is a back propagation (BP) neural network of a multi-output structure, an input layer is a fuzzified waveform characteristic value, and an output layer is diagnosed faults. The engine fuel-injection quantity abnormal fault diagnosis method has the advantages of fusing information of automobile multiple components, improving abnormal fault diagnosis accuracy of the engine fuel injection quantity through correlation among components, and providing technical assistance for automobile maintaining enterprises. The engine fuel-injection quantity abnormal fault diagnosis method can be widely applied to diagnosis of various automobile faults.

Description

Technical field: [0001] The invention is an information fusion-based fault diagnosis method for engine fuel injection abnormalities, which can diagnose engine faults by fusing multiple information of automobiles and applying neural network technology. The technical fields include automotive electronic control technology, neural network technology, fuzzy mathematics, etc. Background technique: [0002] Every sensor in the car has its own standard working waveform. When the tested waveform is different from the standard waveform, it means that the component or its related parts have failed. If the fusion technology is applied to fuse the electronic signals related to a certain fault phenomenon and take into account various signal information, the accuracy of fault diagnosis can be improved. At this stage, the research on engine fault diagnosis based on information fusion technology is relatively extensive, but because the signals fused in each study are different, and the fea...

AI Technical Summary

Problems solved by technology

The fault of abnormal fuel injection volume of the engine is a common fault of the engine. There are many factors that affect the fuel injection volume of the injector. Theref