Wavelet Noise Filtering, Neural Network and Engine Fault Diagnosis
Pla Uni · Neiranji gongcheng · 2002
In this paper an experiment method, of which main purpose was to analyze the cylinder gastightness from starting voltage waveforms was discussed. The noise was filtered from typical waveforms, and 6 fault symptom parameters were put forward. The Radial Basis Function Netword (RBFN) was trained by putting these symptom parameters in. This network can distinguish the fault modes preferably; therefore it will be favourable to diagnose the cylinder compression ratio fault.