Characteristic Optimization and Diesel Engine Fault Diagnosis Based on Rough Set
Ye Yang · Vehicle Engine · 2010
To improve the efficiency of fault diagnosis,a fault diagnosis system based on rough set was put forward.For a high-power diesel engine,the fault characteristics were extracted with the time-frequency analysis and wavelet packet energy spectrum analysis method.By comparison and analysis,it was decided that the latter extracted characteristics,which had better sensitivity and stability,were optimized with rough set.Finally,the fault modes were categorized with neural network.The results show that the characteristics extracted by wavelet packet energy spectrum method have better sensitivity and stability.With rough set,the characteristic attributes are simplified,which reduces the input nodes of neural network.Accordingly,the accuracy of fault classification improves.