基于支持向量机的汽车发动机故障诊断研究

研究在汽车发动机不解体的情况下获取发动机缸盖表面的振动信号和上止点信号，按曲轴转角的周期对振动信号的时域能量进行合理分段；提取各段信号的时域能量作为发动机各缸状态的特征值。建立发动机各缸不同故障状态的训练集，用支持向量机的方法实现发动机故障模式的诊断与识别。研究结果表明，该方法对汽车发动机故障类型、故障位置的诊断识别具有重要工程意义。

Study on fault diagnosis of car engine Based on Support Vector Machine

The research is to obtain the vibration signals and BDC signal of cylinder head surface without disassembling the engine, then section on vibration signal in the time domain energy reasonablely according to crankshaft rotation cycle, and extract the signal in the time domain energy as the engine state characteristic value. We establish the training set of engine under different engine fault states, and use support vector machine method for engine fault diagnosis and recognition. The results show that the method has an important significance on diagnosis of engine fault type and fault location.