强噪声背景下的柴油机失火故障诊断

柴油机失火是常见的故障模式,传统的诊断方法不仅参数获取困难且准确性差。针对此问题,以3缸四冲程柴油机为研究对象,设计了柴油机失火故障的预置试验,采集排气噪声和缸盖振动信号进行故障诊断研究。为提取强噪声背景下的微弱信号,采用二次采样随机共振系统提取柴油机故障特征频率完成柴油机的失火故障诊断。研究结果表明,通过二次采样处理,随机共振系统可以将噪声能量转移到柴油机微弱特征信号上,达到大参数条件下微弱信号特征提取的目的,能有效识别柴油机的早期故障,对其他复杂机械的振动诊断同样具有参考价值。

Misfire Fault Diagnosis of Diesel Engine in Strong Noise Background

Misfire is a common fault mode of diesel engine,but the traditional fault diagnosis methods are difficult to acquire parameters and diagnose poorly.With respect to these problems,the misfire fault preset experiment of diesel engine was conducted to collect the exhaust noise and cylinder head vibration signal for fault diagnosis on a 3-cylinder 4-stroke diesel engine.In order to extract the weak signal in strong noise background,the double sampling stochastic resonance method was used to extract the fault feature frequency of diesel engine to diagnose the misfire fault.The study results show that noise energy can transfer to the weak signal feature of diesel engine by double sampling stochastic resonance system so as to realize the extracting of weak signal feature under large parameter.Accordingly,the early fault of diesel engine is detected effectively and the method is also useful for complex machinery vibration diagnosis.