基于自适应奇异值标准谱和EMD的柴油机故障诊断

针对柴油机多发故障,提出了自适应奇异值标准谱和经验模态分解(Empirical Mode Decomposition,EMD)相结合的故障诊断模型。通过计算平均最近邻域发散度和奇异值标准谱的方法自适应地选择奇异值分解的嵌入维数和重构阶数,提高了奇异值分解降噪的精度。对降噪后的信号进行EMD分解,并利用调整余弦相似度标准提取反映信号真实特征的主固有模态函数(Intrinsic Mode Function,IMF),进而提取故障特征参数。将此模型应用于F3L912柴油机进气门漏气、单缸失火和多缸失火等故障的诊断,通过提取峭度和过零率作为故障特征,获得了较高的故障分类准确率。

Diesel Engine Fault Diagnosis Based on Adaptive Singular Value Standard Spectrum and Empirical Mode Decomposition

For the multiple faults of diesel engine ,fault diagnosis model consisted of adaptive singular value standard spectrum and empirical mode decomposition (EMD) was proposed .The average divergence of neighboring area and singular value stand‐ard spectrum were calculated to determine the embedding dimension and reconstruction order adaptively and hence the precision of noise reduction with the singular value decomposition improved .EMD of signal was conducted after the noise reduction ,the main intrinsic mode function (IMF) with the real characteristic was extracted according to the adjusted cosine similarity stand‐ard and the fault characteristic parameters were extracted .With the model ,diesel engine faults including inlet valve leakage , single cylinder misfire and multiple cylinder misfire of F3L912 were diagnosed .Kurtosis and zero crossing rate were extracted as the fault characteristic parameters and the classification accuracy improved .