基于时频图像极坐标增强的柴油机故障诊断

针对柴油机不同部位的机械故障特征容易混淆且呈现非平稳循环特征的特点,提出了一种基于时频图像极坐标增强的柴油机故障诊断方法。将振动信号Gabor变换的时频特征通过等角度采样映射为极坐标图上某一区域的显著增强的特征,实现了周期瞬态特征的增强。提取不同技术状态振动信号6个工作循环内的极坐标图上区域能量特征作为故障特征参数,输入支持向量机进行分类训练和模式识别。试验结果表明,针对柴油机的5种典型故障,该方法能显著增强故障特征,有效提取故障特征信息,准确识别出不同类型的磨损故障。

Diesel Engine Fault Diagnosis Based on Polar Coordinate Enhancement of Time-Frequency Diagram

The mechanical faults at different parts of a diesel engine are characterized by confusion and nonstationary cycling. A fault diagnose method based on polar coordinate enhancement of time-frequency diagram is proposed. The Gabor transform is applied to achieve the time-frequency feature of the vibration signals; then, the time-frequency features are re-sampled at constant angular inter val and transformed to the polar coordinate as enhanced feature of certain areas. Thus, the periodic transient features are enhanced. Polar diagram areas energy of 6 rotation cycle of different diesel engine status is extracted as the fault feature, which is used to train support vector machine (SVM) for the pattern recognition. Experimental result shows that this method highlights the features of five typical engine faults, extracts the fault feature information, and distinguishes different types of wear fault.