基于高阶累积量的柴油发动机曲轴轴承故障特征提取

利用基于高阶累积量降维处理的1.5维谱、2.5维谱分析曲轴轴承不同磨损间隙下的发动机振动信号，提取曲轴轴承磨损故障的特征参数，有效地解决了高阶累积量计算量巨大，难以实现在线应用的缺点。试验时将振动加速度传感器放置在发动机缸体的5个不同的位置测取振动信号并分析，提取高阶谱降维处理后的特定频段内的频带能量作为特征值。结果表明，本文提出的方法能够有效地抑制噪声的干扰，提取出的特征参数能够较好地反映曲轴轴承的技术状态，且当发动机转速达1300r/min以上，振动加速度传感器置于油底壳与缸体接缝处的左右两侧时，采集的振动信号最能反映曲轴轴承的技术状况。

Extracting fault features of a Diesel engine's crankshaft bearing based on high-order cumulation

Since the method of high order cumulation could not be used on-line because of longer computing time required,a new method using 1.5-,2.5-dimension spectrum was proposed to analyze vibration signals caused by different crankshaft bearing clearances and extract fault features of a crankshaft bearing.This new method helds high order cumulation's features in suppressing noise and extracting nonliner coupling characters.When vibration signals were acquired,a vibrant sensor was fitted in 4 different positions an...