基于多窗谱分析的船舶电机轴承故障检测方法

A detection method for bearing faults of marine motors based on multi-taper technique

为解决船舶电机轴承故障检测中弱特征信号淹没在强噪声背景下难以识别的问题,提出一种基于多窗谱分析的故障检测方法.研究多窗谱分析在频率分辨率与方差间的权衡问题,确定了适用于电机轴承故障检测的最佳权衡值.以数据窗能量作为选择依据,消除了特征频率的根部泄漏,使特征频率易于识别.仿真结果表明,相比其他两种常用的频谱分析方法,多窗谱分析法在提取强噪声背景中弱特征信号方面呈现良好的性能.实验验证了多窗谱分析法的频率分辨能力以及实现电机轴承故障检测的有效性.

A multi-taper technique-based detection method for bearing faults of marine motors was developed to detect weak eigenfrequency of stator current submerged in strong noises environment. The tradeoff problem between frequency resolution and variance was studied, and the optimal tradeoff value was chosen to be applied to detect motor bearing faults. The root leakage of eigenfrequency was eliminated by selecting high energy tapers, and the shape of eigenfrequency was easy to be distinguishable. Simulation results show that the proposed method has better antinoise performance comparing with the two other methods. Tests validate the high frequency resolution and validity in detection for bearing faults of marine motors.