离散余弦变换在轴承故障诊断中的应用

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针对轴承故障难以快速诊断的问题，提出了基于离散余弦变换（DCT）和Hilbert变换提取轴承损伤的特征信息新方法。首先采用离散余弦变换对时域信号进行处理获得系数，再合理选择离散余弦变换系数重构信号，用Hibert包络分析重构信号并从中提取特征频率。实际应用表明，该方法能快速、准确地检测出轴承损伤，可有效应用于轴承故障的在线监测与诊断。 Aiming at the difficulty of quick fault diagnosis for bearings, the novel method based on discrete cosine transform （ DCT） and Hilbert transform for extracting information about characteristics of bearing damage is proposed. Firstly, the DCT is used to process the time domain signals and acquire DCT coefficients; then the signals are reconstructed by selecting reasonable DCT coefficient, and the characteristic frequency is extracted from reconstructed signal by using Hilbert envelop analysis. The practical application shows that this method detects the damage of bearings quickly and properly, it can be effectively applied in online monitoring and diagnosis for beating faults.