基于信号预处理和Hilbert变换的滚动轴承故障诊断

针对滚动轴承振动信号复杂和非平稳的特点,及故障信号常常淹没于各种噪声的情况,先利用消除趋势项和小波降噪对包含故障信息的信号进行预处理,再应用Hilbert变换对信号进行包络解调和频谱分析,提取滚动轴承故障特征频率,并判断其故障模式.对滚动轴承内圈、外圈和滚动体故障的诊断试验,证明了信号预处理和希尔伯特(Hilbert)变换相结合的方法对滚动轴承内圈和外圈局部损伤故障的诊断是有效的和可行的,但不能很好地检验出轴承滚动体的故障特征

Fault Diagnosis of Rolling Bearings Based on Signal Preprocessing and Hilbert Transform

According to the facts that rolling bearing vibration signal is complex and unstable, and fault Signal is often submerged in various kinds of noise, measures for eliminating the trend term and wavelet de-noising are used to preprocess the signals with fault information, then Hilbert transform is applied to envelope demodula- tion and spectrum analysis. Thus fault characteristic frequencies of rolling bearings are extracted, and the mode of the bearing fault is decided. The diagnostic tests of the faulted inner ring, faulted outer ring and faulted roll- ing element of rolling bearings prove that the combination of signal preprocessing and Hilbert transform is effec- tive and feasible to the partial damage fault diagnosis of the inner ring and outer ring of rolling bearings, but not effective to fault diagnosis of the bearing rollerst.