A new synthetic detection technique for trackside acoustic identification of railroad roller bearing defects

The detection of railroad roller bearing defects is of great importance for railway traffic. The acoustic defective bearing detector (ADBD) via a trackside acoustic detection system (TADS) is a popular and reliable tool for trackside identification of railroad bearing incipient defects. However, the defective trackside acoustic signal of bearing is confronted with three challenges: demodulation of acoustic signal, removal of Doppler effect and enhancement of defect frequency. This paper proposes a synthetic detection technique to overcome these difficulties successively. In the technique, the signal envelope is first extracted by a new variable-resolution ridge demodulation (VRRD) method. Then the Doppler effect is removed in the envelope via a dynamic signal resampling method. Finally, the rectified defect frequency is enhanced through the means of logarithmic transformation and piecewise linear detrending. The VRRD technique extracts the envelope from the signal time–frequency distribution (TFD) along the Doppler shift curve of resonance frequency traced by an improved ridge extraction algorithm. The resampling method is carried out on the envelope according to the Doppler shift curve of defect frequency obtained by the same ridge extraction algorithm. The sidebands around defect frequency can be suppressed by the logarithmic transformation and the low-frequency non-linear trend can be removed by the detrending method. The signal amplitude is unified at the same time. Two practical bearing signals with inner-race and outer-race defects separately verify the effectiveness of proposed technique.