Median line-gram and its application in the fault diagnosis of rolling bearing

Abstract

Abstract The level selection of frequency band division structure relies on prior information in most gram approaches that capture the optimal demodulation frequency band (ODFB). When an improper level is specified in these approaches, the fault characteristic information contained in the produced ODFB may be insufficient. This study proposes a unique approach, termed median line-gram, to tackle the level selection problem. To divide the frequency domain signal into a series of demodulation frequency bands, a spectrum median-line segmentation model based on Akima interpolation is first created. The level and boundary of the segmentation model can be adaptively identified by this means. Second, the acquired frequency bands are quantized using the negative entropy index, and the ODFB is defined as the frequency band with the largest value. Third, the envelope spectrum is used to determine the ODFB characteristic frequency to pinpoint the bearing fault location. Finally, both simulation and experimental signal analysis are used to demonstrate the efficiency of the suggested method. Furthermore, the proposed method extracts more defect feature information from the ODFB than existing methods.