A study on BSR diagnosis of power seat frame based on STRE-VK method

To establish an efficient method for the buzz-squeak-rattle (BSR) noise diagnosis of faulty power seat frame on the noisy production line, the S-transform ridgeline extraction & Vold-Kalman filtering (STRE-VK) method was proposed for the purpose of revealing the time-frequency characteristics of vibration signals of the power seat frame. The extraction of ridgelines from the time-frequency distribution was achieved through the utilization of adaptive generalized S-transform, and the separation of multiple harmonic components was accomplished by the Vold-Kalman filtering algorithm. The simulation analysis results demonstrated that the STRE-VK method performed better in terms of extracting ridgelines and segregating harmonic components. Then, the STRE-VK method was employed to the online BSR diagnosis of faulty power seat frames, and the prominence ratio of critical bands inspired by ECMA-74 was further calculated as a metric to identify different BSR noise types based on the separated vibration components. The results showed that the rapid online BSR diagnosis of power seat frame can be achieved accurately.