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.