Resampling method of computed order tracking based on time-frequency scaling property of fourier transform

Order tracking technique is an effective frequency analysis method, which uses multiples of the running speed as the frequency base (orders) and commonly used in rotating machinery vibration signal analysis. It is a dedicated non-stationary vibration processing technique to detect speed-related vibrations. Angular sampling theory based computed order tracking (COT) method is the most widely used method of order tracking. It samples the vibration at a constant rate, and then uses software to resample the sampled data at constant angle increments. Previous research indicates that the computed order components obtained through COT method are not precise, and the program is of high computation complexity. To make COT more accurate and efficient, this paper presents an improved resampling method for COT, which is inspired by time-frequency scaling property of Fourier Transform (FT). A stretching transformation is used to stretch the sampled data on time domain by rotating speed before the resampling process, and the product of the stretching transformation is proved to be non-constant samples of order domain. Simulated results demonstrate the improvements of the proposed method on order tracking accuracy and a lower computation complexity, especially for signals with high order components. At last, a turbocharger quality inspection system is designed, in which the presented method is used to analyze vibrations generated by the turbocharger running under a controlled running-up condition. The testing result indicates that the proposed method works well on extracting harmonic vibrations from the sampled data.