Abstract: The vibration signals of the bearings of coal mine machanical equipment under the working conditions of strong impact and heavy load show strong transient non-stationary and local nonlinear features. It is difficult to identify the fault features by the classical time-domain statistical analysis method and the global domain transformation method. The traditional order tracking method has the problems of inconvenient equipment installation and difficulty in obtaining instantaneous frequency. The traditional keyless phase order tracking method estimates the instantaneous frequency with low precision under the condition of severe speed fluctuation. This leads to poor fault identification effect. To solve these problems, a new method of bearing fault diagnosis based on harmonic matching compensation and keyless phase order tracking is proposed. Firstly, the time-frequency analysis method based on harmonic matching compensation is used to process the bearing vibration signal and estimate the instantaneous frequency accurately. Secondly, the Vold-Kalman filtering method is used to adaptively extract the harmonic component signal. Thirdly, the Hilbert transform is used to calculate the instantaneous phase of the harmonic. The mapping relationship between the time domain and angle domain is obtained, so as to complete the resampling of the original time domain signal in the angle domain. Finally, the resampled signals are processed by fast Fourier transform (FFT). The fault features of the bearing are identified by analyzing the envelope order spectrum. The simulation and experimental results show that the maximum relative error between the estimated instantaneous frequency and the actual value is less than 1%. The feature order of bearing fault is accurate and obvious, which can effectively diagnose the bearing fault.