Tacholess Order Tracking Based on Surrogate Data Test for Bearing Diagnosis under Varying Speed Conditions

Abstract For bearing fault diagnosis, vibration analysis is one of the most primary methods in engineering practice. Many traditional methods are ineffective in engineering applications with variable operating conditions. Tacholess envelope order analysis (TLEOA) technology shows promising application prospects for bearing fault diagnosis in conditions where speed varies, since it does not require additional speed measurement equipment to obtain phase information. Nevertheless, the widespread application of this method requires optimizing the instantaneous phase (IP) extraction algorithm of the reference shaft (RS) under the condition of no rotational speed first, including the requirement for prior knowledge to determine harmonic order and the starting point for ridge tracking, artificial initialization of certain important parameters, and inaccurate phase estimation. To address these issues, this article proposes an adaptive TLEOA approach based on surrogate data test. This approach can adaptively and accurately extract IP of RS from vibratory signal without the requirement for manual parameter initialization. Based on IP of RS, the initial vibratory signal is resampled with equal angular increments to convert it from the time domain to the angular domain, overcoming the adverse impact of variable speed on diagnosis. Finally, resonance demodulation is performed on the resampled signal, and envelope order analysis is performed on the demodulated signal to achieve fault identification. Experimental results demonstrate that the adaptively estimated IP using this approach closely aligns with measurements obtained by the tachometer, and the accuracy of fault diagnosis is superior to many existing methods. It provides a better diagnostic approach in various industrial settings.