The water-lubricated thrust bearings of the marine rim-driven thruster (RDT) are usually composed of polymer composites, which are prone to serious wear under harsh working conditions. Ultrasonic is an excellent non-destructive monitoring technology, but polymer materials are characterized by viscoelasticity, heterogeneity, and large acoustic attenuation, making it challenging to extract ultrasonic echo signals. Therefore, this paper proposes a wear monitoring method based on the amplitude spectrum of the ultrasonic reflection coefficient. The effects of bearing parameters, objective function, and algorithm parameters on the identification results are simulated and analyzed. Taking the correlation coefficient and root mean square error as the matching parameters, the thickness, sound velocity, density, and attenuation factor of the bearing are inversed simultaneously by utilizing the differential evolution algorithm (DEA), and the wear measurement system is constructed. In order to verify the identification accuracy of this method, an accelerated wear test under heavy load was executed on a multi-functional vertical water lubrication test rig with poly-ether-ether-ketone (PEEK) fixed pad and stainless-steel thrust collar as the object. The thickness of pad was measured using the high-precision spiral micrometer and ultrasonic testing system, respectively. Ultimately, the results demonstrate that the thickness identification error of this method is approximately 1%, and in-situ monitoring ability will be realized in the future, which is of great significance to the life prediction of bearings.
This study is supported by the National Key R&D Program of China (No. 2018YFE0197600), the European Union’s Horizon 2020 Research and Innovation Programme RISE under Grant Agreement No. 823759 (REMESH), and the National Natural Science Foundation of China (No. 52071244).
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