A comparison between psychoacoustic parameters and condition indicators for machinery fault diagnosis using vibration signals

There are many methods capable of establishing the diagnosis of machinery. The vast majority make use of different condition indicators, extracting information from the vibration signals obtained in the frame. During this work, in addition to using traditional techniques, it was analysed the validity of psychoacoustic metrics as a tool for detecting mechanical failures. Although these parameters were originally developed to be used with pressure signals, in this work they were applied exclusively to vibrations. A statistically representative group of samples was selected and studied in order to determine the standard behaviour of the device. At the same time, the noise patterns generated by defective samples were catalogued according to the type of failure by means of a subjective analysis. Finally, condition indicators and psychoacoustic metrics were applied to vibration signals, carrying out a comparison between them and establishing the most appropriate parameters for the quality control of gearmotors. The results revealed a high correlation between some indicators and similar outcomes were obtained for both methods. Additionally, the combination of the two techniques provided an improvement of the diagnosis, obtaining near 90% of success. (C) 2020 Elsevier Ltd. All rights reserved.