Abstract 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.

中文翻译：

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基于振动信号的机械故障诊断心理声学参数与状态指标的比较

摘要 建立机械诊断的方法有很多种。绝大多数利用不同的条件指标，从框架中获得的振动信号中提取信息。在这项工作中，除了使用传统技术外，还分析了心理声学指标作为检测机械故障的工具的有效性。虽然这些参数最初是为了与压力信号一起使用而开发的，但在这项工作中，它们专门应用于振动。选择并研究一组具有统计代表性的样品以确定设备的标准行为。同时，通过主观分析，根据故障类型对缺陷样品产生的噪声模式进行分类。最后，将状态指标和心理声学指标应用于振动信号，对它们进行比较，并为减速电机的质量控制建立最合适的参数。结果表明，某些指标之间存在高度相关性，两种方法都获得了相似的结果。此外，这两种技术的结合改进了诊断，成功率接近 90%。