This paper presents a MATLAB-based tutorial to conduct fault diagnosis of a rolling element bearing. While there have been so many new developments in this field, no studies have addressed the tutorial aspects in this field to help the engineers learn the concept and implement by their own effort. The three most common techniques—the autoregressive model, spectral kurtosis, and envelope analysis—are selected to demonstrate the bearing diagnosis process. Simulation signal is introduced to help understand the characteristics of fault signal and carry out the process toward the fault identification. The techniques are then applied to the two real datasets to demonstrate the practical applications, one made by the authors and the other by the Case Western Reserve University, which is known as a standard reference in testing the diagnostic algorithms.

中文翻译：

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诊断101：使用MATLAB中的包络分析进行滚动轴承故障诊断的教程

本文介绍了基于MATLAB的教程，以进行滚动轴承的故障诊断。尽管在该领域有许多新的发展，但是还没有研究解决该领域的教程方面的问题，以帮助工程师们自己学习和实践该概念。选择了三种最常用的技术（自回归模型，光谱峰度和包络分析）来演示轴承诊断过程。引入仿真信号可以帮助理解故障信号的特性，并进行故障识别过程。然后将这些技术应用于两个真实的数据集以演示实际应用，其中一个由作者提出，另一个由Case Western Reserve University提出，后者被称为测试诊断算法的标准参考。