The number of research papers dealing with vibration-based condition monitoring has been exponentially growing in recent decades. As a consequence, one may identify some trends that emerge from this vast literature. The present paper delineates a methodology that can be recognized in several research works, which is rooted in a succession of three stages. The first stage embodies a linear transform of the data, typically in the form of a filterbank, the second stage reduces the dimension of the data through a nonlinear functional, typically in the form of health indicators, and the last stage supplies a statistical decision. Although several variants of this methodology exist, its fundamental principles seem to have converged to a general consensus, at least implicitly. This paper provides a critical overview of this methodology. It discusses its working assumptions under some typical scenarios and formulates several caveats. It also provides a few prospects that may nourish future research.

近几十年来，有关基于振动的状态监测的研究论文数量呈指数增长。结果，人们可能会发现大量文献中出现的一些趋势。本文描述了一种可以在几个研究工作中得到认可的方法，该方法植根于三个阶段。第一阶段以线性滤波器组的形式体现数据的线性变换，第二阶段通过非线性函数（通常以健康指标的形式）减小数据的维数，最后阶段提供统计决策。尽管存在该方法的多种变体，但其基本原理似乎已至少在隐式上已经收敛到普遍共识。本文提供了这种方法的重要概述。它讨论了在某些典型情况下的工作假设，并提出了一些警告。它还提供了一些可能滋养未来研究的前景。