A condition-based maintenance (CBM) has been widely employed to reduce maintenance cost by predicting the health status of many complex systems in prognostics and health management (PHM) framework. Recently, multivariate control charts used in statistical process control (SPC) have been actively introduced as monitoring technology. In this paper, we propose a condition monitoring scheme to monitor the health status of the system of interest. In our condition monitoring scheme, we first define reference data set using one-class support vector machine (OC-SVM) to construct the control limit of multivariate control charts in phase I. Then, parametric control chart or non-parametric control chart is selected according to the results from multivariate normality tests. The proposed condition monitoring scheme is applied to sensor data of two anemometers to evaluate the performance of fault detection power.

通过预测和健康管理（PHM）框架中的许多复杂系统的健康状况，基于状态的维护（CBM）已被广泛用于降低维护成本。近来，用于统计过程控制（SPC）的多元控制图已被积极地引入作为监视技术。在本文中，我们提出了一种状态监视方案来监视目标系统的健康状况。在状态监测方案中，我们首先使用一类支持向量机（OC-SVM）定义参考数据集，以构造第一阶段的多元控制图的控制极限。然后，选择参数控制图或非参数控制图根据多元正态性检验的结果。