Optimal detection filters can greatly enhance fault detection performance, but designing these filters requires fault data which is difficult to obtain in practice. This paper proposes a scheme that automatically determines the optimal detection filter from a filter bank online without using fault data. The method can improve fault detection rate and accelerate detection speed. In order to reduce the false alarm rate, a method of threshold setting is introduced based on kernel density estimation. Implementation issues concerning filter bank design and online decision rule are also discussed. The method is validated in a numerical example and Tennessee Eastman process, and its performance is compared to those of other state-of-the-art methods.

最优检测滤波器可以大大提高故障检测性能，但设计这些滤波器需要的故障数据在实践中很难获得。本文提出了一种无需使用故障数据即可在线从滤波器组中自动确定最佳检测滤波器的方案。该方法可以提高故障检测率，加快检测速度。为了降低误报率，引入了一种基于核密度估计的阈值设置方法。还讨论了有关滤波器组设计和在线决策规则的实施问题。该方法在数值示例和田纳西伊士曼过程中得到验证，并将其性能与其他最先进的方法进行比较。