This paper proposes a new machine learning method for fault detection using a reduced kernel partial least squares (RKPLS), in static and online forms, for handling nonlinear dynamic systems. The choice of the fault detection method has a vital role to improve efficiency and safety as well as production. The kernel partial least squares is a nonlinear extension of partial least squares. The present method has been mostly used as a monitoring method for nonlinear processes. Thus, the standard method cannot perform properly and quickly when the training data set is large. The main contributions of the suggested approach are: the approximation of the components retained by the standard method and the reduction in the computation time as well as the false alarm rate. Using the reduced principal, the online suggested method is presented for fault detection of nonlinear dynamic processes. The online reduced method is developed to monitor the dynamic process online and update the reduced reference model. For this reason, the moving window RKPLS is proposed. The general principle is to check if the new useful observation satisfies, in the feature space, the condition of independencies between variables. Thereafter, the relevance of the suggested methods is used to monitor the chemical stirred tank reactor benchmark process, the air quality and the tennessee eastman process. The simulation results of the suggested methods are compared to the standard one.

本文提出了一种新的机器学习方法，以静态和在线形式使用减少的核偏最小二乘（RKPLS）进行故障检测，以处理非线性动态系统。故障检测方法的选择对于提高效率和安全性以及生产具有至关重要的作用。核偏最小二乘法是偏最小二乘的非线性扩展。本方法已经主要用作非线性过程的监测方法。因此，当训练数据集很大时，标准方法无法正确快速地执行。所建议的方法的主要贡献是：标准方法保留的分量近似，并且减少了计算时间以及误报率。使用简化后的本金，提出了在线建议的非线性动态过程故障检测方法。开发了在线简化方法以在线监视动态过程并更新简化的参考模型。因此，提出了移动窗RKPLS。一般原则是检查新的有用观测值是否在特征空间中满足变量之间独立性的条件。此后，将所建议方法的相关性用于监测化学搅拌釜反应器基准过程，空气质量和田纳西伊士曼过程。所建议方法的仿真结果与标准方法进行了比较。提出了移动窗口RKPLS。一般原则是检查新的有用观察在特征空间中是否满足变量之间独立性的条件。此后，将所建议方法的相关性用于监测化学搅拌釜反应器基准过程，空气质量和田纳西伊士曼过程。所建议方法的仿真结果与标准方法进行了比较。提出了移动窗口RKPLS。一般原则是检查新的有用观察在特征空间中是否满足变量之间独立性的条件。此后，将所建议方法的相关性用于监测化学搅拌釜反应器基准过程，空气质量和田纳西伊士曼过程。所建议方法的仿真结果与标准方法进行了比较。