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Improved Approach to KDI-Based Fault Detection for Non-linear Black-box Systems

机译:用于非线性黑盒系统的基于KDI的故障检测方法

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This paper is concerned with an application study of model-based fault detection method to a ship propulsion system which is the object system for benchmark test of fault diagnosis. When modeling the object, Quasi-ARMAX model with multi-model form is used. In this model, the system non-linearity is incorporated into model parameters by using non-linear non-parametric models (NNMs). Kullback discrimination Information (KDI) is introduced as fault detection index to evaluate the distortion in identified model, which is caused by a fault. Although the fundamental effectiveness of the method has been verified through simulation studies, there have been still remained problems as to the detection performance. In this paper, some improvement schemes to solve these problems are proposed together with simulation results for various fault modes.
机译:本文涉及基于模型的故障检测方法对船舶推进系统的应用研究,这是故障诊断基准测试的对象系统。在建模对象时,使用具有多模型形式的准ARMAX模型。在该模型中,通过使用非线性非参数模型(NNMS)将系统非线性结合到模型参数中。 Kullback判别信息(KDI)被引入为故障检测索引以评估所识别的模型中的失真,这是由故障引起的。尽管通过模拟研究已经验证了该方法的基本效果,但仍然存在对检测性能的问题。在本文中,提出了解决这些问题的一些改进方案,以及各种故障模式的仿真结果。

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