Fault Detection for Nonlinear Systems

Tormod Fretheim, R. Shoureshi, T. Vincent
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Abstract

A new fault detection and isolation scheme has been developed to enable automatic detection of faulty conditions in linear or non-linear systems. The focus of this paper is on the development of a general, and feasible method for nonlinear system fault detection which can be easily implemented on input/output models. The method proposed here is different in that the neural network is used to model the process dynamics, while a dead-beat observer is implemented by solving a set of coupled nonlinear equations. This enables the introduction of constraints into the problem that can improve the power of the fault detection techniques.
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非线性系统的故障检测
提出了一种新的故障检测和隔离方案,可以自动检测线性或非线性系统中的故障条件。本文的重点是开发一种通用的、可行的非线性系统故障检测方法,该方法可以很容易地在输入/输出模型上实现。该方法的不同之处在于采用神经网络对过程动力学进行建模,而通过求解一组耦合非线性方程来实现死拍观测器。这允许在问题中引入约束,从而提高故障检测技术的能力。
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