Fault diagnosis of particle filter nonlinear systems based on adaptive threshold
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摘要: 针对实际非线性系统传统方法难以实现可靠故障诊断的问题,采用粒子滤波算法,利用对数似然函数和作为评价指标,并借助自适应阈值的设计,研究了非线性非高斯系统的故障检测和故障隔离。阈值的选取,是准确判别系统是否发生故障的标准,本文通过分析非线性系统残差的统计特性,在判定残差统计特性成正态分布的基础上,设计了一种基于粒子滤波故障诊断的自适应阈值方法,减少了故障诊断的漏报和误报。通过非恒温连续搅拌水箱式反应堆的仿真实例,验证了该方法在故障诊断中的准确性和有效性。Abstract: In view of the problem of actual nonlinear system that the traditional method is difficult to obtain reliable fault diagnosis, this paper uses the particle filter method and applies the logarithm likelihood function as evaluation index to study the nonlinear non-Gaussian system fault detection and fault isolation with the aid of adaptive threshold design. The selection of threshold value is the criterion for accurately judging system failure. This paper analyzes the statistical properties of residual error, determines the residual error statistical property of normal distribution, and designs an adaptive threshold method based on particle filter fault diagnosis, which reduce the miss alarm and false alarm ratios of fault diagnosis. Through the simulation example of non-constant temperature continuous stirred tank reactor, the accuracy and feasibility of this method in fault diagnosis are verified.
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Key words:
- adaptive threshold /
- particle filter /
- fault diagnosis /
- false alarm ratio /
- miss alarm ratio /
- normal distribution /
- nonlinear system
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