基于动态限的非周期非稳定工况故障检测模型

针对非周期非稳定工况的多变量系统在特征提取后很难进行有效的故障检测，建立了一个基于动态限的非周期非稳定工况的故障检测模型.该模型首先针对实时检测的需要，将过程数据进行分段处理，用动态限代替T2统计量给出的恒定控制限；然后对检测数据进行横移变换，产生分段横移线，通过判断分段横移线与对应动态限的关系实现故障检测.通过可行性分析，证明了该模型的合理性.实验验证结果表明：在非周期非稳定工况下，当多变量的输出突变导致T2统计量的幅值变化较大时，所建立的模型不仅能够实时准确地检测出故障，而且还能够大大减少系统的误判率和漏判率.
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Abstract：

A Fault Detection Model Based on Dynamic Limit under Non-periodic Non-steady Conditions

When the system is working under non periodic non steady conditions, the traditional straight line limit is hard to detect the faults. For these problems above, this paper presented a fault detection model based on the dynamic limit. According to the need for real time fault detection, the process data is used to segment handling. And the paper proposes the dynamic limit to substitute the straight limit line. Then slid on the test data transformation, result in sub sliding line. And then achieve fault detection by determining the sub traverse line and the dynamic limit. At last, the feasibility analysis is given to the model. The experiment results verify that the model is applicable to the fault detection under the non periodic non steady conditions even if the system’s multivariate outputs are mutated and the amplitude of Hotelling T2 changes greatly. Compared with traditional methods, the model greatly reduces the system’s leakage alarm and false alarm.