动态观测下随机离散事件系统模式故障安全诊断方法

    A Safe Diagnosis Method of Pattern Faults of Stochastic Discrete-event Systems Under Dynamic Observations

    • 摘要: 在许多实际应用中,故障往往不是由单一的故障事件引起,而是由于特定事件相继发生(即模式故障)导致的。基于模式故障的安全诊断方法能诊断出引发故障的事件串,但原有系统的静态观测由于可观测事件集和不可观测事件集是预先定义且固定的,对于复杂系统而言,可能无法全面捕捉到系统故障,导致故障诊断的遗漏,为此,提出基于动态观测的随机离散事件系统中模式故障安全诊断方法。首先,给出了动态观测下随机离散事件系统S型和T型模式故障安全可诊断形式化描述;接着,构造了非法语言识别器和安全诊断器,对发生的模式故障进行安全诊断;最后,提出了随机离散事件系统 S 型和 T 型模式故障安全可诊断性的充分必要条件,并通过实例验证了随机离散事件系统模式故障安全诊断的有效性。

       

      Abstract: In many practical applications, faults are frequently caused by the occurrence of specific events in succession (i.e., pattern faults) rather than a single failure event. The safe diagnosis method based on pattern faults can diagnose the event string that triggers faults. However, the static observation of the original system may not be able to fully capture system faults for complex systems due to the pre-defined and fixed set of observable and unobservable events, leading to the omission of the fault diagnosis. The purpose of this research is to address the limitations of traditional static observation methods. For this reason, a safe diagnosis method based on the dynamic observation of pattern faults in stochastic discrete-event systems (SDESs) is proposed. First, the concepts of S-type and T-type pattern safe diagnosability for SDESs under dynamic observations are formally introduced. Then,a pattern-safe diagnoser and a forbidden language recognizer are constructed to diagnose the pattern faults. Finally, the necessary and sufficient conditions for pattern-safe diagnosability of SDESs under dynamic observations are presented, and an example is provided to illustrate the results.

       

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