An improved EKF based on excitation equivalent conversion for EHA multi-factor fault diagnosis
An improved EKF based on excitation equivalent conversion for EHA multi-factor fault diagnosis
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DOI：
10.1177/16878132221131292
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发表时间：
2022-10
影响因子：
2.1
通讯作者：
Pei Chen;Huanguo Chen;Wenhua Chen;Jun Pan;Jianmin Li
中科院分区：
文献类型：
--
作者：
Pei Chen;Huanguo Chen;Wenhua Chen;Jun Pan;Jianmin Li
电静液作动器作为一种新兴的电传作动机构，具有能量效率高、响应速度快等优点，在现代飞行控制系统中得到了广泛的应用。作为飞机的关键部件，电液伺服系统的故障诊断是保证飞机可靠性的必要条件。虽然目前研究人员提出了许多有效的故障诊断技术，但大多数只能有效地处理单因素故障。近年来对多状态可靠性和竞争失效的研究表明，复杂系统（如EHA）比单因素失效更容易发生多因素失效。为此，本文提出了一种基于励磁等效变换的改进EKF方法，实现了EHA的多因素故障诊断。首先，讨论了现有的EHA故障诊断方法及其在多因素故障诊断中的局限性。分析了实现多因素故障诊断的关键问题--多参数估计和可观测性。基于二阶系统的结构特点和可观测性分析，引入激励等效变换，建立未知状态参数的附加可用方程，实现系统不可观测时的多参数估计。最后，通过仿真和样机试验验证了该方法的有效性，并与传统的单因素失效分析方法进行了比较。
Electro-hydrostatic actuator (EHA), as an emerging power-by-wire (PBW) actuation mechanism with high energy efficiency and fast responsiveness, has been widely used in modern flight control systems. As a pivotal component, the fault diagnosis of EHA is necessary to ensure the reliability of the aircraft. Although researchers have proposed many effective fault diagnosis techniques at present, most of them can only deal with single-factor faults effectively. Recent studies on multi-state reliability and competing failure show that complicated systems such as EHA are more prone to multi-factor failures than single-factor failures. Therefore, an improved EKF based on excitation equivalent conversion is proposed in this paper to achieve the multi-factor fault diagnosis of EHA. First, the existing fault diagnosis methods for EHA and their limitations in multi-factor fault diagnosis are discussed. Then, multi-parameters estimation and observability, the key issues to achieve multi-factor fault diagnosis, are analyzed. Based on the structural characteristics and observability analysis of the second-order system, excitation equivalent conversion is introduced to establish additional available equation about the unknown state parameters to realize the multi-parameter estimation when system is unobservable. Finally, simulation and prototype test experiments have been performed, and the results demonstrate the efficacy of the proposed method, which outperforms that of the traditional single-factor failure analysis methods by comparison.