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Distributed Fault Diagnosis and Prognosis of Nonlinear Mechatronic System Using Adaptive Biogeography-based Optimization

机译:基于自适应生物地理学优化的非线性机电系统的分布式故障诊断和预后

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This paper proposes a distributed fault diagnosis and prognosis scheme for nonlinear mechatronic system, where multiple compound faults are considered. Firstly, the bond graph (BG) model of the nonlinear mechatronic system is established, and the BG based model structural decomposition is used to build minimal submodels from the global model. Secondly, distributed fault detection and isolation (FDI) framework is constructed based on minimal submodels, which mainly consists of distributed analytical redundancy relations and distributed fault signature matrix. Then, on the basis of the isolated possible faults obtained from distributed FDI framework, corresponding local estimator of each submodel is designed, where adaptive biogeography-based optimization algorithm is introduced for distributed fault estimation. The local estimator aims to identify the amplitude of abrupt fault, the appearing instants and the degradation model of incipient fault respectively. After that, for incipient fault, the distributed remaining useful life prediction is carried out based on the degradation model obtained from distributed fault estimation. Finally, simulation results show the effectiveness of the proposed distributed fault diagnosis and prognosis method.
机译:本文提出了一种用于非线性机制系统的分布式故障诊断和预后方案,其中考虑了多种复合故障。首先,建立非线性机电系统的键合图(BG)模型,并使用基于BG的模型结构分解来构建全局模型的最小子模型。其次,基于最小的子模型构建了分布式故障检测和隔离(FDI)框架,主要由分布式分析冗余关系和分布式故障签名矩阵组成。然后,基于从分布式FDI框架获得的隔离可能的故障,设计了每个子模型的相应本地估计器,其中引入了自适应生物地理的优化算法进行分布式故障估计。本地估算仪旨在识别分别识别突发故障的幅度,出现的瞬间和初始故障的劣化模型。之后,对于初始故障,基于从分布式故障估计获得的劣化模型进行分布剩余的有用寿命预测。最后,仿真结果表明了拟议的分布式故障诊断和预后方法的有效性。

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