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A multi-source information fusion fault diagnosis for aviation hydraulic pump based on the new evidence similarity distance

机译：基于新证据相似距离的航空液压泵多源信息融合故障诊断

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摘要

Aviation hydraulic pump is one of the key components in aircraft hydraulic system, therefore, high precision fault diagnosis is essential to improve the reliability and performance of hydraulic pump. A novel multi-source information fusion fault diagnosis method is proposed based' on the Dempster Shafer (D-S) evidence theory, which utilizes the three-level signals from pump level, hydraulic power system level and hydraulic actuation system level. The feature vectors of these three levels are extracted as three bodies, of evidences (BOEs) and the fuzzy membership function is employed to construct the basic probability assignments (BPAs) of three BOEs. In order to solve the issue of combining the conflicting evidences, the D-S evidence theory based on the new evidence similarity distance is developed to combine the obtained BPAs. Finally, the making-decision rules are given to diagnose the faults. The diagnosis results validate that the proposed method not only can increase significantly the belief level of supporting the diagnosis target, but also has the ability to diagnose fault of pump correctly even if a sensor is faulty. (C) 2017 Elsevier Masson SAS. All rights reserved.
机译：航空液压泵是飞机液压系统的关键部件之一，因此，高精度的故障诊断对于提高液压泵的可靠性和性能至关重要。基于Dempster Shafer（D-S）证据理论，提出了一种新颖的多源信息融合故障诊断方法，该方法利用了泵级，液压动力系统级和液压执行系统级的三级信号。将这三个级别的特征向量提取为三个证据实体（BOE），并使用模糊隶属函数构造三个BOE的基本概率分配（BPA）。为了解决合并矛盾证据的问题，建立了基于新证据相似度距离的D-S证据理论，将获得的BPA进行合并。最后，给出决策规则来诊断故障。诊断结果表明，该方法不仅可以显着提高支持诊断目标的信念水平，而且即使传感器出现故障也具有正确诊断泵故障的能力。 （C）2017 Elsevier Masson SAS。版权所有。

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