基于WMD和DSI的复杂重型装备健康状态评估
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国家重点研发计划(2018YFB1703000); 国家自然科学基金(61971347); 西安市科技计划基金(2020KJRC0093)


Health Status Assessment Method for Complex Heavy Equipment Based on WMD and DSI
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    摘要:

    设备故障的变化趋势一般从轻微故障开始, 逐渐发展到整个设备丧失工作能力. 为了在设备轻微故障时准确检测, 本文提出了一种基于加权马氏距离 (Weighted Mahalanobis Distance, WMD) 和设备状态指数 (Device Status Index, DSI) 的设备健康状态评估方法. 该方法基于改进的马田系统, 对设备有效运行特征参数构建稳定基准空间, 筛选特征并按照设备故障敏感性计算加权马氏距离, 排除了特征相关性的干扰; 利用Box-Cox变换确定设备状态指数的阈值, 构建复杂重型装备健康状况模型. 通过实验验证模型有效性, 正常样本的WMD值均小于故障阈值, 有将近98.6%的样本值在征兆预警内. 本文提出的方法可为复杂重型装备的维修与管理提供数据支持, 为工业生产提供有效帮助.

    Abstract:

    The device fault generally starts from a minor one and gradually develops to the loss of working capacity of the whole set. Detection in case of a minor fault can recover the unnecessary loss. Therefore, this study proposes a method to evaluate device health status on the basis of the Weighted Mahalanobis Distance (WMD) and the Device Status Index (DSI). Based on an improved Mahalanobis-Taguchi system, the method constructs a stable reference space for the characteristic parameters during the effective operation of the device. It selects the characteristics and calculates the WMD according to the device fault sensitivity, eliminating the interference of characteristic correlation. Then Box-Cox transformation is used to determine the threshold value of the DSI to build a health status model of the complex heavy device, and the model is verified by experiments. The WMD values of the normal samples are all below the fault threshold, and nearly 98.6% of the sample values are within the warning signs. The proposed method can provide data support for maintenance and management of complex heavy devices, thereby facilitating industrial production.

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王怀军,张鸿宇,李军怀,张思秦,张发存,冯连强.基于WMD和DSI的复杂重型装备健康状态评估.计算机系统应用,2021,30(10):12-20

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  • 收稿日期:2020-12-01
  • 最后修改日期:2020-12-28
  • 在线发布日期: 2021-10-08
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