基于证据推理的航天继电器故障预测方法

Failure prognosis method based on evidential reasoning for aerospace relay

针对航天继电器失效比例高、故障预测存在强不确定性等问题,以JRC-7M航天继电器为研究对象,选取吸合时间和超程时间为故障特征变量,提出一种基于证据推理(evidential reasoning,ER)融合多故障特征信息的航天继电器故障预测方法。该方法利用基于三阶Volterra滤波器的在线预测模型预测故障特征未来信息,采用变异系数法自适应求取融合权重,建立基于证据推理的融合框架融合多故障特征信息得到继电器的故障状态,并通过融合其历史、当前和未来状态信息得到继电器综合故障预测结果。利用STS2104A电磁继电器测试系统测试并采集数据,验证了所提方法的有效性。

To solve the high failure ratio problem of aerospace relay and strong uncertainty in its failure prognosis, a failure prognosis method based on evidential reasoning（ER） by fusing multiple fault characteristics information was proposed. The JRC-7M aerospace relay was chosen as the research object and its characteristic parameters, super-path time and pick-up time, were chosen as the main fault characteristics. In the proposed method, a forecasting model based on the third-order Volterra filter was proposed to online predict the fault characteristics＇ information, then an adaptive weighting model based on coefficient of variation-based weighting was adopted to calculate the relative weight. To obtain a comprehensive failure prognosis result of the aerospace relay, an safety assessment aggregation scheme based on the ER approach was developed to fuse multiple fault characteristics, and the ＂history＂, ＂current＂ and ＂future＂ fault state information were synthetically fused. The validity of the proposed method was verified by the testing data collected by the STS2104A electromagnetic relay test system.