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摘要: 分析了安全型继电器的失效机理, 将其划分为3种失效形态; 以接触电阻、吸合时间、超程时间、回跳时间、释放时间和燃弧时间作为失效特性参数, 采用小波变换和移动平均法实现降噪; 针对特性参数间可能存在相关性的情况, 采用主成分分析法实现对多维特性参数的降维处理; 定义了主成分的平均梯度, 采用欧氏距离判别准则, 对18组触点的失效形态进行了判别; 采用Fisher判别方法分析了触点特性参数, 选取能够显著反映安全型继电器寿命的特性参数作为预测变量, 建立了灰色预测模型, 进行了安全型继电器的寿命预测, 并验证了模型的预测效果。研究结果表明: 降噪后特性参数平滑度较好, 同时具有较高的信噪比和较低的均方根误差, 降噪效果较理想; 采用欧氏距离判别准则得到的18组触点失效形态的判别准确度为83.3%;超程时间的Fisher判别函数值最大, 为8.2, 表明超程时间是表征安全型继电器寿命的一个重要参数; 安全型继电器的实际寿命为12.2万次, 基于灰色模型的预测寿命为11.6万次, 寿命预测值的相对误差为4.9%, 表明基于提出模型的寿命预测精度较高, 具有较好的可行性。Abstract: The failure mechanisms of a safety relay were analysed and divided into three failure modes. The contact resistance, closing time, super-path time, bounce time, releasing time and arc time were used as failure characteristic parameters, and the wavelet transform and moving average methods were utilized to achieve denoising. Aimed to the possibility of correlation among characteristic parameters, the principal component analysis method was used to achieve the dimension reduction for the multi-dimensional characteristic parameters to correlate the characteristic parameters. The average gradient value of principal components was defined. The failure modes of 18 sets of contacts were discriminated by using the Euclidean distance discrimination criterion. The characteristic parameters of contacts were analysed using the Fisher discrimination method. The characteristic parameter significantly reflected the features of a safetyrelay's life was selected as the prediction parameter. A grey prediction model was established to predict the safety relay's life, and the prediction effect of the model was verified. Research result indicates that after denoising, the characteristic parameters have good smoothness, high signalto-noise ratios, and low root mean square errors, indicating that a good denoising effect is achieved. The failure modes of 18 sets of contacts are discriminated with an accuracy of 83.3% using the Euclidean distance discrimination criterion. The super-path time has the largest Fisher discrimination function value of 8.2, indicating that the super-path time is an important parameter to represent the life of a safety relay. The actual lifetime of the safety relay is 122 000 times, the prediction life is 116 000 times based on the grey model, and the relative error of the prediction life is 4.9%, indicating that the proposed life prediction model has high accuracy and good feasibility.
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图 6 前2个主成分的平均梯度关系
Figure 6. Relationship of first two principal components'average gradients
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