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Analysis of Equipment Fault Prediction Based on the Metabolism Combined Model

机译:基于代谢组合模型的设备故障预测分析

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Aiming at the difficulty of equipment fault prediction, by the combination of the validity principles and based on the grey model GM (1, 1) and linear regression model (LRM), a new combined model was established. The model was fitted by two models. It used the original data coming from constant duration measurement to simulate and predict when the system reaches the upper limit of failure data, and according to this to infer the system failure time. At the same time, the metabolism method was introduced to improve the prediction accuracy. At last, an example that output voltage of a certain type of radar transmitter data was given to verify the effectiveness and practicality of the model in failure predication.
机译:针对设备故障预测的难点,结合有效性原则,基于灰色模型GM(1,1)和线性回归模型(LRM),建立了新的组合模型。该模型由两个模型拟合。它使用来自恒定持续时间测量的原始数据来模拟和预测系统何时达到故障数据上限,并据此推断系统故障时间。同时,引入了新陈代谢方法以提高预测精度。最后,以某类雷达发射机数据的输出电压为例,验证了该模型在故障预测中的有效性和实用性。

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