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Gaussian mixture model based approach to fault detection for satellite communication equipment

机译:基于高斯混合模型的卫星通信设备故障检测方法

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Aiming at the problem of fault detection for satellite communication system, a prediction method based on Gaussian mixture model is proposed. Firstly, the observation sequence is collected by modem as well as frequency conversion equipment. Then feature parameters are extracted after pre-processing. The expectation maximum algorithm is applied to train the Gaussian mixture model. The posterior probabilities of the feature sequence separately relative to the normal and abnormal models are calculated by the maximum a posteriori probability criterion. In order to determine the right working state, the model corresponding to the larger probability is selected. Since the result of the judgment is presented in the form of probability, it is necessary to choose the threshold value after several times. Finally, the performance and average prediction accuracy of the prediction model are tested by simulation.
机译:针对卫星通信系统的故障检测问题,提出了一种基于高斯混合模型的预测方法。首先,观测序列由调制解调器以及变频设备收集。然后在预处理后提取特征参数。应用期望最大值算法训练高斯混合模型。通过最大后验概率准则来计算特征序列相对于正常模型和异常模型的后验概率。为了确定正确的工作状态,选择对应于较大概率的模型。由于判断结果是以概率的形式呈现的,因此有必要在多次之后选择阈值。最后,通过仿真测试了预测模型的性能和平均预测精度。

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