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A Reliability Model of Intelligent Station Secondary Device Based on Log-Normal Distribution Model and Its Discriminating Method

机译:基于日志正态分布模型的智能站辅助设备的可靠性模型及其辨别方法

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Secondary device of intelligent station has long lifetime and high reliability due to its digital characteristics. The lifetime model of different equipment may obey distinct distributions. But at present, there are few discussions on the reliability model identification of secondary relay protection devices in China. The Log-Normal model and the Weibull model are very adaptable to data due to their flexibility. They are widely used in lifetime prediction and are easy to mix in analysis. This confusion may cause severe consequences when looking for low-percentile life reliability and focusing on equipment aging performance parameters. In this paper, we first establish a lifetime model for the intelligent station secondary equipment that conforms to the Log-Normal distribution model. Then we discriminate diverse models using the maximum likelihood function method. Finally we use the least squares method and the average rank method for parameter estimation. The proposed discriminating method avoids mutual transformation between nonlinear and linear, the identification result is accurate and clear, and the model parameter estimation method is simple.
机译:由于其数字特性,智能电台的二级设备具有长寿命和高可靠性。不同设备的寿命模型可能遵循不同的分布。但目前目前,关于中国中继继电器保护装置的可靠性模型识别很少的讨论。由于它们的灵活性,日志正常模型和威布尔模型非常适应数据。它们广泛用于寿命预测,并且易于混合在分析中。在寻找低百分位的寿命可靠性并专注于设备老化性能参数时,这种混乱可能会导致严重后果。在本文中,我们首先为符合日志正态分布模型的智能站二级设备建立寿命模型。然后我们使用最大似然函数方法区分不同的模型。最后,我们使用最小二乘方法和参数估计的平均等级方法。所提出的辨别方法避免了非线性和线性之间的相互转换,识别结果是准确明确的,并且模型参数估计方法很简单。

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