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牵引供电系统是高速电气化铁路的重要组成部分,其运行状态直接决定了高速铁路的安全和效益,但牵引供电系统故障是不可避免的。为确保牵引供电系统安全稳定运行和增强供电的可靠性和连续性,需要一种优质的牵引供电运行状态检测与故障分析系统,对其故障类别进行快速、正确的识别。本文主要介绍了如何改进牵引供电运行信号的数据采集方式,包括信号进行预处理和提取信号特征值,提出了利用数学统计学中的偏度与峰度概念对牵引供电特征信号进行特征提取的新方法,并对提取结果进行比较,以达到对牵引供电运行系统故障检测的目的。
Traction power supply system is an important part of high-speed electrified railway, and its operating status directly determines the safety and efficiency of high-speed railway, but the traction power supply system failure is inevitable. In order to ensure the safe and stable operation of the traction power supply system and to enhance the reliability and continuity of the power supply, a high-quality traction power supply operation condition detection and fault analysis system is needed to quickly and correctly recognize the fault category. This paper mainly introduces how to improve the data acquisition method of traction power supply operation signal, including signal preprocessing and signal eigenvalue extraction, and proposes a new method to extract the feature of traction power supply signal using the concept of skewness and kurtosis in mathematical statistics Methods, and compare the extraction results in order to achieve the purpose of fault detection of traction power supply operation system.