支持向量机漏电特征模型的电力设施漏电识别

Leakage identification of power facilities based on support vector machine leakage feature model

针对电力设施中漏电引起的故障问题,提出了新型的漏电特性分析方法,该方法融合了基于支持向量机的漏电算法模型,实现了电力设施漏电特性的图像采集和A/D转换处理,最后输出后的数据信息通过DSP计算模块进行计算,最终输出电力设施的强电漏电信息或者弱电漏电信息,实现了电力设施漏电信息的识别。该研究将传统技术中的漏电难以分析的问题转换为微观、直接的数据分析,提高了电力设施中漏电的识别和预防。试验表明,该研究方法误差低,具有较好的应用效果。

Aiming at the fault problem caused by leakage in power facilities,a new leakage characteristic analysis method is proposed.This method integrates the leakage algorithm model based on support vector machine,and realizes the image acquisition and A/D conversion processing of the leakage characteristic of power facilities.The output data information is calculated by the DSP calculation module,and finally output the strong current leakage information or the weak current leakage information of the power facility,which realizes the identification of the leakage information of the power facility.This research converts the difficult-to-analyze problem of electricity leakage in traditional technology into microscopic and direct data analysis,which improves the identification and prevention of electricity leakage in power facilities.The experiment shows that the method of this study has low error and good application effect.