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作 者:何志鹏 赵虎[1] HE Zhipeng;ZHAO Hu(School of Automation,Northwestern Polytechnical University,Xi’an 710129,China)
机构地区:[1]西北工业大学自动化学院,陕西西安710129
出 处:《电器与能效管理技术》2022年第1期19-26,共8页Electrical & Energy Management Technology
摘 要:搭建了小型断路器电寿命试验装置,对试验样品开展了电寿命试验。利用试验过程中采集的电弧电压和电弧电流信号,提取反映小型断路器电寿命退化过程的特征量,并以提取的特征量为输入参数,利用BP神经网络构建了小型断路器电寿命评估模型。研究结果表明,提取的相对合闸时间和跌落时间能够显著反映小型断路器电寿命劣化过程;经过试验数据测试,利用趋势特征量构建的电寿命评估模型具有较好的评估效果。An electrical life test device of miniature circuit breaker(MCB)is built,and the electrical life tests with MCB samples are carried out.Using the arcing voltage and arcing current signals collected in the test,the characteristic quantities that could reflect the degradation process of electrical life of MCB are extracted.In addition to the above works,an electrical life assessment model of MCB based on BP neural network is built,which used characteristic quantites as input parameters.The result of study shows that the extracted relative closing time and arcing voltage dropping time can greatly reflect degradation process of electrical life of MCB,and the electrical life assessment model has good assessment effect.
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