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作 者:张馨月 郭溦 叶赞 邢雅 Zhang Xinyue;Guo Wei;Ye Zan;Xing Ya(State Grid Ningxia Electric Power Party School(State Grid Ningxia Training Center),Yinchuan,Ningxia,China,750000)
机构地区:[1]国网宁夏电力党校(国网宁夏培训中心),宁夏银川750000
出 处:《仪器仪表用户》2024年第12期154-156,共3页Instrumentation
摘 要:本研究针对拆回电能表人工处理低效高错问题,设计了按键式接线盒应用于电子测量。集成灰度分割字符识别、自动核查补录与BP神经网络故障诊断,构建表码识别与故障归类模型。实现电能表图像采集与表码准确复核,确保计量数据准确,支持电量核查、分类再利用与决策,提升服务精益化水平,为电量纠纷追溯提供有力辅证。This study addresses the issue of low efficiency and high error rates in manual processing of dismantled electric meters by designing a push-button terminal block for application in electronic measurement.By integrating grayscale segmentation character recognition,automatic verification and supplementary recording,as well as BP neural network fault diagnosis,a meter code recognition and fault categorization model is constructed.This achieves accurate image acquisition and verification of meter codes,ensuring accurate metering data.It supports electricity verification,classified reuse,and decision-making,enhancing the level of service refinement and providing strong evidence for tracing electricity disputes.
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