基于IGA-BP神经网络的智能电能计量设备状态自动检测系统  

Intelligent Energy Measurement Equipment Status Automatic Detection System Based on IGA-BP Neural Network

作　　者：卢旋 LU Xuan(Guangxi Zhuang Autonomous Region Institute of Metrology and Testing,Nanning 530299,China)

机构地区：[1]广西壮族自治区计量检测研究院,南宁530299

出　　处：《计算机测量与控制》2024年第8期138-144,共7页Computer Measurement &Control

基　　金：广西科技基地和人才专项基金项目(桂科AD21238034)。

摘　　要：针对不断扩大的电网规模和愈加复杂的外部环境对智能电能计量设备安全稳定运行带来的挑战,研究了基于IGA-BP神经网络的智能电能计量设备状态自动检测系统的设计;系统硬件包括数据采集模块、信号处理模块、数据传输模块和数据分析模块;在软件方面,系统采集智能电能计量设备的检测数据,选取基础电能计量误差、电压波动幅度、电流波动幅度、功率因数作为智能电能计量设备状态量;引入IGA-BP神经网络对状态量进行迭代运算,实现了智能电能计量设备状态的自动检测;实验结果表明,该系统对智能电能计量设备状态检测的最短时间为2 s,检测结果与实际结果一致,验证了系统具有较高的设备状态检测效率和精度。To address the growing challenges posed by the expanding power grid scale and increasingly complex external environment,a study was conducted on the design of an intelligent electric energy metering equipment status automatic detection system based on the IGA-BP neural network.The hardware components of the system include a data acquisition module,a signal processing module,a data transmission module,and a data analysis module.In the software aspect,the system collects detection data from intelligent electric energy metering equipment and selects fundamental parameters such as metering error,voltage fluctuation,current fluctuation,and power factor as status indicators.An IGA-BP neural network is then employed to perform iterative calculations on these status indicators,enabling automatic detection of the equipmen's status.Experimental results demonstrate that the proposed system achieves a minimum detection time of 2 seconds for intelligent electric energy metering equipment,with the detection results aligning precisely with actual conditions.This verifies the system's high efficiency and accuracy in equipment status detection.

关 键 词：检测系统 智能电能计量设备 传感器 IGA-BP神经网络模型 状态检测 

分 类 号：TM911[电气工程—电力电子与电力传动]