电网环保噪声监测用低能耗噪声诊断技术研究  

Research on Low Energy Consumption Noise Diagnosis Technology for Power Grid Environmental Noise Monitoring

作　　者：安毅敏 刘寅 王乐乐 王静娟 AN Yi-min;LIU Yin;WANG Le-le;WANG Jing-juan(Electric Power Research Institute,State Grid Xinjiang Electric Power Co.,Ltd.,Urumqi 830000,China)

机构地区：[1]国网新疆电力有限公司电力科学研究院,新疆乌鲁木齐830000

出　　处：《电力电子技术》2025年第4期39-43,共5页Power Electronics

摘　　要：为了实现对电网环保噪声监测的有效控制和节能降耗,该研究设计了基于S3C2440A芯片的低能耗噪声诊断系统。该系统包含MEMS传声器、信号调理模块、数据处理模块及人机交互界面,靠ZigBee协议实现了大型组网的噪声监测。本文采用模拟退火算法改进深度神经网络(DNN)模型,旨在提高噪声诊断精度。实验结果表明,MEMS传声器降低了系统功耗,改进神经网络模型噪声信号检测精度约为99%,对噪声控制效果较好。In order to realize the effective control and energy saving of power grid environmental noise monitoring,a low energy consumption noise diagnosis system based on S3C2440A chip is designed.The system includes MEMS microphone,signal conditioning module,data processing module and human-computer interaction interface,and realizes the noise monitoring of large-scale networking by ZigBee protocol.In this paper,simulated annealing algorithm is used to improve the deep neural network(DNN)model to improve the accuracy of noise diagnosis.The experimental results show that the MEMS microphone reduces the power consumption of the system,and the noise signal detection accuracy of the improved neural network model is about 99%,and the noise control effect is better.

关 键 词：电网 噪声监测 低能耗噪声诊断 深度神经网络模型 

分 类 号：TN819.1[电子电信—信息与通信工程]