摘要
针对5G通信设备性能监测面临的挑战,研究声发射技术在设备异常状态识别和故障预警中的应用。通过分析功率放大器异常、处理器过载、射频器件老化以及散热系统故障等异常状态的声学信号特征,建立基于声发射参数的设备异常监测模型。实验结果表明,声发射技术在故障预警准确率、器件性能监测精度、热管理效率方面均优于传统监测方法,为5G通信设备故障预防和可靠性保障提供了新的技术路径。
Aiming at the challenges faced by performance monitoring of 5G communication equipment,the application of acoustic emission technology in equipment abnormal state identification and fault early warning is studied.By analyzing the acoustic signal characteristics of abnormal conditions such as abnormal power amplifier,processor overload,aging of RF devices and cooling system failure,an equipment abnormality detection model based on acoustic emission parameters is established.The experimental results show that AE technology is superior to traditional monitoring methods in fault early warning accuracy,device performance monitoring accuracy and thermal management efficiency,which provides a new technical path for fault prevention and reliability guarantee of 5G communication equipment.
作者
李亚
LI Ya(Anhui Guangshun Information Technology Co.,Ltd.,Bengbu 230000,China)
出处
《电声技术》
2025年第10期214-216,共3页
Audio Engineering
关键词
声发射技术
5G通信设备
性能监测
故障预警
acoustic emission technology
5G communication equipment
performance monitoring
fault warning
