摘要
针对城市生活中日益严重的噪声问题和人们对噪声监控的现实需求,设计了一种基于STM32和远距离无线通信(LoRa)技术的分布式无线噪声采集分析系统。该系统基于STM32设计了一种集采集噪声、分析噪声数据并上传于一体的采集分析设备,采用快速傅里叶变换(FFT)实现了噪声信号的倍频程分析,该设备具有体积小、续航能力强、便于部署等优点。采用LoRa无线通信技术将采集到的噪声数据上传至上位机,传输范围广,传输效果稳定。利用C#语言开发的上位机软件可以实现对多个监测设备采集分析数据的实时显示和保存,人机交互界面友好。经测试,该系统能准确地监测部署设备区域的噪声情况,达到在20 Hz~20 kHz频率范围上17~136 dB的动态范围,稳定地传输采集分析到的声学数据,适用于多区域噪声的长时间无人监控与分析。
In view of the increasingly serious noise problems in urban life and the actual needs for noise monitoring,a distributed wireless noise acquisition and analysis system based on STM32 and long range radio(LoRa)technology is designed.In this system,a acquisition and analysis equipment which can collect,analyze and upload the noise data is designed based on STM32.The octave analysis of noise signals is realized with fast Fourier transform(FFT).The equipment has the advantages of small size,strong endurance and easy deployment.LoRa wireless communication technology is used to upload the collected noise data to the upper computer,which has a wide transmission range and stable transmission effect.The upper computer software developed by C#can realize the real-time display and storage of data collected and analyzed by multiple monitoring devices,and the human-computer interaction interface is friendly.The test results show that the system can accurately monitor the noise situation in the equipment deployment area,reach the dynamic range of 17~136 dB in the frequency range of 20 Hz~20 kHz,and stably transmit the collected and analyzed acoustic data.Therefore,it is suitable for long-term unmanned monitoring and analysis of noise in multiple areas.
作者
吴礼福
吴佳伟
田朋溢
WU Lifu;WU Jiawei;TIAN Pengyi(School of Electronic&Information Engineering,Nanjing University of Information Science&Technology,Nanjing 210044,China;Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET),Nanjing 210044,China;Locomotive and Car Research Institute,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)
出处
《现代电子技术》
2021年第21期30-34,共5页
Modern Electronics Technique
基金
江苏省“信息与通信工程”优势学科建设项目资助
国家自然科学基金项目(12074192)
中国铁道科学研究院集团有限公司科研开发基金课题(2019YJ008)