• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于数字信号处理器的智能城市户外噪声监测声传感器。

A Digital Signal Processor Based Acoustic Sensor for Outdoor Noise Monitoring in Smart Cities.

机构信息

Grupo de Investigación en Instrumentación y Acústica Aplicada. Universidad Politécnica de Madrid, 28031 Madrid, Spain.

出版信息

Sensors (Basel). 2020 Jan 22;20(3):605. doi: 10.3390/s20030605.

DOI:10.3390/s20030605
PMID:31979005
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7037618/
Abstract

Presently, large cities have significant problems with noise pollution due to human activity. Transportation, economic activities, and leisure activities have an important impact on noise pollution. Acoustic noise monitoring must be done with equipment of high quality. Thus, long-term noise monitoring is a high-cost activity for administrations. For this reason, new alternative technological solutions are being used to reduce the costs of measurement instruments. This article presents a design for a versatile electronic device to measure outdoor noise. This device has been designed according to the technical standards for this type of instrument, which impose strict requirements on both the design and the quality of the device's measurements. This instrument has been designed under the original equipment manufacturer (OEM) concept, so the microphone-electronics set can be used as a sensor that can be connected to any microprocessor-based device, and therefore can be easily attached to a monitoring network. To validate the instrument's design, the device has been tested following the regulations of the calibration laboratories for sound level meters (SLM). These tests allowed us to evaluate the behavior of the electronics and the microphone, obtaining different results for these two elements. The results show that the electronics and algorithms implemented fully fit within the requirements of type 1 noise measurement instruments. However, the use of an electret microphone reduces the technical features of the designed instrument, which can only fully fit the requirements of type 2 noise measurement instruments. This situation shows that the microphone is a key element in this kind of instrument and an important element in the overall price. To test the instrument's quality and show how it can be used for monitoring noise in smart wireless acoustic sensor networks, the designed equipment was connected to a commercial microprocessor board and inserted into the infrastructure of an existing outdoor monitoring network. This allowed us to deploy a low-cost sub-network in the city of Málaga (Spain) to analyze the noise of conflict areas due to high levels of leisure noise. The results obtained with this equipment are also shown. It has been verified that this equipment meets the similar requirements to those obtained for type 2 instruments for measuring outdoor noise. The designed equipment is a two-channel instrument, that simultaneously measures, in real time, 86 sound noise parameters for each channel, such as the equivalent continuous sound level (Leq) (with Z, C, and A frequency weighting), the peak level (with Z, C, and A frequency weighting), the maximum and minimum levels (with Z, C, and A frequency weighting), and the impulse, fast, and slow time weighting; seven percentiles (1%, 5%, 10%, 50%, 90%, 95%, and 99%); as well as continuous equivalent sound pressure levels in the one-third octave and octave frequency bands.

摘要

目前,由于人类活动,大城市存在着严重的噪声污染问题。交通、经济活动和休闲活动对噪声污染有重要影响。声学噪声监测必须使用高质量的设备进行。因此,长期的噪声监测对管理部门来说是一项高成本的活动。出于这个原因,新的替代技术解决方案正被用于降低测量仪器的成本。本文提出了一种用于测量室外噪声的多功能电子设备的设计。该设备是根据这种仪器的技术标准设计的,这些标准对设备的设计和测量质量都有严格的要求。该仪器是根据原始设备制造商 (OEM) 的概念设计的,因此麦克风-电子组件可以作为传感器使用,可以连接到任何基于微处理器的设备上,因此可以很容易地附加到监测网络中。为了验证仪器的设计,该设备按照声级计 (SLM) 的校准实验室的规定进行了测试。这些测试允许我们评估电子设备和麦克风的行为,从而得到这两个元件的不同结果。结果表明,电子设备和所实现的算法完全符合 1 类噪声测量仪器的要求。然而,使用驻极体麦克风会降低设计仪器的技术特性,这只能完全符合 2 类噪声测量仪器的要求。这种情况表明,麦克风是这种仪器的关键元件,也是整体价格的重要元件。为了测试仪器的质量,并展示如何将其用于监测智能无线声传感器网络中的噪声,设计的设备被连接到一个商业微处理器板,并插入到现有的室外监测网络基础设施中。这使得我们能够在西班牙马拉加市部署一个低成本的子网,以分析由于休闲噪声水平高而产生的冲突区域的噪声。还展示了从该设备获得的结果。已经验证,该设备符合测量室外噪声的 2 类仪器的类似要求。所设计的设备是一种双通道仪器,能够同时实时测量每个通道的 86 个声音噪声参数,例如等效连续声级 (Leq)(Z、C 和 A 频率加权)、峰值水平(Z、C 和 A 频率加权)、最大和最小水平(Z、C 和 A 频率加权)以及脉冲、快速和慢速时间加权;七个百分位值(1%、5%、10%、50%、90%、95%和 99%);以及三分之一倍频程和倍频程频段的连续等效声压级。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/65772d5858a3/sensors-20-00605-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/63173e1eae91/sensors-20-00605-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/51050547195a/sensors-20-00605-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/17778f10956e/sensors-20-00605-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/14ebb802ef0f/sensors-20-00605-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/5a9c1324f086/sensors-20-00605-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/03a36866dcfb/sensors-20-00605-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/ea5cb806633e/sensors-20-00605-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/75506bc835c7/sensors-20-00605-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/d4c386a2e789/sensors-20-00605-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/dbd888ad3332/sensors-20-00605-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/170fb4e576dc/sensors-20-00605-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/ef01c93449d9/sensors-20-00605-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/65772d5858a3/sensors-20-00605-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/63173e1eae91/sensors-20-00605-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/51050547195a/sensors-20-00605-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/17778f10956e/sensors-20-00605-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/14ebb802ef0f/sensors-20-00605-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/5a9c1324f086/sensors-20-00605-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/03a36866dcfb/sensors-20-00605-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/ea5cb806633e/sensors-20-00605-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/75506bc835c7/sensors-20-00605-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/d4c386a2e789/sensors-20-00605-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/dbd888ad3332/sensors-20-00605-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/170fb4e576dc/sensors-20-00605-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/ef01c93449d9/sensors-20-00605-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c462/7037618/65772d5858a3/sensors-20-00605-g013.jpg

相似文献

1
A Digital Signal Processor Based Acoustic Sensor for Outdoor Noise Monitoring in Smart Cities.基于数字信号处理器的智能城市户外噪声监测声传感器。
Sensors (Basel). 2020 Jan 22;20(3):605. doi: 10.3390/s20030605.
2
Probe microphone measurements: 20 years of progress.探头式传声器测量:20年的进展。
Trends Amplif. 2001 Jun;5(2):35-68. doi: 10.1177/108471380100500202.
3
Evaluation of mobile smartphones app as a screening tool for environmental noise monitoring.评估移动智能手机应用程序作为环境噪声监测筛查工具的效果。
J Occup Environ Hyg. 2016;13(2):D31-6. doi: 10.1080/15459624.2015.1093134.
4
Accurate Indoor Sound Level Measurement on a Low-Power and Low-Cost Wireless Sensor Node.在低功耗、低成本无线传感器节点上进行精确的室内声级测量。
Sensors (Basel). 2018 Jul 19;18(7):2351. doi: 10.3390/s18072351.
5
An inexpensive sensor for noise.一种用于检测噪音的低成本传感器。
J Occup Environ Hyg. 2018 May;15(5):448-454. doi: 10.1080/15459624.2018.1438614.
6
Wireless Acoustic Sensor Nodes for Noise Monitoring in the City of Linares (Jaén).用于莱纳雷斯(哈恩)市噪声监测的无线声学传感器节点。
Sensors (Basel). 2019 Dec 24;20(1):124. doi: 10.3390/s20010124.
7
Wireless Sensor Networks for Long-Term Monitoring of Urban Noise.用于城市噪声长期监测的无线传感器网络。
Sensors (Basel). 2018 Sep 19;18(9):3161. doi: 10.3390/s18093161.
8
Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network.基于深度神经网络的声传感器网络中的声级预测。
Sensors (Basel). 2020 Feb 7;20(3):903. doi: 10.3390/s20030903.
9
Reduction of electronic delay in active noise control systems--a multirate signal processing approach.有源噪声控制系统中电子延迟的降低——一种多速率信号处理方法。
J Acoust Soc Am. 2002 Feb;111(2):916-24. doi: 10.1121/1.1432980.
10
Noise exposure level while operating electronic arcade games as a leisure time activity.将电子街机游戏作为休闲活动进行操作时的噪声暴露水平。
Ind Health. 1992;30(2):65-76. doi: 10.2486/indhealth.30.65.

引用本文的文献

1
Surveillance of noise exposure levels in workplaces in Beijing.北京工作场所噪声暴露水平监测
Front Public Health. 2025 Apr 29;13:1486497. doi: 10.3389/fpubh.2025.1486497. eCollection 2025.
2
Investigation on multiple traffic noise near an airport and their effect on nearby residents.机场附近多种交通噪声及其对附近居民影响的调查。
Sci Rep. 2024 Nov 29;14(1):29680. doi: 10.1038/s41598-024-80786-4.
3
Estimates of Population Highly Annoyed from Transportation Noise in the United States: An Unfair Share of the Burden by Race and Ethnicity.

本文引用的文献

1
Design and Modeling of a MEMS Dual-Backplate Capacitive Microphone with Spring-Supported Diaphragm for Mobile Device Applications.用于移动设备应用的具有弹簧支撑膜片的 MEMS 双背板电容式麦克风的设计与建模。
Sensors (Basel). 2018 Oct 19;18(10):3545. doi: 10.3390/s18103545.
2
Wireless Sensor Networks for Long-Term Monitoring of Urban Noise.用于城市噪声长期监测的无线传感器网络。
Sensors (Basel). 2018 Sep 19;18(9):3161. doi: 10.3390/s18093161.
3
Development of the WHO Environmental Noise Guidelines for the European Region: An Introduction.
美国因交通噪音而深感困扰的人口估计:种族和族裔所承担的不公平负担份额
Environ Impact Assess Rev. 2024 Jan;104. doi: 10.1016/j.eiar.2023.107338. Epub 2023 Nov 2.
4
Evaluating the Performance of Pre-Trained Convolutional Neural Network for Audio Classification on Embedded Systems for Anomaly Detection in Smart Cities.评估预训练卷积神经网络在嵌入式系统上进行音频分类的性能,以实现智能城市中的异常检测。
Sensors (Basel). 2023 Jul 7;23(13):6227. doi: 10.3390/s23136227.
5
Multirate Audio-Integrated Feedback Active Noise Control Systems Using Decimated-Band Adaptive Filters for Reducing Narrowband Noises.使用抽取带自适应滤波器的多速率音频集成反馈有源噪声控制系统降低窄带噪声。
Sensors (Basel). 2020 Nov 23;20(22):6693. doi: 10.3390/s20226693.
6
Smart Wireless Acoustic Sensor Network Design for Noise Monitoring in Smart Cities.智慧城市噪声监测的智能无线声传感器网络设计。
Sensors (Basel). 2020 Aug 23;20(17):4765. doi: 10.3390/s20174765.
7
Low-Cost Sensors for Urban Noise Monitoring Networks-A Literature Review.用于城市噪声监测网络的低成本传感器——文献综述
Sensors (Basel). 2020 Apr 16;20(8):2256. doi: 10.3390/s20082256.
世卫组织欧洲区域环境噪声指南的制定:引言。
Int J Environ Res Public Health. 2018 Apr 20;15(4):813. doi: 10.3390/ijerph15040813.
4
Accurate Ambient Noise Assessment Using Smartphones.使用智能手机进行精确的环境噪声评估。
Sensors (Basel). 2017 Apr 21;17(4):917. doi: 10.3390/s17040917.
5
Design of a Mobile Low-Cost Sensor Network Using Urban Buses for Real-Time Ubiquitous Noise Monitoring.利用城市公交车设计用于实时无处不在噪声监测的移动低成本传感器网络。
Sensors (Basel). 2016 Dec 29;17(1):57. doi: 10.3390/s17010057.
6
Mapping Urban Environmental Noise Using Smartphones.使用智能手机绘制城市环境噪声地图。
Sensors (Basel). 2016 Oct 13;16(10):1692. doi: 10.3390/s16101692.
7
Smartphone-based noise mapping: Integrating sound level meter app data into the strategic noise mapping process.基于智能手机的噪声地图绘制:将声级计应用程序数据集成到战略噪声地图绘制过程中。
Sci Total Environ. 2016 Aug 15;562:852-859. doi: 10.1016/j.scitotenv.2016.04.076. Epub 2016 Apr 23.