室外安防小型智能聲測傳感節(jié)點(diǎn)測向方案研究
本文選題:智能傳感器網(wǎng)絡(luò) + 智能傳感節(jié)點(diǎn)。 參考:《南京理工大學(xué)》2017年碩士論文
【摘要】:隨著社會的發(fā)展和科學(xué)技術(shù)的進(jìn)步,數(shù)字網(wǎng)絡(luò)生活時(shí)代已經(jīng)到來,家庭智能化、物業(yè)管理現(xiàn)代化和社區(qū)服務(wù)信息化已成為發(fā)展趨勢,智能安防的出現(xiàn)成為必然。本文針對室外遠(yuǎn)場環(huán)境,采用小型傳聲器陣列構(gòu)成的測向系統(tǒng)作為智能傳感節(jié)點(diǎn),為智能傳感器網(wǎng)絡(luò)實(shí)現(xiàn)對聲源位置的定位打下基礎(chǔ)。智能聲傳感器網(wǎng)絡(luò)采用分布式結(jié)構(gòu),具有成本低廉、部署簡便靈活、精確度高等優(yōu)越性能,可用于室外監(jiān)控等方面。本文研究的測向系統(tǒng)包含三個部分,分別為傳感、處理、通信部分,可實(shí)現(xiàn)對聲音信號的采集、分離和聲源位置測向等功能。其制成的智能傳感節(jié)點(diǎn)外圍有金屬材料做成的封裝外殼保護(hù)內(nèi)部電路,可以在惡劣環(huán)境、天氣下代替人工對室外環(huán)境進(jìn)行長時(shí)間的監(jiān)控。在智能聲傳感器網(wǎng)絡(luò)結(jié)構(gòu)中,考慮到環(huán)境監(jiān)測無需實(shí)時(shí)處理,本文對所監(jiān)測的聲音信號采用斷續(xù)實(shí)時(shí)處理模式。受系統(tǒng)結(jié)構(gòu)小型化、處理器的運(yùn)算性能等方面的限制,節(jié)點(diǎn)的數(shù)據(jù)處理量不能太大,需要在時(shí)間限制內(nèi)完成計(jì)算任務(wù)。采用聲音活動性檢測(VAD)與廣義互相關(guān)(GCC)相結(jié)合的方式,在節(jié)點(diǎn)處理器上對采集到的數(shù)據(jù)進(jìn)行聲音活動性檢測截取出有效信號段,然后利用算法PHAT-GCC進(jìn)行測向估計(jì),后臺可綜合多個節(jié)點(diǎn)的測向結(jié)果最終實(shí)現(xiàn)聯(lián)合定位。這種利用單節(jié)點(diǎn)測向、多節(jié)點(diǎn)定位的方式,減少了在節(jié)點(diǎn)上的處理量及在傳輸上的通信帶寬。在單節(jié)點(diǎn)的測向過程中,節(jié)點(diǎn)由于受到結(jié)構(gòu)小型化及其封裝外殼的影響,在遠(yuǎn)場環(huán)境下得到的實(shí)際聲源測向結(jié)果存在一定的偏差。文章基于上述問題做了多種實(shí)驗(yàn)并對結(jié)果進(jìn)行分析,從中找出對誤差的補(bǔ)償方法,提高小型智能傳感節(jié)點(diǎn)的測向準(zhǔn)確度,為智能傳感器網(wǎng)絡(luò)在聲源定位的實(shí)用化進(jìn)程方向上做了鋪墊。
[Abstract]:With the development of society and the progress of science and technology, the era of digital network life has arrived, the family intelligence, the property management modernization and the community service information have become the development trend, the appearance of intelligent security has become inevitable. In this paper, a direction finding system composed of a small microphone array is used as an intelligent sensor node to lay a foundation for the location of sound source in an intelligent sensor network. The intelligent acoustic sensor network has the advantages of low cost, simple and flexible deployment, high precision and so on. It can be used in outdoor monitoring and control. The direction-finding system in this paper consists of three parts: sensing, processing and communication, which can realize the functions of sound signal acquisition, separation and sound source position direction finding. The intelligent sensor node has a metal encapsulated shell to protect the inner circuit, which can monitor the outdoor environment for a long time instead of manual in the bad environment and weather. In the network structure of intelligent acoustic sensor, considering that the environment monitoring does not need real-time processing, this paper adopts the intermittent real-time processing mode for the monitored sound signal. Limited by the miniaturization of the system structure and the computational performance of the processor, the data processing capacity of the node can not be too large, so it is necessary to complete the computing task within the time limit. Based on the combination of acoustic activity detection (VAD) and generalized cross correlation (GCC), the effective signal segment is intercepted from the collected data on the node processor, and then the direction finding is estimated by using the algorithm PHAT-GCC. The backstage can synthesize the result of direction finding of many nodes and finally realize the joint positioning. By using single node direction finding and multi-node location, the processing capacity on the node and the communication bandwidth on the transmission are reduced. In the process of single node direction finding, due to the influence of the miniaturization of the structure and the encapsulation of the shell, the actual sound source direction finding results obtained in the far field environment have a certain deviation. Based on the above problems, this paper makes a variety of experiments and analyzes the results, and finds out the compensation method for the error, and improves the accuracy of the small intelligent sensor node. It lays the groundwork for the practical orientation of sound source location in intelligent sensor networks.
【學(xué)位授予單位】:南京理工大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2017
【分類號】:TN929.5;TP212.9
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 趙兆;顧添翼;吳亞琦;許志勇;;通用可編程聲測傳感網(wǎng)智能節(jié)點(diǎn)及其應(yīng)用[J];電聲技術(shù);2015年02期
2 張帆;羅積浩;蘭軍建;黃杰軍;;基于麥克風(fēng)陣列的智能監(jiān)控系統(tǒng)[J];電子測量技術(shù);2013年05期
3 徐明;;水聲傳感器網(wǎng)中基于網(wǎng)絡(luò)編碼的多徑路由協(xié)議[J];傳感器與微系統(tǒng);2013年01期
4 趙麗霞;紀(jì)松波;;無線傳感器網(wǎng)絡(luò)在智能交通中的應(yīng)用[J];物聯(lián)網(wǎng)技術(shù);2012年06期
5 李偉紅;湯海兵;龔衛(wèi)國;;公共場所異常聲源定位中時(shí)延估計(jì)方法研究[J];儀器儀表學(xué)報(bào);2012年04期
6 逯靜洲;Sung-Han Sim;金波;Billie F Spencer,Jr;;基于分布式無線智能傳感器網(wǎng)絡(luò)的結(jié)構(gòu)模態(tài)識別[J];應(yīng)用基礎(chǔ)與工程科學(xué)學(xué)報(bào);2011年05期
7 林岳松;陳琳;郭寶峰;;基于數(shù)據(jù)驅(qū)動的信息融合及其在車輛聲辨識中的應(yīng)用[J];電子與信息學(xué)報(bào);2011年09期
8 郭寶峰;林岳松;彭冬亮;;聲傳感網(wǎng)中的語義增強(qiáng)型信息融合方法[J];杭州電子科技大學(xué)學(xué)報(bào);2011年04期
9 鐘永信;黃建國;韓晶;;基于空間喚醒的水聲傳感器網(wǎng)絡(luò)節(jié)能路由協(xié)議[J];電子與信息學(xué)報(bào);2011年06期
10 黨月芳;;無線傳感器網(wǎng)絡(luò)在軍事領(lǐng)域中的應(yīng)用研究[J];信息通信;2011年03期
,本文編號:1990541
本文鏈接:http://sikaile.net/kejilunwen/xinxigongchenglunwen/1990541.html