【摘要】：傳統(tǒng)的淺層地下爆炸定位是利用多個地震檢波器陣列獲取地下震動信號,經(jīng)過信號特征提取方法得到地下震動信號初至波時刻,然后利用時差定位算法完成震源位置的測量。由于地下介質(zhì)結(jié)構(gòu)比較復(fù)雜,各種橫波、縱波相互交疊,群速不穩(wěn),震源近場頻散現(xiàn)象明顯,導(dǎo)致時差定位精度不高。針對這些問題,本文提出了一種基于到達(dá)角度的分布式交叉定位算法,即通過各傳感器節(jié)點(diǎn)獲取直達(dá)縱波的角度信息,建立縱波波束模型,進(jìn)行波束交叉定位,實(shí)現(xiàn)地下震源的精確定位。 根據(jù)小區(qū)域淺層地下震源定位需求,本文在設(shè)計(jì)地下淺層交叉定位系統(tǒng)基礎(chǔ)上,經(jīng)過外場模擬試驗(yàn)獲取震源與傳感器間俯仰角、方位角信息,進(jìn)行坐標(biāo)轉(zhuǎn)換并利用最小二乘定位算法、加權(quán)融合定位算法、三維空間優(yōu)化交叉定位算法、最小二乘-泰勒級數(shù)定位算法分別對獲取的信息進(jìn)行計(jì)算,預(yù)測出震源位置信息,采用BP神經(jīng)網(wǎng)絡(luò)訓(xùn)練的方法篩選有效實(shí)驗(yàn)數(shù)據(jù),利用最小二乘、加權(quán)數(shù)據(jù)融合算法分別擬合出震源位置信息,分析不同定位算法得到的定位結(jié)果和定位精度,并設(shè)計(jì)軟件平臺直觀地顯示預(yù)測震源位置和定位結(jié)果。 實(shí)驗(yàn)結(jié)果表明：在20m*20m地下震動監(jiān)測范圍內(nèi),地下交叉定位均方根誤差為0.40m,基本滿足分布式淺層地下震動定位的需求。
[Abstract]:In the traditional shallow underground explosion location, several geophone arrays are used to obtain the underground vibration signal, and the first arrival wave time of the underground vibration signal is obtained by the signal feature extraction method, and then the source position is measured by using the time difference location algorithm. Because of the complexity of the underground medium structure, all kinds of shear waves, P-waves overlap with each other, the group velocity is unstable, and the dispersion of the source near the field is obvious, which leads to the low accuracy of time difference positioning. In order to solve these problems, a distributed cross-location algorithm based on angle of arrival is proposed in this paper, that is, the angle information of direct P-wave is obtained by each sensor node, the P-wave beam model is established, and the beam cross-location is carried out. The accurate location of underground source is realized. According to the requirements of shallow underground source location in small area, based on the design of underground shallow cross positioning system, the pitch angle and azimuth information between source and sensor are obtained by external field simulation test. The coordinate transformation is carried out and the source position information is predicted by using the least square positioning algorithm, the weighted fusion positioning algorithm, the three-dimensional spatial optimization cross-location algorithm and the least square Taylor series positioning algorithm, respectively, and the source position information is predicted by using the least square positioning algorithm, the weighted fusion positioning algorithm, the three-dimensional spatial optimization cross-location algorithm and the least square series positioning algorithm. The effective experimental data are screened by BP neural network training method. The focal position information is fitted by least square and weighted data fusion algorithm, and the positioning results and positioning accuracy obtained by different positioning algorithms are analyzed. The software platform is designed to display the predicted source position and location results intuitively. The experimental results show that the root mean square error of underground cross positioning is 0.40m in the range of 20m*20m underground vibration monitoring, which basically meets the needs of distributed shallow underground vibration location.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：P631.4

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王國斌;利奕年;楊文東;;爆炸應(yīng)力波傳播規(guī)律與TSP基本原理分析[J];爆破;2010年02期

2 程擂;韓焱;王鑒;杜娟;;基于改進(jìn)HHT的水中爆炸沖擊波信號時頻特性分析方法[J];爆炸與沖擊;2011年03期

3 石成鋼,劉西拉;人工神經(jīng)元網(wǎng)絡(luò)在震害預(yù)測中的應(yīng)用[J];地震工程與工程振動;1991年02期

4 劉利軍;韓焱;;基于最小二乘法的牛頓迭代信源定位算法[J];彈箭與制導(dǎo)學(xué)報;2006年03期

5 田s，

本文編號：2494844