【摘要】：安全是煤礦生產(chǎn)的第一要務,但煤礦的特殊工作環(huán)境導致安全隱患依然存在。煤礦井下人員定位技術(shù)能對井下工作人員實時定位,特別是當?shù)V難發(fā)生時,能為救援工作提供重要的位置信息,提高了救援效率�；诖�,本文在分析現(xiàn)有一些人員定位算法基礎(chǔ)上,對基于位置指紋的定位算法進行了研究,并提出了改進的算法。首先,本文分析了幾種常用的定位技術(shù)以及它們在煤礦井下應用的可行性,得出基于位置指紋的定位技術(shù)更加適合在煤礦井下使用。由于位置指紋定位算法是基于信號強度的,本文分析了信號在井下傳播的特點,以及信號的多徑效應對定位的影響。并指出了指紋定位中的關(guān)鍵問題,為下面的算法研究打下基礎(chǔ)。其次,針對礦井巷道狹長的特點,本文引入?yún)^(qū)域劃分的思想,利用井下實驗得到的數(shù)據(jù)確定區(qū)域閾值,將被定位區(qū)域均勻劃分為多個子區(qū)域,在進行定位時,根據(jù)終端接收的信號強度判斷出終端所在的子區(qū)域,在子區(qū)域內(nèi)用位置指紋算法對其進行精確定位。最后,通過對K鄰近法和貝葉斯匹配算法的優(yōu)缺點進行分析,提出了一種加權(quán)K-Bayes定位匹配方法。此算法先采用加權(quán)歐式距離計算出符合條件的K個位置參考點,然后通過設(shè)定閾值排除偏差較大參考點的影響,緊接著通過貝葉斯方法計算出剩余參考點處的概率,對結(jié)果進行加權(quán)處理,并通過實驗證明了該算法的可行性。
[Abstract]:Safety is the most important task in coal mine production, but the safety hidden danger still exists due to the special working environment of coal mine. The technology can locate the underground workers in real time, especially when the mine accident occurs, it can provide the important position information for the rescue work, and improve the rescue efficiency. In this paper, based on the analysis of some existing location algorithms, the location algorithm based on location fingerprint is studied, and an improved algorithm is proposed. Firstly, this paper analyzes several common positioning techniques and the feasibility of their application in underground coal mines, and concludes that the location fingerprint based positioning technology is more suitable for use in coal mines. Because the location fingerprint location algorithm is based on the signal intensity, this paper analyzes the characteristics of the signal propagation in the underground and the influence of the multi-path effect of the signal on the location. The key problem of fingerprint location is pointed out, which lays a foundation for the following algorithm research. Secondly, in view of the long and narrow characteristics of mine roadway, this paper introduces the idea of regional division, using the data obtained from underground experiments to determine the regional threshold, and divides the location area into multiple sub-areas evenly. According to the signal strength received by the terminal, the sub-region of the terminal is determined, and the location fingerprint algorithm is used to locate the sub-region accurately. Finally, by analyzing the advantages and disadvantages of K-neighborhood method and Bayesian matching algorithm, a weighted K-Bayes location matching method is proposed. In this algorithm, the weighted Euclidean distance is used to calculate the K position reference points, and then the probability of the remaining reference points is calculated by the Bayesian method by setting a threshold to exclude the influence of large deviation reference points. The results are weighted and the feasibility of the algorithm is proved by experiments.
【學位授予單位】：中國礦業(yè)大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TD65

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本文編號：2381222