本文關(guān)鍵詞： 礦井人員定位 小波包 支持向量機 動作識別 虛擬儀器　出處：《吉林大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：煤炭是世界各國的支柱型能源,我國屬于煤炭大國,煤炭產(chǎn)量高居世界前列,但國內(nèi)中小型煤礦普遍存在井下環(huán)境復(fù)雜、條件差且巷道狹窄等安全隱患問題,并且井上管理人員不能及時了解井下作業(yè)人員的運行軌跡及實時位置,一旦發(fā)生礦井事故導(dǎo)致人員被困,救援隊伍會因不能及時掌握井下被困人員位置而難以展開工作,對救援工作是十分不利的。本文基于國內(nèi)現(xiàn)有礦井人員定位系統(tǒng)定位精度低及成本高昂等問題,提出了一種基于動作識別的礦井人員定位系統(tǒng),該系統(tǒng)的工作機制如下:井下人員需佩戴數(shù)據(jù)采集單元,將采集到的數(shù)據(jù)信號通過藍牙模塊傳輸給上位機軟件系統(tǒng),上位機軟件系統(tǒng)采用小波包特征提取及支持向量機(SVM,Support Vector Machine)分類算法確定人員的動作類型(包括走步、跑步、站立),再依據(jù)Y軸加速度信號數(shù)據(jù)的波峰數(shù)得到人員動作的數(shù)量,事先輸入井下人員的步行步幅及跑步步幅,從而通過計算確定井下人員的運行距離,同時根據(jù)電子羅盤判定人員是否轉(zhuǎn)彎,確定出井下人員的運行軌跡,并結(jié)合射頻識別(RFID,Radio Frequency Identification)作為誤差校正時使用,最后比對井下平面圖確定人員位置。具體的研究內(nèi)容分為如下幾個方面:首先,研究人員步行的周期性狀態(tài)及其特點,由此得出數(shù)據(jù)采集單元的最佳佩戴位置,并對采集到的數(shù)據(jù)信號進行觀察分析,確定采用小波包特征提取方法來處理信號數(shù)據(jù),提取人員動作信號的特征向量。其次,對系統(tǒng)中的關(guān)鍵技術(shù)進行了簡單介紹,并對動作信號進行時頻分析,確定了系統(tǒng)核心算法采用小波包特征提取及支持向量機分類的方法,為系統(tǒng)提供了理論基礎(chǔ)。再次,本系統(tǒng)采用支持向量機分類器來區(qū)分人員的動作類別,其分類依據(jù)為動作信號的能量特征向量,因為人員在做不同動作時會產(chǎn)生不同的振動能量。將通過小波包特征提取到的能量特征向量送入SVM中進行數(shù)據(jù)訓(xùn)練和分類,以此來實現(xiàn)人員動作類型的判定。最后,設(shè)計了一套礦井人員定位系統(tǒng),由數(shù)據(jù)采集單元及上位機軟件系統(tǒng)兩大部分組成。數(shù)據(jù)采集單元由三軸陀螺儀、電子羅盤、藍牙通信模塊、三軸向加速度計及單片機最小系統(tǒng)組成,完成對人員動作信號的采集傳輸功能;上位機軟件系統(tǒng)從虛擬儀器的角度出發(fā),采用Lab VIEW及MATLAB語言編寫,完成對信號數(shù)據(jù)存儲、算法應(yīng)用、數(shù)據(jù)處理及井下人員定位等功能。
[Abstract]:Coal is the pillar energy of all countries in the world. Our country belongs to the big coal country, and the coal output is high in the world. However, the underground environment is complex, the condition is poor and the roadway is narrow and so on. And the well management personnel can not understand the operation trajectory and real-time location of underground operators in time, once the mine accidents lead to people trapped. Rescue team can not grasp the location of trapped underground workers in time and difficult to start work, which is very unfavorable to rescue work. This paper based on the problems of low positioning accuracy and high cost of the existing mine personnel positioning system in China. A mine personnel positioning system based on action recognition is proposed. The working mechanism of the system is as follows: underground personnel need to wear data acquisition unit. The collected data signal is transmitted to the upper computer software system through Bluetooth module. The upper computer software system adopts wavelet packet feature extraction and support vector machine (SVM). The Support Vector Machine classification algorithm determines the movement type of the person (including walking, running, standing). Then according to the Y-axis acceleration signal data of the number of peaks to get the number of personnel action, and input in advance the walking and running stride of the underground personnel, so as to determine the operating distance of the underground personnel by calculation. At the same time, according to the electronic compass to determine whether the personnel turn, determine the trajectory of the underground personnel, and combined with RFID RFID. The Radio Frequency Identification is used as an error correction. Finally, compared with the underground plan to determine the location of personnel. The specific research content can be divided into the following aspects: first, the periodic state and characteristics of the walking of the researchers, from which the data acquisition unit of the best wearing position. And the collected data signal is observed and analyzed, the wavelet packet feature extraction method is adopted to process the signal data and extract the characteristic vector of the human action signal. Secondly. The key technology of the system is introduced briefly, and the time-frequency analysis of the action signal is carried out, and the method of wavelet packet feature extraction and support vector machine classification for the core algorithm of the system is determined. Third, the support vector machine classifier is used to distinguish the category of action, which is based on the energy feature vector of the action signal. Because people will produce different vibration energy when they do different actions, the energy feature vector extracted by wavelet packet feature will be sent into SVM for data training and classification. Finally, a mine personnel positioning system is designed, which consists of two parts: data acquisition unit and PC software system. The data acquisition unit is composed of three-axis gyroscope. Electronic compass, Bluetooth communication module, triaxial accelerometer and the minimum system of single chip microcomputer, complete the collection and transmission of human action signal; From the point of view of virtual instrument, the upper computer software system uses Lab VIEW and MATLAB language to complete the functions of signal data storage, algorithm application, data processing and downhole personnel positioning.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TD76

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