【摘要】：由于我國(guó)煤礦環(huán)境復(fù)雜，條件特殊，井上無(wú)法實(shí)時(shí)掌握井下人員的位置信息。特別是當(dāng)煤礦井下發(fā)生災(zāi)害后，搜救工作難以開(kāi)展。另一方面，在我國(guó)發(fā)生的特大煤礦事故中，有很大比例是由環(huán)境因素造成的。但是，目前的監(jiān)控系統(tǒng)對(duì)于礦井工人來(lái)說(shuō)都是被動(dòng)感知。因此，本文結(jié)合這兩種情況，從煤礦物聯(lián)網(wǎng)應(yīng)用出發(fā)，結(jié)合感知礦山建設(shè)的核心問(wèn)題，設(shè)計(jì)了智能定位終端，，對(duì)人員進(jìn)行實(shí)時(shí)定位，同時(shí)感知井下人員周圍的環(huán)境。 結(jié)合煤礦物聯(lián)網(wǎng)應(yīng)用模型，比較現(xiàn)有無(wú)線通信方案，確定采用Wi-Fi無(wú)線技術(shù)，介紹基于Wi-Fi的定位方法，并且確定了基于RSSI的定位方法。設(shè)計(jì)了智能定位系統(tǒng)架構(gòu)圖，并對(duì)軟硬件進(jìn)行設(shè)計(jì)實(shí)現(xiàn)。 分析了煤礦巷道下無(wú)線信號(hào)的傳播情況，為定位算法的研究提供了基礎(chǔ)。為實(shí)現(xiàn)井下全覆蓋的定位功能，在位置指紋技術(shù)的基礎(chǔ)上，研究了全覆蓋的定位算法。在建立指紋庫(kù)時(shí)，采用高斯模型對(duì)采樣數(shù)據(jù)進(jìn)行修正。在實(shí)時(shí)定位階段，采用經(jīng)典的K鄰近匹配算法，并采用基于時(shí)間的補(bǔ)償算法進(jìn)行修正。根據(jù)實(shí)際應(yīng)用情況，提出了補(bǔ)充盲區(qū)定位算法。將盲區(qū)定義為半盲區(qū)和全盲區(qū)，對(duì)半盲區(qū)提出線性插值預(yù)測(cè)算法，對(duì)全盲區(qū)提出了基于歷史運(yùn)動(dòng)的預(yù)測(cè)模型，并進(jìn)行仿真驗(yàn)證。實(shí)驗(yàn)證明，在盲區(qū)中，最大定位誤差為8.7米。
[Abstract]:Because of the complex environment and special conditions in coal mines in our country, it is impossible to grasp the location information of underground personnel in real time. Especially when the underground coal mine disaster, search and rescue work is difficult to carry out. On the other hand, a large proportion of coal mine accidents in China are caused by environmental factors. However, the current monitoring system for mine workers are passive perception. Therefore, combining these two situations, starting from the application of the Internet of things in coal mines, combining with the core problems in the construction of perceptual mines, the intelligent positioning terminal is designed to locate the personnel in real time, and at the same time to perceive the surrounding environment of the personnel in the mine. Combined with the application model of Internet of things in coal mine, this paper compares the existing wireless communication schemes, determines the use of Wi-Fi wireless technology, introduces the positioning method based on Wi-Fi, and determines the location method based on RSSI. The architecture diagram of intelligent positioning system is designed, and the software and hardware are designed and implemented. The transmission of wireless signal under coal mine roadway is analyzed, which provides the foundation for the research of localization algorithm. In order to realize the location function of downhole full coverage, the location algorithm of full cover is studied on the basis of location fingerprint technology. In the establishment of fingerprint database, the Gao Si model is used to modify the sampled data. In the phase of real-time localization, the classical K-neighborhood matching algorithm is adopted, and the time-based compensation algorithm is used to correct it. According to the practical application, a supplementary blind area location algorithm is proposed. The blind area is defined as the half blind area and the full blind area. The linear interpolation prediction algorithm is proposed for the half blind area. The prediction model based on historical motion for the full blind area is proposed and verified by simulation. Experimental results show that the maximum positioning error is 8.7 meters in the blind area.
【學(xué)位授予單位】：中國(guó)礦業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5;TP391.44

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