本文選題：采煤機(jī) + 相對(duì)定位��； 參考：《中國(guó)礦業(yè)大學(xué)》2015年碩士論文

【摘要】：綜采工作面自動(dòng)化是煤礦安全高效生產(chǎn)的重要保證,采煤機(jī)作為綜采工作面的核心裝備,其自動(dòng)控制是實(shí)現(xiàn)綜采工作面自動(dòng)化和智能化的前提條件,而采煤機(jī)自動(dòng)控制中的精確定位方法又是實(shí)現(xiàn)采煤機(jī)自動(dòng)控制的核心內(nèi)容。本文采用基于綜采工作面慣性坐標(biāo)系的采煤機(jī)慣性導(dǎo)航定位算法實(shí)現(xiàn)了采煤機(jī)的高速、精確、自主的定位,進(jìn)而通過(guò)紅外傳感器、軸編碼器以及慣性導(dǎo)航三種定位手段的融合,達(dá)到了采煤機(jī)定位準(zhǔn)確可靠的要求,在此基礎(chǔ)上利用校正策略消除了底板曲線(xiàn)形狀產(chǎn)生的定位誤差,使底板變得平整光滑,并且有效改善了推溜移架的條件。本文的主要研究?jī)?nèi)容和成果如下:1)研究了采煤機(jī)-液壓支架相對(duì)位置融合校正系統(tǒng)的控制策略,建立了采煤機(jī)-液壓支架相對(duì)位置融合校正系統(tǒng)的物理傳感體系,設(shè)計(jì)了采煤機(jī)-液壓支架相對(duì)位置融合校正系統(tǒng)的總體控制方案。2)建立了基于綜采工作面慣性坐標(biāo)系的采煤機(jī)慣性導(dǎo)航模型,分析了三種常見(jiàn)的采煤機(jī)姿態(tài)矩陣實(shí)時(shí)求解算法的性能和誤差特性,建立了采煤機(jī)慣性導(dǎo)航定位算法和融合校正系統(tǒng)的融合模型。3)設(shè)計(jì)了采煤機(jī)-液壓支架相對(duì)位置融合校正系統(tǒng)的數(shù)據(jù)存儲(chǔ)策略,利用基于自體集層次聚類(lèi)的否定選擇算法進(jìn)行了采煤機(jī)工作狀態(tài)傳感數(shù)據(jù)診斷,實(shí)現(xiàn)了失真?zhèn)鞲袛?shù)據(jù)識(shí)別。4)建立了采煤機(jī)-液壓支架相對(duì)位置的校正模型,包括采煤機(jī)的剛體運(yùn)動(dòng)學(xué)模型和底板曲線(xiàn)的獲取方法,研究了基于工作面慣性坐標(biāo)系的采煤機(jī)截割過(guò)程中的位置姿態(tài)變化,通過(guò)實(shí)時(shí)動(dòng)態(tài)校正策略實(shí)現(xiàn)了工作面底板曲線(xiàn)的修正。實(shí)驗(yàn)結(jié)果表明:采煤機(jī)-液壓支架慣性導(dǎo)航定位算法能夠克服底板曲線(xiàn)不平整帶來(lái)的累積誤差,累積定位誤差減小至0.04m左右,定位相對(duì)偏差為0.4%;基于改進(jìn)否定選擇算法的傳感數(shù)據(jù)異常診斷的平均識(shí)別率為95.2%,利用本文提出的校正策略對(duì)后滾筒截割高度進(jìn)行實(shí)時(shí)控制后,采煤機(jī)底板的截割路徑高度差由原來(lái)的0.0500米減小為0.0186米,優(yōu)化率達(dá)62.8%,標(biāo)準(zhǔn)偏差由原來(lái)的0.0247米減小為0.0057米,優(yōu)化率達(dá)76.9%,提高了底板曲線(xiàn)的平整度,顯著減小了采煤機(jī)定位的累積誤差。
[Abstract]:The automation of fully mechanized coal face is an important guarantee for the safe and efficient production of coal mine. As the core equipment of fully mechanized mining face, the automatic control is the precondition to realize the automation and intelligence of fully mechanized mining face. The accurate positioning method in automatic control of shearer is the core of automatic control of shearer. In this paper, the inertial navigation algorithm based on inertial coordinate system of fully mechanized coal mining face is used to realize the high-speed, accurate and autonomous positioning of the shearer, and then through the fusion of infrared sensor, shaft encoder and inertial navigation three kinds of positioning methods, such as infrared sensor, shaft encoder and inertial navigation, are adopted. On the basis of this, the positioning error caused by the curve shape of the bottom plate is eliminated, the bottom plate becomes smooth and smooth, and the condition of pushing and sliding frame is improved effectively. The main contents and achievements of this paper are as follows: (1) the control strategy of the relative position fusion correction system between shearer and hydraulic support is studied, and the physical sensing system of the relative position fusion correction system of shearer and hydraulic support is established. The overall control scheme of relative position fusion correction system of shearer and hydraulic support is designed. 2) the inertial navigation model of shearer based on inertial coordinate system of fully mechanized mining face is established. In this paper, the performance and error characteristics of three common real-time algorithms for calculating attitude matrix of shearer are analyzed. In this paper, the inertial navigation algorithm of shearer and the fusion model of fusion correction system. 3) the data storage strategy of relative position fusion correction system of shearer and hydraulic support is designed. The negative selection algorithm based on autologous set hierarchical clustering is used to diagnose the working state sensing data of shearer, and the distortion sensing data recognition. 4) the relative position correction model of shearer and hydraulic support is established. Including the rigid body kinematics model of shearer and the method of obtaining the curve of bottom plate, the change of position and attitude in the cutting process of shearer based on the working face inertial coordinate system is studied. The correction of the floor curve of the working face is realized by the real-time dynamic correction strategy. The experimental results show that the inertial navigation algorithm of the shearer and hydraulic support can overcome the accumulated error caused by the uneven curve of the bottom plate, and the cumulative positioning error is reduced to about 0.04m. The average recognition rate of abnormal diagnosis of sensor data based on the improved negative selection algorithm is 95.2. The correction strategy proposed in this paper is used to control the cutting height of the back drum in real time. The cutting path height difference of the shearer's bottom plate is reduced from 0.0500 meters to 0.0186 meters, the optimization rate is 62.8, the standard deviation is reduced from 0.0247 meters to 0.0057 meters, and the optimization rate is 76.9, which improves the flatness of the bottom plate curve. The cumulative error of shearer positioning is significantly reduced.
【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】：2015
【分類(lèi)號(hào)】：TD421.6

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本文編號(hào)：1934441