本文選題：采煤機 + 記憶截割�。� 參考：《重慶大學》2016年碩士論文

【摘要】：采煤機是綜采工作面的關鍵設備之一,是實現(xiàn)高效集約化采煤、減少井下重大惡性事故和改善工作面勞動條件的重要技術裝備。目前“三機聯(lián)動技術”已實現(xiàn)了刮板輸送機和液壓支架的聯(lián)動自動化控制,但采煤機的自動化控制還未真正實現(xiàn)。因此,采煤機的自動化、智能化、無人化控制是實現(xiàn)整個工作面自動化、智能化和無人化控制的關鍵,有必要對采煤機的自動化控制進行研究,從而為煤礦的安全、高效生產(chǎn)提供技術保障。本課題是國家重點基礎研究計劃(973計劃)(2014CB046304)研究內(nèi)容的組成部分,結合采煤機記憶截割控制技術,本文進行了采煤機自適應截割的控制研究,以實現(xiàn)采煤機滾筒高度、牽引速度和滾筒轉(zhuǎn)速的“三調(diào)控”,主要研究內(nèi)容有:(1)在詳細了解采煤機整機以及各部件的結構原理、工作原理和特性的基礎上,建立了基于記憶截割的采煤機自適應截割控制系統(tǒng)的總體架構,包括系統(tǒng)組成、系統(tǒng)控制原理和“三調(diào)控”耦合關系,最后分析了記憶截割的原理、記憶策略并建立了采煤機截割滾筒負載模型。(2)為了提高采煤機滾筒調(diào)高系統(tǒng)在調(diào)高過程中的快速性、平穩(wěn)性和準確性,找到適合井下惡劣工況下滾筒調(diào)高的控制方法,建立了采煤機滾筒調(diào)高液壓系統(tǒng)的數(shù)學模型,得到了基于偏差變量的電液比例伺服系統(tǒng)狀態(tài)空間方程,設計了變速指數(shù)趨近律的滑�？刂破饕詫崿F(xiàn)快、穩(wěn)、準而抖振小的滾筒調(diào)高過程,有效克服系統(tǒng)的不確定性、外部負載的擾動沖擊。(3)提出了基于記憶截割技術的平均煤層硬度的預測方法,在此基礎上為確定采煤機記憶跟蹤階段最優(yōu)控制參數(shù)并實現(xiàn)采煤機無人自動化采煤時滾筒截割性能綜合最優(yōu),建立了以不同性能指標為分目標的多目標優(yōu)化模型,得到了不同煤層硬度下綜合性能最優(yōu)的牽引速度和滾筒轉(zhuǎn)速,比較了傳統(tǒng)運動參數(shù)匹配方法和最優(yōu)運動參數(shù)匹配方法的優(yōu)劣,結果表明最優(yōu)運動參數(shù)動態(tài)匹配方法的采煤機滾筒多方面的截割性能都優(yōu)于傳統(tǒng)運動參數(shù)匹配方法,聯(lián)合調(diào)速優(yōu)于單一牽引調(diào)速。(4)為了實現(xiàn)采煤機的“三調(diào)控”自適應修正控制以適應記憶截割過程中煤巖狀況的變化,將截割電機電流、牽引電機電流和調(diào)高油缸油壓信號進行小波包分解處理和數(shù)據(jù)融合,通過建立煤巖截割狀態(tài)的BP神經(jīng)網(wǎng)絡識別模型對煤巖截割狀態(tài)進行識別,在此基礎上結合截割危險系數(shù),提出采煤機“三調(diào)控”的自適應修正控制策略,仿真結果表明自適應修正策略可在采煤機記憶截割過程中適應煤巖狀況的變化,保證整機的安全性和高效性。
[Abstract]:Shearer is one of the key equipments in fully mechanized coal mining face. It is an important technical equipment to realize high efficiency and intensive mining, to reduce serious accidents and to improve working conditions. At present, the "three machine linkage technology" has realized the automatic control of scraper conveyor and hydraulic support, but the automatic control of shearer has not been realized. Therefore, the automatic, intelligent and unmanned control of shearer is the key to realize the automation, intelligence and unmanned control of the whole working face. It is necessary to study the automatic control of the shearer for the safety of coal mine. Efficient production provides technical support. This subject is a part of the research content of the national key basic research plan "Yu973" (2014CB046304). Combined with the memory cutting control technology of shearer, this paper studies the control of self-adaptive cutting of shearer in order to realize the height of shearer drum. On the basis of detailed understanding of the structure, working principle and characteristics of the shearer and its components, the "three regulation" of the traction speed and the rotational speed of the drum is mainly studied. The overall structure of self-adaptive cutting control system of shearer based on memory cutting is established, including system composition, system control principle and coupling relation of "three regulation and control". Finally, the principle of memory cutting is analyzed. In order to improve the speed, stability and accuracy of the height adjustment system of the shearer drum, the control method suitable for the drum height adjustment under the bad working conditions is found, and the load model of the cutting drum of the shearer is established in order to improve the speed, stability and accuracy of the height adjustment system of the drum in the coal mining machine. The mathematical model of hydraulic system for height adjustment of shearer drum is established, the state space equation of electro-hydraulic proportional servo system based on deviation variable is obtained, and a sliding mode controller with variable speed exponential approach law is designed to realize fast and stable. In order to overcome the uncertainty of the system effectively, a prediction method of average seam hardness based on memory cutting technique is proposed for the quasi buffeting drum height adjustment process, which can effectively overcome the uncertainty of the system. On this basis, in order to determine the optimal control parameters in the memory tracking stage of shearer and to realize the comprehensive optimization of the cutting performance of the drum when the shearer is unautomated, a multi-objective optimization model with different performance indexes as the sub-objective is established. The optimal traction speed and drum speed under different coal hardness are obtained, and the advantages and disadvantages of the traditional motion parameter matching method and the optimal motion parameter matching method are compared. The results show that the cutting performance of shearer drum by dynamic matching method of optimal motion parameters is better than that of traditional motion parameter matching method. In order to realize the "three regulation" adaptive correction control of the shearer to adapt to the change of the coal and rock condition during the memory cutting process, the electric current will be cut off. The current of traction motor and the oil pressure signal of the oil cylinder are processed by wavelet packet decomposition and data fusion. Based on the BP neural network recognition model of coal and rock cutting state, the cutting state of coal and rock is identified, and the cutting hazard coefficient is combined. The adaptive correction control strategy of "three regulation" for shearer is put forward. The simulation results show that the adaptive correction strategy can adapt to the change of coal and rock condition in the process of memory cutting of shearer, and ensure the safety and high efficiency of the whole machine.
【學位授予單位】：重慶大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TD632.1

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