本文選題：液壓支架運行 + 液壓支架供液模型��； 參考：《太原理工大學(xué)》2017年博士論文

【摘要】：隨著煤炭工業(yè)由數(shù)字礦山向智慧礦山轉(zhuǎn)變,實現(xiàn)綜采工作面智能化成為煤礦生產(chǎn)安全、高效的關(guān)鍵技術(shù)。為保證采煤機、液壓支架(以下簡稱“支架”)和刮板輸送機三機協(xié)同運行,支架供液系統(tǒng)起到了重要作用,其智能化程度也成為智能開采的核心技術(shù)之一。因此,有必要對供液系統(tǒng)智能控制技術(shù)進行研究,保障支架運行的跟機速度,穩(wěn)定液壓系統(tǒng)壓力波動,為液壓支架安全高效運行提供技術(shù)保障。論文以支架運行過程不同動作供液需求特征為研究起點,以支架運行自適應(yīng)智能供液研究為目標(biāo),借鑒高等人工智能理論與技術(shù)成果,采用了現(xiàn)場供液壓力信號實測與特征分析、支架供液地面試驗系統(tǒng)構(gòu)建、支架運行供液理論分析與建模仿真、供液系統(tǒng)智能控制模型框架設(shè)計、供液基礎(chǔ)控制設(shè)計與實現(xiàn)、穩(wěn)壓供液人工神經(jīng)網(wǎng)絡(luò)預(yù)測、支架供液多目標(biāo)規(guī)劃設(shè)計與算法仿真、井下工業(yè)性試驗一整套的技術(shù)路線與方法,展開支架運行自適應(yīng)智能供液研究,研發(fā)了完整的智能供液系統(tǒng)并進行了井下工業(yè)性試驗,試驗結(jié)果證明了本論文研究成果的有效性,主要成果如下:(1)采集井下支架實際運行過程液壓系統(tǒng)壓力數(shù)據(jù),分析其供液過程特征及其和支架動作之間的關(guān)系和特點,設(shè)計了支架供液試驗系統(tǒng),以此為基礎(chǔ)建立了支架液壓系統(tǒng)AMESim仿真模型。通過仿真模型同地面試驗系統(tǒng)以及真實支架運行數(shù)據(jù)的對比,驗證了仿真模型的正確性。在此基礎(chǔ)上,基于仿真模型進行了支架具體動作過程和支架跟機運行過程的仿真模擬,提出了基于支架動作過程的穩(wěn)壓供液和適應(yīng)支架運行過程的智能供液新思路。(2)探討供液系統(tǒng)的功能需求與控制目標(biāo),提出以“安全可靠、有序協(xié)調(diào)、穩(wěn)壓提速、智能規(guī)劃”為理念的逐級智能供液控制目標(biāo)。在此基礎(chǔ)上,依據(jù)高等人工智能理論,提出基于感知-動作的自動化技術(shù)、基于神經(jīng)網(wǎng)絡(luò)的供液智能化預(yù)測技術(shù)和基于多目標(biāo)規(guī)劃的智能供液技術(shù)的供液系統(tǒng)智能控制模型的總體框架。(3)針對論文提出智能供液總體框架,論文首先重點研究了供液系統(tǒng)控制層的關(guān)鍵技術(shù):提出基于SPC的溫度監(jiān)控方法,實現(xiàn)乳化液泵溫度保護控制,以保障乳化液泵等關(guān)鍵設(shè)備更好的服務(wù)于供液的智能控制;提出并設(shè)計了調(diào)節(jié)供液流量的控制層邏輯,實現(xiàn)自適應(yīng)供液的基礎(chǔ)控制技術(shù),并進行了地面試驗驗證。上述研究內(nèi)容為智能供液提供了控制層基礎(chǔ)。(4)圍繞支架具體動作過程的穩(wěn)壓供液理論,通過將神經(jīng)網(wǎng)絡(luò)嵌入智能控制模型,實現(xiàn)了基于支架動作過程的穩(wěn)壓供液預(yù)測。論文利用試驗數(shù)據(jù)建立了穩(wěn)壓供液流量與支架動作類型、動作行程、動作數(shù)量和壓力限制的神經(jīng)網(wǎng)絡(luò)回歸模型,實現(xiàn)了穩(wěn)壓供液流量的預(yù)測輸出。并進行了地面試驗驗證,同時根據(jù)穩(wěn)壓供液試驗,確立了支架動作時間參數(shù),該研究為智能供液控制提供了必要的初值條件。(5)研究了支架供液與支架跟機速度、支架動作時間、泵組動作時間之間的約束關(guān)系,建立了供液智能控制的多目標(biāo)規(guī)劃模型,為支架自動控制的時間設(shè)定提供了依據(jù)。圍繞工作面支架自適應(yīng)智能供液,論文提出了智能供液策略規(guī)劃問題,建立了極速模式和優(yōu)化模式的雙層規(guī)劃數(shù)學(xué)模型,仿真計算證明了供液策略規(guī)劃效果。設(shè)計智能供液控制的物理符號系統(tǒng),將其嵌入智能控制模型,實現(xiàn)支架運行自適應(yīng)智能供液,地面試驗驗證了預(yù)期的控制效果。在對工作面支架供液系統(tǒng)智能控制技術(shù)研究的基礎(chǔ)上,研發(fā)了工作面智能供液系統(tǒng)。該系統(tǒng)在潞安集團王莊礦8110綜采工作面進行了工業(yè)性試驗,試驗結(jié)果表明:該系統(tǒng)基本實現(xiàn)了支架運行自適應(yīng)智能供液控制,供液運行技術(shù)指標(biāo)達到了預(yù)期要求。本論文研究成果對于提高供液系統(tǒng)智能化水平,對實現(xiàn)智能化開采具有重要意義。
[Abstract]:With the change of the coal industry from the digital mine to the intelligent mine, realizing the intelligentization of the fully mechanized mining face becomes the key technology of the coal mine production safety and high efficiency. In order to ensure the coal mining machine, the hydraulic support (hereinafter referred to as "the support") and the scraper conveyor three machines, the support fluid system has played an important role, and its intelligentized degree is also intelligent. Therefore, it is necessary to study the intelligent control technology of the liquid supply system, ensure the speed of the running of the support, stabilize the pressure fluctuation of the hydraulic system, and provide the technical guarantee for the safe and efficient operation of the hydraulic support. In order to adapt to the research of intelligent fluid supply, using the theory and technical achievements of higher artificial intelligence, the field supply fluid pressure signal measurement and characteristic analysis are adopted, the support fluid ground test system is constructed, the theoretical analysis and modeling simulation of the support fluid supply for the support are established, the intelligent control model frame of the liquid supply system is designed, the design and Realization of the fluid foundation control are made and the stability is stable. Artificial neural network prediction of pressure supply fluid, multi-objective programming design and algorithm simulation of support fluid, a complete set of technical route and method in downhole industrial test, research on self-adaptive intelligent fluid supply for support operation, developed a complete intelligent liquid supply system and carried out a downhole industrial test. The results of the experiment prove the results of this paper. The main results are as follows: (1) collect the pressure data of the hydraulic system in the actual running process of the downhole support, analyze the characteristics of the fluid supply process and the relationship between the support and the support action, and design the support fluid test system. On this basis, the AMESim simulation model of the support hydraulic system is established. The simulation model is the same as the ground test system. On the basis of the simulation model, the simulation model is simulated on the basis of the simulation model. Based on the simulation model, a new idea of intelligent fluid supply for the steady pressure supply and the running process of the support frame based on the support action process is proposed. (2) the discussion is made. The function demand and control target of the liquid system, and put forward the target of intelligent liquid supply control with the concept of "safe and reliable, orderly coordination, steady pressure and speed raising, intelligent planning". On this basis, based on the theory of higher artificial intelligence, this paper puts forward the automation technology based on perception action, based on neural network and based on the intelligent prediction technology of liquid supply and based on neural network. The overall framework of the intelligent control model of the liquid supply system for multi-objective programming. (3) aiming at the overall framework of intelligent liquid supply for the paper, the key technology of the control layer of the liquid supply system is studied in this paper. The temperature monitoring method based on SPC is put forward to realize the temperature protection control of the emulsion pump, so as to ensure the key of the emulsion pump. The equipment is better serving the intelligent control of the liquid supply, and the control layer logic regulating the flow flow is proposed and designed to realize the basic control technology of the adaptive fluid supply, and the ground test verification is carried out. The above research content provides the control layer for the intelligent fluid supply. (4) the theory of steady pressure feeding around the concrete action process of the support frame, through will The neural network is embedded with the intelligent control model to realize the steady pressure supply prediction based on the action process of the scaffold. The paper uses the experimental data to establish the neural network regression model of the pressure supply flow and the type of support action, the movement stroke, the number of action and the pressure limit, and realizes the prediction output of the steady pressure flow flow rate. At the same time, the time parameters of the support are established according to the test of steady pressure supply. The study provides the necessary initial value conditions for the intelligent fluid supply control. (5) the constraint relationship between the support fluid and the support speed of the support, the action time of the support and the action time of the pump group is studied, and the multi-objective programming model of the intelligent control of the fluid supply is established. The time setting of the frame automatic control provides the basis. Around the self-adaptive intelligent feeding of the working face support, the paper puts forward the problem of intelligent liquid supply strategy planning, establishes a double-layer programming mathematical model of the speed mode and the optimization model. The simulation calculation proves the effect of the planning of the liquid supply strategy. The intelligent control model is embedded to realize the self-adaptive intelligent feeding of the support, and the ground test verifies the expected control effect. On the basis of the research on the intelligent control technology of the working face support liquid supply system, the intelligent water supply system of the working face is developed. The system has carried out the industrial test in the Wang Zhuangkuang 8110 fully mechanized face of Lu'an Group, and the test is carried out. The results show that the system basically realizes the self-adaptive intelligent liquid supply control for the running of the support, and the technical indexes of the supply liquid have reached the expected requirements. The research results of this paper are of great significance for improving the intelligent level of the liquid supply system and realizing the intelligent mining.

【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：TD67;TD355.4

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