基于记忆截割的采煤机自适应截割控制研究

发布时间：2018-06-07 18:36

本文选题：采煤机 + 记忆截割　；参考：《重庆大学》2016年硕士论文

【摘要】：采煤机是综采工作面的关键设备之一,是实现高效集约化采煤、减少井下重大恶性事故和改善工作面劳动条件的重要技术装备。目前“三机联动技术”已实现了刮板输送机和液压支架的联动自动化控制,但采煤机的自动化控制还未真正实现。因此,采煤机的自动化、智能化、无人化控制是实现整个工作面自动化、智能化和无人化控制的关键,有必要对采煤机的自动化控制进行研究,从而为煤矿的安全、高效生产提供技术保障。本课题是国家重点基础研究计划(973计划)(2014CB046304)研究内容的组成部分,结合采煤机记忆截割控制技术,本文进行了采煤机自适应截割的控制研究,以实现采煤机滚筒高度、牵引速度和滚筒转速的“三调控”,主要研究内容有:(1)在详细了解采煤机整机以及各部件的结构原理、工作原理和特性的基础上,建立了基于记忆截割的采煤机自适应截割控制系统的总体架构,包括系统组成、系统控制原理和“三调控”耦合关系,最后分析了记忆截割的原理、记忆策略并建立了采煤机截割滚筒负载模型。(2)为了提高采煤机滚筒调高系统在调高过程中的快速性、平稳性和准确性,找到适合井下恶劣工况下滚筒调高的控制方法,建立了采煤机滚筒调高液压系统的数学模型,得到了基于偏差变量的电液比例伺服系统状态空间方程,设计了变速指数趋近律的滑模控制器以实现快、稳、准而抖振小的滚筒调高过程,有效克服系统的不确定性、外部负载的扰动冲击。(3)提出了基于记忆截割技术的平均煤层硬度的预测方法,在此基础上为确定采煤机记忆跟踪阶段最优控制参数并实现采煤机无人自动化采煤时滚筒截割性能综合最优,建立了以不同性能指标为分目标的多目标优化模型,得到了不同煤层硬度下综合性能最优的牵引速度和滚筒转速,比较了传统运动参数匹配方法和最优运动参数匹配方法的优劣,结果表明最优运动参数动态匹配方法的采煤机滚筒多方面的截割性能都优于传统运动参数匹配方法,联合调速优于单一牵引调速。(4)为了实现采煤机的“三调控”自适应修正控制以适应记忆截割过程中煤岩状况的变化,将截割电机电流、牵引电机电流和调高油缸油压信号进行小波包分解处理和数据融合,通过建立煤岩截割状态的BP神经网络识别模型对煤岩截割状态进行识别,在此基础上结合截割危险系数,提出采煤机“三调控”的自适应修正控制策略,仿真结果表明自适应修正策略可在采煤机记忆截割过程中适应煤岩状况的变化,保证整机的安全性和高效性。
[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.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TD632.1

【相似文献】