基于刮板输送机负载预测的采煤机调速技术研究

发布时间：2018-11-22 06:19

【摘要】：随着煤炭开采技术的不断发展和进步,提高综采工作面的自动化水平是煤矿实现高效安全生产的关键。采煤机和刮板输送机作为综采工作面生产和运输的关键机电装备,提高其协同工作性能和可靠性是实现综采自动化的主要问题。为解决采煤机不合理运行导致的刮板输送机负载变化大甚至出现过载运行的问题,本文以采煤机和刮板输送机的协同控制关键技术为研究目标,在对刮板输送机负载预测的基础上,提出了一种刮板输送机/采煤机协同控制策略,开发了基于刮板输送机负载预测的采煤机调速系统。论文主要研究内容如下:(1)基于刮板输送机负载预测的采煤机调速系统总体架构设计。在确定基于刮板输送机负载预测的采煤机调速系统功能的基础上,完成了顺槽PLC控制器、刮板输送机机头机尾PLC控制器、采煤机机载PLC控制器和组合开关PLC控制器之间的集成设计与网络组态。(2)刮板输送机的负载预测及仿真。通过分析刮板输送机负载与电机电流的映射关系,选用小波神经网络建立刮板输送机负载的预测模型,对刮板输送机负载电流这一关键特征参数进行预测。(3)基于刮板输送机负载预测的采煤机调速策略研究。利用模糊逻辑对刮板输送机的负载状态进行模糊划分,建立刮板输送机负载状态判定模型,确定刮板输送机不同负载状态下采煤机速度的调节区间。在规定的速度区间内,利用Elman神经网络对采煤机进行调速。本课题研制的基于刮板输送机负载预测的采煤机调速系统在阳煤集团二矿71507综采工作面进行了相关工业性试验,试验结果表明该系统达到了预期功能,为实现采煤机和刮板输送机的协同控制奠定了基础。
[Abstract]:With the continuous development and progress of coal mining technology, improving the automation level of fully mechanized mining face is the key to realize high efficiency and safety production in coal mine. Shearer and scraper conveyor are the key mechanical and electrical equipment in the production and transportation of fully mechanized mining face. It is the main problem to realize the automation of fully mechanized mining to improve the cooperative working performance and reliability of shearer and scraper conveyor. In order to solve the problem that the load of scraper conveyer changed greatly or even overloaded caused by the unreasonable operation of shearer, the key technology of collaborative control between shearer and scraper conveyor is taken as the research goal in this paper. Based on the load prediction of scraper conveyer, this paper puts forward a cooperative control strategy of scraper conveyor / shearer, and develops a speed regulating system of shearer based on load prediction of scraper conveyor. The main contents of this paper are as follows: (1) the overall structure design of speed regulation system of shearer based on load prediction of scraper conveyor. On the basis of determining the function of speed regulation system of shearer based on load prediction of scraper conveyer, the PLC controller with slot and the PLC controller with head and tail of scraper conveyor are completed. Integrated design and network configuration between airborne PLC controller and combined switch PLC controller of shearer. (2) load prediction and simulation of scraper conveyor. By analyzing the mapping relationship between scraper conveyor load and motor current, wavelet neural network is used to establish the load prediction model of scraper conveyor. The load current of scraper conveyor is predicted as a key characteristic parameter. (3) the speed regulation strategy of shearer based on load prediction of scraper conveyor is studied. The load state of scraper conveyor is divided by fuzzy logic, and the model of judging load state of scraper conveyor is established, and the regulating interval of shearer speed under different load state of scraper conveyor is determined. In the specified speed range, the Elman neural network is used to speed the shearer. Based on the load prediction of scraper conveyer, the shearer speed regulation system has been tested in No. 71507 fully mechanized coal face of No. 2 Coal Mine. The test results show that the system has achieved the expected function. It lays a foundation for the cooperative control of shearer and scraper conveyor.
【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TD421.6

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