刮板输送机—采煤机协同调速关键技术研究

发布时间：2018-03-02 11:56

本文选题：刮板输送机　切入点：采煤机　出处：《中国矿业大学》2016年硕士论文　论文类型：学位论文

【摘要】：刮板输送机作为综采工作面的主要运输设备,受运行过程中负载变化大及恶劣工况的影响,存在故障频发、运行能耗高等问题。本文以提高刮板输送机负载平稳性为目标,研究刮板输送机和采煤机的协同调速技术,通过对刮板输送机载煤量变化规律的分析和对负载电流的动态预测,设计协同速度规划策略和调速算法,主要工作及研究成果如下:(1)在刮板输送机和采煤机配套设计基础上,给出了一种刮板输送机-采煤机的协同调速控制方案,完成了包括采煤机机载调速系统、刮板输送机机载调速系统和顺槽远程协同调速系统的刮板输送机-采煤机协同调速系统总体设计。(2)研究了刮板输送机载煤量变化的计算模型,在负载与电机电流正相关映射关系的基础上,建立了基于BP神经网络的刮板输送机负载预测模型,通过现场数据进行训练后,负载预测结果的平均绝对误差率为2.46%,为刮板输送机-采煤机协同速度调节提供了依据。(3)设计了基于粒子群多目标优化算法的刮板输送机-采煤机协同速度规划策略,将规划值作为采煤机和刮板输送机的速度跟踪目标,并采用模糊PID作为刮板输送机负载异常时刮板输送机-采煤机的速度调节算法。仿真结果表明,协同速度规划策略和调速算法可以从刮板输送机载煤量和电机电流两方面实现对刮板输送机负载平稳性的控制。2015年11月在中煤张家口煤矿机械有限公司地面试验平台上对刮板输送机-采煤机协同调速系统进行了试验,结果表明:刮板输送机-采煤机按照协同规划速度运行可使刮板输送机负载电流波动性减小61.3%,刮板输送机负载电流的预测精度达92.4%,刮板输送机-采煤机协同调速系统工作正常,提升了刮板输送机负载的平稳性。
[Abstract]:Scraper conveyor of fully mechanized working face as the main transportation equipment, the load change and the harsh conditions in the process of operation, there are frequent faults, the problem of higher energy consumption. In order to improve the stability of the scraper conveyor load as the goal, cooperative control technology research of scraper conveyor and coal mining machine, the change of the amount of coal on the scraper conveyor of the airborne analysis and dynamic prediction of the load current, speed and speed control strategy design collaborative planning algorithm, the main work and research results are as follows: (1) in scraper conveyor and shearer supporting the design basis, then the cooperative speed control scheme of a scraper conveyor - mining machine, including the completion of the coal shearer speed control system. Scraper conveyor speed control system and airborne remote collaborative mining scraper conveyor trough - speed control system for cooperative overall design of speed control system. (2) of the scraper Change the amount of coal conveying calculation model of airborne, based on the load and the motor current is related to the mapping relationship, to establish a prediction model of the load of scraper conveyor based on BP neural network, which is trained by the field data, the average absolute error of load forecasting results rate was 2.46%, and provides a basis for the scraper conveyor - shearer collaborative speed regulation. (3) design of scraper conveyor coal mining - multi-objective particle swarm optimization algorithm for cooperative velocity planning strategy based on the planning value as the shearer and conveyor speed tracking, and uses fuzzy PID as the load of scraper conveyor scraper conveyor - mining machine speed regulation algorithm is abnormal. The simulation results show that collaborative planning strategy and speed control algorithm can from two aspects of the scraper conveyor airborne coal and motor current control.2015 load stability of scraper conveyor In November on the ground test platform of Zhangjiakou Coal Mine Machinery Co., Ltd. of scraper conveyor - mining machine cooperative control system for the test, the results show that the scraper conveyor - mining machine in accordance with the collaborative planning speed can make the scraper conveyor and the fluctuation of the load current is reduced by 61.3%, the prediction accuracy of the current load of scraper conveyor 92.4%, scraper conveyor - mining cooperative control system is working properly, enhance the stability of the scraper conveyor load.

【学位授予单位】：中国矿业大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TD528.3;TD421.6

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