采煤机截割振动信号采集系统的研究

发布时间：2018-03-16 16:52

本文选题：采煤机　切入点：煤岩识别　出处：《煤炭科学研究总院》2017年硕士论文　论文类型：学位论文

【摘要】：煤岩界面识别技术使采煤机在截割作业时具有自动追踪煤岩界面的能力,即采煤机按照顶板和底板的变化规律或者按照人们设定的规律自动调节采煤机滚筒高度。可靠的识别系统有巨大的经济效益以及安全价值,能提高煤层回采率;减少矸石、硫等成分的含量,提高原煤质量;减少设备磨损,延长机器寿命,提高设备可靠性;减少工作面工人数量,实现"无人跟机作业"的开采场景,实现煤矿区采煤工作面智能化开采。大量学者对基于振动信号的煤岩界面自动识别技术进行研究,但尚未有成熟的产品很好的满足采煤工作面的实际需求。由于实验条件以及现实情况的限制,导致很多方法都停留在实验室以及理论层面,未能把理论与实践很好的结合在一起。鉴于此本文依托煤机企业与煤矿企业的优势,研制了新型采煤机摇臂截割振动信号采集与识别装置,与采煤机电控系统通讯,采集采煤机不同负载时振动信号并关联存储采煤机实时工况信息。本文叙述了采煤机的工作原理、分析了采煤机滚筒破煤原理,利用采煤机截割振动信号采集与识别装置采集采煤机截割作业时,摇臂振动信号并进行分析与处理,得出:采煤机截割负载类型变化时,Y轴方向振动信号最为敏感;通过归一化处理后,振动信号时域特征值有短时能量、时域峭度指标及短时过零率;振动信号频域特征值有信号倒频谱距离Dcep,及第一 Mel尺度滤波器的Mel尺度倒谱系数MFCC。论文完成的主要工作和结论:(1)详细地论述了基于振动信号的煤岩界面识别技术研究现状,指出实现智能化开采、工作面无人化的煤矿生产要求亟需综采设备采煤机煤岩界面自动识别技术,提出了基于采煤机截割特性分析的研究内容、方案及技术路线。(2)在研究采煤机振动信号产生机理与传播特性的基础上,研制了新型采煤机振动信号采集与识别装置,采集装置安装处采煤机三轴振动信号,在MG900/2400-WD采煤机上测试,采集并记录了大量高精度数据。(3)利用采煤机截割振动信号采集与识别装置获取的采煤机状态信息,利用数字信号处理技术,对振动信号进行时域、频域波形分析,振动特性与割煤、割岩工况下的测试数据分析,负载与振动信号时域、频域特征值提取以及不同工况下的时域与频域特征对比分析,确定时域、频域特征值完成对采煤机截割负载的识别。最后,对论文的主要研究工作和创新性成果进行了总结,并对下一步的研究工作进行了展望。
[Abstract]:The coal and rock interface recognition technology enables the shearer to track the coal and rock interface automatically during cutting operation. That is, the shearer automatically adjusts the height of the shearer drum according to the changing law of roof and floor or according to the law set by people. A reliable recognition system has great economic benefit and safety value, it can improve coal seam recovery rate and reduce gangue. The content of sulfur and other components can improve the quality of raw coal, reduce the wear of equipment, prolong the life of the machine, improve the reliability of the equipment, reduce the number of working face workers, and realize the mining scene of "unattended machine working". The intelligent mining of coal face in coal mining area is realized. A large number of scholars have studied the automatic recognition technology of coal and rock interface based on vibration signal. However, there are not mature products to meet the actual needs of coal mining face. Due to the limitations of experimental conditions and practical conditions, many methods remain in the laboratory and theoretical level. In view of the advantages of coal mining enterprises and coal mining enterprises, a new type of shearer rocker cutting vibration signal acquisition and identification device is developed, which communicates with the shearer electric control system. The vibration signals of shearer under different loads are collected and stored in real time. The working principle of shearer is described in this paper, and the principle of breaking coal in drum of shearer is analyzed. The vibration signal of rocker arm is collected, analyzed and processed by means of the vibration signal acquisition and identification device of shearer cutting. It is concluded that the vibration signal of Y axis is the most sensitive when the cutting load type of shearer changes; After normalization, the time domain eigenvalues of vibration signals have short time energy, time domain kurtosis index and short time zero crossing rate. The frequency domain eigenvalues of vibration signal include signal cepstrum distance, and Mel scale cepstrum coefficient of the first Mel scale filter. The main work and conclusion of this paper are discussed in detail. The research status of coal and rock interface recognition technology based on vibration signal is discussed in detail. It is pointed out that the automatic recognition technology of coal and rock interface of fully mechanized mining equipment shearer is urgently needed to realize intelligent mining and no man made coal face production, and the research content based on cutting characteristic analysis of shearer is put forward. On the basis of studying the mechanism of vibration signal generation and propagation characteristics of shearer, a new type of vibration signal acquisition and identification device for shearer is developed, and the three-axis vibration signal of shearer is installed in the collecting device. A large number of high precision data are collected and recorded on MG900/2400-WD shearer. The state information of shearer is acquired by means of cutting vibration signal acquisition and identification device. The vibration signal is processed in time domain by digital signal processing technology. Frequency domain waveform analysis, vibration characteristic and coal cutting, test data analysis under rock cutting condition, load and vibration signal time domain, frequency domain eigenvalue extraction and contrast analysis of time domain and frequency domain characteristic under different working conditions are determined. The characteristic value in frequency domain is used to identify the cutting load of shearer. Finally, the main research work and innovative achievements are summarized, and the future research work is prospected.
【学位授予单位】：煤炭科学研究总院
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TD632.1

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