CAI Yusheng, DENG Shijian, XU Jingyu, GAO Xu. Load measurement method of vertical shaft construction hoisting system based on torque current[J]. Journal of Mine Automation, 2019, 45(12): 35-39. DOI: 10.13272/j.issn.1671-251x.2019050047
Citation: CAI Yusheng, DENG Shijian, XU Jingyu, GAO Xu. Load measurement method of vertical shaft construction hoisting system based on torque current[J]. Journal of Mine Automation, 2019, 45(12): 35-39. DOI: 10.13272/j.issn.1671-251x.2019050047

Load measurement method of vertical shaft construction hoisting system based on torque current

More Information
  • At present, load measurement method of mine hoisting system is mainly to measure load by adding a weighing sensor at the bottom of the shaft, but this method cannot be applied to vertical shaft construction hoisting system.The method of measuring hoisting load by analyzing functional relationship between wire rope tension and load has realized dynamic measurement of load. However, it is difficult to solve measurement accuracy problem caused by sensor installation and plastic deformation of wire rope itself, which brings hidden danger of safety. To solve the above problems, in view of situation that electric drive system of hoisting system is AC/AC inverter vector control of asynchronous motor, a hoisting load measurement method based on torque current was proposed according to torque current can be directly output by inverter. By establishing mathematical model and dynamic analysis of hoisting system, correlation between torque current and hoisting load is determined; on the basis, particle swarm optimization-least squares support vector machine was introduced to establish relationship model between torque current and hoisting load at three running stages of acceleration, uniform speed and deceleration;different disturbances are applied to the load at each running stage, and the relationship between hoisting load and torque current is analyzed by Matlab simulation. The simulation results show that there is a correspondence between hoisting load and torque current at each running stage, the torque current can accurately restore the hoisting load and its fluctuation.
  • Related Articles

    [1]CHENG Lei, LI Zhengjian, SHI Haorong, WANG Xin. A bottom air temperature prediction model based on PSO-Elman neural network[J]. Journal of Mine Automation, 2024, 50(1): 131-137. DOI: 10.13272/j.issn.1671-251x.2023090062
    [2]TIAN Jie, LI Yang, ZHANG Lei, LIU Zhen. Adaptive control of temporary support force based on PSO-BP neural network[J]. Journal of Mine Automation, 2023, 49(7): 67-74. DOI: 10.13272/j.issn.1671-251x.2022100017
    [3]HUI Ali, LU Weiqiang, RONG Xiang, WEI Lipeng, CHEN Wenya. Research on fault diagnosis method of asynchronous motor based on Park-WPT and WOA-LSSVM[J]. Journal of Mine Automation, 2021, 47(12): 106-113. DOI: 10.13272/j.issn.1671-251x.2021070035
    [4]TIAN Jie, YIN Xiaoqi, WEN Yicheng. Method of cutting trajectory planning of roadheader based on hybrid IWO-PSO algorithm[J]. Journal of Mine Automation, 2021, 47(12): 55-61. DOI: 10.13272/j.issn.1671-251x.2021050018
    [5]JU Chen, ZHANG Chao, FAN Hongwei, ZHANG Xuhui, YANG Yiqing, YAN Yang. Rolling bearing fault diagnosis based on wavelet packet decomposition and PSO-BPN[J]. Journal of Mine Automation, 2020, 46(8): 70-74. DOI: 10.13272/j.issn.1671-251x.2019120022
    [6]CUI Lizhen, XU Fanfei, WANG Qiaoli, GAO Lili. Underground adaptive positioning algorithm based on PSO-BP neural network[J]. Journal of Mine Automation, 2018, 44(2): 74-79. DOI: 10.13272/j.issn.1671-251x.2017090028
    [7]PAN Lei, LI Li-juan, DING Ting-ting, LIU Dui. Forecasting of Short-term Power Load Based on Improved PSO Algorithm and LS-SVM[J]. Journal of Mine Automation, 2012, 38(9): 55-59.
    [8]SUN Jie, HAN Yan, DUAN Yong, CUI Bao-xia. PID Neural Network Control System of Ball Mill Based on Modified PSO Algorithm[J]. Journal of Mine Automation, 2011, 37(5): 59-62.
    [9]SU Po, CHEN Qing, . Analysis of Mine Low-voltage Leakage Protection in Situation of Great Disparity between Long and Short Lines and Big Unbalanced Current[J]. Journal of Mine Automation, 2010, 36(10): 32-35.
    [10]LIU Rui-fang, MEI Xiao-a. Nonlinear Correction of Methane Sensor Based on Least Square Support Vector Machine[J]. Journal of Mine Automation, 2009, 35(5): 8-12.
  • Cited by

    Periodical cited type(14)

    1. 谭超,闵薪宇,辛亮,孙其浩,谭继伟,欧星作. 一种基于单轴向充磁永磁环励磁的钢丝绳无损检测方法. 传感技术学报. 2024(04): 731-736 .
    2. 赵陆. 电梯钢丝绳损伤检测装置设计. 机械管理开发. 2024(12): 105-106+109 .
    3. 曹义威,张士超,陈小伟,徐光鹏,何宝林. 海洋石油钻修井钢丝绳在线监测技术研究与应用. 无损探伤. 2023(04): 30-33 .
    4. 王文庆,刘文辉,李生辉,徐午言. 基于永磁环励磁结构的钢丝绳无损检测设计. 西安邮电大学学报. 2023(05): 92-101 .
    5. 田劼,孙钢钢,李睿峰,王伟. 基于正交试验的钢丝绳探伤仪结构参数优化. 工矿自动化. 2022(09): 100-108 . 本站查看
    6. 王红尧,吴佳奇,李长恒,唐文锦,张艳林. 矿用钢丝绳损伤检测信号处理方法研究. 工矿自动化. 2021(02): 58-62 . 本站查看
    7. 窦连城,战卫侠,白晓瑞. 钢丝绳内外部断丝损伤识别. 工矿自动化. 2021(03): 83-88 . 本站查看
    8. 王红尧,田劼,张艳林,刘志宏,陈艺童. 矿用钢丝绳在线监测教学实验装置关键技术. 煤矿安全. 2021(06): 177-182 .
    9. 王锐. 参加者较少的钢丝拉伸能力验证评价方法应用. 机械研究与应用. 2021(03): 208-211 .
    10. 靳志强. 矿用提升机钢丝绳损伤检测装置的设计. 机械管理开发. 2021(08): 253-255 .
    11. 田劼,王洋洋,郭红飞,赵彩跃. 基于漏磁检测的钢丝绳探伤原理与方法研究. 煤炭工程. 2021(09): 95-100 .
    12. 王红尧,李小伟,韩亦淼,吕昕. 矿用钢丝绳损伤检测系统设计. 工矿自动化. 2020(06): 92-97 . 本站查看
    13. 张方泽. 矿用提升机制动过程与制动效果分析. 低碳世界. 2020(08): 166-167 .
    14. 窦连城,战卫侠. 钢丝绳断丝损伤漏磁场计算与仿真研究. 工矿自动化. 2020(10): 87-91 . 本站查看

    Other cited types(12)

Catalog

    Article Metrics

    Article views (38) PDF downloads (15) Cited by(26)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return