Citation: | LI Lei, XU Chunyu, SONG Jiancheng, et al. Attitude monitoring method for hydraulic support in fully mechanized working face based on PSO-ELM[J]. Journal of Mine Automation,2024,50(8):14-19. doi: 10.13272/j.issn.1671-251x.2024070023 |
[1] |
王国法,范京道,徐亚军,等. 煤炭智能化开采关键技术创新进展与展望[J]. 工矿自动化,2018,44(2):5-12.
WANG Guofa,FAN Jingdao,XU Yajun,et al. Innovation progress and prospect on key technologies of intelligent coal mining[J]. Industry and Mine Automation,2018,44(2):5-12.
|
[2] |
王国法,杜毅博,徐亚军,等. 中国煤炭开采技术及装备50年发展与创新实践——纪念《煤炭科学技术》创刊50周年[J]. 煤炭科学技术,2023,51(1):1-18.
WANG Guofa,DU Yibo,XU Yajun,et al. Development and innovation practice of China coal mining technology and equipment for 50 years:commemorate the 50th anniversary of the publication of Coal Science and Technology[J]. Coal Science and Technology,2023,51(1):1-18.
|
[3] |
马旭东,许春雨,宋建成. 综采工作面液压支架姿态监测系统设计[J]. 煤炭技术,2019,38(7):174-177.
MA Xudong,XU Chunyu,SONG Jiancheng. Design of attitude monitoring system for hydraulic support in fully mechanized face[J]. Coal Technology,2019,38(7):174-177.
|
[4] |
杨崇浩,白国长. 基于数字孪生的液压支架姿态监测[J]. 机床与液压,2023,51(22):39-44. doi: 10.3969/j.issn.1001-3881.2023.22.007
YANG Chonghao,BAI Guochang. Attitude monitoring of hydraulic support based on digital twin[J]. Machine Tool & Hydraulics,2023,51(22):39-44. doi: 10.3969/j.issn.1001-3881.2023.22.007
|
[5] |
杨金衡,宋单阳,田慕琴,等. 基于自适应卡尔曼滤波的双惯导采煤机定位方法[J]. 工矿自动化,2021,47(7):14-20,28.
YANG Jinheng,SONG Danyang,TIAN Muqin,et al. Double inertial navigation shearer positioning method based on adaptive Kalman filter[J]. Industry and Mine Automation,2021,47(7):14-20,28.
|
[6] |
王勇,刘文江,胡军,等. 多传感器检测系统的自适应融合算法[J]. 西安电子科技大学学报(自然科学版),2004,31(3):483-487. doi: 10.3969/j.issn.1001-2400.2004.03.035
WANG Yong,LIU Wenjiang,HU Jun,et al. The adaptive fusion algorithm in multiple-sensors detecion system[J]. Journal of Xidian University,2004,31(3):483-487. doi: 10.3969/j.issn.1001-2400.2004.03.035
|
[7] |
银桥. 基于多传感器信息融合的运动系统姿态解算方法研究[D]. 桂林:桂林电子科技大学,2022.
YIN Qiao. Research on attitude calculation method of motion system based on multi-sensor information fusion[D]. Guilin:Guilin University of Electronic Technology,2022.
|
[8] |
张坤,孙政贤,刘亚,等. 基于信息融合技术的超前液压支架姿态感知方法及实验验证[J]. 煤炭学报,2023,48(增刊1):345-356.
ZHANG Kun,SUN Zhengxian,LIU Ya,et al. Advanced hydraulic support posture perception method based on information fusion technology and experimental verification[J]. Journal of China Coal Society,2023,48(S1):345-356.
|
[9] |
张坤. 基于信息融合技术的液压支架姿态监测方法研究[D]. 太原:太原理工大学,2018.
ZHANG Kun. Research on attitude monitoring method of hydraulic support based on information fusion technology[D]. Taiyuan:Taiyuan University of Technology,2018.
|
[10] |
司垒,王忠宾,王浩,等. 基于惯性传感组件和BP神经网络的防冲钻孔机器人钻具姿态解算[J]. 仪器仪表学报,2022,43(4):213-223.
SI Lei,WANG Zhongbin,WANG Hao,et al. Drilling tool attitude calculation of drilling robot for rockburst prevention based on inertial sensing assembly and BP neural network[J]. Chinese Journal of Scientific Instrument,2022,43(4):213-223.
|
[11] |
徐西华. 液压支架姿态监测关键技术研究[D]. 徐州:中国矿业大学,2018.
XU Xihua. Research on key technologies of hydraulic support posture monitoring[D]. Xuzhou:China University of Mining and Technology,2018.
|
[12] |
袁祥. 液压支架位姿-负载耦合特性分析及感知基础研究[D]. 太原:太原理工大学,2022.
YUAN Xiang. Analysis of position-attitude- load coupling characteristics of hydraulic support and basic research on perception[D]. Taiyuan:Taiyuan University of Technology,2022.
|
[13] |
王忠乐. 液压支架姿态监测及控制技术[J]. 工矿自动化,2022,48(增刊2):116-117,137.
WANG Zhongle. Posture monitoring and control technology of fully mechanized hydraulic support[J]. Journal of Mine Automation,2022,48(S2):116-117,137.
|
[14] |
陈冬方,李首滨. 基于液压支架倾角的采煤高度测量方法[J]. 煤炭学报,2016,41(3):788-793.
CHEN Dongfang,LI Shoubin. Measurement of coal mining height based on hydraulic support structural angle[J]. Journal of China Coal Society,2016,41(3):788-793.
|
[15] |
彭道刚,段睿杰,王丹豪. 两级融合的多传感器数据融合算法研究[J]. 仪表技术与传感器,2024(1):87-93. doi: 10.3969/j.issn.1002-1841.2024.01.016
PENG Daogang,DUAN Ruijie,WANG Danhao. Research on multi-sensor data fusion algorithm based on two-level fusion[J]. Instrument Technique and Sensor,2024(1):87-93. doi: 10.3969/j.issn.1002-1841.2024.01.016
|
[16] |
孙君令. 姿态数据驱动的液压支架运动状态监测技术研究[D]. 徐州:中国矿业大学,2019.
SUN Junling. Research on monitoring technology of hydraulic support motion state driven by attitude data[D]. Xuzhou:China University of Mining and Technology,2019.
|
[17] |
王忠宾,司垒,王浩,等. 基于空间阵列式惯性单元的防冲钻孔机器人位姿解算方法[J]. 煤炭学报,2022,47(1):598-610.
WANG Zhongbin,SI Lei,WANG Hao,et al. Position and attitude calculation method of anti-impact drilling robot based on spatial array inertial units[J]. Journal of China Coal Society,2022,47(1):598-610.
|
[18] |
常钰坤,曹港生,马振九,等. 基于PSO−LSTM模型的上肢动作识别方法[J/OL]. 华东理工大学学报(自然科学版):1-11[2024-06-20]. https://doi.org/10.14135/j.cnki.1006-3080.20231009001.
CHANG Yukun,CAO Gangsheng,MA Zhenjiu,et al. Upper limb motion recognition method based on PSO-LSTM model[J]. Journal of East China University of Science and Technology (Natural Science Edition):1-11[2024-06-20]. https://doi.org/10.14135/j.cnki.1006-3080.20231009001.
|
[19] |
于海洋. 在线预测的极限学习机方法研究[D]. 长春:吉林大学,2019.
YU Haiyang. Research on extreme learning machine method for online prediction[D]. Changchun:Jilin University,2019.
|
[20] |
李海锋. 基于BP神经网络的液压支架支护位姿运动学分析[J]. 煤炭工程,2018,50(9):117-120.
LI Haifeng. Kinematics analysis of support position and posture of hydraulic support based on BP neural network[J]. Coal Engineering,2018,50(9):117-120.
|
[21] |
寇发荣,杨天祥,罗希,等. 基于ISSA−ELM算法的锂电池SOC估计 [J/OL]. 电源学报:1-8[2024-06-20]. http://kns.cnki.net/kcms/detail/12.1420.TM.20240229.1408.005.html.
KOU Farong,YANG Tianxiang,LUO Xi,et al. Lithium battery SOC estimation based on ISSA-ELM algorithm[J/OL]. Journal of Power Supply:1-8[2024-06-20]. http://kns.cnki.net/kcms/detail/12.1420.TM.20240229.1408.005.html.
|