Design of mine pressure acquisition gateway based on Cortex M3
1.
College of Information Science and Technology, Shandong University of Science and Technology, Qingdao 266510, China
2.
College of Geomatics, Shandong University of Science and Technology, Qingdao 26
More Information
Abstract
According to functional requirements of intelligent gateway in smart distributed network data acquisition system of hydraulic support, a design scheme of real-time gateway based on Cortex M3 was proposed, and designs of hardware and software of the gateway were introduced. The gateway realizes batch sampling of pressure data through RS485 or CAN bus, can upload data to the remote upper computer through Ethernet or Modem, and can offline backup massive sampled data using a SD card. The experiment result shows that the gateway has advantages of low cost, simple structure and high stability and reliability.
Related Articles
[1] LI Shasha. Multi-source data processing and decision support system for coal mine based on artificial intelligence [J]. Journal of Mine Automation, 2024, 50(S2): 89-92.
[2] FU Xiang, QIN Yifan, LI Haojie, NIU Penghao. Summary of research on artificial intelligence empowerment technology for new generation intelligent coal mine [J]. Journal of Mine Automation, 2023, 49(9): 122-131, 139. DOI: 10.13272/j.issn.1671-251x.18113
[3] GUO Yonghong, LIU Daoyuan, YANG Yunbo. Design of mine remote identification system based on artificial intelligence technology [J]. Journal of Mine Automation, 2022, 48(S1): 105-107.
[4] SHE Xiaojiang, LIU Jiang, WANG Lanhao. Application status and prospect of AI video image analysis in intelligent coal preparation plant [J]. Journal of Mine Automation, 2022, 48(11): 45-53, 109. DOI: 10.13272/j.issn.1671-251x.2022060092
[5] JIN Zhixin, WANG Hongwei, FU Xiang. Development path of new generation intelligent coal mine under HCPS theory system [J]. Journal of Mine Automation, 2022, 48(10): 1-12. DOI: 10.13272/j.issn.1671-251x.17988
[6] ZHANG Peng. Exploration on construction of big data system for intelligent mine [J]. Journal of Mine Automation, 2021, 47(S1): 21-23.
[7] HU Qingsong, QIAN Jiansheng, LI Shiyin, SUN Yanjing. Status of intelligent coal technology research and policy development [J]. Journal of Mine Automation, 2021, 47(3): 1-8. DOI: 10.13272/j.issn.1671-251x.17708
[8] ZHENG Xuezhao, TONG Xin, GUO Jun, ZHANG Duo. Research status and development trend of intelligent monitoring and early warning technology in coal mine [J]. Journal of Mine Automation, 2020, 46(6): 35-40. DOI: 10.13272/j.issn.1671-251x.17530
[9] ZHANG Fan, LI Chuang, LI Hao, LIU Yi. Research on digital twin technology for smart mine and new engineering discipline [J]. Journal of Mine Automation, 2020, 46(5): 15-20. DOI: 10.13272/j.issn.1671-251x.2020040042
[10] MA Xiaoping, YANG Xuemiao, HU Yanjun, MIAO Yanzi. Preliminary study on application of artificial intelligence technology in mine intelligent constructio [J]. Journal of Mine Automation, 2020, 46(5): 8-14. DOI: 10.13272/j.issn.1671-251x.17593
Cited by
Periodical cited type(20)
1.
谭凯, 胡宇, 戴剑波. 基于UWB技术的井下电子围栏系统. 煤矿安全. 2025(08)
2.
赵斌, 付帅, 高丽霞, 李森森. 融合RSSI-TDOA的煤矿井下机车定位. 测绘通报. 2025(06)
3.
陈伟, 穆华星, 管彦允, 刘珏廷, 徐婷婷, 王泽华. 改进YOLOv8s的煤矿井下矿工行为检测方法. 辽宁工程技术大学学报(自然科学版). 2025(03)
4.
康岩龙. 基于轨迹盲推的人员普适定位方法. 电子设计工程. 2025(02): 68-71+76 .
5.
何晓晗. UWB技术人员定位系统在煤矿中的应用. 江西煤炭科技. 2025(01): 171-173+178 .
6.
陈贤. 基于UWB的TOF与TDOA井下联合定位方法. 煤矿安全. 2025(02): 220-225 .
7.
孙继平,彭铭. 室内电磁波传播衰减统计模型用于矿井的适用性研究. 工矿自动化. 2025(02): 1-8 .
本站查看
8.
贾佳,秦冬冬,王霞. 基于BP极大似然估计井下人员定位方法研究. 煤炭技术. 2025(05): 224-228 .
9.
彭铭. 通用无线传输路径损耗统计模型用于矿井的适用性研究. 工矿自动化. 2025(04): 57-63+85 .
本站查看
10.
李明锋,常建明. 基于5G和UWB融合基站的煤矿井下人员定位系统研究. 中国宽带. 2025(05): 121-123 .
11.
王端,刘世平,王利军. 基于机器视觉的煤矿巷道人员定位研究. 矿山机械. 2024(01): 56-60 .
12.
孙继平,彭铭. 煤矿信息综合承载网标准研究制定. 工矿自动化. 2024(04): 1-8 .
本站查看
13.
吴文臻. 基于改进时间同步的矿井UWB优化定位方法. 工矿自动化. 2024(S1): 34-38 .
本站查看
14.
张雪军,黎卓芳. 煤矿多参数复合风险智能分级决策预警系统. 工矿自动化. 2024(S1): 88-91 .
本站查看
15.
貟婧. 基于超带宽测距算法的舞台灯光控制系统与自动追踪模型研究. 自动化与仪器仪表. 2024(06): 85-88+93 .
16.
陈代伟,胡峰平,钱正峰,唐银. 基于3D人脸识别的煤矿人员出入井唯一性识别装置设计. 煤炭科技. 2024(04): 116-120 .
17.
陈贤,周澍,张蓉. 一种井下人员乘车识别与定位方法. 煤矿安全. 2024(11): 217-221 .
18.
孙继平,彭铭,刘斌. 矿井无线传输测试分析与矿用5G优选工作频段研究. 工矿自动化. 2024(10): 1-11+20 .
本站查看
19.
李烨,金业勇. 小型化双向波束矿用定位终端天线设计. 工矿自动化. 2024(11): 127-131+178 .
本站查看
20.
孙继平. 煤矿用5G通信系统标准研究制定. 工矿自动化. 2023(08): 1-8 .
本站查看
Other cited types(7)