Automated real-time absolute positioning technology on intelligent fully mechanised coal faces using the gyro RTS system

• Autorzy: Li Ben , Mao Shanjun , Zhang Haoyuan , Li Xinchao , Chen Huazhou

Identyfikatory

DOI

10.24425/ams.2023.146863

• Języki publikacji: EN

Abstrakty

EN

The absolute positions of shearers on advancing coal faces are requisite for providing references for adaptive mining combined with geological models. Common coalmine localization techniques (e.g. UWB, INS, etc.) are not fully applicable to adaptive mining due to their drifting error or the messy environment. The gyro robotic total station (RTS) is versatile and precise in measuring coordinates in coal mines, while its conventional usage is of low automation and poor timeliness, impeding its application on mining faces. This article proposed an automated gyro RTS system for real-time absolute positioning on fully mechanised coal faces. The measuring process was changed to fit mining requirements, and a new state-transferring model was used to automate it. Programs were developed and installed in available instruments, forming a prototype. Field experiments were carried out on a simulative working face, verifying the system’s accuracy and applicability. Results show that the relative positioning error is better than 2.6143×10-4, which meets the demand of advancing faces. The error of the gyro is estimated at 55.5187”, justifying its nominal indicators. To sum up, the automated gyro RTS system proposed in this paper can offer real-time and accurate absolute positions of equipment on working faces, supporting adaptive mining combined with the geological model.

Słowa kluczowe

EN

fully mechanised faces; absolute positioning; adaptive mining; gyro RTS; automated measuring

PL

pomiar automatyczny; żyroskop; pozycjonowanie

• Wydawca: Instytut Mechaniki Górotworu PAN
• Czasopismo: Archives of Mining Sciences
• Rocznik: 2023
• Tom: Vol. 68, no. 3
• Strony: 475--493
• Opis fizyczny: Bibliogr. 31 poz., fot., rys., tab., wykr.

Twórcy

autor

Li Ben

• Peking University, Institute of Remote Sensing and Geographic Informat ion System, Beijing 100871, China

• https://orcid.org/0000-0001-8216-3599

autor

Mao Shanjun

• Peking University, Institute of Remote Sensing and Geographic Informat ion System, Beijing 100871, China

• https://orcid.org/0000-0002-5428-6863

autor

Zhang Haoyuan

• Peking University, Institute of Remote Sensing and Geographic Informat ion System, Beijing 100871, China

• https://orcid.org/0000-0001-7978-8045

autor

Li Xinchao

• Beijing Longruan Technologies Co., Ltd., Beijing 100871, China

• https://orcid.org/0000-0001-8710-1338

autor

Chen Huazhou

• Beijing Longruan Technologies Co., Ltd., Beijing 100871, China

• https://orcid.org/0000-0002-5265-7157

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)