Online shearer-onboard personnel detection method for the intelligent fully mechanized mining face. (March 2022)
- Record Type:
- Journal Article
- Title:
- Online shearer-onboard personnel detection method for the intelligent fully mechanized mining face. (March 2022)
- Main Title:
- Online shearer-onboard personnel detection method for the intelligent fully mechanized mining face
- Authors:
- Wei, Dong
Wang, Zhongbin
Si, Lei
Tan, Chao
Lu, Xuliang - Abstract:
- As unmanned coal mining technology gradually replaces the traditional mechanized coal mining technology, shearer operation mode is changed from local control to remote control in intelligent fully mechanized mining face. In remote control mode, it is difficult to protect the personnel who straying into the shearer operator space without observation and reminder from the shearer operator. Hence, it is necessary to establish an intelligent personnel detection method to protect the safety of coal miners in intelligent unmanned mining face. The environment of low and non-uniform illumination in fully mechanized coal mining face has seriously restricted the application of personnel detection technology based on visible light imaging. Therefore, a personnel detection method based on infrared thermal imaging is proposed in this paper to solve the disadvantages of using visible light imaging in downhole applications. On this basis, a spatiotemporal guided filter is proposed to harmonize the relationship between edge-preserving and noise-removing. Then, an improved Lucas-Kanade method based on the adaptive-size window is utilized to achieve a more robust personnel detection. Moreover, the personnel detection in the shearer operating space is realized based on epipolar geometry and morphology processing. Finally, the laboratory experiment and industrial test are carried out to evaluate the proposed method, and the results indicate the feasibility and superiority of the proposedAs unmanned coal mining technology gradually replaces the traditional mechanized coal mining technology, shearer operation mode is changed from local control to remote control in intelligent fully mechanized mining face. In remote control mode, it is difficult to protect the personnel who straying into the shearer operator space without observation and reminder from the shearer operator. Hence, it is necessary to establish an intelligent personnel detection method to protect the safety of coal miners in intelligent unmanned mining face. The environment of low and non-uniform illumination in fully mechanized coal mining face has seriously restricted the application of personnel detection technology based on visible light imaging. Therefore, a personnel detection method based on infrared thermal imaging is proposed in this paper to solve the disadvantages of using visible light imaging in downhole applications. On this basis, a spatiotemporal guided filter is proposed to harmonize the relationship between edge-preserving and noise-removing. Then, an improved Lucas-Kanade method based on the adaptive-size window is utilized to achieve a more robust personnel detection. Moreover, the personnel detection in the shearer operating space is realized based on epipolar geometry and morphology processing. Finally, the laboratory experiment and industrial test are carried out to evaluate the proposed method, and the results indicate the feasibility and superiority of the proposed methods which show considerable application prospects. … (more)
- Is Part Of:
- Proceedings of the Institution of Mechanical Engineers. Volume 236:Number 6(2022)
- Journal:
- Proceedings of the Institution of Mechanical Engineers
- Issue:
- Volume 236:Number 6(2022)
- Issue Display:
- Volume 236, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 236
- Issue:
- 6
- Issue Sort Value:
- 2022-0236-0006-0000
- Page Start:
- 3058
- Page End:
- 3072
- Publication Date:
- 2022-03
- Subjects:
- Personnel detection -- intelligent mining -- infrared image imaging -- spatiotemporal filter -- improved optical flow
Mechanical engineering -- Periodicals
621.05 - Journal URLs:
- http://pic.sagepub.com/ ↗
http://www.uk.sagepub.com/home.nav ↗
http://journals.pepublishing.com/content/119771 ↗ - DOI:
- 10.1177/09544062211030973 ↗
- Languages:
- English
- ISSNs:
- 0954-4062
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19891.xml