Special Issue "Recent Advances in Optical Sensor for Mining"
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Optical Sensors".
Deadline for manuscript submissions: 30 October 2023 | Viewed by 746
Special Issue Editors
Dr. Minfu Liang
2. Research Center of Intelligent Mining, China University of Mining and Technology, Xuzhou 221116, China
Interests: intelligent mining; fiber optic sensing monitoring of coal mining information; development and application of fiber optic sensors for coal mines
Prof. Dr. Xinqiu Fang
2. Research Center of Intelligent Mining, China University of Mining and Technology, Xuzhou 221116, China
Interests: Intelligent mining; fiber optic sensing technology for coal mines; application of fiber Bragg grating sensors/fiber optic sensors in coal mines
Interests: geotechnical engineering monitoring based on distributed fiber optic sensing technology; remote data acquisition; geological disaster evaluation based on the Internet of Things
Special Issues, Collections and Topics in MDPI journals
Interests: optical fiber monitoring for mining process dynamics
Special Issue Information
Dear Colleagues,
The intelligent recognition of major coal mine disasters, early warning signs, and hidden risk is the foundation of coal mine safety. Clarifying the distribution characteristics, influencing laws, and evolution mechanisms of coal mine disasters, and achieving comprehensive perception, dynamic monitoring, intelligent early warning systems, and graded response with regard to coal mine information and other innovative technologies will become the key principles of the intelligent construction of coal mines.
With the in-depth application of optical fiber sensing technology in the field of engineering monitoring, its passive, wide-area, refined, and anti-interference characteristics make it one of the top choices for engineering protection in disaster environments. As an intrinsically safe sensing and monitoring method, optical fiber sensing technology has natural advantages in coal mine applications and has made significant progress in areas such as mine pressure monitoring, roadway support, strata control, goaf fires, coal mine micro-seismic activity monitoring, and underground equipment safety. Its application in mining engineering can help further realize the progression from the perception to the cognition of mine disasters and accidents, which will effectively promote efficient, high-yield, green, and safe coal mining and can become a key solution to promote the intelligent construction of coal mines.
This Special Issue entitled "Recent Advances in Optical Sensors for Mining" aims to provide selected contributions on advances in the theory, experimentation, and application of fiber optic sensing technology in mining engineering monitoring. Meanwhile, it seeks to deepen the application of optical fiber sensing technology in the intelligent construction of coal mines. Potential topics include, but are not limited to, the following:
- Advances in sensors and sensing technologies (fiber Bragg grating sensing, distributed fiber optic sensing, multi-parameter optical fiber sensors for mining, etc.);
- Opto-electronic monitoring in mining engineering (deformation monitoring, stress monitoring, temperature monitoring, vibration monitoring, seepage monitoring, etc.);
- Artificial intelligence algorithms for fiber optic monitoring data processing in mine engineering;
- Big data mining and risk assessment of mine engineering monitoring;
- Fine monitoring technology of underground mining;
- Intelligent monitoring and maintenance of mine engineering;
- Monitoring practice and typical case analysis of major mine engineering;
- Intelligent real-time monitoring technology for mine engineering.
Dr. Minfu Liang
Prof. Dr. Xinqiu Fang
Dr. Gang Cheng
Dr. Qiang Yuan
Guest Editors
Manuscript Submission Information
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Keywords
- fiber optic sensing
- optical sensor
- mining disaster monitoring
- opto-electronic monitoring
- artificial intelligence algorithm
- big data mining
- risk assessment
- coal mine disaster early warning systems.
