Research on Mine Gas Over-Limit Alarm Data Based on Big Data Technology

Abstract:

Based on the statistics of gas exceeding limit data in a high-gas mine in the southwest region in 2022, the big data method is used to analyze and summarize the regular characteristics of gas exceeding limit data from different dimensions such as the time of occurrence of the over-limit alarm, duration and maximum value. The analysis results show that the months with the most gas over-limit alarms are April, May and August, accounting for 41.66% of the total; the months with the least number of gas over-limit alarms are December, January and February, accounting for 12.09% of the total. . The highest number of alarms per day is at 1:00, 12:00 and 14:00, accounting for 17.69% of the total number; the lowest frequency is at 6:00, 7:00 and 15:00, accounting for 7.09% of the total number. Analyzed by the duration of the alarm, nearly 50% of the alarms are within 30 seconds. Comparing the maximum gas concentration during the alarm period, more than 85% of the alarm data have maximum values between 1.0 and 1.5. Analyzed by the area of occurrence, more than 80% of gas over-limit alarm accidents occurred in the three main operating areas of drilling construction, return air tunnels and transportation tunnels. Summarizing the analysis results, the mine strengthens gas safety prevention and control measures in the middle of each year, early morning and noon; focuses on dealing with over-limit alarms of more than 30 seconds, reducing the alarm duration, and reducing the number of high-concentration gas over-limits by stopping mining or strengthening ventilation. to reduce mine safety risks.

• Periodical: Advances in Science and Technology (Volume 166)
• Pages: 117-122
• DOI: https://doi.org/10.4028/p-3Otr2a
• Online since: June 2025
• Authors: Yun Qi Chen*
• Keywords: Big Data Technology, Mathematical Statistics, Multi-Dimensional Comparative Analysis, Over-Limit Alarms

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DOI: 10.3389/fenrg.2022.846500

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