Coal mine natural fire prediction and alarm method based on CO isotope database

Abstract

The invention discloses a coal mine natural fire prediction and alarm method based on a CO isotope database, and relates to the technical field of coal mine fireproof safety. S1, sample collection; s2, temperature programming; s3, isotope analysis; s4, constructing a database; and S5, real-time monitoring. Gas samples at specific positions under a coal mine are collected in real time, CO isotope composition of the gas samples is analyzed, data are input into an established database model, the occurrence probability and the development trend of the natural fire of the coal mine are rapidly and accurately predicted through comparative analysis, and an alarm signal is sent out in time when a preset danger threshold value is reached. Scientific basis and sufficient response time are provided for coal mine disaster prevention and control.

Description

Technical Field

[0001] This patent relates to the field of coal mine fire safety technology, especially a coal mine natural fire prediction and alarm method based on CO isotope database. Background Art

[0002] In coal mining operations, natural fires in coal mines have always been an extremely severe safety challenge. It not only causes a large loss of coal resources, but also seriously threatens the life safety of underground workers and the normal operation of coal mine production facilities, causing huge economic losses and social impacts.

[0003] There are many traditional methods for predicting natural fires in coal mines, but all of them have defects to varying degrees. Gas analysis is one of the more commonly used methods, which mainly infers the possibility of fire by monitoring the concentration changes of indicator gases such as carbon monoxide (CO) and ethylene (C2H4). However, in practical applications, the concentration of indicator gases is easily affected by a variety of complex factors. For example, differences in coal seam geological conditions, fluctuations in ventilation systems, and gas interference caused by other underground operations may cause abnormal fluctuations in the concentration of indicator gases, which are not entirely caused by spontaneous combustion. In the very early stages of a fire, changes in the concentration of indicator gases are often very weak and unstable, and it is easy to misjudge or miss, making it difficult to accurately determine the start time and development trend of spontaneous combustion.

[0004] Temperature monitoring is also widely used. Its principle is based on the characteristic that the temperature of coal will gradually increase during spontaneous combustion. However, this method has obvious lag, because only when the fire source forms a certain scale and the heat accumulates to a certain extent can a significant temperature change be detected at the monitoring point. In the incubation period and early development stage of spontaneous combustion in coal mines, the temperature rise is not obvious. At this time, if only relying on temperature monitoring, it is often impossible to detect the hidden dangers of spontaneous combustion in time, thus missing the best prevention and control time.

[0005] In recent years, with the in-depth study of the mechanism of spontaneous combustion in coal mines, it has been found that during the spontaneous combustion of coal, carbon (C) and oxygen (O) isotopes will undergo specific fractionation phenomena. This isotope fractionation is closely related to the oxidation process of coal, and shows regular changes in different stages of spontaneous combustion. Compared with traditional prediction methods, CO isotope analysis has unique advantages. It can reflect the oxidation reaction process inside the coal body at a microscopic level, is relatively less affected by external interference factors, and can show a more obvious change trend in the early stage of spontaneous combustion, providing new ideas and directions for the ultra-early and accurate prediction of natural fires in coal mines. Based on this, it is particularly urgent and necessary to build a CO isotope database and develop efficient coal mine natural fire prediction and alarm technology based on it, which is expected to fill the shortcomings of traditional prediction methods and significantly improve the level of coal mine fire safety. Summary of the invention

[0006] The present invention aims at addressing the deficiencies in the background technology and provides a coal mine natural fire prediction and alarm method based on a CO isotope database.

[0007] The present invention first collects a large number of coal samples, rock samples and gas samples in different areas, different coal seams and different mining stages in the coal mine, and performs high-precision analysis and determination of the CO isotopes therein to obtain rich isotope data. Then, using advanced data processing algorithms and machine learning models, a CO isotope database is constructed, and a correlation model between CO isotope characteristics and different development stages of natural fires in coal mines is established. In practical applications, gas samples at specific locations underground in coal mines are collected in real time and their CO isotope composition is analyzed. The data is input into the established database model. Through comparative analysis, the probability and development trend of natural fires in coal mines are quickly and accurately predicted, and an alarm signal is issued in time when the preset danger threshold is reached, providing a scientific basis and sufficient response time for coal mine disaster prevention and control.

[0008] To achieve the above technical objectives, the technical solution adopted by the present invention is: a coal mine natural fire prediction and alarm method based on CO isotope database, which specifically includes the following steps: S1 Sample Collection Collect coal samples from different coal mines, different coal seams and different mining stages, and systematically measure their CO isotope composition; S2 temperature program The coal sample collected in step S1 is placed in a programmed temperature oxidation experimental device and heated at a set heating rate; S3 isotope analysis The collected samples are subjected to high-precision analysis and determination of CO isotopes to obtain isotope data; S4 database construction The CO isotope database is constructed based on the collected sample location information, sample type information and corresponding CO isotope data, and the correlation between CO isotope characteristics and different development stages of coal mine natural fires is established; S5 real-time monitoring Collect gas samples in real time underground in coal mines and analyze their CO isotope composition to predict the probability and development trend of natural fires in coal mines, and issue an alarm signal in time when the preset danger threshold is reached.

[0009] As a preferred technical solution: in step S1, the determination content of the coal sample includes the numerical changes of carbon isotopes and oxygen isotopes of the coal sample at various stages of oxidation at room temperature and elevated temperature.

[0010] As a preferred technical solution: for each sampling point, coal samples at different depths are collected respectively, from the surface to the deep of the coal seam, so as to obtain characteristic information of the coal body at different positions.

[0011] As a preferred technical solution: in step S2, the coal sample is heated at a predetermined heating rate by a programmed temperature oxidation experimental device, and reaction gases at different temperature stages are collected.

[0012] As a preferred technical solution: heating is performed according to a set heating program. During the heating process, the temperature change of the coal sample is continuously monitored. The monitored temperature points include 30°C, 50°C, 80°C, and 120°C.

[0013] As a preferred technical solution: the database construction in step S4 includes the following steps: (1) Data collation and entry Organize and classify the relevant information in the sample collection process, programmed temperature experimental data and isotope analysis results to establish a database; (2) Database architecture design The database adopts a layered architecture design, including the basic data layer, data processing layer and application layer; Establish data indexes and association relationships, integrate related data together through association relationships, and realize fast retrieval and call of data.

[0014] As a preferred technical solution: the relevant data includes different data tables; Based on the database constructed in step (1), the data in each table are statistically analyzed to establish a prediction alarm model between CO isotopes and the spontaneous combustion state of coal mines; by analyzing the changing trends and characteristics of isotope data, the isotope threshold range or change pattern of different spontaneous combustion stages is determined.

[0015] As a preferred technical solution: in step S5, real-time monitoring includes the following steps: (1) Monitoring equipment installation Install CO isotope monitoring equipment and supporting temperature and gas concentration monitoring sensors in key areas underground in coal mines; (2) Monitoring data transmission and processing The data collected by the monitoring equipment is transmitted to the monitoring center on the well through a wired or wireless communication network; at the monitoring center, the data is processed and analyzed in real time, and the current monitoring data is compared with the historical data and predictive alarm model in the database to determine the risk status of natural fires in the coal mine.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. Construction of isotope database: Collect coal samples from different coal mines and coal seams, systematically measure their CO isotope composition during the spontaneous combustion simulation experiment, integrate the experimental data with the field data, and establish a CO isotope database containing basic information of coal samples (such as coal type and coal quality parameters), isotope change data during the experiment, field monitoring isotope data, and corresponding time, temperature, gas concentration and other multi-parameters for easy verification; 2. Establishment of the prediction and alarm model. Based on the constructed database and statistical analysis of the data, a prediction and alarm model between CO isotopes and the spontaneous combustion status of coal mines (such as the spontaneous combustion latent period, spontaneous combustion development period, and spontaneous combustion intense period) is established. By analyzing the changing trends and characteristics of the isotope data, the isotope threshold range or change pattern of different spontaneous combustion stages is determined, and the possibility of fire occurrence and the expected development time are calculated through the model.

[0017] 3. Collect coal or gas samples regularly and send them to the laboratory on the well or use on-site rapid detection equipment for isotope analysis; the data is transmitted to the monitoring center via wired or wireless transmission. The software system of the monitoring center processes and analyzes the data in real time based on the pre-established prediction alarm model. Once the isotope data or comprehensive calculation results exceed the set warning threshold, the system immediately sends out an audible and visual alarm signal and provides detailed fire prediction information (such as possible ignition location, fire development trend, etc.) so that coal mine workers can take corresponding fire prevention and fire fighting measures in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a design block diagram of the present invention.

[0019] Figure 2 It is a schematic diagram of the engineering of the present invention. DETAILED DESCRIPTION

[0020] The following is combined with Figure 1-2 The present invention is described in detail with reference to embodiments.

[0021] The present invention utilizes the changes in CO isotopes that occur during the spontaneous combustion of coal, and the change pattern is closely related to the progress of the spontaneous combustion of coal. Based on this principle, a CO isotope database is established, and a corresponding prediction and alarm model is established.

[0022] The method for predicting and alarming natural fires in coal mines based on a CO isotope database disclosed in the present invention specifically comprises the following steps: S1 Sample Collection Coal samples were collected from different coal mines, different coal seams and different mining stages, and their CO isotope compositions were systematically determined.

[0023] 1. Sampling site selection Sampling was conducted in multiple coal seams in different coal mines, covering the working face, the mined area and the coal seams to be mined. At the same time, different geological structural areas were considered, such as near faults and folded areas, because the coal structure and properties in these areas may be different, and the sensitivity to spontaneous combustion is also different.

[0024] For each sampling point, coal samples are collected at different depths, from the surface to the deep part of the coal seam, to obtain characteristic information of the coal body at different locations.

[0025] 2. Sampling Method Coal core drilling equipment is used to collect coal core samples to ensure the integrity and representativeness of the samples. For coal samples in goaf areas, loose coal or gas samples are collected through boreholes using samplers. During the collection process, the sampling location, depth, time, and surrounding environmental conditions (such as temperature, humidity, gas concentration, etc.) are strictly recorded.

[0026] S2 temperature program The coal sample collected in step S1 is placed in a programmed temperature oxidation experimental device and heated at a set heating rate.

[0027] 1. Experimental setup A special programmed temperature oxidation experimental device is designed and used. The device has a precise temperature control system and can heat the coal sample at a predetermined heating rate (such as 0.5℃ / min - 5℃ / min). The device is equipped with a gas circulation system and a gas sampling port to ensure the uniformity of the gas environment during the oxidation process of the coal sample and collect the reaction gas at different temperature stages.

[0028] 2. Experimental Procedure The collected coal samples are processed, such as crushing and screening, and coal samples with appropriate particle size (such as 0.15 - 0.25mm) are selected and placed in the reaction container of the experimental device. Before the experiment begins, an inert gas (such as nitrogen) is introduced to remove the air in the device. Then, the coal samples are heated according to the set heating program. During the heating process, the temperature changes of the coal samples are continuously monitored, and the temperature points include 30℃, 50℃, 80℃, and 120℃. The gas samples after the reaction are collected for subsequent gas composition analysis and isotope analysis.

[0029] S3 isotope analysis The collected samples are subjected to high-precision CO isotope analysis and measurement to obtain isotope data.

[0030] 1. Preparation before analysis The collected gas samples at different temperatures and the original gas samples are pre-processed. The gas samples are purified and enriched to remove impurities and interfering gases.

[0031] 2. Analytical instruments and methods Use a high-precision stable isotope analyzer to perform isotope analysis on the processed samples. For carbon isotopes, the main Values, for oxygen isotopes, determined During the analysis, the instrument was operated strictly in accordance with its operating procedures and calibrated with international standard materials to ensure the accuracy and comparability of the analysis results. This facilitates the subsequent comparison of the CO isotope values ​​of the two gas samples and the determination of the temperature of the coal mine where the original gas sample is located.

[0032] S4 database construction A CO isotope database was constructed based on the collected sample location information, sample type information and corresponding CO isotope data, and the correlation between CO isotope characteristics and different development stages of natural fires in coal mines was established.

[0033] 1. Data collation and entry The relevant information during the sample collection process (such as sampling location, depth, time, coal sample characteristics, etc.), programmed temperature experiment data (such as temperature change curve, gas composition and concentration at different temperature points, etc.) and isotope analysis results (such as coal sample and gas , Values) are sorted and classified to establish a database with functions such as data storage, query, update and data security protection. These data are entered into it for subsequent use.

[0034] As a preferred method, a database is established, which has the functions of data storage, query, update and data security protection, etc. These data are entered into it for subsequent use.

[0035] 2. Database architecture design The database adopts a layered architecture design, including a basic data layer (storing original sampling, experimental and analysis data), a data processing layer (preprocessing and calculating the original data, such as calculating the isotope fractionation coefficient, etc.) and an application layer (providing data interface and data support for subsequent prediction and alarm models).

[0036] At the same time, data indexes and associations are established. The associations here refer to the related connections between different data tables, including sample collection data tables and programmed temperature rise experiment data tables. Among them, the sample collection data table generally includes basic information of coal samples (such as sampling number, sampling location, etc.); the programmed temperature rise experiment data table includes data such as temperature changes and gas composition during the experiment. These two tables can establish an association through the common field of "sampling number". In this way, when it is necessary to view the collection information of a coal sample and the corresponding experimental data, the relevant data can be integrated together through this association, which is convenient for the comprehensive use and analysis of data, so as to quickly retrieve and call data and make it easier to judge the temperature of the coal mine.

[0037] S5 real-time monitoring In the coal mine (preferably 15 meters behind the working face), raw gas samples are collected in real time and their CO isotope composition is analyzed to predict the probability and development trend of natural fires in coal mines, and to issue an alarm signal in time when the preset danger threshold is reached.

[0038] 1. Monitoring equipment installation In the key areas of coal mines (such as coal mining faces, goafs, return air lanes, etc.), 15 meters behind the working face is a relatively specific location, which can be used as a key monitoring point in the key areas. The coal mining face has a wide range, and 15 meters behind the working face may be within the scope of the coal mining face; goafs and return air lanes are also key areas that need to be monitored underground in coal mines. Monitoring equipment can also be reasonably arranged in these areas, and together with 15 meters behind the working face, a comprehensive monitoring system is formed. Install CO isotope monitoring equipment and supporting temperature and gas concentration monitoring sensors. The isotope monitoring equipment has online sampling, analysis and data transmission functions, and can obtain isotope information of coal and gas in real time.

[0039] 2. Monitoring data transmission and processing The data collected by the monitoring equipment is transmitted to the monitoring center on the well through a wired or wireless communication network. In the monitoring center, the data is processed and analyzed in real time, and the current monitoring data is compared with the historical data and the prediction alarm model in the database to determine the risk status of the coal mine temperature and natural fire. Once an abnormality is found, an alarm signal is immediately issued, and detailed monitoring data and risk assessment reports are provided so that coal mine workers can take corresponding prevention and control measures in a timely manner.

[0040] The present invention is further described below by taking specific experimental methods as embodiments.

[0041] 1. Coal seams contain no CO (carbon monoxide) First, the coal is heated by a program, and its gas is analyzed based on C and O isotopes. A database of the relationship between temperature T and C and O isotope peak ratios is established, and an analysis model is constructed. Gas from the coal seam to be tested is taken through holes at the working face, and the C and O isotope peak ratios are measured. The coal seam temperature is obtained by comparing it with the database, and whether the coal mine is natural is determined, and an early warning is issued.

[0042] 2. Coal seams contain CO (carbon monoxide) First, take the coal and heat it up programmatically. Then analyze the gas based on the C and O isotopes. The value is recorded as A1( )、A1( ), establish the temperature T and , The peak ratio relationship database is used to build an analysis model. Gas is taken from the coal seam to be tested through holes at the working face and the gas is measured. , The value is recorded as A( )、A( ). Then take the original , The value is recorded as A2( )、A2( ). Let A1( )、A1( ) accounts for a, then A2( )、A2( ) accounts for (1-a), so the equation can be set as: A( )=A1( )a+A2( )(1-a) A( )=A1( )a+A2( )(1-a) The simultaneous equations give: We can obtain A1( )、A1( ) ratio. Comparing with the previous database, at different temperatures T and The peak ratio is used to determine the temperature at this time.

[0043] In addition, the specific function of this ratio is to compare the current monitoring data with the historical data and predictive alarm model in the database to determine the risk status of natural fires in coal mines.

[0044] Abnormal status is divided into: 1. Early oxidation: At room temperature, if / The ratio is beyond the fluctuation range of the same temperature stable state in the database, indicating the possible existence; 2. Early oxidation anomaly: In this stage, the carbon and oxygen isotopes in the coal are affected by the oxidation reaction and begin to fractionate slightly; 3. Accelerated oxidation: When the temperature reaches a higher temperature, if the rate of change of the ratio is higher than the standard of normal oxidation at the same temperature stage in the database, it means that oxidation is accelerated and the fire risk increases; 4. Approaching spontaneous combustion: Approaching the spontaneous combustion temperature, when the ratio reaches the critical value in the database, or the ratio fluctuates extremely unstably, it indicates that a fire is about to break out and the risk is extremely high.

Claims

1. A method for predicting and alarming natural fires in coal mines based on a CO isotope database, characterized in that: The specific steps include: S1 Sample Collection Collect coal samples from different coal mines, different coal seams and different mining stages, and systematically measure their CO isotope composition; S2 temperature program The coal sample collected in step S1 is placed in a programmed temperature oxidation experimental device and heated at a set heating rate; S3 isotope analysis The collected samples are subjected to high-precision analysis and determination of CO isotopes to obtain isotope data; S4 database construction The CO isotope database is constructed based on the collected sample location information, sample type information and corresponding CO isotope data, and the correlation between CO isotope characteristics and different development stages of coal mine natural fires is established; S5 real-time monitoring Collect gas samples in real time underground in coal mines and analyze their CO isotope composition to predict the probability and development trend of natural fires in coal mines, and issue an alarm signal in time when the preset danger threshold is reached.

2. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 1, characterized in that: In step S1, the content of the measurement of the coal sample includes the numerical changes of carbon isotopes and oxygen isotopes of the coal sample at various stages of oxidation at room temperature and elevated temperature.

3. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 2, characterized in that: For each sampling point, coal samples are collected at different depths, from the surface to the deep part of the coal seam, to obtain characteristic information of the coal body at different locations.

4. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 1, characterized in that: In step S2, the coal sample is heated at a predetermined heating rate by a programmed temperature oxidation experimental device, and reaction gases at different temperature stages are collected.

5. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 4, characterized in that: Heating is carried out according to the set heating program. During the heating process, the temperature changes of the coal sample are continuously monitored. The monitoring temperature points include 30℃, 50℃, 80℃, and 120℃.

6. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 1, characterized in that: The database construction in step S4 includes the following steps: (1) Data collation and entry Organize and classify the relevant information in the sample collection process, programmed temperature experimental data and isotope analysis results to establish a database; (2) Database architecture design The database adopts a layered architecture design, including the basic data layer, data processing layer and application layer; Establish data indexes and association relationships, integrate related data together through association relationships, and realize fast retrieval and call of data.

7. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 6, characterized in that: The relevant data include tables containing different data; Based on the database constructed in step (1), the data in each table are statistically analyzed to establish a prediction alarm model between CO isotopes and the spontaneous combustion state of coal mines; by analyzing the changing trends and characteristics of isotope data, the isotope threshold range or change pattern of different spontaneous combustion stages is determined.

8. The method for predicting and alarming natural fires in coal mines based on a CO isotope database according to claim 7, characterized in that: In step S5, real-time monitoring includes the following steps: (1) Monitoring equipment installation Install CO isotope monitoring equipment and supporting temperature and gas concentration monitoring sensors in key areas underground in coal mines; (2) Monitoring data transmission and processing The data collected by the monitoring equipment is transmitted to the monitoring center on the well through a wired or wireless communication network; at the monitoring center, the data is processed and analyzed in real time, and the current monitoring data is compared with the historical data and predictive alarm model in the database to determine the risk status of natural fires in the coal mine.

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