A coal seam hidden fire area detection method and system based on ferroelectric material

Abstract

This invention provides a method and system for detecting hidden coal seam fires based on ferroelectric materials, relating to the field of underground coal fire prevention technology. By pre-burying finished ferroelectric materials in the goaf and using ground-penetrating radar for real-time detection, this method can accurately capture changes in the dielectric constant caused by coal seam temperature variations, thereby identifying potential spontaneous combustion risks earlier. Based on the design of cross-temperature and reference dielectric constant, the ferroelectric material can sensitively reflect changes in electromagnetic properties caused by temperature changes. Combined with ground-penetrating radar detection data, a clear electromagnetic characteristic map is formed. This invention solves the blind spot problem of traditional temperature and gas detection technologies, providing more comprehensive and seamless monitoring coverage. By effectively analyzing the electromagnetic characteristic map of monitoring points, the occurrence of spontaneous combustion can be determined in a timely manner, allowing for the layout and delineation of coal fire areas, effectively improving the level of coal mine safety management.

Description

Technical Field

[0001] This invention relates to the field of underground coal fire prevention technology, specifically to a method and system for detecting concealed fire zones in coal seams based on ferroelectric materials. Background Technology

[0002] Concealed coal seam fire zones refer to spontaneous combustion that occurs along the coal seam during coal mining due to natural conditions or human factors, especially in goaf areas. Due to oxygen penetration and heat accumulation, these areas are prone to developing hidden spontaneous combustion fires. Coal spontaneous combustion is characterized by high temperatures, long durations, and the release of large amounts of toxic and harmful gases, seriously threatening the environment and human health. Therefore, timely and effective prevention and control are important research topics for scholars, with early monitoring of coal spontaneous combustion being the most crucial. During coal spontaneous combustion, the temperature field, structural field, chemical field, and electric field of the coal and rock near the fire zone change. These changes can be used to study and determine coal spontaneous combustion. Ground-penetrating radar (GPR) is widely used for early coal fire monitoring due to its high reliability and low cost.

[0003] However, existing ground-penetrating radar (GPR) technologies for detecting coal spontaneous combustion typically suffer from low detection accuracy, limited detection depth, and low resolution, making early detection and location of coal spontaneous combustion difficult and lacking sensitivity. Therefore, in addressing the issue of precise prevention and control for safe and efficient mine production, and specifically for early monitoring of concealed fire zones, a method that can effectively improve detection accuracy and depth is urgently needed to improve early-stage precise monitoring and control technology for coal spontaneous combustion.

[0004] Existing technologies mostly employ traditional temperature monitoring and gas detection methods, which typically rely on installing temperature or gas sensors to monitor for signs of fire. However, these methods are often limited by environmental conditions, sensor accuracy, and monitoring range. Especially in complex underground goaf areas, sensor installation and maintenance face significant challenges. Furthermore, conventional methods cannot fully cover the entire goaf area, resulting in monitoring blind spots and failing to detect spontaneous combustion risks in a timely manner.

[0005] Existing technologies have shortcomings in terms of detection accuracy and reliability. Traditional methods can only provide early warnings after a visible fire has occurred, and cannot detect potential spontaneous combustion risks in advance. The fragility of sensors and the difficulty of data transmission further limit their application. In addition, existing schemes usually do not consider the electromagnetic properties of the coal seam medium and ignore the changes in the dielectric properties of such materials with temperature variations, which may be an important indicator for judging spontaneous combustion. Therefore, there is an urgent need for a new, high-precision method for monitoring coal seam spontaneous combustion to overcome the shortcomings of traditional technologies.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a method and system for detecting concealed fire zones in coal seams based on ferroelectric materials, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A method for detecting concealed fire zones in coal seams based on ferroelectric materials, comprising the following steps:

[0010] Step 1: Coal samples are taken in the area of ​​the goaf to be detected. The oxygen concentration in the goaf is collected and calibrated as the reference oxygen concentration. The obtained coal samples are subjected to a heating experiment under the reference oxygen concentration to obtain the temperature-mass curve and temperature-heat flow curve of the coal samples. Based on the temperature-mass curve and temperature-heat flow curve, the temperature value corresponding to the maximum change in mass and heat flow is found and calibrated as the cross temperature.

[0011] Step 2: Measure the dielectric constant curve of the coal sample during the heating process under the reference oxygen concentration, determine the maximum dielectric constant of the coal sample during the heating process, and calibrate it as the reference dielectric constant. Determine the Curie temperature design reference value of the ferroelectric material based on the cross temperature, and determine the reference dielectric constant value of the ferroelectric material based on the reference dielectric constant.

[0012] Step 3: Based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials, construct the finished ferroelectric material, pre-embed the finished ferroelectric material at the working face of the goaf to be detected, and use each pre-embedded point as a monitoring point, record the coordinate information of each monitoring point, including the location coordinate information and the depth information from the ground, to form a coal seam ferroelectric material detection network;

[0013] Step 4: Use ground-penetrating radar to conduct real-time detection on the ground above the goaf, obtain ground-penetrating radar reflected wave data above each monitoring point, obtain radar characteristic data of each detection point based on the reflected wave data, and calculate the actual dielectric constant of the ferroelectric material product at each monitoring point based on the radar characteristic data and the coordinate information of the monitoring point, and construct the electromagnetic characteristic map of the goaf.

[0014] Step 5: Compare the electromagnetic characteristic diagram with the dielectric constant reference value of the finished ferroelectric material to determine the spontaneous combustion situation at each monitoring point in the goaf, and extract the location coordinate information of each monitoring point where spontaneous combustion occurred to divide the coal fire area.

[0015] Furthermore, the method for obtaining the temperature-mass curve and temperature-heat flow curve of the coal sample is as follows:

[0016] The coal sample was divided into two equal parts and placed in the sample trays of the thermogravimetric analyzer and the differential scanning calorimeter, respectively. The oxygen concentration in the thermogravimetric analyzer and the differential scanning calorimeter was adjusted to be consistent with the reference oxygen concentration.

[0017] The heating rate was set to 2℃ / s, and the heating experiment was started. The temperature was increased from room temperature to the target temperature. During the heating process, the thermogravimetric analyzer recorded the data of the mass of the coal sample changing with temperature, and the differential scanning calorimeter recorded the data of the heat flow of the sample changing with temperature.

[0018] Plot the temperature on the x-axis and the percentage change in sample mass (i.e., the real-time mass to the initial mass) on the y-axis to show the mass change trend throughout the heating process, thus forming a temperature-mass curve.

[0019] Plot the heat flow trend throughout the heating process with temperature on the x-axis and heat flow on the y-axis to form a temperature-heat flow curve.

[0020] Furthermore, the logic for obtaining the cross temperature is as follows:

[0021] The temperature-mass curve and temperature-heat flux curve are divided according to temperature and isothermal width. The formulas used to calculate the rate of change of sample mass and the rate of change of heat flux within each temperature range are as follows:

[0022]

[0023]

[0024] in, and They represent the first The rate of change of sample mass and the rate of change of heat flux within a temperature range and These represent the values ​​in the temperature-mass curve, respectively. Sample mass change data at the start and end times of each temperature range. and These represent the first and second parts of the temperature-heat flux curve, respectively. Heat flow data at the start and end times of each temperature range and They represent the first The start and end times of each temperature range , and These represent the room temperature data and the target temperature data during the heating experiment, respectively.

[0025] Calculate the product of the sample mass change rate and the heat flow change rate within each temperature range, and select the temperature range where the product of the sample mass change rate and the heat flow change rate is the largest. Use the median temperature within the temperature range where the product is the largest as the cross temperature.

[0026] Furthermore, the cross temperature is equal to the Curie temperature design reference value for ferroelectric materials. The reference dielectric constant is then multiplied by at least 10 and set as the reference value for the dielectric constant of ferroelectric materials, based on the following formula:

[0027]

[0028]

[0029] in, and These represent the Curie temperature design reference value and the dielectric constant reference value for ferroelectric materials, respectively. Indicates cross temperature. Indicates the reference dielectric constant. Indicates the amplification factor of the reference dielectric constant, and .

[0030] Furthermore, the method for constructing finished ferroelectric materials based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials is as follows:

[0031] Lithium niobate was chosen as the base material for ferroelectric materials, and magnesium or manganese was selected as the doping element. The influence of the Curie temperature design reference value and the dielectric constant reference value were considered, and the doping amount of the doping element was adjusted according to the following formula:

[0032]

[0033]

[0034] in, and This indicates the adjusted Curie temperature and dielectric constant. and These represent the initial Curie temperature and initial dielectric constant of lithium niobate, respectively. and These are the Curie temperature doping coefficient and the dielectric constant doping coefficient, respectively. This represents the doping concentration of the doped element.

[0035] Choose an initial doping concentration, and adjust the doping concentration of the dopant element using an iterative algorithm until the errors of the two equations simultaneously meet the error requirements. When both requirements are met:

[0036]

[0037]

[0038] Determine the doping concentration of the dopant element. Indicates the allowable error range. Based on the determined doping concentration values ​​of the doping elements, a ferroelectric material product with a fixed thickness is generated.

[0039] Furthermore, the radar characteristic data includes the total reflection time of the radar wave, and the formula used to calculate the actual dielectric constant of the ferroelectric material product at each monitoring point is as follows:

[0040]

[0041]

[0042] in, and They represent the first The propagation time and actual dielectric constant of ferroelectric materials at each monitoring point during ground-penetrating radar detection. Indicates the first The total reflection time of radar waves at each monitoring point during ground-penetrating radar detection. ,and They represent the first The thickness of the stratum above the ferroelectric material and its depth from the ground at each monitoring point. Indicates the first The dielectric constant of the strata above each monitoring point It represents the speed of light.

[0043] Furthermore, the thickness of the stratum above the ferroelectric material and the dielectric constant of the stratum above all monitoring points are taken as the same value. When constructing the electromagnetic characteristic map of the goaf, the actual dielectric constant and location coordinate information of each monitoring point are mapped one by one to construct the electromagnetic characteristic map of the entire goaf.

[0044] Furthermore, the logic used to determine the spontaneous combustion situation at each monitoring point within the goaf is as follows:

[0045] Based on the location coordinates of each detection point, the closest detection point to the point to be judged is selected, and the distance between them is calculated. Based on the actual dielectric constants of the two monitoring points and the distance between them, the spontaneous combustion risk index is calculated using the following formula:

[0046]

[0047] in, This indicates the spontaneous combustion risk index of the detection point to be assessed. This represents the distance between the detection point to be judged and the nearest detection point. and These represent the actual dielectric constants of the detection point to be judged and the detection point closest to the detection point to be judged, respectively. This indicates a reference value for the dielectric constant of the finished ferroelectric material.

[0048] When the spontaneous combustion risk index When the threshold value exceeds the empirical assessment threshold, it is determined that spontaneous combustion has occurred at the monitoring point.

[0049] The present invention also provides a coal seam concealed fire zone detection system based on ferroelectric materials. The detection system is used to execute the aforementioned coal seam concealed fire zone detection method based on ferroelectric materials, comprising:

[0050] The sample calibration module is used to sample coal in the area of ​​the goaf to be detected, collect the oxygen concentration in the goaf and calibrate it as the reference oxygen concentration, conduct a heating experiment on the obtained coal sample under the reference oxygen concentration condition, obtain the temperature-mass curve and temperature-heat flow curve of the coal sample, find the temperature value corresponding to the maximum change of mass and heat flow based on the temperature-mass curve and temperature-heat flow curve, and calibrate it as the cross temperature.

[0051] The reference analysis module is used to measure the dielectric constant curve of a coal sample during the heating process under reference oxygen concentration conditions, determine the maximum dielectric constant of the coal sample during the heating process, and calibrate it as the reference dielectric constant. Based on the cross temperature, the Curie temperature design reference value of the ferroelectric material is determined, and based on the reference dielectric constant, the reference value of the dielectric constant of the ferroelectric material is determined.

[0052] The network construction module is used to construct ferroelectric material products based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials. The ferroelectric material products are pre-embedded in the working face of the goaf to be detected, and each pre-embedded point is used as a monitoring point. The coordinate information of each monitoring point is recorded. The coordinate information includes the location coordinate information of the monitoring point and the depth information from the ground, forming a coal seam ferroelectric material detection network.

[0053] The radar detection module uses ground-penetrating radar to conduct real-time detection on the ground above the goaf, acquires ground-penetrating radar reflected wave data above each monitoring point, obtains radar characteristic data of each detection point based on the reflected wave data, and calculates the actual dielectric constant of the ferroelectric material product at each monitoring point based on the radar characteristic data and the coordinate information of the monitoring point, and constructs an electromagnetic characteristic map of the goaf.

[0054] The fire zone analysis module is used to compare the electromagnetic characteristic diagram with the dielectric constant reference value of the finished ferroelectric material to determine the spontaneous combustion situation of each monitoring point in the goaf, and extract the location coordinate information of each monitoring point where spontaneous combustion is determined to occur to divide the coal fire zone.

[0055] Compared with the prior art, the beneficial effects of the present invention are:

[0056] This invention achieves more efficient detection of hidden fire zones in coal seams by utilizing the unique dielectric properties of ferroelectric materials. By pre-embedding finished ferroelectric materials in the goaf and using ground-penetrating radar for real-time detection, this method can accurately capture changes in the dielectric constant caused by coal seam temperature variations, thereby identifying potential spontaneous combustion risks earlier. Based on the design of cross-temperature and reference dielectric constant, the ferroelectric material can sensitively reflect changes in electromagnetic properties caused by temperature changes. Combined with ground-penetrating radar detection data, a clear electromagnetic characteristic map is formed. This invention solves the blind spot problem of traditional temperature and gas detection technologies, providing more comprehensive and seamless monitoring coverage. By effectively analyzing the electromagnetic characteristic maps of monitoring points, the occurrence of spontaneous combustion can be determined in a timely manner, allowing for the layout and delineation of coal fire zones, effectively improving the level of coal mine safety management. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the overall method flow of the present invention;

[0058] Figure 2 This is a schematic diagram of the temperature range division in this invention;

[0059] Figure 3 This is a schematic diagram illustrating the operation of the ground-penetrating radar in the goaf detection area according to the present invention;

[0060] Figure 4 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0062] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0063] Example:

[0064] Please see Figures 1-3 The present invention provides a technical solution:

[0065] A method for detecting concealed fire zones in coal seams based on ferroelectric materials, comprising the following steps:

[0066] Step 1: Coal samples are taken in the goaf area to be explored. The oxygen concentration in the goaf is collected and calibrated as the reference oxygen concentration. The obtained coal samples are subjected to a heating experiment under the reference oxygen concentration conditions to obtain the temperature-mass curve and temperature-heat flow curve of the coal samples. Based on the temperature-mass curve and temperature-heat flow curve, the temperature value corresponding to the maximum change in both mass and heat flow is found and calibrated as the cross temperature.

[0067] Representative coal samples and oxygen concentration data from the goaf were collected. This oxygen concentration was designated as a reference concentration for setting subsequent heating experiment conditions, ensuring consistency with the actual environment. After sampling, the coal samples needed to be homogenized to ensure consistency in the heating experiment and accuracy of the data. Therefore, the coal samples were mechanically ground into uniformly sized small particles to increase the surface area of ​​the samples, ensuring uniform heating and a more complete reaction during thermal analysis.

[0068] In this embodiment, the method for obtaining the temperature-mass curve and temperature-heat flow curve of the coal sample is as follows:

[0069] The coal sample was divided into two equal parts by mass and placed in the sample pans of a thermogravimetric analyzer (TGA) and a differential scanning calorimeter (DSC), respectively. The oxygen concentration in both the TGA and DSC was adjusted to match the reference oxygen concentration. Dividing the coal sample into two equal parts allowed for simultaneous measurements on different types of analytical instruments, thus obtaining more comprehensive thermal reaction information. The TGA is mainly used to measure the mass loss of the sample as the temperature increases, which helps to understand the volatile components, pyrolysis, and oxidation behavior of the sample. The DSC is used to measure the heat flow changes of the sample at different temperatures, helping to identify exothermic or endothermic processes. Therefore, the two instruments provide different but complementary information. Dividing the sample into two equal parts ensures that the sample has similar initial conditions in both analyzers, thus making the heating experiment results comparable and accurate.

[0070] The heating rate was set to 2℃ / s, and the heating experiment was started. The temperature was increased from room temperature to the target temperature. During the heating process, the thermogravimetric analyzer recorded the data of the mass of the coal sample changing with temperature, and the differential scanning calorimeter recorded the data of the heat flow of the sample changing with temperature.

[0071] Plot the temperature on the x-axis and the percentage change in sample mass (i.e., the real-time mass to the initial mass) on the y-axis to show the mass change trend throughout the heating process, thus forming a temperature-mass curve.

[0072] Plot the heat flow trend throughout the heating process with temperature on the x-axis and heat flow on the y-axis to form a temperature-heat flow curve.

[0073] As the temperature rises, the thermogravimetric analyzer records the mass loss data of the sample. The instrument records mass changes at certain time intervals or temperature intervals. The differential scanning calorimeter records the heat flow changes of the sample, representing the endothermic or exothermic process of the sample at different temperatures. Heat flow data is also recorded at time or temperature intervals.

[0074] The temperature-mass curve has temperature on the x-axis (in degrees Celsius) and sample mass change on the y-axis (the percentage of real-time mass to initial mass). The temperature-heat flux curve has temperature on the x-axis (in degrees Celsius) and heat flux on the y-axis (in milliwatts). The x-axis of the temperature-mass and temperature-heat flux curves are strictly corresponding. Both curves are based on the same temperature program, hence their x-axis is temperature. During the experiment, the sample temperature is controlled by a set heating rate, and data acquisition is synchronous. Therefore, for any given time point, the temperatures recorded by the two instruments should be consistent.

[0075] By accurately simulating the actual oxygen concentration environment of a goaf, a systematic thermal analysis of coal samples can more realistically reflect the thermal behavior and reaction characteristics of coal in a real environment. Analyzing under a reference oxygen concentration ensures that the experimental conditions more closely resemble the actual goaf environment. This realistic simulation improves the reliability and practicality of the experimental results. By analyzing temperature-mass and temperature-heat flow curves, the crossover temperature points of coal during pyrolysis or oxidation reactions can be precisely located, helping to better predict the risk of spontaneous combustion in coal.

[0076] Furthermore, the logic for obtaining the cross temperature is as follows:

[0077] The temperature-mass curve and temperature-heat flux curve are divided according to temperature and isothermal width. The formulas used to calculate the rate of change of sample mass and the rate of change of heat flux within each temperature range are as follows:

[0078]

[0079]

[0080] in, and They represent the first The rate of change of sample mass and the rate of change of heat flux within a temperature range and These represent the values ​​in the temperature-mass curve, respectively. Sample mass change data at the start and end times of each temperature range. and These represent the first and second parts of the temperature-heat flux curve, respectively. Heat flow data at the start and end times of each temperature range and They represent the first The start and end times of each temperature range , and These represent the room temperature data and the target temperature data during the heating experiment, respectively.

[0081] Calculate the product of the sample mass change rate and the heat flow change rate within each temperature range, and select the temperature range where the product of the sample mass change rate and the heat flow change rate is the largest. Use the median temperature within the temperature range where the product is the largest as the cross temperature.

[0082] When analyzing temperature-mass curves and temperature-heat flow curves, the crossover temperature is a key indicator. It helps identify the most significant thermal changes in the sample. The heating experiment starts at room temperature and proceeds to the target temperature, dividing this temperature range evenly. There are several temperature ranges, each with a width of [missing value]. This ensures that the temperature change is uniform within each interval.

[0083] For each temperature range, calculate the rate of change of sample mass. and rate of change of heat flux , This indicates the change in mass within this interval. This represents the change in heat flow. Dividing it by the temperature span of the interval can standardize the rate of change for different intervals, making the results for different intervals comparable.

[0084] The product of the rate of change of mass and the rate of change of heat flux within each temperature range reflects the overall intensity of thermal change within that range. Calculating these products helps identify which temperature ranges exhibit the most intense thermal response in the sample. This product calculation aims to combine two distinct thermal response indicators—mass and heat flux—to provide a more comprehensive analysis, identifying the ranges with the largest products of rate of change across all temperature ranges. These product values ​​reflect the intensity of the sample's thermal response in different temperature ranges. The range with the largest product signifies the most significant thermal change occurring within that range, and is our focus because it may indicate a specific thermal event or transition.

[0085] The median temperature within the temperature range where the product is maximized is used as the cross temperature. This choice ensures that the cross temperature accurately reflects the most significant thermal changes in the sample. The cross temperature is a comprehensive indicator, combining information on changes in mass and heat flux, which helps to understand the thermal dynamics of the sample more deeply. The median temperature within the range is chosen when determining the cross temperature because it represents the overall temperature characteristics of that range. The median is the average value of the temperature range, which can better reflect the overall temperature state of that range. Using the median as the cross temperature avoids the influence of extreme cases and provides a robust representative temperature.

[0086] By calculating the product of the rates of change, two independent thermal response parameters, mass and heat flux, are integrated to provide a more comprehensive indicator to capture significant changes in the sample during heating. This combination provides a more sensitive and comparable way to identify dramatic thermal changes in a temperature range, and more accurately reflects the thermal behavior of the sample compared to using mass or heat flux data alone.

[0087] By simultaneously considering the product of the rates of change of these two parameters, we can more accurately identify the critical thermal transition points of a sample. Thermal transition processes typically involve significant changes in the physical or chemical properties of coal samples, such as phase transitions, decomposition, or chemical reactions. At these transition points, both the sample's mass and heat flux change significantly. By calculating the product of the rate of change of mass and the rate of change of heat flux, we can obtain a comprehensive index, which naturally peaks at the transition points because both independent changes are most dramatic at this time. The changes in mass and heat flux occur simultaneously with respect to temperature, and their synergistic effect reaches its maximum during the thermal transition process. Therefore, the point of maximum product reflects the strongest synergistic effect of these two processes.

[0088] Step 2: Measure the dielectric constant curve of the coal sample during the heating process under the reference oxygen concentration, determine the maximum dielectric constant of the coal sample during the heating process, and calibrate it as the reference dielectric constant. Determine the Curie temperature design reference value of the ferroelectric material based on the cross temperature, and determine the reference dielectric constant value of the ferroelectric material based on the reference dielectric constant.

[0089] Prepare coal samples, ensuring their size and shape are suitable for placement in the measuring equipment. Select a network analyzer as the dielectric constant measuring instrument, placing the sample in the controlled temperature environment of the thermal analyzer to record the dielectric constant in real time during sample heating. Set oxygen concentration as a reference standard to ensure the stability and comparability of the measurement conditions.

[0090] The temperature was gradually increased at a rate of 2℃ / s from room temperature to the target temperature. Throughout the heating process, the dielectric constant of the sample was continuously recorded. After the heating was completed, the data was analyzed to identify the peak point of the dielectric constant curve, i.e., the maximum value. This maximum value is the highest dielectric constant reached by the coal sample during the heating process and is designated as the reference dielectric constant.

[0091] In this embodiment, the cross temperature is equal to the Curie temperature design reference value for ferroelectric materials. The reference dielectric constant is increased by at least 10 times and set as the reference value for the dielectric constant of the ferroelectric material. The formula used is:

[0092]

[0093]

[0094] in, and These represent the Curie temperature design reference value and the dielectric constant reference value for ferroelectric materials, respectively. Indicates cross temperature. Indicates the reference dielectric constant. Indicates the amplification factor of the reference dielectric constant, and .

[0095] The Curie temperature is the temperature at which a ferroelectric material transitions from its ferroelectric to its paraelectric state. At this temperature, the dielectric properties of the material change significantly, making it a critical detection point. Setting the cross temperature as the design reference value for the Curie temperature is based on actual measurements from heating experiments. The cross temperature is the temperature at which the product of mass and rate of change of heat flux reaches its maximum during the heating process of coal, reflecting the key thermal transition point of the coal sample. Equating it with the Curie temperature design reference value for ferroelectric materials ensures that the material is sensitive to potential thermal anomalies in the detection environment, thereby improving the accuracy and sensitivity of the detection.

[0096] Set the dielectric constant reference value as the reference dielectric constant. The purpose of multiplying the dielectric constant is to enhance the response capability of the detection system. Near the Curie temperature, the dielectric constant of ferroelectric materials increases significantly. Therefore, the dielectric constant is amplified in the design to expand the dynamic range of the material during the detection process. This amplification ensures that even with small thermal changes, the change in the dielectric constant of ferroelectric materials can be detected, thereby improving the sensitivity and detection distance of the detection system.

[0097] In this embodiment, the selection is... As a magnification factor, this factor is sufficient in most cases to cover the range of dielectric constant variation of ferroelectric materials near the Curie temperature, ensuring that it can provide sufficient detection signal strength and resolution when faced with different degrees of spontaneous combustion or thermal anomalies, without detection interference or misjudgment due to excessive amplification.

[0098] Step 3: Based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials, construct the finished ferroelectric material, pre-embed the finished ferroelectric material at the working face of the goaf to be detected, and use each pre-embedded point as a monitoring point, record the coordinate information of each monitoring point, including the location coordinate information and the depth information of the monitoring point from the ground, to form a coal seam ferroelectric material detection network.

[0099] In this implementation, the method for constructing the finished ferroelectric material based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials is as follows:

[0100] Lithium niobate was chosen as the base material for ferroelectric materials, and magnesium or manganese was selected as the doping element. The influence of the Curie temperature design reference value and the dielectric constant reference value were considered, and the doping amount of the doping element was adjusted according to the following formula:

[0101]

[0102]

[0103] in, and This indicates the adjusted Curie temperature and dielectric constant. and These represent the initial Curie temperature and initial dielectric constant of lithium niobate, respectively. and These are the Curie temperature doping coefficient and the dielectric constant doping coefficient, respectively. This represents the doping concentration of the dopant element.

[0104] Doping concentration The molar fraction of the doping element in lithium niobate was used to conduct a series of experiments, measuring the Curie temperature and dielectric constant at different doping concentrations. The optimal doping concentration was then determined through linear regression analysis. and value

[0105] Lithium niobate is a widely used ferroelectric material with excellent ferroelectric properties and a high Curie temperature, making it perform well in high-temperature environments. Furthermore, lithium niobate possesses good thermal stability and mechanical strength, making it suitable for use in complex geological environments. Its high dielectric constant allows it to effectively respond to changes in the environmental electric field, making it ideal for detection applications. Magnesium or manganese doping helps optimize the performance of lithium niobate. Magnesium doping can improve the material's fatigue resistance and crack resistance, enhancing its stability and durability under high stress conditions, while manganese doping can increase the material's electrical conductivity and dielectric response speed, resulting in a faster response in environments with rapid temperature changes. Doping with magnesium or manganese can adjust the Curie temperature of lithium niobate to better meet the requirements of this embodiment.

[0106] High-purity ferroelectric material powder was synthesized by controlling temperature and chemical composition. It was then sintered into cylinders with a diameter of 5 cm and a length of 10 cm. The cylindrical shape was chosen to reduce stress concentration during pre-embedding and to provide a larger surface area for improved detection sensitivity. Before pre-embedding, the dielectric constant and Curie temperature of the prepared ferroelectric material samples were tested. A precision dielectric analyzer was used to measure the change in dielectric constant under simulated underground temperature and pressure conditions to ensure consistency with the design value. This step was conducted in a controlled laboratory environment to eliminate the influence of external variables on material performance and ensure predictable material performance under field conditions.

[0107] On the working face of the goaf, a drilling rig is used to drill holes at predetermined points. The hole diameter is slightly larger than the diameter or thickness of the material. The upper end of the finished ferroelectric material is level with the working face of the goaf. The finished ferroelectric material is placed into the hole and fixed with high-temperature resistant ceramic filler to protect the material from mechanical damage and chemical corrosion. After pre-embedding, GPS equipment is used to record the geographical coordinates and depth information of each monitoring point to ensure that the location information of each monitoring point is associated with the characteristic data of the ferroelectric material, which facilitates subsequent ground-penetrating radar data collection and analysis. During pre-embedding, the material is pre-embedded in areas that are identified as potentially risky and areas with representative geological features, and the minimum distance between the finished ferroelectric materials is 10 meters.

[0108] Choose an initial doping concentration, and adjust the doping concentration of the dopant element using an iterative algorithm until the errors of the two equations simultaneously meet the error requirements. When both requirements are met:

[0109]

[0110]

[0111] Determine the doping concentration of the dopant element. Indicates the allowable error range. Based on the determined doping concentration values ​​of the doping elements, a ferroelectric material product with a fixed thickness is generated.

[0112] The purpose of setting this iterative algorithm and error range is to achieve precise performance standards during the material optimization process, while ensuring production feasibility and economy. The reasons for this setting and the origin of the value range 0 < δ < 0.05 are as follows:

[0113] The initial concentration is only an estimate. Through iteration, the doping concentration can be gradually adjusted to better match the target Curie temperature and dielectric constant. Two independent performance indicators need to be met simultaneously. The iterative algorithm, through continuous adjustment, gradually approaches these two targets. Through iterative adjustments, batch-to-batch performance consistency can be achieved in experiments and production, reducing the impact of performance fluctuations. In practical materials science and engineering applications, completely eliminating errors is unrealistic. Allowing a certain degree of error allows materials to be produced and applied within reasonable manufacturing tolerances. This means that the error range for Curie temperature and dielectric constant is within 5%. In industrial applications, an error within 5% is acceptable. This can be achieved by setting... This ensures that the performance of the finished ferroelectric materials is close enough to the requirements, while allowing for certain manufacturing and measurement tolerances, thereby achieving better stability and reliability in practical applications.

[0114] In iterative algorithms, the initial Curie temperature and dielectric constant of the material are calculated using an initial concentration. The errors between these calculated values ​​and the target values ​​are then compared. If the error is within a set range, the current concentration is the optimal solution; otherwise, the doping concentration needs to be adjusted. This adjustment can utilize existing techniques, such as numerical optimization algorithms, including gradient descent, or more advanced machine learning optimization strategies. These methods update the concentration based on the direction and magnitude of the error. Typically, in each iteration, new performance values ​​are calculated and the error is evaluated, gradually adjusting the concentration to be as close to the equilibrium point as possible to minimize the error. In this way, the algorithm can converge to a doping concentration that satisfies the conditions more quickly.

[0115] Step 4: Use ground-penetrating radar to conduct real-time detection on the ground above the goaf, obtain ground-penetrating radar reflected wave data above each monitoring point, obtain radar characteristic data of each detection point based on the reflected wave data, and calculate the actual dielectric constant of the ferroelectric material product at each monitoring point based on the radar characteristic data and the coordinate information of the monitoring point, and construct the electromagnetic characteristic map of the goaf.

[0116] Ground-penetrating radar (GPR) equipment is deployed above the goaf. It scans the area according to the coordinates of each monitoring point. Each scan generates a set of reflected wave data. The total reflection time of the radar wave refers to the time elapsed from the emission of the radar wave to the reception of the reflected wave. When the GPR equipment is operating, the antenna emits high-frequency electromagnetic pulses. These pulses are reflected when they encounter interfaces between different underground media. The receiver records these reflected signals. The GPR equipment contains a precise timing device that starts counting when a pulse is emitted. When the receiver receives the reflected signal, the timer records the current time. The difference between these two time points is the reflection time.

[0117] In this embodiment, the radar characteristic data includes the total reflection time of the radar wave, and the formula used to calculate the actual dielectric constant of the ferroelectric material product at each monitoring point is as follows:

[0118]

[0119]

[0120] in, and They represent the first The propagation time and actual dielectric constant of ferroelectric materials at each monitoring point during ground-penetrating radar detection. Indicates the first The total reflection time of radar waves at each monitoring point during ground-penetrating radar detection. ,and They represent the first The thickness of the stratum above the ferroelectric material and its depth from the ground at each monitoring point. Indicates the first The dielectric constant of the strata above each monitoring point It represents the speed of light.

[0121] This implementation utilizes the total reflection time of radar waves. To obtain the propagation time of ferroelectric materials The total reflection time includes the propagation time of electromagnetic waves between different layers. By subtracting the propagation time in the stratum above the ferroelectric material and the propagation time in the air, the propagation time in the ferroelectric material is decomposed. In order to obtain the propagation time in the ferroelectric material from the total reflection time, this embodiment considers the propagation time of electromagnetic waves in the stratum above the ferroelectric material. This time is determined by the stratum thickness and the dielectric constant of the stratum, because these factors affect the propagation speed of the wave in the stratum, ensuring that only the propagation of the ferroelectric material is considered.

[0122] Once the propagation time in a pure ferroelectric material is obtained, the dielectric constant can be calculated based on the formula for the propagation speed of electromagnetic waves in a medium, using the known speed of light and the thickness of the ferroelectric material. The dielectric constant directly affects the speed of the wave in the material, allowing the total reflection time obtained by ground penetrating radar to be converted into an accurate assessment of the actual dielectric properties of the ferroelectric material. This enables the separation of the influence of each layer of material on radar wave propagation, providing more accurate data on the characteristics of underground materials.

[0123] Furthermore, the thickness of the stratum above the ferroelectric material and the dielectric constant of the stratum above all monitoring points are taken as the same value. When constructing the electromagnetic characteristic map of the goaf, the actual dielectric constant and location coordinate information of each monitoring point are mapped one by one to construct the electromagnetic characteristic map of the entire goaf.

[0124] In ground-penetrating radar (GPR) detection, using the same stratum thickness and dielectric constant of the overlying stratum for all monitoring points is based on the simplification and homogeneity assumptions of the actual exploration scenario. In areas where geological conditions do not vary much, the composition and properties of the strata are relatively uniform. Therefore, using uniform parameters simplifies the computational complexity and improves the efficiency of data processing. The determination of stratum thickness and dielectric constant depends on existing geological exploration data, drilling sample analysis, or preliminary ground-penetrating radar measurements.

[0125] A preliminary assessment of the target area is conducted through geological surveys and historical data collection. This includes reviewing regional geological maps, existing borehole records, and geological reports to gain a preliminary understanding of the stratigraphic structure. If ground-penetrating radar (GPR) data is available, it can be used to identify stratigraphic interfaces and variations in thickness. In the field, detailed exploration is carried out through drilling to collect samples and GPR measurements. Drilling provides precise information on stratigraphic thickness, and sampling analysis reveals its physical and chemical properties. Simultaneously, GPR equipment is used to measure the propagation characteristics of electromagnetic waves within the strata. Combined with geological profiles and reflection data, the dielectric constant is preliminarily estimated, enabling precise determination of stratigraphic parameters. Collected geological samples undergo further analysis in the laboratory to accurately determine the dielectric constant of the strata.

[0126] Step 5: Compare the electromagnetic characteristic diagram with the dielectric constant reference value of the finished ferroelectric material to determine the spontaneous combustion situation at each monitoring point in the goaf, and extract the location coordinate information of each monitoring point where spontaneous combustion occurred to divide the coal fire area.

[0127] In this embodiment, the logic used to determine the spontaneous combustion status of each monitoring point within the goaf is as follows:

[0128] Based on the location coordinates of each probe point, the closest probe point to the probe point to be judged is selected, and the distance between them is calculated. The location coordinates of the probe points refer to the numerical representation of their positions in space; these coordinates can be latitude and longitude on a plane. When selecting the closest probe point to the probe point to be judged based on the location coordinates of each probe point, it is necessary to calculate the distances between the probe point to be judged and all other probe points. These distances are calculated using the Euclidean distance formula, and the minimum distance value is determined by comparison to identify which probe point is closest to the probe point to be judged.

[0129] The spontaneous combustion risk index is calculated based on the actual dielectric constants of the two monitoring points and the distance between them, using the following formula:

[0130]

[0131] in, This indicates the spontaneous combustion risk index of the detection point to be assessed. This represents the distance between the detection point to be judged and the nearest detection point. and These represent the actual dielectric constants of the detection point to be judged and the detection point closest to the detection point to be judged, respectively. This indicates a reference value for the dielectric constant of the finished ferroelectric material.

[0132] When the spontaneous combustion risk index When the spontaneous combustion risk index exceeds the empirical assessment threshold, it is determined that spontaneous combustion has occurred at the monitoring point. When the spontaneous combustion risk index exceeds the empirical assessment threshold, it is determined that the monitoring point has a spontaneous combustion risk and may have already experienced spontaneous combustion. The determination of the empirical assessment threshold is usually based on historical data analysis and expert experience. By collecting a large amount of historical spontaneous combustion event data, the patterns of spontaneous combustion under different conditions are analyzed to identify which index value ranges are more frequent. A reasonable threshold is set to ensure that it can provide timely warnings of potential spontaneous combustion events without causing unnecessary intervention due to false alarms.

[0133] Spontaneous combustion and other geological activities are often characterized by localization. The spread of heat, gas, or chemical reactions in space is often gradual rather than instantaneous. Therefore, anomalies at one monitoring point can affect neighboring areas. By analyzing the situation at the nearest point, we can better understand the patterns of change and risks within a local area. In spontaneous combustion environments, anomalies have a certain degree of spatial expansion. Selecting the nearest point helps to capture this spatial diffusion effect. Temperature changes or gas accumulation in goaf areas often affect adjacent areas. By comparing adjacent points, we can identify whether the anomaly has regional characteristics, rather than just being an isolated event.

[0134] Ferroelectric materials have a high dielectric constant, which varies significantly with temperature. By pre-burying them in the working face, when spontaneous combustion occurs in the coal seam, the material gradually heats up, and the change in dielectric constant is quite obvious. This can significantly improve the detection resolution and accuracy. Furthermore, since the working face has a large area, by pre-burying the material and arranging it to form a coal seam ferroelectric material detection network, the evolution of dielectric signals in a region can be reflected, thereby reflecting the temperature changes in that region.

[0135] The spontaneous combustion risk index reflects the degree of change in the dielectric constant at a monitoring point and its correlation with neighboring monitoring points. A higher spontaneous combustion risk index indicates a greater difference between the dielectric constant at that monitoring point and the reference value for the dielectric constant of the finished ferroelectric material. Furthermore, this difference is more consistent with changes at neighboring monitoring points, thus indicating a higher risk of spontaneous combustion. It reflects local changes in the material's state; the greater the deviation between the actual dielectric constant and the reference value, the more significant the change and the higher the risk of spontaneous combustion. The introduction of nonlinear growth means that as the distance increases, the influence of nearby points gradually increases under the same deviation, but it will not increase too quickly. This is because, under the same deviation, the farther the distance, the more serious the risk or situation of spontaneous combustion, which can already affect the nearest monitoring point.

[0136] Please see Figure 4 The present invention also provides a coal seam concealed fire zone detection system based on ferroelectric materials. The detection system is used to execute the above-described coal seam concealed fire zone detection method based on ferroelectric materials, comprising:

[0137] The sample calibration module is used to sample coal in the area of ​​the goaf to be detected, collect the oxygen concentration in the goaf and calibrate it as the reference oxygen concentration, conduct a heating experiment on the obtained coal sample under the reference oxygen concentration condition, obtain the temperature-mass curve and temperature-heat flow curve of the coal sample, find the temperature value corresponding to the maximum change of mass and heat flow based on the temperature-mass curve and temperature-heat flow curve, and calibrate it as the cross temperature.

[0138] The reference analysis module is used to measure the dielectric constant curve of a coal sample during the heating process under reference oxygen concentration conditions, determine the maximum dielectric constant of the coal sample during the heating process, and calibrate it as the reference dielectric constant. Based on the cross temperature, the Curie temperature design reference value of the ferroelectric material is determined, and based on the reference dielectric constant, the reference value of the dielectric constant of the ferroelectric material is determined.

[0139] The network construction module is used to construct ferroelectric material products based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials. The ferroelectric material products are pre-embedded in the working face of the goaf to be detected, and each pre-embedded point is used as a monitoring point. The coordinate information of each monitoring point is recorded. The coordinate information includes the location coordinate information of the monitoring point and the depth information from the ground, forming a coal seam ferroelectric material detection network.

[0140] The radar detection module uses ground-penetrating radar to conduct real-time detection on the ground above the goaf, acquires ground-penetrating radar reflected wave data above each monitoring point, obtains radar characteristic data of each detection point based on the reflected wave data, and calculates the actual dielectric constant of the ferroelectric material product at each monitoring point based on the radar characteristic data and the coordinate information of the monitoring point, and constructs an electromagnetic characteristic map of the goaf.

[0141] The fire zone analysis module is used to compare the electromagnetic characteristic diagram with the dielectric constant reference value of the finished ferroelectric material to determine the spontaneous combustion situation of each monitoring point in the goaf, and extract the location coordinate information of each monitoring point where spontaneous combustion is determined to occur to divide the coal fire zone.

[0142] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0143] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0144] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0145] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for detecting concealed fire zones in coal seams based on ferroelectric materials, characterized in that, The specific steps include: Step 1: Coal samples are taken in the area of ​​the goaf to be detected. The oxygen concentration in the goaf is collected and calibrated as the reference oxygen concentration. The obtained coal samples are subjected to a heating experiment under the reference oxygen concentration to obtain the temperature-mass curve and temperature-heat flow curve of the coal samples. Based on the temperature-mass curve and temperature-heat flow curve, the temperature value corresponding to the maximum change in mass and heat flow is found and calibrated as the cross temperature. Step 2: Measure the dielectric constant curve of the coal sample during the heating process under the reference oxygen concentration, determine the maximum dielectric constant of the coal sample during the heating process, and calibrate it as the reference dielectric constant. Determine the Curie temperature design reference value of the ferroelectric material based on the cross temperature, and determine the reference dielectric constant value of the ferroelectric material based on the reference dielectric constant. Step 3: Based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials, construct the finished ferroelectric material, pre-embed the finished ferroelectric material at the working face of the goaf to be detected, and use each pre-embedded point as a monitoring point, record the coordinate information of each monitoring point, including the location coordinate information and the depth information from the ground, to form a coal seam ferroelectric material detection network; Step 4: Use ground-penetrating radar to conduct real-time detection on the ground above the goaf, obtain ground-penetrating radar reflected wave data above each monitoring point, obtain radar characteristic data of each detection point based on the reflected wave data, and calculate the actual dielectric constant of the ferroelectric material product at each monitoring point based on the radar characteristic data and the coordinate information of the monitoring point, and construct the electromagnetic characteristic map of the goaf. Step 5: Compare the electromagnetic characteristic diagram with the dielectric constant reference value of the finished ferroelectric material to determine the spontaneous combustion situation at each monitoring point in the goaf, and extract the location coordinate information of each monitoring point where spontaneous combustion occurred to divide the coal fire area.

2. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 1, characterized in that: The method for obtaining the temperature-mass curve and temperature-heat flow curve of a coal sample is as follows: The coal sample was divided into two equal parts and placed in the sample trays of the thermogravimetric analyzer and the differential scanning calorimeter, respectively. The oxygen concentration in the thermogravimetric analyzer and the differential scanning calorimeter was adjusted to be consistent with the reference oxygen concentration. The heating rate was set to 2℃ / s, and the heating experiment was started. The temperature was increased from room temperature to the target temperature. During the heating process, the thermogravimetric analyzer recorded the data of the mass of the coal sample changing with temperature, and the differential scanning calorimeter recorded the data of the heat flow of the sample changing with temperature. Plot the temperature on the x-axis and the percentage change in sample mass (i.e., the real-time mass to the initial mass) on the y-axis to show the mass change trend throughout the heating process, thus forming a temperature-mass curve. Plot the heat flow trend throughout the heating process with temperature on the x-axis and heat flow on the y-axis to form a temperature-heat flow curve.

3. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 2, characterized in that: The logic for obtaining the cross temperature is as follows: The temperature-mass curve and temperature-heat flux curve are divided according to temperature and isothermal width. The formulas used to calculate the rate of change of sample mass and the rate of change of heat flux within each temperature range are as follows: in, and They represent the first The rate of change of sample mass and the rate of change of heat flux within a temperature range and These represent the values ​​in the temperature-mass curve, respectively. Sample mass change data at the start and end times of each temperature range. and These represent the first and second parts of the temperature-heat flux curve, respectively. Heat flow data at the start and end times of each temperature range and They represent the first The start and end times of each temperature range , and These represent the room temperature data and the target temperature data during the heating experiment, respectively. Calculate the product of the sample mass change rate and the heat flow change rate within each temperature range, and select the temperature range where the product of the sample mass change rate and the heat flow change rate is the largest. Use the median temperature within the temperature range where the product is the largest as the cross temperature.

4. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 1, characterized in that: The cross temperature is equal to the Curie temperature design reference value for ferroelectric materials. This reference dielectric constant is then multiplied by at least 10 and set as the dielectric constant reference value for ferroelectric materials. The formula used is: in, and These represent the Curie temperature design reference value and the dielectric constant reference value for ferroelectric materials, respectively. Indicates cross temperature. Indicates the reference dielectric constant. Indicates the amplification factor of the reference dielectric constant, and .

5. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 4, characterized in that: The method for constructing finished ferroelectric materials based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials is as follows: Lithium niobate was chosen as the base material for ferroelectric materials, and magnesium or manganese was selected as the doping element. The influence of the Curie temperature design reference value and the dielectric constant reference value were considered, and the doping amount of the doping element was adjusted according to the following formula: in, and This indicates the adjusted Curie temperature and dielectric constant. and These represent the initial Curie temperature and initial dielectric constant of lithium niobate, respectively. and These are the Curie temperature doping coefficient and the dielectric constant doping coefficient, respectively. This represents the doping concentration of the doped element. Choose an initial doping concentration, and adjust the doping concentration of the dopant element using an iterative algorithm until the errors of the two equations simultaneously meet the error requirements. When both requirements are met: Determine the doping concentration of the dopant element. Indicates the allowable error range. Based on the determined doping concentration values ​​of the doping elements, a ferroelectric material product with a fixed thickness is generated.

6. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 1, characterized in that: The radar characteristic data includes the total reflection time of the radar wave. The formula used to calculate the actual dielectric constant of the ferroelectric material product at each monitoring point is as follows: in, and They represent the first The propagation time and actual dielectric constant of ferroelectric materials at each monitoring point during ground-penetrating radar detection. Indicates the first The total reflection time of radar waves at each monitoring point during ground-penetrating radar detection. ,and They represent the first The thickness of the stratum above the ferroelectric material and its depth from the ground at each monitoring point. Indicates the first The dielectric constant of the strata above each monitoring point It represents the speed of light.

7. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 6, characterized in that: The thickness of the stratum above the ferroelectric material and the dielectric constant of the stratum above all monitoring points are taken as the same value. When constructing the electromagnetic characteristic map of the goaf, the actual dielectric constant and location coordinate information of each monitoring point are mapped one by one to construct the electromagnetic characteristic map of the entire goaf.

8. The method for detecting concealed fire zones in coal seams based on ferroelectric materials according to claim 7, characterized in that: The logic used to determine the spontaneous combustion situation at each monitoring point within the goaf is as follows: Based on the location coordinates of each detection point, the closest detection point to the point to be judged is selected, and the distance between them is calculated. Based on the actual dielectric constants of the two monitoring points and the distance between them, the spontaneous combustion risk index is calculated using the following formula: in, This indicates the spontaneous combustion risk index of the detection point to be assessed. This represents the distance between the detection point to be judged and the nearest detection point. and These represent the actual dielectric constants of the detection point to be judged and the detection point closest to the detection point to be judged, respectively. This indicates a reference value for the dielectric constant of the finished ferroelectric material. When the risk index of spontaneous combustion When the threshold value exceeds the empirical assessment threshold, it is determined that spontaneous combustion has occurred at the monitoring point.

9. A coal seam concealed fire zone detection system based on ferroelectric materials, characterized in that: The detection system is used to perform the method for detecting concealed fire zones in coal seams based on ferroelectric materials as described in any one of claims 1-8, including: The sample calibration module is used to sample coal in the area of ​​the goaf to be detected, collect the oxygen concentration in the goaf and calibrate it as the reference oxygen concentration, conduct a heating experiment on the obtained coal sample under the reference oxygen concentration condition, obtain the temperature-mass curve and temperature-heat flow curve of the coal sample, find the temperature value corresponding to the maximum change of mass and heat flow based on the temperature-mass curve and temperature-heat flow curve, and calibrate it as the cross temperature. The reference analysis module is used to measure the dielectric constant curve of a coal sample during the heating process under reference oxygen concentration conditions, determine the maximum dielectric constant of the coal sample during the heating process, and calibrate it as the reference dielectric constant. Based on the cross temperature, the Curie temperature design reference value of the ferroelectric material is determined, and based on the reference dielectric constant, the reference value of the dielectric constant of the ferroelectric material is determined. The network construction module is used to construct ferroelectric material products based on the Curie temperature design reference value and dielectric constant reference value of ferroelectric materials. The ferroelectric material products are pre-embedded in the working face of the goaf to be detected, and each pre-embedded point is used as a monitoring point. The coordinate information of each monitoring point is recorded. The coordinate information includes the location coordinate information of the monitoring point and the depth information from the ground, forming a coal seam ferroelectric material detection network. The radar detection module uses ground-penetrating radar to conduct real-time detection on the ground above the goaf, acquires ground-penetrating radar reflected wave data above each monitoring point, obtains radar characteristic data of each detection point based on the reflected wave data, and calculates the actual dielectric constant of the ferroelectric material product at each monitoring point based on the radar characteristic data and the coordinate information of the monitoring point, and constructs an electromagnetic characteristic map of the goaf. The fire zone analysis module is used to compare the electromagnetic characteristic diagram with the dielectric constant reference value of the finished ferroelectric material to determine the spontaneous combustion situation of each monitoring point in the goaf, and extract the location coordinate information of each monitoring point where spontaneous combustion is determined to occur to divide the coal fire zone.

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