Coal pile multi-band microwave remote sensing monitoring method and system

Abstract

The invention relates to the technical field of microwave remote sensing monitoring, in particular relates to microwave remote sensing monitoring applied to the internal temperature of a coal storage yard, and particularly discloses a coal pile multi-frequency-band microwave remote sensing monitoring method and a coal pile multi-frequency-band microwave remote sensing monitoring system. The system comprises a multi-band microwave transmitting and receiving module, a signal data processing module, a data fusion and inversion model, a data storage module, a visual early warning control system and the like. Microwave signals of the surface layer and / or the shallow layer of the coal pile are detected through high-frequency-band microwaves; temperature distribution data in the coal pile are analyzed through inversion calculation of a pre-established data fusion and inversion model, laser spectrum data of the coal pile are obtained through detection of laser equipment, and harmful gas concentration data and corresponding position data are obtained. The method and the system can be used for early warning and monitoring the internal temperature and the spontaneous combustion point of the coal pile of the coal storage yard, and can effectively and accurately monitor.

Description

Technical Field

[0001] The present invention relates to the technical field of microwave remote sensing monitoring, in particular to microwave remote sensing monitoring of the internal temperature of a coal storage yard. Background Art

[0002] Spontaneous combustion of coal piles in coal storage yards is a significant safety hazard faced by enterprises such as thermal power plants, chemical plants, steel mills, docks, and coal mines. Spontaneous combustion occurs when coal slowly oxidizes and accumulates heat, undergoing a latent period and a self-heating period before eventually rising to its ignition point and spontaneously combusting. Spontaneous combustion can impact production safety and, in severe cases, lead to accidents. It can also cause significant economic losses and release harmful gases and smoke, polluting the environment. Therefore, real-time monitoring of coal pile temperature is crucial for timely detection and resolution of spontaneous combustion. Traditional temperature monitoring methods, such as infrared detection, can only monitor the surface temperature of the coal seam (generally ≤5 cm) and cannot detect temperatures within the coal pile. If the internal temperature rise is not transmitted to the surface, it will remain undetected by infrared detection. Distributed fiber optic temperature measurement technology, which senses the temperature at the detection point and transmits an optical signal, also cannot detect the internal temperature of the coal pile because coal is a poor thermal conductor. Thermocouple technology, a contact sensor, requires a fixed placement and is unsuitable for placement within circulating materials.

[0003] National and industry standards, such as the "Technical Regulations for Coal Transportation Design in Thermal Power Plants" and the "Design Fire Protection Code for Thermal Power Plants and Substations," do not specify design requirements for coal pile heights, but only set requirements for coal storage volume and area. For example, coal pile heights in thermal power plant coal storage yards typically reach 20m (strip) or 30m (circular), while those in chemical plant coal storage yards are generally no higher than 15m. At these coal pile heights, the three traditional temperature monitoring technologies mentioned above cannot detect the temperature distribution within the coal pile. In light of this, the inventors of this case have devoted themselves to developing precise methods for detecting the internal temperature and spontaneous combustion of coal piles in coal storage yards, which led to this case. Summary of the Invention

[0004] The purpose of the present invention is to provide a coal pile multi-band microwave remote sensing monitoring method and a coal pile multi-band microwave remote sensing monitoring system that can be used for early warning monitoring of the internal temperature and auto-ignition point of coal piles in coal storage yards and can effectively and accurately monitor.

[0005] To achieve the above-mentioned purpose, the technical solution of the present invention is: a multi-band microwave remote sensing monitoring method for coal piles, the monitoring method is as follows: microwave signal data of the coal pile is obtained by detecting with a multi-band microwave transmitting and receiving device, the multi-band microwave transmitting and receiving device uses low-band microwaves to detect microwave signal data of the deep layer of the coal pile, and uses high-band microwaves to detect microwave signal data of the surface and / or shallow layer of the coal pile; laser spectrum data of the coal pile is obtained by detecting with a laser device, and spectrum characteristics are extracted from the laser spectrum data to obtain harmful gas concentration data and corresponding position data; the microwave signal data, harmful gas concentration data and corresponding position data are input into a pre-established data fusion and inversion model to perform inversion calculation and analysis to obtain temperature distribution data inside the coal pile.

[0006] The data fusion and inversion model includes a module for the relationship between temperature, moisture content and dielectric constant at different stages of the coal pile spontaneous combustion process, a module for the relationship between dielectric constant and multi-band microwave signal data, an inversion calculation module for calculating temperature through multi-band microwave signal data and inversion, and a module for the relationship between harmful gases, spectral characteristics and temperature.

[0007] The data fusion and inversion model uses a convolutional neural network as the basic network architecture; and / or, the microwave signal is preprocessed by filtering technology or environmental electromagnetic interference signal technology; and / or, the frequency range of the low-frequency microwave is 1-2 GHz; and / or, the frequency range of the high-frequency microwave is 8-12 GHz; and / or, the laser spectrum data is preprocessed by filtering technology or a compensation algorithm; and / or, the laser spectrum technology uses a tunable diode laser absorption spectroscopy method.

[0008] The data fusion and inversion model is provided with an algorithm compensation and / or correction function to correct the dielectric constant to improve the accuracy of the temperature distribution data inside the coal pile obtained by inversion calculation and analysis; and / or; the data fusion and inversion model also includes a temperature field establishment module for establishing a three-dimensional temperature field through temperature distribution data.

[0009] The method also includes establishing a visual monitoring software system, importing the three-dimensional temperature field established by the temperature field establishment module into the visual monitoring software system, and generating a temperature distribution map with hot spot markings.

[0010] The data fusion and inversion model also includes a judgment and prediction module that performs judgment and change prediction analysis based on microwave signals, temperature distribution data, and harmful gas data, generates monitoring and early warning information data and transmits it to the visual monitoring software system; and / or, also includes storing microwave signal data and temperature distribution data in a database.

[0011] A multi-band microwave remote sensing monitoring system for coal piles, the detection system includes:

[0012] The multi-band microwave transmission and reception module is an antenna array and connected hardware deployed in the coal pile site to support multi-band microwave signal transmission and reception. It uses multi-band microwave signal data to detect different depths and different physical characteristics of the coal pile to obtain microwave signal data;

[0013] The laser detection module is a device that can perform laser detection on coal piles. It obtains laser spectrum data and position data through laser scanning, and extracts spectrum characteristics from them to obtain harmful gas data and corresponding position data.

[0014] Signal data processing module, including filtering technology, environmental electromagnetic interference signal technology and compensation algorithm technology, is used for pre-processing microwave signals, harmful gas data and position data;

[0015] A data fusion and inversion model includes a module for analyzing the relationship between temperature, moisture content, and dielectric constant at different stages of the coal pile spontaneous combustion process, a module for analyzing the relationship between dielectric constant and multi-band microwave signal data, an inversion calculation module for calculating temperature through multi-band microwave signal data and inversion, a temperature field establishment module for establishing a three-dimensional temperature field through temperature distribution data, and a module for analyzing the relationship between harmful gases, spectral characteristics, and temperature, and a judgment and prediction module for performing judgment and prediction analysis based on temperature distribution data; the inversion calculation module performs inversion analysis and calculation on pre-processed microwave signals, harmful gas data, and position data based on other models other than the temperature field establishment module to obtain temperature distribution data of the coal pile, and the temperature field establishment module establishes a three-dimensional temperature field through the temperature distribution data;

[0016] The visual early warning control system obtains temperature distribution data from data fusion and inversion models, displays three-dimensional temperature fields, generates temperature distribution maps with hotspot annotations, and generates monitoring and early warning information.

[0017] Communication module, used for communication within the system and remote communication.

[0018] The storage module is used to store various data in the system.

[0019] The data fusion and inversion model also includes a judgment and prediction module for performing judgment and predictive analysis. The judgment and prediction module determines whether there is abnormal temperature based on the temperature distribution data, and uses a machine learning algorithm to predict the changing trend of the temperature distribution of the coal pile based on the real-time microwave signal and temperature distribution data, sets the change threshold, generates early warning data, and sends it to a visual early warning control system.

[0020] By adopting the above technical solution, the beneficial effects of the present invention are as follows: in order to timely or preemptively detect the auto-ignition point inside the coal pile in the coal storage yard, the present invention overcomes the shortcomings of traditional monitoring methods and develops a multi-band microwave remote sensing monitoring method and system for coal piles that integrates multi-band microwave remote sensing fusion technology and multi-source remote sensing calibration technology, thereby realizing a method and system for detecting the auto-ignition point inside the coal pile, which has important practical significance. The invention includes microwave signal transmission and reception, signal processing and temperature inversion, etc., which can accurately and timely detect the auto-ignition point inside the coal pile, and further can visualize temperature distribution, detect harmful gases by laser, store data and intelligent early warning analysis, etc., develops a complex model integrating multi-band microwave remote sensing fusion technology and intelligent inversion temperature, coal pile humidity compensation, laser data, and an algorithm based on a neural network infrastructure, forming a system that can be used for early warning monitoring of the temperature and auto-ignition point inside the coal pile in the coal storage yard and can effectively and accurately monitor, thereby achieving the above-mentioned purpose of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 The present invention relates to a method and system for monitoring a coal pile using multi-band microwave remote sensing, and a schematic diagram of a three-dimensional temperature field therein. DETAILED DESCRIPTION

[0022] In order to further explain the technical solution of the present invention, the present invention is described in detail below through specific embodiments.

[0023] This section illustrates the technical solution of the present invention by disclosing an embodiment that integrates multiple technical solutions. In actual applications, the technical solution disclosed in this embodiment can be applied by deleting some technical contents, adjusting and combining, or adding other technical solutions according to application needs. This embodiment is not a specific limitation.

[0024] Microwave remote sensing technology has strong penetrating properties and offers advantages such as all-weather operation, real-time monitoring, and non-contact operation. However, microwave signals are sensitive to factors such as the dielectric constant and moisture content of coal piles, and are also subject to interference signals from other electromagnetic sources (high-voltage lines, communication equipment). Therefore, there is no existing microwave remote sensing method for accurately detecting the internal temperature and spontaneous combustion of coal piles in coal storage yards.

[0025] This embodiment discloses a multi-band microwave remote sensing monitoring system for coal piles, including a multi-band microwave transmitting and receiving module, a laser detection module, a signal data processing module, a data fusion and inversion model, a storage module, a visual early warning control system, a communication module, etc.

[0026] The multi-band microwave transmitting and receiving module is an antenna array and connected hardware equipment deployed in the coal pile site to support the transmission and reception of multi-band microwave signals. It obtains microwave signals by detecting coal piles at different depths and with different physical properties through multi-band microwave signals.

[0027] The laser detection module is a device that can perform laser detection on coal piles. It obtains laser spectrum data and position data through laser scanning, and extracts spectrum characteristics from them to obtain harmful gas data and corresponding position data.

[0028] The signal data processing module includes filtering technology, environmental electromagnetic interference signal technology and compensation algorithm technology, which is used for preprocessing microwave signals, harmful gas data and position data.

[0029] The data fusion and inversion model includes a module for calculating the relationship between temperature, moisture content and dielectric constant at different stages of the coal pile spontaneous combustion process, a module for calculating the relationship between dielectric constant and multi-band microwave signal data, an inversion calculation module for calculating temperature through multi-band microwave signal data and inversion, a temperature field establishment module for establishing a three-dimensional temperature field through temperature distribution data, a module for calculating the relationship between harmful gases, spectral characteristics and temperature, and a judgment and prediction module for judgment and prediction analysis; the inversion calculation module performs inversion analysis and calculation on the pre-processed microwave signal, harmful gas data and position data based on other models other than the temperature field establishment module to obtain the temperature distribution data of the coal pile, and the temperature field establishment module establishes a three-dimensional temperature field through the temperature distribution data; the judgment and prediction module determines whether there is abnormal temperature based on the temperature distribution data, and uses a machine learning algorithm to predict the changing trend of the temperature distribution of the coal pile based on the real-time microwave signal and temperature distribution data, sets the change threshold, and generates early warning data.

[0030] The visual early warning control system obtains temperature distribution data and early warning data from data fusion and inversion models, displays three-dimensional temperature fields, generates temperature distribution maps with hotspot annotations, and provides monitoring and early warning information.

[0031] Communication module, used for communication within the system and remote communication.

[0032] The storage module is used to store various data in the system.

[0033] In conjunction with the above-mentioned multi-band microwave remote sensing monitoring system for coal piles, a multi-band microwave remote sensing monitoring method for coal piles is disclosed below. The monitoring method is as follows:

[0034] First, the microwave signal data of the coal pile is obtained by detecting the multi-band microwave transmitting and receiving device of the multi-band microwave transmitting and receiving module, and the laser spectrum data is obtained by the laser equipment of the laser detection module.

[0035] The multi-band microwave transmitting and receiving device detects microwave signal data from deep layers of the coal pile through low-band microwaves, and detects microwave signal data from the surface and / or shallow layers of the coal pile through high-band microwaves. In the embodiment test, the low-band microwave frequency range is 1-2 GHz for best effect, and the high-band microwave frequency range is 8-12 GHz for best effect.

[0036] The microwave signal data and laser spectrum data can be pre-processed by the signal data processing module before being sent out, wherein the microwave signal can be pre-processed by filtering technology, denoising technology, environmental electromagnetic interference signal technology, etc., and the laser data can be pre-processed by filtering technology, compensation algorithm, etc.

[0037] Next, the signal intensity, phase and spectrum characteristics are extracted from the above-mentioned processed microwave signal data and laser spectrum data, and the temperature distribution data inside the coal pile is analyzed by inversion calculation through the pre-established data fusion and inversion model to obtain harmful gas data. The temperature distribution data and harmful gas data are then used to determine whether abnormal temperatures and harmful gases exist. At the same time, the changing trend of the temperature distribution of the coal pile can be predicted based on the real-time microwave signal and temperature distribution data using a machine learning algorithm (such as a convolutional neural network (CNN) as the basic network architecture), and a change threshold can be set to generate monitoring and early warning information data, such as for predicting the probability of spontaneous combustion within the next 24 hours. When the probability of spontaneous combustion predicted by the model exceeds the set threshold, an early warning signal is immediately issued, and the harmful gas data can be used to detect spontaneous combustion points during the incubation period and self-heating period.

[0038] The data fusion and inversion model is established based on the relationship between the dielectric constant of the coal pile and the spontaneous combustion mechanism, thermophysical properties and / or chemical properties. As described in this embodiment, the data fusion and inversion model includes a relationship module between the temperature, moisture content and dielectric constant at different stages of the coal pile spontaneous combustion process, a relationship module between the dielectric constant and multi-band microwave signal data, an inversion calculation module for calculating the temperature through multi-band microwave signal data and inversion, and a relationship module between harmful gases, spectral characteristics and temperature. The data fusion and inversion model is provided with an algorithm compensation and / or correction function to correct the relationship between the dielectric constant and the thermophysical properties.

[0039] Then, the various data (including microwave signals, temperature distribution data, warning data, etc.) can be stored in the data storage module, and the temperature distribution data can be generated into a temperature distribution map with hot spot markings (such as Figure 1 As shown), the temperature distribution map is imported into the visual early warning control system with visual monitoring software for visual detection of personnel, and the monitoring and early warning information data is transmitted to the system for monitoring, control, early warning, etc.

[0040] During the development of the technical solution of the present invention, the mechanism of coal spontaneous combustion was studied to establish a multi-band microwave fusion system that matches the dielectric constant and moisture content of the coal pile. Coal spontaneous combustion refers to the phenomenon in which coal slowly oxidizes and accumulates heat, causing the temperature to rise to the ignition point and spontaneous combustion. Its mechanism is a complex physical and chemical process, mainly including three stages: low-temperature oxidation stage (latent period), self-heating stage (self-heating period), and spontaneous combustion stage (combustion period). Through research and experiments on the physical and chemical characteristics of coal spontaneous combustion, the accuracy of temperature detection was analyzed and studied. In addition, further research was conducted on the changes in the composition of gases released by coal spontaneous combustion to identify suitable marker gases for monitoring, such as ethylene C2H4, ethane C2H6, sulfur dioxide SO2, hydrogen sulfide H2S, methane CH4, carbon monoxide CO, etc. The range of changes in the total moisture content of coal and the moisture content before and after spontaneous combustion was studied, and a function was established to calibrate the influence of the dielectric constant and moisture content of the coal pile on the microwave signal.

[0041] The above method utilizes multi-band microwave fusion technology, which combines microwave signals of different frequencies. Compared to single-band techniques, it offers significant advantages in terms of penetration depth, resolution, and interference resistance. Different microwave frequency bands (such as the L-band, C-band, and X-band) have varying penetration depth and resolution characteristics. Low-frequency bands (such as the L-band, 1-2 GHz) have greater penetration depth and are suitable for detecting temperatures deep within coal piles. High-frequency bands (such as the X-band, 8-12 GHz) offer higher resolution and can identify surface and shallow details. By fusing multi-band data, both deep-layer temperature distribution and surface hotspots can be accurately located. Multi-band data can reduce temperature deviations caused by errors in dielectric constant estimation in a single frequency band. A microwave signal is transmitted through the coal pile, and the signal attenuation and phase change are measured at the receiving end. The dielectric constant is calculated by combining data fusion with an inversion model. The dielectric constant of the coal pile varies with microwave frequency (dispersion effect). Multi-band data can be used to invert the dielectric constant versus frequency curve. Combined with a model that reflects the relationship between temperature and dielectric constant, the accuracy of temperature inversion is improved. Different frequency bands have different sensitivities to electromagnetic interference. Multi-band data can suppress noise interference (such as metal reflection and electromagnetic wave interference) in a single frequency band through complementarity. This invention establishes a full-dimensional temperature field by integrating multi-band microwave technology. The focus is on establishing a multivariate relationship module between temperature, humidity, dielectric constant, frequency, etc. to improve the reliability and accuracy of the inversion.

[0042] The multi-band microwave fusion technology described above primarily encompasses the following aspects: 1. A mixed-medium dielectric model of the coal pile's dielectric constant is established based on the physicochemical properties of coal (such as composition, density, and moisture content). Since water has a much higher dielectric constant than coal, changes in moisture content significantly affect the overall dielectric constant of the coal pile. Therefore, it is necessary to simultaneously detect and calculate the moisture content of the coal pile. This involves measuring the reflection characteristics of electromagnetic waves at different frequencies (frequency domain response) and combining data fusion with an inversion model to calculate the dielectric constant. A database for commonly used coal types must be established, and algorithmic compensation and calibration must be performed. 2. Systematic microwave signal transmission and reception: A microwave transmitter transmits and receives microwave signals of specific frequencies into and from the coal pile. 3. Signal processing and temperature inversion: Preprocessing the received microwave signals to extract signal strength, phase, and spectral characteristics. A data fusion and inversion model tailored to the dielectric constant and moisture content of the coal pile is established to infer the internal temperature distribution of the coal pile. 4. Temperature distribution visualization: The inverted temperature data is visualized to generate a temperature distribution map of the coal pile. By analyzing the magnitude of abnormal temperature fluctuations, spontaneous combustion points can be detected or potential spontaneous combustion points can be warned. 5. Use laser technology to detect harmful gases in coal piles. For the absorption spectrum of harmful gases, the tunable diode laser absorption spectroscopy (TDLAS) method is suitable. Considering that dust in the coal storage yard will scatter or absorb laser light, filtering or algorithm compensation must also be considered simultaneously. 6. An artificial intelligence optimization algorithm for a complex model can be developed, covering microwave detection signal data, coal pile dielectric constant, coal pile humidity, temperature inversion, coal pile harmful gases, etc. Convolutional neural network (CNN) can be used as the basic network architecture to implement machine learning. 7. Data storage and analysis: The characteristic data of the company's commonly used coal is stored in the database and analyzed in combination with the historical data of the coal storage yard to adapt to the monitoring of different coal qualities.

[0043] The present invention provides a monitoring method and system technology based on multi-band microwave remote sensing fusion monitoring. The technology can be applied to monitoring spontaneous combustion points within coal piles in coal storage yards such as thermal power plants, chemical plants, steel mills, docks, and coal mines. This monitoring method and system utilizes multi-band microwave remote sensing fusion technology and a complex model-based artificial intelligence temperature inversion algorithm, integrating multi-source remote sensing calibration technologies such as humidity. The method and system offer the following advantages and benefits: 1. Comprehensive coverage: Multi-band microwave technology can penetrate coal piles, covering areas within the pile that are difficult to detect with traditional technologies; 2. Real-time monitoring: Multi-band microwave technology can monitor temperature changes within the coal pile in real time, enabling timely and proactive detection of spontaneous combustion points within the coal pile; 3. High-precision positioning: Through data fusion and inversion models, inversion algorithms, and gas detection, signal processing and analysis can accurately locate the location of spontaneous combustion points; 4. Automated early warning: Hotspots can be detected up to 12 hours in advance. The system automatically analyzes data and issues early warnings, effectively helping to prevent spontaneous combustion in coal piles; 5. Non-contact measurement: No temperature measurement fiber or temperature sensors are required, adapting to the process requirements of continuous unloading, storage, and transportation.

[0044] The above embodiments and drawings do not limit the product form and style of the present invention. Any appropriate changes or modifications made by ordinary technicians in the relevant technical field should be deemed to be within the patent scope of the present invention.

Claims

1. A coal pile multi-band microwave remote sensing monitoring method, characterized in that: The monitoring method is as follows: Acquiring microwave signal data of the coal pile by detecting using a multi-band microwave transmitting and receiving device, wherein the multi-band microwave transmitting and receiving device detects microwave signal data of a deep layer of the coal pile using low-band microwaves and detects microwave signal data of a surface layer and / or shallow layer of the coal pile using high-band microwaves; The microwave signal data is input into the pre-established data fusion and inversion model to perform inversion calculation and analysis to obtain the temperature distribution data inside the coal pile.

2. A coal pile multi-band microwave remote sensing monitoring method according to claim 1, characterized in that: The data fusion and inversion model includes a module for the relationship between temperature, moisture content and dielectric constant at different stages of the coal pile spontaneous combustion process, a module for the relationship between dielectric constant and multi-band microwave signal data, and an inversion calculation module for calculating temperature through multi-band microwave signal data and inversion.

3. A coal pile multi-band microwave remote sensing monitoring method according to claim 2, characterized in that: Laser spectrum data of the coal pile is also obtained through laser detection equipment, and harmful gas concentration data and corresponding position data are obtained from the laser spectrum data; The data fusion and inversion model also includes a relationship module between harmful gases, spectral characteristics and temperature; The harmful gas concentration data and the corresponding position data are input together with the microwave signal data into the pre-established data fusion and inversion model to perform inversion calculation and analysis to obtain the temperature distribution data inside the coal pile.

4. A coal pile multi-band microwave remote sensing monitoring method according to claim 3, characterized in that: The data fusion and inversion model uses a convolutional neural network as the basic network architecture; and / or, the microwave signal is pre-processed by filtering technology or environmental electromagnetic interference signal technology; And / or, the low-band microwave frequency range is 1-2 GHz; And / or, the high-frequency microwave frequency range is 8-12 GHz; And / or, the data fusion and inversion model is provided with an algorithmic compensation and / or correction function to correct the dielectric constant; and / or, the laser spectrum data is pre-processed by filtering technology or compensation algorithm; And / or, the laser spectroscopy technique adopts a tunable diode laser absorption spectroscopy method.

5. A coal pile multi-band microwave remote sensing monitoring method according to claim 3, characterized in that: It also includes establishing a visual monitoring software system. The data fusion and inversion model also includes a temperature field establishment model that establishes a three-dimensional temperature field through temperature distribution data. The three-dimensional temperature field established by the temperature field establishment module is imported into the visual monitoring software system and generates a temperature distribution map with hotspot annotations.

6. A coal pile multi-band microwave remote sensing monitoring method according to claim 1 or 2, characterized in that: The data fusion and inversion model also includes a judgment and prediction module that performs judgment and change prediction analysis based on microwave signal data, temperature distribution data, and harmful gas data, and generates monitoring and early warning information data for transmission to the visual monitoring software system; And / or, it also includes storing the microwave signal and temperature distribution data in a database.

7. A coal pile multi-band microwave remote sensing monitoring method according to any one of claims 3 to 5, characterized in that: The data fusion and inversion model also includes a judgment and prediction module that performs judgment and change prediction analysis based on microwave signals, temperature distribution data, and harmful gas data, and generates monitoring and early warning information data for transmission to the visual monitoring software system; And / or, it also includes storing the microwave signal and temperature distribution data in a database.

8. A coal pile multi-band microwave remote sensing monitoring system, characterized in that: The detection system includes: The multi-band microwave transmission and reception module is an antenna array and connected hardware deployed in the coal pile site to support multi-band microwave signal transmission and reception. It uses multi-band microwave signal data to detect different depths and different physical characteristics of the coal pile to obtain microwave signal data; Signal data processing module, including filtering technology and environmental electromagnetic interference signal technology for pre-processing microwave signal data; A data fusion and inversion model includes a module for analyzing the relationship between temperature, moisture content, and dielectric constant at different stages of a coal pile's spontaneous combustion process, a module for analyzing the relationship between dielectric constant and multi-band microwave signal data, an inversion calculation module for calculating temperature through multi-band microwave signal data and inversion, a temperature field establishment module for establishing a three-dimensional temperature field through temperature distribution data, and a judgment and prediction module for performing judgment and prediction analysis based on temperature distribution data. The inversion calculation module performs inversion analysis and calculation on pre-processed microwave signals, harmful gas data, and position data based on other models other than the temperature field establishment module to obtain temperature distribution data of the coal pile, and the temperature field establishment module establishes a three-dimensional temperature field through the temperature distribution data. The visual early warning control system obtains temperature distribution data from data fusion and inversion models, displays three-dimensional temperature fields, generates temperature distribution maps with hotspot annotations, and generates monitoring and early warning information. Communication module, used for communication within the system and remote communication. The storage module is used to store various data in the system.

9. A coal pile multi-band microwave remote sensing monitoring system, characterized in that: The detection system includes: The multi-band microwave transmission and reception module is an antenna array and connected hardware deployed in the coal pile site to support the transmission and reception of multi-band microwave signals. It uses multi-band microwave signal data to detect different depths and physical characteristics of the coal pile to obtain microwave signals. The laser detection module is a device that can perform laser detection on coal piles. It obtains laser spectrum data and position data through laser scanning, and extracts spectrum characteristics from them to obtain harmful gas data and corresponding position data. Signal data processing module, including filtering technology, environmental electromagnetic interference signal technology and compensation algorithm technology, is used for pre-processing microwave signals, harmful gas data and position data; A data fusion and inversion model includes a module for analyzing the relationship between temperature, moisture content, and dielectric constant at different stages of the coal pile spontaneous combustion process, a module for analyzing the relationship between dielectric constant and multi-band microwave signal data, an inversion calculation module for calculating temperature through multi-band microwave signal data and inversion, a temperature field establishment module for establishing a three-dimensional temperature field through temperature distribution data, and a module for analyzing the relationship between harmful gases, spectral characteristics, and temperature, and a judgment and prediction module for performing judgment and prediction analysis based on temperature distribution data; the inversion calculation module performs inversion analysis and calculation on pre-processed microwave signals, harmful gas data, and position data based on other models other than the temperature field establishment module to obtain temperature distribution data of the coal pile, and the temperature field establishment module establishes a three-dimensional temperature field through the temperature distribution data; The visual early warning control system obtains temperature distribution data from data fusion and inversion models, displays three-dimensional temperature fields, generates temperature distribution maps with hotspot annotations, and generates monitoring and early warning information. Communication module, used for communication within the system and remote communication. The storage module is used to store various data within the system.

10. A coal pile multi-band microwave remote sensing monitoring system according to claim 8 or 9, characterized in that: The data fusion and inversion model also includes a judgment and prediction module for performing judgment and predictive analysis. The judgment and prediction module determines whether there is abnormal temperature based on the temperature distribution data, and uses a machine learning algorithm to predict the changing trend of the temperature distribution of the coal pile based on the real-time microwave signal and temperature distribution data, sets the change threshold, generates early warning data, and sends it to a visual early warning control system.

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