A method and system for locating personnel underground in mines based on environmental characteristics.

Abstract

This invention belongs to the technical field of positioning technology, specifically relating to a method and system for personnel positioning in underground mines based on environmental characteristics. It is suitable for accurate personnel positioning and dynamic correction in complex structures and environments with strong interference. The method includes: data classification and standardization processing, mine structure modeling, sensitive area identification and labeling, real-time positioning data acquisition and correction, and dynamic correction of the original positioning results by incorporating environmental characteristics such as electromagnetic signal fluctuations, thereby improving the accuracy and stability of underground positioning. The system includes a data processing module, a structure modeling module, a sensitive area identification module, a region fusion module, and a positioning correction module. These modules work together to achieve high-precision tracking of personnel positions and early warning of sensitive areas. This invention effectively overcomes the error accumulation problem of traditional positioning methods under strong interference conditions underground, and is applicable to underground operation scenarios such as coal mines and metal and non-metal mines, possessing broad application prospects.

Description

Technical Field

[0001] This invention belongs to the technical field of positioning technology, specifically relating to a method and system for locating personnel underground in mines based on environmental characteristics. Background Technology

[0002] With the deepening development of mining operations, the safety of underground workers has received increasing attention. Traditional methods for locating personnel underground in mines mainly rely on wireless communication technologies, such as positioning systems built on communication protocols like RFID, UWB (Ultra-Wideband), or ZigBee. These systems typically achieve real-time positioning based on signals from personnel-worn terminals by deploying numerous base station nodes within mine tunnels. However, the complex and variable underground environment in mines, characterized by high humidity, high temperature, high dust levels, metal shielding, and confined spaces, severely interferes with the propagation of wireless signals. This makes it difficult to guarantee the accuracy of positioning based on communication signals, and the system deployment and maintenance costs are also high.

[0003] In recent years, some studies have attempted to introduce assisted positioning methods such as inertial navigation and visual SLAM to improve personnel tracking capabilities under conditions of communication interruption or signal obstruction. However, inertial navigation is susceptible to accumulated errors, and visual SLAM is unstable in low-light or dusty environments, both exhibiting insufficient reliability. Meanwhile, the underground environment of mines itself has certain spatial distribution patterns, such as tunnel structure, wall material, ventilation direction, temperature and humidity distribution, and cable and pipeline distribution. These environmental characteristics are usually unique or relatively stable in different locations.

[0004] However, existing technologies rarely consider incorporating underground environmental features as auxiliary or primary information sources into positioning models. This lack of deep perception and modeling of environmental information makes current personnel positioning systems prone to failure under conditions of signal loss, obstructed access, or extreme environments, failing to meet the requirements of mine safety supervision and emergency rescue. Therefore, there is an urgent need for a novel underground personnel positioning method that integrates environmental features for fusion perception and reasoning, providing stable and reliable positioning capabilities even under weak signal conditions, and possessing strong scalability and adaptability. Summary of the Invention

[0005] To address the above problems, the present invention aims to propose a method for locating personnel underground in mines based on environmental characteristics, comprising the following steps:

[0006] S1. Data Classification and Processing: Acquire basic information about the underground mine, including working face structure, roadway layout, equipment distribution, lighting configuration, and track arrangement; classify the information into planar information set and feature information set, and standardize parameters such as electromagnetic signal interference and electrical equipment status in the feature information set to form standard feature data that can be used for subsequent analysis and evaluation.

[0007] S2. Plane Map Construction: Based on the set of planar information, a plan map reflecting the underground structure of the mine is constructed. The plan map is drawn according to a preset reference plane, which is a representative working face. A connection surface is formed with the reference plane by setting an angle, which is used for subsequent positioning reference.

[0008] S3. Key Area Identification and Marking: Collect electromagnetic signals generated during the operation of underground equipment and combine them with real-time location data collected by deployed high-precision positioning and control equipment to extract corresponding feature information; compare the differences in this information to identify areas where electromagnetic signals fluctuate significantly and mark such areas as sensitive areas; mark the sensitive areas on the constructed underground mine plan.

[0009] S4. Real-time Positioning Correction and Output: Based on the deployment of positioning control equipment, the real-time location information of the miners working underground is collected to form raw positioning data. The relevant feature information of their current location is extracted, and the raw positioning data is corrected in real time based on the feature information to obtain the corrected effective location information.

[0010] In a preferred embodiment, the standardization processing of the feature information includes extracting the fluctuation value of the electromagnetic signal, setting an allowable deviation range based on the fluctuation value, and constructing a function model for determining the sensitivity.

[0011] In a preferred technical solution, electromagnetic signal parameters within adjacent time periods are extracted, and the difference between the parameters is calculated. This difference is set as a reference value for electromagnetic signal fluctuation. The fluctuation reference values ​​of multiple samples are averaged to obtain a preliminary judgment parameter. The standard deviation corresponding to the electromagnetic signal is further extracted, multiplied by a preset coefficient, and then combined with the preliminary judgment parameter to obtain a final deviation judgment value. This deviation judgment value is compared with a specific judgment threshold to obtain a judgment conclusion. Based on the judgment conclusion, the parameter to be measured is determined and the function model calculation is performed. If the judgment result is sensitive, the sensitivity level parameter is output and summarized as feature information. If the judgment result is non-sensitive, the original parameter is retained as reference data.

[0012] In a preferred technical solution, during the function model calculation process, the difference between the parameter to be measured and the reference parameter is used as an input variable and input into the correction function to obtain the output result as the correction value. The correction value is compared with a preset tolerance range. If it falls within the tolerance range, the electromagnetic environment of the region is determined to be relatively stable and is considered a reliable region. If it exceeds the tolerance range, it is determined to be a fluctuating region.

[0013] In a preferred technical solution, the process of correcting personnel positioning also includes the following steps:

[0014] Collect real-time location data of on-site workers;

[0015] Determine whether its current location is in a sensitive area;

[0016] If the location is not in a sensitive area, the location information will be used directly as the location result.

[0017] If it is in a sensitive area, then the sensitivity level parameters of that area are obtained and compared.

[0018] If the sensitivity level does not exceed the risk threshold, this parameter can be used as a fault tolerance factor to correct the position offset within a certain range.

[0019] If the risk threshold is exceeded, the person will be marked as being in a high-risk area, and an alarm message will be sent to the monitoring system.

[0020] In a preferred embodiment, when performing fault-tolerant correction, an adjustable correction coefficient is introduced; the sensitivity level parameter required for the current correction is multiplied by the correction coefficient to obtain a fault-tolerant value; the fault-tolerant value is applied to the original positioning result of the personnel, and the corrected positioning data is output.

[0021] This invention also provides a mine underground personnel positioning system based on environmental characteristics, for implementing the method described above, comprising:

[0022] Data processing module: Used to acquire and classify basic information data of various areas underground in the mine, dividing it into planar information sets and feature information sets, and performing standardization processing;

[0023] Structural modeling module: used to construct the corresponding mine plan structure diagram based on the classification results;

[0024] Sensitive area identification module: used to analyze the degree of change in feature information, identify and label sensitive areas;

[0025] Region fusion module: used to overlay the location information of sensitive areas onto the planar structure map, and automatically identify adjacent or overlapping parts, optimizing them into coherent sensitive blocks;

[0026] Positioning correction module: Used to receive real-time collected location information of workers, and then output the result after correcting the positioning result by calling feature parameters.

[0027] The present invention also provides a mine underground personnel positioning terminal based on environmental characteristics, including at least one processor and a data storage device connected to the processor, wherein the data storage device stores a computer program; when the program is loaded and executed, the processor is able to execute the method described thereon.

[0028] The beneficial effects of this invention are as follows:

[0029] 1. Significantly improves downhole positioning accuracy and stability: This invention introduces environmental characteristic data (such as electromagnetic signal fluctuations) to correct the original positioning results in real time, which can effectively suppress signal interference in complex environments, improve the accuracy and continuity of personnel positioning, and maintain stable positioning even in the presence of electrical equipment, metal obstacles and other interference conditions.

[0030] 2. Achieve dynamic identification and early warning of sensitive areas: This invention constructs a sensitive area identification mechanism based on the difference of characteristic parameters, which can monitor the electromagnetic fluctuation of various areas downhole in real time and mark them as high-risk areas. It can dynamically identify and warn personnel in the area, which helps to improve downhole safety protection capabilities.

[0031] 3. Excellent system scalability and deployment adaptability: This invention adopts a modular design, which can be integrated into existing underground dispatching systems or operated independently; it supports multi-source sensor data access and flexible deployment, making it easy to promote and apply in different mine structures, reducing operation and maintenance costs and improving system reliability. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0033] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0034] Example 1

[0035] like Figure 1 As shown, this embodiment provides a method for locating personnel underground in mines based on environmental features. This method is applied to the accurate identification and dynamic correction of personnel positions in complex underground structures and environments with strong interference. The method includes the following steps:

[0036] S1. Data Classification and Processing:

[0037] Obtain basic information about the underground mine, including the working face structure, roadway layout, equipment distribution, lighting configuration, and track arrangement;

[0038] The information is divided into a planar information set and a feature information set. Parameters such as electromagnetic signal interference and electrical equipment status in the feature information set are standardized to form standard feature data that can be used for subsequent analysis and evaluation. During feature data processing, an allowable deviation range is set based on the fluctuation value of the electromagnetic signal, and a function model is constructed to determine the sensitivity level, in the following form:

[0039]

[0040] Where σ is a deviation index constructed based on the current fluctuation value and the historical average, and T is a set threshold.

[0041] S2, Plan Construction:

[0042] Based on the aforementioned planar information set, a planar diagram reflecting the underground structure of the mine is constructed. The planar diagram is drawn according to a preset reference plane, which is a representative working face. An angle is set to form a connecting surface with the reference plane, which is used as the coordinate reference and path restoration for subsequent positioning.

[0043] S3. Key Area Identification and Marking:

[0044] Electromagnetic signals generated during the operation of downhole equipment are collected, and combined with real-time location data collected by the deployed high-precision positioning and control equipment, corresponding feature information is extracted.

[0045] By comparing the differences in information, regions with significant fluctuations in electromagnetic signals are identified and these regions are classified as sensitive areas.

[0046] During the identification process, electromagnetic signal parameters within adjacent time periods are extracted, and their differences are calculated as a fluctuation reference. The standard deviation of this parameter is further extracted and combined with preset coefficients to form a deviation judgment value. This value is then compared with a judgment threshold to draw a conclusion. Finally, the sensitive areas are marked on the constructed underground mine plan.

[0047] S4. Real-time positioning correction and output:

[0048] Based on the deployment of positioning and control equipment, the real-time location information of miners working underground is collected to form raw positioning data, and relevant feature information of their current location is extracted. The raw positioning data is then corrected in real time based on the feature information to obtain corrected and valid location information.

[0049] Specifically, it includes:

[0050] S41. Raw Positioning Fusion: Relying on high-precision positioning and control equipment deployed underground in the mine, the initial position information of the workers is collected in real time to form a raw positioning dataset. This raw data includes UWB (Ultra-Wideband) ranging information, and also combines the displacement and direction increments provided by the IMU (Inertial Measurement Unit), thereby improving the position continuity and robustness in dynamic scenarios. The Extended Kalman Filter (EKF) algorithm is used to fuse the multi-source data. By dynamically updating the state transition and observation matrix, the raw coordinates are estimated, including: the wearable terminal collects the UWB ranging observation vector z at discrete time k. u The uncorrected position estimate is obtained by using the cumulative displacement Δp(k) and inertial navigation Δp(k) with an extended Kalman filter (EKF):

[0051]

[0052] in, For two-dimensional coordinate estimation; H is the observation matrix, and K(k) is the Kalman gain.

[0053] S42. Constructing a Dynamic Deviation Index: Based on the established database of environmental characteristics of the mining area, extract the changes in electromagnetic field parameters of the area where the current coordinates are located, and construct a dynamic deviation index accordingly. In the specific calculation, the comprehensive electromagnetic fluctuation deviation is defined as... Where δ(k) is the expected value of the electromagnetic signal in the current region, σ E (k) represents the standard deviation of historical volatility, and k0 is the adjustment factor; subsequently, this parameter is normalized using a sigmoid-form sensitivity function:

[0054]

[0055] Where T is the adjustable sensitivity threshold, representing the upper limit of the system's tolerance to electromagnetic anomalies. When δ(k) deviates significantly from T, the function value approaches 1, indicating that the current location is a strong interference area; while when δ(k) is close to or lower than T, the function output is smaller, indicating that the environment is relatively stable.

[0056] S43. Execute a fault-tolerant correction mechanism: Based on the output value of the aforementioned environmental sensitivity function, a fault-tolerant correction mechanism with consistent direction is adopted. This mechanism maps the sensitivity function result to a unit vector direction consistent with the current channel direction, thereby ensuring that the position correction does not deviate from the work channel. The specific correction displacement is defined by the following formula:

[0057]

[0058] Where α is the fault tolerance adjustment coefficient, the unit is meters (m), and different ranges can be set according to the risk level of the mining environment; This is the tangent unit vector of the channel to which the current position belongs, ensuring that the correction direction is consistent with the channel geometry. This correction vector represents the displacement offset compensation performed by the system on the estimated coordinates when a large electromagnetic disturbance is detected.

[0059] S44. Implement coordinate correction: The system superimposes the above-mentioned fault-tolerant displacement vector with the initial estimated position output by EKF to obtain the corrected actual position coordinates of the personnel:

[0060]

[0061] Wherein, P(k) represents the final effective positioning result of the personnel at time k. Through the three processes of fusion, evaluation, and correction, it can achieve dynamic positioning and identification with high robustness and high accuracy in the complex environment of actual underground mines. This positioning result will be uploaded to the monitoring system interface of the ground dispatch center in real time via wireless link and participate in subsequent task execution processes such as safety early warning and path planning.

[0062] Example 2

[0063] This embodiment proposes an environmental feature-assisted positioning method applicable to actual production scheduling systems, addressing the characteristics of deep mines, such as numerous underground roadways, strong electromagnetic interference, and complex spatial environments. This method enables precise real-time location correction for workers, dynamic identification of sensitive areas, and early warning output for high-risk situations, ensuring the safety of underground personnel and providing data support for scheduling management.

[0064] S1: Data Classification and Processing

[0065] In the initial stage of system deployment, a comprehensive data collection of the target mine's underground environment is required. The collection scope includes typical areas such as the main shaft, auxiliary shaft, mining faces, transport roadways, refuge chambers, and equipment concentration areas. The collected content is mainly divided into two categories: planar information sets and feature information sets.

[0066] The planar information set includes roadway orientation, dimensions, intersection angles, cross-section types, dip angles, elevations, etc., which are used to construct a two-dimensional structure map of the mine.

[0067] The feature information set covers perceptible environmental feature data, such as electromagnetic interference intensity, illuminance, temperature and humidity, motor operating status, airflow changes, and track signal interference.

[0068] After collecting the aforementioned information, the system standardizes the feature information to facilitate subsequent modeling and analysis. The standardization process mainly includes: unit unification, normalization, noise filtering, and interpolation completion. Electromagnetic fluctuation data is a key factor among the environmental feature data. The system statistically analyzes the fluctuation amplitude of electromagnetic signals over different time periods and identifies abnormal fluctuations by setting deviation ranges. Furthermore, the system incorporates a fault-tolerance mechanism, introducing buffers for slowly changing data such as temperature and humidity to avoid misidentification caused by small fluctuations.

[0069] After completing data standardization, the system archives the planar data and feature data separately, forming a "structural benchmark library" and a "feature fluctuation benchmark library" as references for subsequent positioning correction and sensitive area identification.

[0070] S2: Plane Construction:

[0071] Based on the processed planar information set, the system constructs an underground mine structure map in the background. This structure map is a two-dimensional planar map, using the current working area (such as the coal mining face) as the coordinate reference plane, and gradually expanding to areas such as main transport roadways, return air roadways, belt conveyor roadways, and the mine bottom yard using connecting lines.

[0072] During the mapping process, the system automatically calculates the direction vector, intersection coordinates, and turning angle of each tunnel, and combines this with actual dip angles and elevation changes to generate a structural map with positioning aids. To improve map accuracy, each tunnel segment is assigned a unique code, and the accuracy of node positions and coordinates is controlled within ±0.2m.

[0073] Furthermore, to ensure synchronized use by dispatchers and mobile terminals, the structural map is deployed as a GIS layer on the dispatch dashboard and underground handheld terminals, enabling unified display and updates across multiple devices. Map information includes tunnel attributes, equipment distribution, emergency escape routes, and personnel activity areas.

[0074] S3: Key Area Identification and Marking:

[0075] During the positioning process, the system continuously acquires the latest environmental feature data from the perception layer and performs real-time analysis of feature changes. The data acquisition frequency is set to refresh every 30 seconds, and the analysis includes:

[0076] Electromagnetic interference signal analysis: If the electromagnetic signal in a certain area fluctuates drastically within three consecutive cycles, the system will classify it as a "preliminary area of ​​concern".

[0077] Equipment status overlay analysis: Based on the equipment operation status in this area, if phenomena such as frequent equipment start-stop, repeated motor start-up, and communication link fluctuations occur, the risk level will be increased;

[0078] Historical data comparison and analysis: The system will compare the current feature value with the historical stable period value. If the deviation continues to exceed the set threshold (such as 20% fluctuation), the area will be marked as "official sensitive area".

[0079] The identified sensitive areas will be labeled with numbers and sensitivity levels (e.g., Level I, Level II, Level III), and overlaid on the structure diagram as a color layer, where:

[0080] Yellow indicates areas of slight fluctuation, which may affect positioning accuracy;

[0081] Orange indicates areas of moderate interference with significant positioning deviation;

[0082] Red indicates areas of severe interference, with a high risk of positioning failure.

[0083] The system will also automatically perform sensitive area fusion processing based on the proximity of the areas. For example, if two sensitive areas are less than 3 meters apart, the system will merge them into a unified area and optimize its shape into a regular polygon or rectangle for easy visualization.

[0084] S4: Real-time positioning correction and output:

[0085] After the UWB / INS dual-mode positioning and control device worn by the personnel is put into operation, the system will receive position information in 2-second increments and execute the following processing flow:

[0086] Raw positioning data extraction: The system first obtains the initial coordinates sent by the card control device, including the horizontal position, vertical position and the lane number;

[0087] Environmental feature matching: The system reads the latest feature information of the area corresponding to the coordinate point (including the current electromagnetic level, interference trend, etc.);

[0088] Correct strategy matching:

[0089] If the personnel are not in any sensitive area, the original coordinates are the final location coordinates;

[0090] If personnel are in a Level I sensitive area (mild), the system will activate the fine-tuning fault tolerance rule and make a slight correction to the coordinates by comparing them with the roadway direction vector (e.g., the direction line will be offset by 0.2m).

[0091] If the location is in a Level II sensitive area (moderate), the system will correct the positioning result based on the historical offset error model of the area and mark the result as "pending confirmation" to alert the dispatcher.

[0092] If personnel are in a Level III sensitive area (severe), the system will mark the location as "high risk" and send a real-time alarm to the dispatch control console to remind on-duty personnel to manually confirm or guide personnel to evacuate.

[0093] Data output and log recording: The corrected positioning results will be dynamically displayed on the dispatch system map and simultaneously displayed on the downhole terminal. At the same time, information such as positioning time, original value, correction value, whether an alarm was triggered, and sensitivity level will be recorded to form a complete and traceable positioning data record.

[0094] In addition, to ensure data security and traceability, the system uploads all location information, sensitive events, and correction processes to the central database for later review and analysis and algorithm optimization.

[0095] This embodiment fully constructs a closed-loop process from data acquisition and model building to positioning correction and result output, significantly improving the accuracy and stability of personnel positioning in underground mines. Especially in complex interference environments, the system can identify the impact of electromagnetic fluctuations and equipment malfunctions on positioning accuracy in real time, and adopts intelligent correction strategies to achieve dynamic calibration and risk alerts, greatly enhancing the safety assurance capabilities of underground workers.

[0096] Example 3

[0097] This embodiment provides a mine underground personnel positioning system based on environmental characteristics. It is suitable for scenarios with complex mine structures, significant electromagnetic interference, and insufficient accuracy of traditional positioning methods. It can be used in conjunction with the aforementioned positioning correction method to achieve accurate identification and dynamic correction of personnel location information. The system adopts a modular configuration in its structural design, including the following functional modules:

[0098] The data processing module is responsible for the initial data collection and processing. The system acquires raw data such as underground mine structure information, lighting layout, equipment location, track alignment, and historical maintenance records through sensing terminals deployed in key areas. The collected data is processed and divided into planar information sets and feature information sets, used to describe the mine structure and reflect regional characteristics, respectively. After classification, the system standardizes the feature information, including normalization, deviation quantification, and difference extraction of multi-dimensional parameters such as electromagnetic signal strength, electrical equipment operating status, and communication fluctuations, to ensure comparability and stability in subsequent analyses.

[0099] The structural modeling module constructs an underground mine structure diagram based on the set of planar information. The system automatically draws spatial relationship diagrams of each roadway, intersection, working face, and facility area based on the reference plane parameters, connection angles, and reference point information from the collected data. This structural diagram not only has a display function but also provides coordinate references for subsequent overlay and positioning correction of sensitive areas.

[0100] The sensitive area identification module focuses on dynamic environmental monitoring and area assessment. The system periodically acquires information on changes in key indicators from a set of feature information, paying particular attention to electromagnetic field fluctuations, signal obstruction frequency, and the duration of abnormal interference. Based on predefined rules, it identifies areas with significant changes and marks them as potential sensitive areas. Furthermore, to avoid false positives, the system performs cross-validation using historical data to improve the accuracy and robustness of the identification.

[0101] The region fusion module, based on sensitive area identification, maps the coordinates of the marked sensitive areas onto the planar map generated by the structural modeling module. To optimize spatial representation, this module possesses intelligent fusion capabilities, able to determine characteristics such as boundary continuity and environmental interference correlation between adjacent or overlapping areas, automatically merging them into coherent and consistent sensitive blocks. This approach simplifies complex layers, allowing dispatchers to intuitively grasp the distribution of key monitoring areas.

[0102] The positioning correction module is one of the core functions of the system. It receives real-time location information from the positioning devices worn by workers and dynamically evaluates and corrects it based on the environmental characteristics of the area. When the positioning point is located in an identified sensitive area, the system will correct the current coordinates based on factors such as the magnitude of changes in characteristic parameters, the sensitivity level of the area, and historical error models, outputting more reliable actual location information. Finally, the corrected positioning result will be displayed in real-time on the dispatch center interface and can be used for applications such as trajectory analysis, risk warning, and dispatch guidance.

[0103] This embodiment breaks through the technical bottleneck of large errors in underground scenarios by deeply integrating environmental features with structural diagrams. It achieves accurate personnel positioning and dynamic correction in high-risk working environments, providing high-precision and robust technical support for mine safety management.

[0104] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for locating personnel underground in mines based on environmental characteristics, characterized in that, Includes the following steps: S1. Data Classification and Processing: Acquire basic information about the underground mine, including working face structure, roadway layout, equipment distribution, lighting configuration, and track arrangement; classify the information into planar information set and feature information set, and standardize parameters such as electromagnetic signal interference and electrical equipment status in the feature information set to form standard feature data that can be used for subsequent analysis and evaluation. S2. Plane Map Construction: Based on the set of planar information, a plan map reflecting the underground structure of the mine is constructed. The plan map is drawn according to a preset reference plane, which is a representative working face. A connection surface is formed with the reference plane by setting an angle, which is used for subsequent positioning reference. S3. Key Area Identification and Marking: Collect electromagnetic signals generated during the operation of downhole equipment, and combine them with real-time location data collected by the deployed high-precision positioning and control equipment to extract corresponding feature information; The standardization processing of the feature information includes extracting the fluctuation value of the electromagnetic signal, setting an allowable deviation range based on the fluctuation value, and constructing a function model for determining the sensitivity. Electromagnetic signal parameters within adjacent time periods are extracted, and the difference between these parameters is calculated. This difference is set as a reference value for electromagnetic signal fluctuation. The fluctuation reference values ​​of multiple samples are averaged to obtain a preliminary judgment parameter. The standard deviation corresponding to the electromagnetic signal is further extracted, multiplied by a preset coefficient, and then combined with the preliminary judgment parameter to obtain a final deviation judgment value. This deviation judgment value is compared with a specific judgment threshold to obtain a judgment conclusion. Based on the judgment conclusion, the parameter to be measured is determined and the function model is executed. If the judgment result is sensitive, the sensitivity level parameter is output and summarized as feature information. If the parameter is determined to be non-sensitive, the original parameter is retained as reference data. By comparing the differences in feature information, regions where electromagnetic signals fluctuate significantly are identified, and these regions are classified as sensitive regions. The sensitive areas are marked on the constructed underground mine plan; S4. Real-time Positioning Correction and Output: Based on the deployment of positioning control equipment, the real-time location information of the miners working underground is collected to form raw positioning data. The relevant feature information of their current location is extracted, and the raw positioning data is corrected in real time based on the feature information to obtain the corrected effective location information. The process of revising personnel positioning also includes the following steps: Collect real-time location data of on-site workers; Determine whether its current location is in a sensitive area; If the location is not in a sensitive area, the location information will be used directly as the location result. If it is in a sensitive area, then the sensitivity level parameters of that area are obtained and compared. If the sensitivity level does not exceed the risk threshold, the sensitivity level parameter will be used as a fault tolerance factor to correct the position offset within a certain range. If the risk threshold is exceeded, the person will be marked as being in a high-risk area, and an alarm message will be sent to the monitoring system.

2. The method for locating personnel underground in mines based on environmental characteristics according to claim 1, characterized in that: During the function model calculation, the difference between the measured parameter and the reference parameter is used as the input variable and input into the correction function to obtain the output result as the correction value. The correction value is compared with the preset tolerance range. If it falls within the tolerance range, the electromagnetic environment of the region is determined to be relatively stable and is considered a reliable region. If it exceeds the tolerance range, it is determined to be a fluctuating region.

3. The method for locating personnel underground in mines based on environmental characteristics according to claim 2, characterized in that: When performing fault tolerance correction, an adjustable correction coefficient is introduced; the sensitivity level parameter required for the current correction is multiplied by the correction coefficient to obtain a fault tolerance value; the fault tolerance value is applied to the personnel's original positioning results, and the corrected positioning data is output.

4. A personnel positioning system for underground mines based on environmental characteristics, used to implement the method according to any one of claims 1 to 3, characterized in that, include: Data processing module: Used to acquire and classify basic information data of various areas underground in the mine, dividing it into planar information sets and feature information sets, and performing standardization processing; Structural modeling module: used to construct the corresponding mine plan structure diagram based on the classification results; Sensitive area identification module: used to analyze the degree of change in feature information, identify and label sensitive areas; Region fusion module: used to overlay the location information of sensitive areas onto the planar structure map, and automatically identify adjacent or overlapping parts, optimizing them into coherent sensitive blocks; Positioning correction module: Used to receive real-time collected location information of workers, and then output the result after correcting the positioning result by calling feature parameters.

5. A personnel positioning terminal for underground mines based on environmental characteristics, characterized in that: The device includes at least one processor and a data storage device connected to the processor, wherein the data storage device stores a computer program; when the program is loaded and executed, it enables the processor to perform the method of any one of claims 1 to 4.

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