Intelligent monitoring method for underground hidden illegal operation based on double-source data linkage verification

Abstract

The application discloses an underground hidden illegal operation intelligent monitoring method based on double-source data linkage verification and belongs to the technical field of mine safety monitoring.The application first delimits a mine monitoring area, arranges personnel flow counting sensing equipment at the exits and entrances of all personnel in the area, collects the actual personnel residence quantity in the area as first source data, reuses an existing mine personnel positioning system, synchronously collects the quantity of registered personnel wearing positioning terminals in the area as second source data, compares the difference between the two groups of data in real time, automatically discriminates risks in combination with a preset hierarchical fault tolerance threshold value in different scenes, distinguishes three types of risks, i.e., normal working conditions, personnel disconnection and overlayer boundary crossing hidden private mining, and hierarchically pushes the early warning, and after the early warning is triggered, automatically retains the sensing counting, personnel positioning and mine map information to form a complete evidence chain.The application can accurately identify underground malignant illegal behaviors such as no card entering the mine, hidden roadway private mining and overlayer boundary crossing mining, and greatly improves the fine level of mine underground safety supervision.

Description

Technical Field

[0001] This invention relates to the field of mine safety monitoring technology, specifically to an intelligent monitoring method for concealed illegal operations underground based on dual-source data linkage verification. Background Technology

[0002] Mining beyond permitted depths or boundaries, unauthorized mining in concealed tunnels, and workers entering the mine without proper permits are common and extremely dangerous safety hazards in underground mines, and also key and challenging aspects of current mine safety supervision. Currently, various coal and non-coal mines in China widely use personnel positioning systems such as UWB, RFID, and Bluetooth to track the location of underground workers, count the number of personnel in different areas, and manage designated zones. However, these systems have inherent technical limitations, and their effectiveness depends entirely on workers wearing positioning terminals correctly throughout the entire process, resulting in numerous blind spots in supervision.

[0003] Firstly, if underground workers do not wear or remove their positioning terminals without authorization, or if mining companies deliberately fail to provide positioning cards to workers and organize workers to enter the mine without cards, the personnel positioning system will be unable to collect the corresponding personnel data, resulting in distorted statistics on registered personnel in the corresponding area and creating a regulatory vacuum for uncarded personnel.

[0004] Secondly, some mining companies circumvent regulations by submitting false mining drawings, illegally excavating hidden tunnels and mining beyond designated depths, and failing to deploy positioning base stations in these unregistered areas. This means that the entire process of personnel entering, staying, and conducting mining operations is completely outside the monitoring capabilities of the positioning system. Relying solely on personnel positioning systems is insufficient to identify such malicious violations of "compliant registered drawings but concealed illegal mining underground." In the event of safety accidents such as gas outbursts, water inrushes, or roof collapses underground, the lack of accurate data on the number and location of personnel underground, along with precise tunnel drawings, will significantly increase the difficulty of underground rescue operations and further amplify the scale of casualties and property damage.

[0005] Third, existing human detection devices such as video AI and millimeter-wave radar are mostly deployed independently and have not established a unified time-series, two-way data comparison and linkage mechanism with the personnel positioning system in use in the mine. They can only identify human targets underground independently and cannot distinguish between unregistered and unauthorized personnel who are "identified by the detection device but have no corresponding personnel record in the positioning system". They do not have the ability to automatically determine risks.

[0006] Fourth, the traditional mine safety supervision model relies mainly on manual underground inspections, which have limited coverage and low frequency. The detection of safety anomalies is significantly delayed, allowing for follow-up work only after accidents or violations occur. It lacks pre-emptive warning and in-process intervention capabilities, resulting in extremely high underground safety management risks. Furthermore, most existing intelligent mine monitoring upgrade solutions require replacing all hardware equipment and reconstructing the entire monitoring system, involving large investments and long construction periods, making them difficult to implement and promote in existing small and medium-sized mines.

[0007] Therefore, the industry urgently needs an intelligent monitoring method that requires low investment, is easy to deploy on-site, and can reuse existing mine monitoring systems to solve long-standing pain points in mine safety supervision, such as unlicensed operations, covert illegal mining, mining beyond permitted layers or boundaries, and the failure of a single regulatory system. Summary of the Invention

[0008] To address the practical problems in the mining industry, such as the reliance on wearable devices for personnel positioning systems, difficulty in identifying concealed violations, lagging manual supervision, and high costs associated with intelligent upgrades, this invention provides an intelligent monitoring method for concealed violations in underground mining operations based on dual-source data linkage verification. By comparing and linking personnel flow sensing equipment with existing personnel positioning systems, it automatically identifies safety risks such as unauthorized personnel leaving their posts, illegal mining beyond permitted layers or boundaries, and data distortion from positioning devices, enabling early warning and end-to-end evidence collection. Simultaneously, it maximizes the reuse of existing mine hardware and software facilities, reduces investment in intelligent mine upgrades, and addresses the shortcomings of existing technologies to the greatest extent possible.

[0009] To achieve the above objectives, the present invention provides the following solution: A smart monitoring method for concealed illegal operations in wells based on dual-source data linkage verification includes: The monitoring area is delineated as needed, and personnel flow counting and sensing devices are deployed at all entrances and exits of the monitoring area; the existing personnel positioning system in the mine is reused; the personnel positioning system is synchronized with all personnel flow counting and sensing devices at the millisecond level; The number of people entering the area is calculated by a personnel flow counting and sensing device, which serves as the first source of measured data; the number of registered online people simultaneously staying in the same area is obtained through a personnel positioning system, which serves as the second source of measured data. Real-time verification and comparison of the first source measured data and the second source measured data are performed to determine the difference between the two source data. Based on different scenarios, a fault tolerance threshold is preset. If the difference between the two source data exceeds the fault tolerance threshold, it is determined that a violation has occurred in the current area, and an early warning response is sent to the regulatory authorities. After the early warning response is triggered, source tracing and evidence collection will be carried out.

[0010] Furthermore, the normal personnel work areas within the monitoring area have achieved full coverage of personnel positioning in accordance with regulatory requirements; all entrances and exits of the monitoring area refer to all wellheads or passages that can enter and exit the monitoring area and are located at the boundary of the monitoring area.

[0011] Furthermore, the method for obtaining the first source of measured data is as follows: all entrances and exits of the monitoring area are equipped with personnel flow counting and sensing devices; assuming there are n entrances and exits in the monitoring area, a total of n sensing devices need to be installed, and the number of people entering the monitoring area counted by the i-th sensing device is defined as... The number of people who left was The formula for the total number of people remaining in the region is: ; The method for obtaining the second source of measured data is as follows: the personnel positioning system obtains the number of registered online personnel simultaneously staying within the designated monitoring area, which serves as the second source of measured data. .

[0012] Furthermore, fault tolerance thresholds are preset according to different scenarios. ,include: Fault tolerance threshold configured for any monitoring area Less than 20% of the maximum number of workers allowed per shift in the current monitoring area; Regular traffic monitoring area: including the main shaft entrance, transport roadway, and pedestrian / vehicle passageway, with the fault tolerance threshold set at the first threshold range; Mining operation area: includes fully mechanized mining, blasting mining, fully mechanized tunneling, and blasting tunneling working faces, and the fault tolerance threshold is uniformly set to the second threshold; During equipment maintenance periods, personnel movement is frequent, so the tolerance threshold for the mining operation area is temporarily raised to the third threshold. The fault tolerance threshold for blasting operations within a 100-meter control range and for roadways at risk of rock bursts is uniformly set to the fourth threshold. High-risk restricted areas include mine boundary roadways, mine field boundaries, closed and idle roadways, and suspicious hidden passages not marked on the drawings. The fault tolerance threshold is set directly to 0.

[0013] Furthermore, it also includes: a dynamic correction mechanism, specifically including: Time window correction: During the 2-hour window period of daily shift handover, the fault tolerance threshold for the entire region will be automatically increased by 1; Frequency adaptive correction: If the same monitoring area triggers the difference exceeding the limit warning multiple times within a week, the system will automatically lower the fault tolerance threshold by one level, and the minimum value of the lowered fault tolerance threshold will be 0.

[0014] Furthermore, there are multiple levels of abnormal risks, including: normal status, risk of personnel being abnormally out of control, suspected overstepping of boundaries, and covert illegal mining.

[0015] Furthermore, the determination of a normal state includes: If the absolute value of the difference between the two source data is within the preset fault tolerance threshold, that is... The data from both sources were determined to be consistent, indicating that the personnel in the corresponding area underground were operating normally and there were no violations or abnormalities.

[0016] Furthermore, the assessment of the risk of personnel being abnormally absconded with includes: If the absolute value of the difference between the two source data is greater than the preset fault tolerance threshold, that is... It was determined that there was a risk of personnel being unsupervised at the scene; When the measured data from the first source is greater than the measured data from the second source, and the difference between the two source data is greater than the preset fault tolerance threshold, it is determined that there are unattended personnel on site. When the measured data from the first source is less than the measured data from the second source, and the difference between the two source data is greater than the preset fault tolerance threshold, it is determined that there is a situation where one person has multiple cards on site.

[0017] Further, the determination of suspected over-level, boundary-crossing, and concealed illegal mining includes: When the monitored area exceeds the preset number of safety anomalies within a preset time, or the absolute value of the difference between the two source data exceeds the fault tolerance threshold. When there are 5 people, it is determined to be suspected of exceeding the floor area and illegal mining.

[0018] Furthermore, after triggering the early warning response, a full-chain tracing and evidence collection process is conducted, including: When any early warning response is triggered, the system acquires the serial numbers, location information, and continuous counting data streams before and after the alarm for all personnel flow counting sensing devices at the time of the alarm trigger; the online registered list and real-time location information of the personnel positioning system; and the latest mine map information. All of the above information serves as the traceability evidence chain.

[0019] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects: Compared with existing mine safety monitoring technologies, this invention has the following technical advantages: (1) Low transformation cost and strong reusability of existing equipment. There is no need to replace or reconstruct the existing personnel positioning system in the mine. Only the flow sensing equipment is deployed at the entrance and exit of the monitoring area (and even existing AI cameras can be reused), which greatly reduces the investment in intelligent transformation of the mine, shortens the on-site construction cycle, and is suitable for implementation and promotion in various existing small and medium-sized mines.

[0020] (2) Fill the gaps in the supervision of single positioning systems. By adopting a dual-source linkage verification mode of actual personnel flow underground and the number of registered personnel, the supervision work is freed from the dependence on personnel positioning terminal wearing behavior, and can accurately identify hidden violations that are difficult to detect by traditional monitoring methods, such as entering the mine without a card, personnel leaving the management, illegal mining in hidden roadways, and mining beyond the layer and boundary.

[0021] (3) The graded fault tolerance thresholds are set according to the general underground personnel control specifications for mines. The thresholds are strictly controlled within the critical value of 20% of the approved personnel in the area for major hidden dangers. At the same time, a dynamic correction mechanism for time period and frequency is provided to adapt to multiple scenarios and take into account both system operation stability and monitoring accuracy. Different fault tolerance thresholds are configured for regular access areas and high-risk prohibited mining areas. This avoids frequent false alarms caused by environmental interference such as underground personnel movement and dust obstruction, and enables high-sensitivity monitoring in high-risk areas such as illegal mining and boundary crossing.

[0022] (4) Fully automated unattended operation reduces the pressure of manual supervision. The entire process of data collection, numerical comparison, risk assessment, and early warning push is automated, eliminating the need for staff to monitor the supervision platform in real time, reducing the frequency of manual underground inspections, and avoiding the problems of lagging and missed inspections in manual supervision.

[0023] (5) A complete chain of evidence supports the closed-loop law enforcement. After the early warning is triggered, three types of core evidence are collected simultaneously: perception count, personnel positioning, and mining maps, forming an unalterable traceability certificate. This provides objective data support for mine safety law enforcement and underground hazard investigation, and accurately delineates the scope of hidden illegal roadways and illegal mining faces. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating the method of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] The core implementation logic of this invention is as follows: reuse the existing personnel positioning system in the mine, deploy two-way flow sensing devices at all personnel access entrances and exits in key underground monitoring areas, and collect personnel number data synchronously in millisecond time series between the two systems. By comparing the difference in the number of people from the two sources with the scene-level fault tolerance threshold, the system automatically distinguishes three types of working conditions: normal operation, personnel being out of control, and covert illegal mining. After the warning is triggered, the system automatically retains the entire chain of evidence, thereby realizing intelligent closed-loop supervision of covert illegal activities underground.

[0028] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] like Figure 1 As shown, this invention provides an intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification, including: Step 1: Reuse the mine's existing personnel positioning system; deploy personnel flow counting and sensing devices at all entrances and exits in the monitoring area; synchronize the personnel positioning system with all personnel flow counting and sensing devices at the millisecond level; All entrances and exits refer to all wellheads or passages that can enter and exit the monitoring area and are located at the boundary of the monitoring area, including but not limited to the main entrance wellhead, auxiliary entrance wellhead, return air wellhead, and all personnel passages.

[0030] The aforementioned sensing equipment uses a bidirectional human body sensing flow counting device suitable for underground use, meeting the requirements of dust prevention, moisture prevention, low illumination, and high dust conditions in coal mines and non-coal mines. This invention adopts functional limitations on the sensing equipment, covering all mining hardware, sensing technologies, and subsequent iteration solutions capable of identifying bidirectional passage of personnel underground, counting the flow of people entering and exiting, and calculating the number of people staying in a region. Optional adaptation technologies include video AI human body recognition, millimeter-wave radar, infrared grating, laser detection, thermal imaging, microwave sensing, and ultrasonic detection. The equipment has a built-in underground interference filtering algorithm that can automatically filter interference from mine cars, anchor bolts, pipelines, light and shadow debris, and accurately distinguish human targets.

[0031] All devices are connected to the monitoring platform, achieving millisecond-level time synchronization and standardized interface docking with the personnel positioning system. This unifies the data collection sequence, eliminates discrepancies in the comparison of personnel from two sources caused by time differences, and ensures verification accuracy.

[0032] Step 2: Calculate the number of people entering the area using the personnel flow counting and sensing device, which serves as the first source of measured data; obtain the number of registered online people simultaneously staying in the same area using the personnel positioning system, which serves as the second source of measured data. The method for obtaining the first source of measured data is as follows: all entrances and exits of the monitoring area are equipped with personnel flow counting and sensing devices; assuming there are n entrances and exits in the monitoring area, a total of n sensing devices need to be installed, and the number of people entering the monitoring area counted by the i-th sensing device is defined as... The number of people who left was The formula for the total number of people remaining in the region is: This data represents the total number of personnel actually working underground within the monitored area, and is not constrained by the wearing status of the positioning terminal.

[0033] The method for obtaining the second source measured data is as follows: the system retrieves the existing UWB / RFID / Bluetooth personnel positioning system database of the mine in real time, filters and delineates the total number of registered personnel within the monitoring area who are currently online and wearing positioning terminals normally, and uses this as the second source measured data. This data only includes compliant personnel carrying valid location cards.

[0034] Step 3, real-time analysis of the first source measured data Second source measured data Perform verification and comparison to determine the difference between the two source data. ; Step 4: Preset fault tolerance thresholds according to different scenarios. If the difference between the two source data exceeds the fault tolerance threshold, it is determined that a violation has occurred in the current area, and an early warning response is sent to the regulatory authorities, including: Normal state determination: Judgment conditions: Conclusion: The absolute value of the difference between the two source data is within the preset fault tolerance threshold range, the personnel working in the corresponding area downhole are in normal condition, and there are no violations or abnormalities.

[0035] Risk assessment of personnel aberration (general regulatory risks): Judgment conditions: It is further divided into two categories of scenarios: : The conclusion is that there are instances of unauthorized and unmanaged behavior, such as not wearing a positioning card, the company not distributing positioning cards, and personnel removing the terminal without authorization. A general warning will be issued. : The conclusion is: there is evidence of one person using multiple cards; a general warning will be issued. Suspected over-limit and unauthorized mining activities (significant regulatory risks): Judgment criteria: Triggered within one week in the same monitoring area The frequency is ≥3 times, or the difference in a single instance exceeds the fault tolerance threshold of 5 or more people in the corresponding scenario (i.e. ); Conclusion: There is a high suspicion of illegal mining activities, including exceeding boundaries and covert unauthorized mining, in the monitored area. A high-level warning has been issued.

[0036] When the risk of personnel absconding or suspected illegal mining beyond designated boundaries is triggered, the mine comprehensive supervision platform will display a high-brightness warning pop-up window, indicating the warning area, difference data, and risk level; at the same time, the warning information will be pushed to the on-site safety officer, mine-level supervisor, and local regulatory department's mobile terminal via SMS and supervision APP.

[0037] In this embodiment, the fault tolerance threshold is set according to the principle that the fault tolerance threshold of each monitoring zone must be strictly less than 20% of the legal maximum number of workers per shift in that zone. If the number of personnel in a zone exceeds the limit by 20%, it will be directly judged as a major safety hazard.

[0038] Under the aforementioned constraints, the system comprehensively considers dust interference from downhole sensing equipment, personnel obstruction effects, and normal errors in instantaneous counting during shift handover, while ensuring the ability to quickly identify unauthorized overloading and unauthorized personnel intrusion.

[0039] Specifically, the fault tolerance thresholds are quantified and configured for different operating scenarios as follows: Example 1: The main access roadway of the mine has a maximum of 180 people per shift and a critical value of 36 people. A fault tolerance threshold of 5 people is selected. The normal counting error of ±5 people by the equipment will not trigger an alarm. Only when a large number of people without cards stay for a long time will an alarm be pushed. Example 2: In a typical mining production face, the approved number of people per shift is 20, the critical value is 4 people, the basic threshold is 2, the potential for personnel to escape supervision is detected in advance, and an early warning buffer is provided before the major potential for overcrowding. Example 3: When tunneling the face and rockburst roadway, the approved number of people per shift is 15, the critical value is 3 people, and the threshold is set to 1. Even a very small deviation in the number of people can identify people who have secretly entered the hidden roadway. Example 4: The mining area is closed off at the boundary of the mine, the approved number of workers is 0, and the threshold is 0. As long as the sensing equipment detects personnel, it is judged as a high risk of illegal mining beyond the boundary.

[0040] To further improve the accuracy of monitoring, this system also incorporates a dynamic correction mechanism to fine-tune the basic thresholds in real time or periodically. 1. Time Window Correction (Shift Change Mode): The system sets a special period for the daily shift change (e.g., a 1-hour window before and after, totaling 2 hours). During this period, the system automatically increments the fault tolerance threshold for the entire area by 1 (+1). This measure aims to offset the instantaneous counting deviation caused by dense overlapping passage of people during shift changes, thus avoiding large-scale false alarms.

[0041] 2. Frequency Adaptive Correction (Sensitive Mode): The system monitors the warning trigger frequency of each region in real time. If the same monitored region triggers the "Dual-Source Data Difference Exceeds Limit" warning multiple times within a week, the system will determine that there is a high risk of continuous violations in that region and automatically lower the fault tolerance threshold by one level (e.g., from 2 people to 1 person). By tightening the threshold, the system's sensitivity in identifying continuous unauthorized data collection or violations in that region is significantly improved.

[0042] Step 5: After triggering the early warning response, conduct full-chain source tracing and evidence collection, including: When any early warning response is triggered, the system acquires the serial numbers, location information, and continuous counting data streams before and after the alarm for all personnel flow counting sensing devices at the time of the alarm trigger; the online registered list and real-time location information of the personnel positioning system; and the latest mine map information. All of the above information serves as the traceability evidence chain.

[0043] It should be noted that this invention is not limited to specific hardware devices and detection principles. All mining sensing devices and technical solutions with functions such as two-way personnel access identification, flow statistics, and regional personnel retention calculation are within the scope of protection of this invention. In addition to video AI sensing and millimeter-wave radar detection technologies commonly used in mines, similar sensing technologies such as infrared sensing, laser detection, microwave sensing, grating monitoring, thermal imaging sensing, and ultrasonic detection can all be adapted to this solution. All recognition algorithms have been optimized and trained for complex working conditions underground, including high dust, low illumination, partial personnel obstruction, and mixed equipment and debris. They can effectively filter out various interferences such as mine cars, pipelines, anchor bolts, changes in light and shadow, and roadway debris, accurately identify human targets, and ensure the accuracy and operational stability of two-way personnel counting underground.

[0044] The system adopts a scenario-based, hierarchical fault-tolerant configuration approach, abandoning fixed, uniform threshold settings. For regular passage areas with frequent personnel entry and exit and high traffic volume, a higher fault-tolerant threshold is configured to offset recognition errors caused by daily fluctuations in personnel flow and minor environmental interference, ensuring stable system operation. For high-risk and strictly controlled areas such as mining boundaries, prohibited mining areas, and hidden illegal mining channels, a lower fault-tolerant threshold is configured to significantly improve data comparison sensitivity, accurately capture various hidden violations, and balance system operational stability with the stringent regulatory requirements of high-risk scenarios.

[0045] This invention supports independent zonal verification of multiple coal seams, roadways, and blind zones underground, enabling separate dual-source data comparison and anomaly analysis for different mining areas. The system employs a distributed grid-based deployment approach, with a single sensing device deployed in a single-entrance area, achieving full coverage of sensing devices in areas with multiple entrances. It accurately calculates the real-time number of people remaining in the area using a formula for summing the number of people in each area. Combining the roadway coordinates and spatial positioning attributes of the personnel positioning system, a comprehensive three-dimensional monitoring system is established. Through features such as multi-point data linkage, unidirectional personnel aggregation patterns, and abrupt changes in the difference between dual-source data, it can reversely pinpoint the entry paths of undocumented personnel and areas of illegal gatherings. It can also accurately delineate the specific areas of hidden roadways not marked on maps and unauthorized excavations, providing reliable data support for the investigation of hidden hazards underground and for refined safety management.

[0046] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0047] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for intelligent monitoring of concealed illegal operations in wells based on dual-source data linkage verification, characterized in that, include: Delineate monitoring areas as needed, and deploy personnel flow counting and sensing devices at all entrances and exits of the monitoring areas; Reuse the mine's existing personnel positioning system; synchronize the personnel positioning system with all personnel flow counting and sensing devices at the millisecond level. The number of people entering the area is calculated by a personnel flow counting and sensing device, which serves as the first source of measured data; the number of registered online people simultaneously staying in the same area is obtained through a personnel positioning system, which serves as the second source of measured data. Real-time verification and comparison of the first source measured data and the second source measured data are performed to determine the difference between the two source data. Based on different scenarios, a fault tolerance threshold is preset. If the difference between the two source data exceeds the fault tolerance threshold, it is determined that a violation has occurred in the current area, and an early warning response is sent to the regulatory authorities. After the early warning response is triggered, source tracing and evidence collection will be carried out.

2. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 1, characterized in that, The normal personnel work area within the monitoring area has achieved full coverage of personnel positioning in accordance with regulatory requirements; all entrances and exits of the monitoring area refer to all wellheads or passages that can enter and exit the monitoring area and are located at the boundary of the monitoring area.

3. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 1, characterized in that, The method for obtaining the first source measured data is as follows: all entrances and exits of the monitoring area are equipped with personnel flow counting and sensing devices; assuming there are n entrances and exits in the monitoring area, a total of n sensing devices need to be installed, and the number of people entering the monitoring area counted by the i-th sensing device is defined as... The number of people who left was The formula for the total number of people remaining in the region is: ； The method for obtaining the second source measured data is as follows: the personnel positioning system obtains the number of registered online personnel simultaneously staying in the designated monitoring area in real time, which serves as the second source measured data. .

4. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 1, characterized in that, The preset fault tolerance threshold according to different scenarios ,include: Fault tolerance threshold configured for any monitoring area Less than 20% of the maximum number of workers allowed per shift in the current monitoring area; Regular traffic monitoring area: including the main shaft entrance, transport roadway, and pedestrian / vehicle passageway, with the fault tolerance threshold set at the first threshold range; Mining operation area: includes fully mechanized mining, blasting mining, fully mechanized tunneling, and blasting tunneling working faces, and the fault tolerance threshold is uniformly set to the second threshold; During equipment maintenance periods, personnel movement is frequent, so the tolerance threshold for the mining operation area is temporarily raised to the third threshold. The fault tolerance threshold for blasting operations within a 100-meter control range and for roadways at risk of rock bursts is uniformly set to the fourth threshold. High-risk restricted areas include mine boundary roadways, mine field boundaries, closed and idle roadways, and suspicious hidden passages not marked on the drawings. The fault tolerance threshold is set directly to 0.

5. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 4, characterized in that, Also includes: The dynamic correction mechanism specifically includes: Time window correction: During the 2-hour window period of daily shift handover, the fault tolerance threshold for the entire region will be automatically increased by 1; Frequency adaptive correction: If the same monitoring area triggers the difference exceeding the limit warning multiple times within a week, the system will automatically lower the fault tolerance threshold by one level, and the minimum value of the lowered fault tolerance threshold will be 0.

6. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 1, characterized in that, Multi-level abnormal risks include: normal status, risk of personnel being abnormally out of control, suspected overstepping of boundaries and covert illegal mining.

7. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 6, characterized in that, The determination of the normal state includes: If the absolute value of the difference between the two source data is within the preset fault tolerance threshold, that is... The data from both sources were determined to be consistent, indicating that the personnel in the corresponding area underground were operating normally and there were no violations or abnormalities.

8. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 6, characterized in that, The assessment of the risk of personnel abnormally escaping supervision includes: If the absolute value of the difference between the two source data is greater than the preset fault tolerance threshold, that is... It was determined that there was a risk of personnel being unsupervised at the scene; When the measured data from the first source is greater than the measured data from the second source, and the difference between the two source data is greater than the preset fault tolerance threshold, it is determined that there are unattended personnel on site. When the measured data from the first source is less than the measured data from the second source, and the difference between the two source data is greater than the preset fault tolerance threshold, it is determined that there is a situation where one person has multiple cards on site.

9. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 6, characterized in that, The determination of suspected over-level, boundary-crossing, and concealed illegal mining includes: When the monitored area exceeds the preset number of safety anomalies within a preset time, or the absolute value of the difference between the two source data exceeds the fault tolerance threshold. When there are 5 people, it is determined to be suspected of exceeding the floor area and illegal mining.

10. The intelligent monitoring method for concealed illegal operations in wells based on dual-source data linkage verification according to claim 1, characterized in that, After the early warning response is triggered, full-chain tracing and evidence collection are performed, including: When any early warning response is triggered, the system acquires the serial numbers, location information, and continuous counting data streams before and after the alarm for all personnel flow counting sensing devices at the time of the alarm trigger; the online registered list and real-time location information of the personnel positioning system; and the latest mine map information. All of the above information serves as the traceability evidence chain.

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