Gas monitoring and early warning method, device and system combined with personnel positioning

Abstract

The application relates to a gas monitoring and early warning method, device and system combined with personnel positioning, and relates to the technical field of mine safety monitoring. The method comprises the following steps: determining gas trend characteristics of multiple gases in each risk area in a mine shaft according to time sequence data of the concentrations of the multiple gases; determining a target risk level and a regional early warning threshold of each risk area according to corresponding risk attribute parameters of each risk area; determining a comprehensive risk value of each risk area according to the target risk level of each risk area, the gas trend characteristics of the multiple gases and position information of underground operation personnel; and comparing the comprehensive risk value with the regional early warning threshold to determine a gas abnormal early warning result of each risk area.

Description

Technical Field

[0001] This application relates to mine safety monitoring, and in particular to gas monitoring and early warning methods, devices and systems that combine personnel positioning. Background Technology

[0002] In the underground working environment of metal and non-metal mines, the accumulation and leakage of toxic and harmful gases (CO, H2S, NO2, SO2) are among the main factors threatening the lives of workers. Due to the complex geological conditions and diverse mining methods in metal and non-metal mines, the ventilation conditions and spatial structures of different areas underground (working faces, transport roadways, goaf, etc.) vary significantly, and the gas migration patterns are unique, posing higher technical requirements for gas monitoring and early warning.

[0003] Currently, most underground metal and non-metal mines in China have deployed separate toxic and hazardous gas monitoring systems and personnel positioning systems. These two systems only display data independently and lack effective linkage logic. Furthermore, current gas exceedance warnings mostly use fixed thresholds to trigger alarms, resulting in static warning logic that fails to consider the rate and acceleration of gas concentration changes, making it impossible to sense gas trends and provide dynamic warnings. Simultaneously, current personnel monitoring only assesses risk based on the gas concentration at a person's current location, neglecting personnel movement trends, thus failing to guarantee safety during personnel movement. Summary of the Invention

[0004] This invention provides a gas monitoring and early warning method, device, and system that combines personnel positioning, to at least solve the problems of limited gas detection methods, static early warning logic, and inability to provide dynamic and intelligent early warnings based on gas diffusion trends and personnel movement trends. The technical solution of this invention is as follows: According to a first aspect of the present invention, a gas monitoring and early warning method incorporating personnel location is provided. The method includes: determining the gas trend characteristics of multiple gases in each risk area of ​​a mine based on time-series concentration data of multiple gases; the multiple gases include carbon monoxide, hydrogen sulfide, nitrogen dioxide, and sulfur dioxide; determining the target risk level and regional early warning threshold for each risk area based on risk attribute parameters corresponding to each risk area; determining the comprehensive risk value for each risk area based on the target risk level, the gas trend characteristics of multiple gases, and the location information of underground workers; and comparing the comprehensive risk value with the regional early warning threshold to determine the gas anomaly early warning result for each risk area.

[0005] As one implementation method, before determining the target risk level and regional early warning threshold of each risk area based on the risk attribute parameters corresponding to each risk area, the method includes: dividing the underground space of the mine into multiple risk areas according to the actual working area of ​​the mine; the actual working area includes roadways, mining faces and goaf; and determining the risk attribute parameters of each risk area based on the ventilation design air volume, space volume and historical gas concentration distribution data of each risk area.

[0006] In this implementation, based on the actual layout of metal and non-metal mine roadways, working faces, and goaf areas, the underground area is divided into three zones: a conventional operation zone, a risk buffer zone, and a high-risk restricted area, each uniquely numbered and marked. Dynamic risk attribute parameters are also assigned to each risk zone, providing a basis for subsequent gas risk classification and comprehensive risk assessment.

[0007] As one implementation method, risk attribute parameters include regional ventilation coefficient, volume coefficient, and risk warning adjustment factor. Based on the risk attribute parameters corresponding to each risk area, the target risk level for each risk area is determined, including: comparing the measured concentrations of various gases in each risk area with preset risk level thresholds to determine the initial risk level for each risk area; the preset risk level thresholds include a first risk threshold, a second risk threshold, a third risk threshold, and a fourth risk threshold; based on the risk attribute parameters corresponding to each risk area, the initial risk level is corrected to obtain the target risk level for each risk area; specifically, if the measured concentration is within the range of the first risk threshold, the initial risk level is determined to be a blue warning level; if the measured concentration is within the range of the second risk threshold, the initial risk level is determined to be a yellow warning level; if the measured concentration is within the range of the third risk threshold, the initial risk level is determined to be an orange warning level; and if the measured concentration is within the range of the fourth risk threshold, the initial risk level is determined to be an orange warning level.

[0008] As one implementation method, gas trend characteristics include concentration change rate, concentration acceleration, and diffusion direction vector. Based on the target risk level of each risk area, the gas trend characteristics of multiple gases, and the location information of downhole personnel, a comprehensive risk value for each risk area is determined. This includes: determining the location information of downhole personnel in each risk area; location information includes movement direction vector, movement speed, and estimated time to reach the high-risk area; high-risk areas are those corresponding to target risk levels of yellow, orange, or red alerts; based on the gas trend characteristics of multiple gases and the location information of downhole personnel, current exposure risk, trend evolution risk, movement approach risk, and regional attribute risk correction values ​​are determined; and the comprehensive risk value is determined by the weighted sum of these values.

[0009] In this implementation, by deeply integrating trend evolution risk and moving approach risk, it is more able to capture the spread trend and approach speed of risk, and introduce regional attribute correction values ​​to accurately quantify the risk level and quickly trace the main disaster-causing factors, thereby achieving refined quantitative driving and supporting accurate decision-making. In this way, risk assessment is transformed from a static and isolated scoring into a dynamic, related, and forward-looking intelligent analysis process.

[0010] As one implementation method, a regional early warning threshold is determined for each risk area based on the risk attribute parameters corresponding to each risk area. The comprehensive risk value is compared with the regional early warning threshold to determine the gas anomaly early warning result for each risk area. This includes: determining the regional early warning threshold for each risk area based on the risk attribute parameters corresponding to each risk area and a preset global benchmark threshold; determining a first early warning threshold, a second early warning threshold, a third early warning threshold, and a fourth early warning threshold based on the regional early warning threshold; if the comprehensive risk value is detected to be less than the first early warning threshold, the abnormal early warning result is determined as no early warning is triggered; if the comprehensive risk value is detected to be greater than or equal to the first early warning threshold and less than the second early warning threshold, the abnormal early warning result is determined. To trigger a blue alert, the system notifies the ground control terminal of each risk area corresponding to the blue alert. If the overall risk value is greater than or equal to the second alert threshold and less than the third alert threshold, an abnormal alert result is determined to trigger a yellow alert, and an alarm is sent to the field terminals in each risk area corresponding to the yellow alert. If the overall risk value is greater than or equal to the third alert threshold and less than the fourth alert threshold, an abnormal alert result is determined to trigger an orange alert, and an alarm is sent to the personnel terminals in each risk area corresponding to the orange alert. If the overall risk value is greater than or equal to the fourth alert threshold, an abnormal alert result is determined to trigger a red alert, and an alarm is sent to the personnel terminals in each risk area corresponding to the red alert.

[0011] As one approach, low-risk evacuation routes for downhole workers are determined based on their location information and gas anomaly warnings for each risk area.

[0012] As one implementation method, the system monitors the early warning response time, the evacuation efficiency of downhole workers, and the concentration change characteristics of various gases in each risk area in real time. It uses a Bayesian optimization algorithm to adjust the comprehensive risk value. When the comprehensive risk value of each risk area corresponding to the triggering of a blue, yellow, orange, or red early warning is less than the first early warning threshold, the alarm is automatically lifted.

[0013] As one approach, the gas concentration and diffusion direction of each risk area are predicted based on environmental factors and gas trend characteristics, resulting in a predicted gas concentration value for each risk area. Environmental factors include wind speed, temperature, humidity, and production operation status. The predicted gas concentration value is compared with a preset risk level threshold to determine the target risk level of each risk area within a preset time domain. Based on the target risk level, the on-site terminals in each risk area are triggered to issue an alarm in advance.

[0014] According to a second aspect of the present invention, a gas monitoring and early warning device incorporating personnel positioning is provided, the device comprising: The gas data processing unit is configured to determine the gas trend characteristics of multiple gases in each risk zone of the mine based on the time series data of the concentration of multiple gases in each risk zone; the multiple gases include carbon monoxide, hydrogen sulfide, nitrogen dioxide and sulfur dioxide.

[0015] The risk level identification unit is configured to determine the target risk level and regional early warning threshold for each risk area based on the risk attribute parameters corresponding to each risk area.

[0016] The risk assessment unit is configured to determine the comprehensive risk value of each risk area based on the target risk level of each risk area, the gas trend characteristics of multiple gases, and the location information of downhole workers.

[0017] The risk warning unit is configured to compare the comprehensive risk value with the preset warning threshold to determine the gas anomaly warning result.

[0018] According to a third aspect of the present invention, a gas monitoring and early warning system incorporating personnel location is provided, the gas monitoring and early warning system incorporating personnel location being configured to perform a gas monitoring and early warning method incorporating personnel location as described in the first aspect and any possible implementation thereof.

[0019] According to a fourth aspect of the present invention, a gas monitoring and early warning device incorporating personnel location is provided, the device being configured to perform a gas monitoring and early warning method incorporating personnel location as described in the first aspect and any possible implementation thereof.

[0020] According to a fifth aspect of the present invention, a computer-readable storage medium is provided, on which instructions are stored, such that when the instructions in the computer-readable storage medium are executed by a processor of a gas monitoring and early warning device in conjunction with personnel positioning, the gas monitoring and early warning device in conjunction with personnel positioning is able to perform a gas monitoring and early warning method in conjunction with personnel positioning as described in the first aspect and any possible implementation thereof.

[0021] According to a sixth aspect of the present invention, a computer program product is provided, the computer program product including computer instructions, which, when executed in conjunction with a gas monitoring and early warning device for personnel location, cause the gas monitoring and early warning device for personnel location to perform the gas monitoring and early warning method for personnel location in conjunction with the first aspect and any possible implementation thereof.

[0022] The technical solution provided by the embodiments of the present invention brings at least the following beneficial effects: by integrating gas trend characteristics, regional risk attributes, and personnel movement trajectories, multi-dimensional intelligent early warning of gas anomalies in mines is achieved. First, by extracting the gas trend characteristics of multiple gases in various regions, potential gas accumulation or leakage signs are captured in advance, significantly improving the foresight and sensitivity of risk perception. Simultaneously, by combining the risk attribute parameters corresponding to each risk region, the gas concentration in each risk region is accurately classified. Based on this, the target risk level, gas trend characteristics, and location information of underground workers in each risk region are coupled in multiple dimensions to comprehensively evaluate the comprehensive risk value of each region. This effectively avoids false alarms and blind spots caused by single-point instantaneous concentration monitoring. Furthermore, by integrating personnel movement trajectories, the safety of workers moving between different areas in the mine is ensured. Finally, based on the risk attribute parameters of each region, regional early warning thresholds are set differently. By comparing the comprehensive risk value with the regional early warning thresholds, differentiated and graded gas anomaly early warning results are obtained for each region, ensuring that high-risk areas are matched with higher-intensity emergency responses, achieving refined and intelligent mine safety management.

[0023] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0025] Figure 1 This is a schematic diagram illustrating a gas monitoring and early warning system that incorporates personnel positioning, according to an exemplary embodiment. Figure 2 This is a flowchart illustrating a gas monitoring and early warning method incorporating personnel location, according to an exemplary embodiment. Figure 3 This is a threshold chart for multiple gas risk levels, illustrated according to an exemplary embodiment; Figure 4 This is a block diagram illustrating a gas monitoring and early warning device incorporating personnel positioning, according to an exemplary embodiment. Figure 5This is a schematic diagram illustrating a gas monitoring and early warning device that incorporates personnel positioning, according to an exemplary embodiment. Detailed Implementation

[0026] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0027] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0028] Before providing a detailed introduction to the gas monitoring and early warning method combined with personnel positioning provided in the embodiments of this application, let's first briefly introduce the application scenarios and implementation environment involved in the embodiments of this application.

[0029] Research has revealed that the accumulation and leakage of toxic and harmful gases (CO, H2S, NO2, SO2) are among the main factors threatening the lives of workers in underground metal and non-metal mines. Due to the complex geological conditions and diverse mining methods in metal and non-metal mines, the ventilation conditions and spatial structures of different underground areas (working faces, transport roadways, goafs, etc.) vary significantly, resulting in unique gas transport patterns and placing higher demands on gas monitoring and early warning systems. Currently, most underground metal and non-metal mines in China have separately deployed toxic and harmful gas monitoring systems and personnel positioning systems. These two systems only display data independently and lack effective linkage logic. When abnormal underground gas conditions occur, targeted early warnings cannot be issued based on personnel location, leading to generalized warnings and low identification rates among on-site personnel.

[0030] Specifically, the following five defects are included: First, the gas detection means are single and lack coordination. Traditional gas detection mostly relies on fixed point sensors, which can only provide concentration information at local points, and lack the spatial perception capability for gas diffusion trends. Underground in metal and non-metal mines, there are extreme working conditions with wide variation ranges of atmospheric pressure and temperature, high relative humidity, and strong electromagnetic interference, making a single sensor highly susceptible to environmental interference. Moreover, the migration laws of different gases in the underground space differ significantly: CO (density 0.97kg / m³, slightly lighter than air) tends to accumulate near the roof; H2S (density 1.19kg / m³, slightly heavier than air) is easily soluble in water and greatly affected by underground humidity; both NO2 (density 1.45kg / m³) and SO2 (density 2.26kg / m³) have densities greater than air, and tend to deposit at the bottom of roadways and low-lying areas. Due to the differences in physical and chemical properties of the above gases, their accumulation positions and diffusion paths underground are completely different, and it is currently impossible to design differentiated monitoring and early warning strategies for the characteristics of different gases. Second, the early warning logic is static and lacks trend prediction. Changes in the concentration of toxic and harmful gases are affected by many complex factors such as ventilation conditions, blasting operations, and ore oxidation, showing instability and non-linearity. However, fixed thresholds are mostly used to trigger alarms at present, without considering the change rate and acceleration of different gas concentrations. Even if the gas concentration is rising rapidly but has not yet exceeded the standard, the system cannot issue an early warning in advance. Third, the dimension of personnel risk assessment is single. In the actual judgment of personnel movement risk, the actual risk of a person who is rapidly approaching a high-concentration area is far higher than that of a person staying in an area with the same concentration, but current linked early warning schemes usually determine the risk only based on the gas concentration at the current position of the person, without considering the movement trend of the person, that is, whether the person is moving towards or away from the high-concentration area. Fourth, the early warning threshold lacks regional adaptive capability. Ventilation conditions and spatial volumes of different areas (working faces, haulage roadways, chambers) underground in metal and non-metal mines differ significantly, and the actual risk corresponding to the same concentration threshold in different areas is completely different. Currently, the early warning threshold is not dynamically adjusted according to regional attributes. Fifth, the data sharing and association mechanism is missing. There is a lack of a unified data interaction interface and linked judgment logic between the two systems of gas monitoring and personnel positioning, making it impossible to realize real-time comprehensive analysis and judgment of "gas risk and personnel position".

[0031] In view of the above problems, this application proposes a gas monitoring and early warning method combined with personnel positioning. Aiming at the characteristics of underground metal and non-metal mines, this linked method can integrate multi-source gas detection, dynamic trend perception, continuous personnel positioning and regional adaptive early warning, and realize multi-dimensional intelligent early warning of underground gas anomalies and mine safety management by fusing gas trend features, regional risk attributes and personnel movement trajectories.

[0032] Next, the implementation architecture involved in this application is briefly introduced below.

[0033] Figure 1 This is a schematic diagram of a gas monitoring and early warning system that incorporates personnel positioning, as provided in this application. Figure 1 As shown, the gas monitoring and early warning system that combines personnel positioning includes a gas data processing module 11, a risk level identification module 12, a risk assessment module 13, a risk early warning module 14, an evacuation route planning module 15, and an early warning closed-loop control module 16.

[0034] The gas data processing module 11, risk level identification module 12, risk assessment module 13, risk early warning module 14, evacuation route planning module 15, and early warning closed-loop control module 16 mentioned above are connected via communication.

[0035] The gas data processing module 11 is configured to determine the gas trend characteristics of multiple gases in each risk area based on the time series data of the concentration of multiple gases in each risk area of ​​the mine; the multiple gases include carbon monoxide, hydrogen sulfide, nitrogen dioxide and sulfur dioxide.

[0036] The risk level identification module 12 is configured to determine the target risk level and regional early warning threshold of each risk area based on the risk attribute parameters corresponding to each risk area.

[0037] The risk assessment module 13 is configured to determine the comprehensive risk value of each risk area based on the target risk level of each risk area, the gas trend characteristics of multiple gases, and the location information of downhole workers.

[0038] The risk warning module 14 is configured to compare the comprehensive risk value with the preset warning threshold to determine the gas anomaly warning result.

[0039] The evacuation route planning module 15 is configured to determine the low-risk evacuation route for the downhole workers based on their location information and the gas anomaly warning results for each risk area.

[0040] The early warning closed-loop control module 16 is configured to monitor the early warning response time, the evacuation efficiency of downhole workers, and the concentration change characteristics of multiple gases in each risk area in real time. It uses a Bayesian optimization algorithm to adjust the comprehensive risk value. When the comprehensive risk value of each risk area corresponding to the triggering of a blue, yellow, orange, or red early warning is less than the first early warning threshold, the alarm is automatically lifted.

[0041] For ease of understanding, the gas monitoring and early warning method combined with personnel positioning provided in this application will be described in detail below with reference to the accompanying drawings.

[0042] Figure 2 This is a flowchart illustrating a gas monitoring and early warning method incorporating personnel location, according to an exemplary embodiment. Figure 2As shown, the gas monitoring and early warning method that combines personnel positioning includes the following steps.

[0043] S21. Based on the time series data of the concentration of multiple gases in each risk area of ​​the mine, determine the gas trend characteristics of multiple gases in each risk area.

[0044] Among them are various gases including carbon monoxide (CO), hydrogen sulfide (H2S), nitrogen dioxide (NO2), and sulfur dioxide (SO2).

[0045] Determining the gas trend characteristics of multiple gases in each risk area involves the following two steps.

[0046] First, the actual working environment in underground metal and non-metal mines is complex. Therefore, before gas detection, the area is divided and the area attributes are marked according to the actual environment in the mine.

[0047] In one implementation, the underground space of the mine is divided into multiple risk zones based on the actual working area underground; the risk attribute parameters of each risk zone are determined based on the ventilation design air volume, space volume and historical gas concentration distribution data of each risk zone.

[0048] The actual operating area includes roadways, mining faces, and goaf areas.

[0049] Risk attribute parameters include regional ventilation coefficient, volume coefficient, and risk warning adjustment factor.

[0050] The ventilation coefficient represents the design air volume for ventilation in each area.

[0051] The volume factor represents the spatial volume of each region.

[0052] The risk warning adjustment factor is obtained from historical gas concentration distribution statistics.

[0053] Understandably, based on the actual layout of metal and non-metal mine roadways, working faces, and goaf areas, the underground area is divided into three zones: a conventional operation zone, a risk buffer zone, and a high-risk restricted area, each uniquely numbered and marked. Dynamic risk attribute parameters are also assigned to each risk zone to provide a basis for subsequent gas risk classification and comprehensive risk assessment.

[0054] Secondly, multiple types of gas sensors are deployed in a grid pattern in areas such as mining faces, transport roadways, and goaf edges of underground metal and non-metal mines to collect time-series data of multiple gases in each risk area. Based on the concentration time-series data, the gas trend characteristics of multiple gases in each risk area are determined.

[0055] Specifically, an electrochemical sensor is used in conjunction with a tunable semiconductor laser absorption spectroscopy (TDLAS) sensor to collect various gases. Each sensor collects gas concentration data in real time at different sampling frequencies, and the gas concentration data is labeled with device ID, high-precision timestamp (accuracy ≤1ms), and spatial coordinate information in real time. Based on the continuous time series of gas concentration data, the trend characteristics of each region are extracted in real time.

[0056] The electrochemical sensor has a sampling frequency of 10Hz, while the TDLAS sensor has a sampling frequency of 2Hz. Time synchronization of all sensors is achieved through a Precision Time Protocol (PTP, IEEE1588), ensuring a time deviation of <10ms between devices.

[0057] Gas trend characteristics include concentration change rate, concentration acceleration, and diffusion direction vector.

[0058] In one embodiment, the concentration change rate, concentration acceleration, and diffusion direction vector are specifically characterized by the following formulas (1) to (3).

[0059] (1).

[0060] in, The rate of concentration change; Let be the gas concentration value at time t; This represents the gas concentration value at the previous moment; This represents the time difference between two consecutive samplings. A positive rate of change in concentration indicates an increase in concentration, while a negative rate indicates a decrease in concentration.

[0061] (2).

[0062] in, Concentration acceleration; The rate of concentration change; The time difference between two consecutive samples.

[0063] (3).

[0064] in, The diffusion direction vector; The gas concentration in the adjacent region; The current gas concentration in the region; This represents the distance between adjacent regions. A negative diffusion direction vector indicates that the gas is diffusing outwards.

[0065] In this implementation, the trend characteristics of gas changes in each region are extracted, avoiding the lag or false alarms caused by relying solely on concentration for judgment. After collecting concentration time series data, the concentration change rate, concentration acceleration and diffusion direction vector are further extracted, which can locate and judge the danger earlier and more accurately, and effectively guide the emergency response.

[0066] S22. Based on the risk attribute parameters corresponding to each risk area, determine the target risk level and regional early warning threshold for each risk area.

[0067] Based on the risk attribute parameters of each risk area marked in step S21 above, the risk level of each area and the differentiated regional early warning threshold are determined, specifically including the following two aspects.

[0068] First, gas anomalies are classified into four risk levels: blue alert, yellow alert, orange alert, and red alert, and the target risk level for each risk area is determined.

[0069] In one implementation, the measured concentrations of various gases in each risk area are compared with preset risk level thresholds to determine the initial risk level of each risk area. Based on the risk attribute parameters corresponding to each risk area, the initial risk level is corrected to obtain the target risk level for each risk area.

[0070] The preset risk level thresholds include a first risk threshold, a second risk threshold, a third risk threshold, and a fourth risk threshold.

[0071] If the measured concentration falls within the first risk threshold, the initial risk level is set as a blue alert; if the measured concentration falls within the second risk threshold, the initial risk level is set as a yellow alert; if the measured concentration falls within the third risk threshold, the initial risk level is set as an orange alert; if the measured concentration falls within the fourth risk threshold, the initial risk level is set as an orange alert.

[0072] For example, such as Figure 3 As shown, safety threshold benchmarks for four gases are set with reference to the "Safety Regulations for Metal and Non-metal Mines" and the "Occupational Exposure Limits for Hazardous Factors in the Workplace" (GBZ 2.1).

[0073] Set preset risk level thresholds for each gas to classify four risk levels: blue alert, yellow alert, orange alert, and red alert.

[0074] The safe threshold for carbon monoxide (CO) is 24 ppm; the first risk threshold corresponding to the blue alert level is 24~50 ppm; the second risk threshold corresponding to the yellow alert level is 50~100 ppm; the third risk threshold corresponding to the orange alert level is 100~300 ppm; and the fourth risk threshold corresponding to the red alert level is ≥300 ppm.

[0075] The safe threshold for hydrogen sulfide (H2S) is 6.6 ppm; the first risk threshold corresponding to the blue alert level is 6.6~15 ppm; the second risk threshold corresponding to the yellow alert level is 15~30 ppm; the third risk threshold corresponding to the orange alert level is 30~50 ppm; and the fourth risk threshold corresponding to the red alert level is ≥50 ppm.

[0076] The safe threshold for nitrogen dioxide (NO2) is 2.5 ppm; the first risk threshold corresponding to the blue alert level is 2.5~5 ppm; the second risk threshold corresponding to the yellow alert level is 5~10 ppm; the third risk threshold corresponding to the orange alert level is 10~15 ppm; and the fourth risk threshold corresponding to the red alert level is ≥15 ppm.

[0077] The safe threshold for sulfur dioxide (SO2) is 5 ppm; the first risk threshold corresponding to the blue warning level is 5~10 ppm; the second risk threshold corresponding to the yellow warning level is 10~20 ppm; the third risk threshold corresponding to the orange warning level is 20~30 ppm; and the fourth risk threshold corresponding to the red warning level is ≥30 ppm.

[0078] Based on this, after determining the initial risk level of each risk area, the initial risk level is adjusted according to the risk attribute parameters of each risk area, either by increasing or decreasing the risk level, thereby providing early warning.

[0079] Optionally, based on the environmental factors and gas trend characteristics of each risk area, the gas concentration and diffusion direction of each risk area are predicted to obtain the predicted gas concentration value of each risk area; the environmental factors include wind speed, temperature, humidity and production operation status; the predicted gas concentration value is compared with the preset risk level threshold to determine the target risk level of each risk area in the future preset time domain; according to the target risk level, the on-site terminal of each risk area is triggered to issue an alarm in advance.

[0080] Thus, by employing a multivariate time-series forecasting model and combining multi-source data such as wind speed, temperature, humidity, and production operation status, rolling predictions of gas concentrations for the next 5-10 minutes can be achieved. This allows for proactive early warning through dynamic trend sensing. By extracting the rate of change, acceleration, and diffusion direction of gas concentration and combining them with the multivariate time-series forecasting model, early warnings can be issued before gas concentrations exceed the standard.

[0081] For example, on a certain day, the CO concentration changes at a mining face in the -200m section were monitored as follows: at t=0s, the gas concentration was 15ppm; at t=10s, the gas concentration was 20ppm; and at t=20s, the gas concentration was 28ppm. The concentration change rate and concentration acceleration, which are used to extract trend characteristics, are respectively... It is 0.5 ppm / s. It is 0.8 ppm / s. It is 0.03 ppm / s². A value greater than 0 indicates that the concentration is rising rapidly.

[0082] Furthermore, the current gas concentration in the area was detected to be 28 ppm, which is only slightly above the safety threshold of 24 ppm, and is therefore a blue alert level. However, based on the risk attribute parameters and trend characteristics of the area, it was determined that the concentration acceleration in the area was on the rise, and the environmental conditions in the area were identified as "rapidly deteriorating". The initial risk level was then raised to a yellow alert level, triggering an alarm at the on-site terminal in the area ahead of schedule.

[0083] Using a multivariate time-series prediction model, combined with a wind speed of 0.5 m / s and a temperature of 28°C, the system predicted that the CO concentration would reach 55 ppm within the next 5 minutes, triggering a yellow alert. Four workers in the area were promptly notified to evacuate. Five minutes later, the concentration reached 58 ppm, verifying the accuracy of the prediction. This proactive early warning system ensured the safety of the workers.

[0084] Secondly, determine the regional early warning threshold for each area.

[0085] Based on the risk warning adjustment factor in the risk attribute parameters, the regional warning threshold for each region is determined. Specifically, it is represented by the following formula (4).

[0086] (4).

[0087] in, This is the regional early warning threshold; This is the global baseline threshold; This is an adjustment factor for risk warning.

[0088] It is understandable that the working environment is different in each risk area. The warning threshold for each risk area is determined based on the different risk warning adjustment factors of each area, and the actual risk level is matched to achieve tiered and precise prevention and control.

[0089] S23. Based on the target risk level of each risk area, the gas trend characteristics of various gases, and the location information of downhole workers, determine the comprehensive risk value of each risk area.

[0090] The location information includes the direction vector of movement, movement speed, and estimated time to reach the high-risk area.

[0091] High-risk areas are those with a target risk level of yellow, orange, or red alert.

[0092] In one implementation, determining the overall risk value for each risk area involves the following three steps.

[0093] First, determine the location information of downhole workers in each risk area.

[0094] Specifically, UWB (Ultra-Wideband) technology is used to achieve continuous real-time positioning of personnel underground: UWB tags worn by personnel periodically transmit pulse signals at a frequency of 10-20Hz, and multiple fixed base stations receive the signals. The three-dimensional coordinates (x, y, z) of the tags are solved using the Time Difference of Arrival (TDoA) method, achieving a positioning accuracy of <30cm. Simultaneously, the system continuously transmits the real-time location information of all personnel and calculates their movement trends in real time based on historical trajectory data, thereby obtaining the real-time location information of underground workers.

[0095] Gas monitoring data and personnel location data are aggregated in real time through a unified data interface. The spatiotemporal reference of gas monitoring data and personnel location information for each area is unified. The unified data interface uses either OPC UA or MQTT protocol. The time synchronization deviation for spatiotemporal reference unification is ≤50ms, and the spatial reference is unified through a coordinate transformation matrix.

[0096] The inverse distance weighted (IDW) interpolation method is used to calculate the gas concentration at the personnel location in real time. The specific characteristics are shown in the following formula (5).

[0097] (5).

[0098] in, The gas concentration at the location of personnel; Gas concentration; As weight; For distance.

[0099] For example, when the UWB system outputs the coordinates of a person (88, 43, -300), the system quickly queries the surrounding sensor nodes using a three-dimensional octree index. The CO concentrations of the four nearest nodes are 45ppm, 52ppm, 38ppm, and 48ppm, respectively, and the distances are 1.2m, 1.8m, 2.5m, and 3.0m.

[0100] The gas concentration value at the location of the person is determined by the IDW interpolation method, as shown in the following formula (6).

[0101] (6).

[0102] By linking the location of the workers with the gas concentration data, the gas concentration at the location of the workers moving in real time can be accurately determined, thus ensuring the safety of the workers working downhole.

[0103] Secondly, the comprehensive risk value is determined based on the gas trend characteristics of various gases and the location information of downhole workers.

[0104] Specifically, a three-dimensional risk matrix is ​​constructed based on the gas trend characteristics of various gases and the location information of downhole workers, and the comprehensive risk value is calculated accordingly, as specifically represented by the following formulas (7) to (11).

[0105] The three-dimensional risk matrix includes current exposure risk, trend evolution risk, moving approach risk, and regional attribute risk correction values.

[0106] First, based on the actual concentration of a certain gas, the corresponding gas safety threshold, and the gas toxicity weight, the current exposure risk is determined to characterize the real-time gas exposure risk at the current location of the personnel. The following formula (7) specifically characterizes this risk.

[0107] Toxicity weights are relative coefficients characterizing the toxicity of gases, where H2S = 1.5, NO2 = 1.3, CO = 1.2, and SO2 = 1.1.

[0108] (7).

[0109] in, For current exposed risks; The actual concentration of the i-th gas; Let i be the safety threshold for the i-th gas; Let be the toxicity weight of the i-th gas.

[0110] Secondly, based on the assessment timeframe for predicting future risks, the trend evolution risk is determined to characterize the future risks predicted based on concentration change trends. This is specifically represented by the following formula (8).

[0111] (8).

[0112] in, Risks associated with trend evolution; The rate of concentration change; Concentration acceleration; The exposure time window is set to 60 seconds for prediction. , These are trend risk weighting coefficients, which control the degree of influence of the concentration change rate and concentration acceleration on the trend evolution risk, respectively.

[0113] Third, the risk of movement is determined based on the distance of personnel to the boundary of the high-risk area. This is specifically represented by the following formula (9).

[0114] (9).

[0115] in, Risk of moving closer to risk; The speed at which people move; The distance of personnel from the boundary of high-risk areas; To approximate the risk weighting coefficient.

[0116] Fourth, based on the regional ventilation coefficient, determine the regional attribute risk correction value. The following formula (10) specifically represents this.

[0117] (10).

[0118] in, This is a correction value for regional attribute risk. Ventilation coefficient; The volume factor; This is an adjustment factor for risk warning.

[0119] Finally, the comprehensive risk value is obtained by weighting the current exposure risk, trend evolution risk, moving approach risk, and regional attribute risk correction values. The following formula (11) specifically represents this.

[0120] (11).

[0121] in, The overall risk value is represented by w1, w2, w3, and w4, which are the risk weighting coefficients for each dimension. For current exposed risks; Risks associated with trend evolution; Risk of moving closer to risk; This is a correction value for regional attribute risk.

[0122] In this implementation, by deeply integrating trend evolution risk and moving approach risk, it is more able to capture the spread trend and approach speed of risk, and introduce regional attribute correction values ​​to accurately quantify the risk level and quickly trace the main disaster-causing factors, thereby achieving refined quantitative driving and supporting accurate decision-making. In this way, risk assessment is transformed from a static and isolated scoring into a dynamic, related, and forward-looking intelligent analysis process.

[0123] Optionally, the current exposure risk is not just a single gas monitoring, but a risk assessment of four gases working together. Although each gas is under a blue alert, the risk of multiple gases combined increases significantly, and the alert level is automatically raised to ensure personnel safety in multi-gas joint exposure scenarios.

[0124] For example, on a certain day, multiple gas anomalies were detected simultaneously in a certain area at -300m: CO concentration 45ppm (blue alert level), H2S concentration 12ppm (blue alert level), NO2 concentration 3ppm (blue alert level), and SO2 concentration 8ppm (blue alert level).

[0125] =45 / 24×1.2+12 / 6.6×1.5+3 / 2.5×1.3+8 / 5×1.1=8.30. Thus, the risk of multiple gases overlapping significantly increases. Although each individual gas is under a blue alert, the system automatically upgraded the alert level to a yellow alert. The six workers in the area received a warning of "Multiple gas anomalies, evacuation recommended" and evacuated in an orderly manner.

[0126] S24 compares the comprehensive risk value with the regional early warning threshold to determine the gas anomaly early warning result for each risk area.

[0127] In one implementation, as shown in formula (4), the regional early warning threshold for each risk area is determined based on the risk attribute parameters corresponding to each risk area and the preset global benchmark threshold.

[0128] Based on the regional early warning thresholds, a first, second, third, and fourth early warning thresholds are determined. Specifically, these include the following five scenarios.

[0129] Specifically, based on the regional early warning threshold, 0.5 times, 1 time, 1.5 times, and 2 times the regional early warning threshold are respectively determined as the first early warning threshold, the second early warning threshold, the third early warning threshold, and the fourth early warning threshold.

[0130] First, if the overall risk value is detected to be less than the first warning threshold, the abnormal warning result is determined to be that no warning is triggered. This is specifically represented by the following formula (12).

[0131] (12).

[0132] in, This is the overall risk value; This is the first warning threshold.

[0133] Secondly, if the overall risk value is detected to be greater than or equal to the first warning threshold and less than the second warning threshold, the abnormal warning result is determined to trigger a blue warning. The following formula (13) specifically represents this.

[0134] (13).

[0135] in, This is the overall risk value; The first warning threshold; This is the second warning threshold.

[0136] Third, if the detected comprehensive risk value is greater than or equal to the second warning threshold and less than the third warning threshold, the abnormal warning result is determined to trigger a yellow warning. The following formula (14) specifically represents this.

[0137] (14).

[0138] in, This is the overall risk value; This is the second warning threshold; This is the third warning threshold.

[0139] Fourth, if the overall risk value is detected to be greater than or equal to the third warning threshold and less than the fourth warning threshold, the abnormal warning result is determined to trigger an orange warning.

[0140] (15).

[0141] in, This is the overall risk value; This is the third warning threshold; This is the fourth warning threshold.

[0142] Fifth, if the overall risk value is detected to be greater than or equal to the fourth warning threshold, the abnormal warning result is determined to trigger a red warning.

[0143] (16).

[0144] in, This is the overall risk value; This is the fourth warning threshold.

[0145] Furthermore, different levels of alarms are triggered based on the different levels of warning results.

[0146] Upon detecting a blue alert, the system alerts the ground control terminal to each risk area corresponding to the blue alert.

[0147] If a yellow alert is detected, an alarm will be sent to the on-site terminals of each risk area corresponding to the yellow alert, and an alarm will also be sent to the ground control terminal.

[0148] Upon detecting an orange alert, an alarm is sent to the personnel terminals in each risk area corresponding to the orange alert, and an alarm is also sent to the ground control terminal.

[0149] Upon detecting a red alert, an alarm is sent to the terminals of personnel in each risk area corresponding to the red alert, and an alarm is also sent to the ground control terminal.

[0150] Optionally, the warning level can be dynamically adjusted based on the evolving trend of the risk.

[0151] The abnormal warning results are adjusted based on the concentration acceleration. Specifically, when the concentration acceleration is greater than zero, the abnormal warning result is upgraded in advance. When the concentration acceleration is less than or equal to zero and persists, the abnormal warning result is downgraded.

[0152] Optionally, based on the location information of the downhole workers and the gas anomaly warning results for each risk area, a low-risk evacuation route for the downhole workers can be determined.

[0153] Optionally, the early warning response time, the evacuation efficiency of downhole workers, and the concentration change characteristics of various gases in each risk area can be monitored in real time, and the comprehensive risk value can be adjusted using a Bayesian optimization algorithm.

[0154] Record the response time, evacuation efficiency, and concentration change curve for each warning; use Bayesian optimization to continuously optimize parameters, including toxicity weight, risk weight, and risk threshold adjustment factor.

[0155] Optionally, if the overall risk value of each risk area corresponding to a blue, yellow, orange, or red alert is detected to be less than the first alert threshold, the alarm will be automatically deactivated.

[0156] Understandably, the system continuously monitors whether the gas concentration has steadily decreased to a safe threshold. If so, the alarm for the corresponding risk area is automatically deactivated, completing the closed loop. If not, monitoring continues without deactivating the alarm.

[0157] For example, the above gas monitoring and early warning methods will be explained in detail using a typical underground metal mine in China as an example.

[0158] This mine is a large underground metal mine with an annual output of 2 million tons. The underground operating area includes three intermediate sections: -150m, -200m, and -300m. The main mining method is caving. The main toxic and harmful gases underground include CO (generated by explosion), H2S (generated by ore oxidation), NO2 (generated by explosion), and SO2 (generated by ore oxidation).

[0159] First, the deployment was determined. Electrochemical sensors were deployed in a grid pattern at key locations such as the mining faces, transport roadways, and edges of goaf areas. A total of 120 sensor nodes were deployed, with CO ranging from 0 to 500 ppm, H2S from 0 to 50 ppm, NO2 from 0 to 20 ppm, and SO2 from 0 to 30 ppm. 85 UWB positioning base stations were deployed throughout the mine to achieve full coverage positioning for underground personnel. Four TDLAS sensors (detection limit ppb) were deployed in high-risk areas such as the mining faces. Simultaneously, all data was uploaded to the ground-based central station edge computing server via industrial Ethernet.

[0160] Based on this, gas trend characteristics are extracted and early warning is provided. On a certain day, the system monitored the CO concentration changes at a mining face in the -200m section: 15ppm at t=0, 20ppm at t=10s, and 28ppm at t=20s. Based on this, the following determinations are made: It is 0.5 ppm / s. It is 0.8 ppm / s. It is 0.03 ppm / s². A value greater than 0 indicates that the concentration is rising rapidly.

[0161] Although the current concentration of 28 ppm only slightly exceeds the safe threshold of 24 ppm (blue alert), the system identified a "rapid deterioration" trend and upgraded the risk level to a yellow alert, triggering an early alarm at the on-site terminal in the area. Furthermore, using a multivariate time-series prediction model (combined with a wind speed of 0.5 m / s and a temperature of 28°C), it predicted that the CO concentration would reach 55 ppm within the next 5 minutes, promptly notifying the four workers in the area to evacuate.

[0162] Furthermore, gas diffusion direction sensing and early warning were implemented. Simultaneously, a continuous increase in CO concentration was detected at the mining face (45 ppm), and the CO concentration in the adjacent transport roadway increased from 8 ppm to 15 ppm. The diffusion direction vector was calculated. =(15-45) / 20=-1.5ppm / m, determine A negative value indicates that the gas is spreading towards the transport roadway. Based on the concentration propagation delay time, the diffusion velocity is estimated to be approximately 0.15 m / s, and it is expected to reach the personnel location in the transport roadway in about 80 seconds. The system immediately sends a warning to the three workers in the transport roadway: "Attention! CO is spreading from the -200m mid-section mining face to your area, expected to arrive in 80 seconds. Please evacuate upwind (east side)." The three workers safely evacuated to the fresh airflow to the east within 60 seconds of receiving the warning.

[0163] Secondly, risk assessment should be conducted based on the approaching movement of personnel, and low-risk evacuation routes should be planned.

[0164] An inspection worker carrying a UWB tag was moving from the transport roadway towards the mining face. The system continuously transmitted his coordinates: t=0 (105, 52, -200), t=5s (100, 50, -200), and t=10s (95, 47, -200). It was determined that the worker was moving towards the mining face, where the CO concentration was 120 ppm (orange alert). His movement speed was approximately 1.12 m / s, and his estimated arrival time was about 27 seconds. It was determined that the worker was rapidly approaching a high-risk area, and the risk level was significantly increasing. An advance warning was sent to the worker's terminal: "CO concentration 25 meters ahead is severely exceeded (120 ppm). Please stop immediately! It is recommended to detour via the north ventilation roadway." The worker followed the guidance and changed his route, avoiding entering the high-risk area.

[0165] Finally, the effectiveness of the early warning closed loop and long-term operation is demonstrated.

[0166] After 12 months of operation using this method at the mine, the statistical results are as follows: average early warning time: 42 seconds (approximately 35 seconds earlier than the traditional fixed threshold); false alarm rate decreased by 47% (from an average of 23 times per month to 12 times); average personnel response time: 9 seconds (from the issuance of the warning to the start of action); successful prevention of personnel from entering high-risk areas: 17 times; accurate identification rate of multi-gas collaborative risks: 94%. Furthermore, through Bayesian optimization, the CO toxicity weight was adjusted from 1.2 to 1.35, the H2S weight from 1.5 to 1.6, and the measurement cycle of the regional ventilation coefficient K_v was shortened from 10 minutes to 5 minutes. The early warning accuracy improved from 85% initially to 92%.

[0167] Therefore, this invention is specifically designed for underground metal and non-metal mines. Taking into full account the complex underground spatial structure, varying ventilation conditions, and diverse types of toxic and harmful gases (CO, H2S, NO2, SO2) in such mines, a differentiated monitoring and early warning strategy is implemented based on the differences in the physicochemical properties of different gases. An electrochemical sensor and a TDLAS sensor are used in synergistic detection of four toxic and harmful gases (CO, H2S, NO2, SO2), overcoming the vulnerability of single sensors to interference under extreme underground conditions. The gas concentration change rate, acceleration, and diffusion direction vectors are extracted to achieve dynamic trend perception, providing early warning before gas concentrations exceed limits. UWB technology is used for continuous real-time location tracking of personnel and perception of their movement trends. A unified data interface enables real-time sharing of gas monitoring and personnel location data. Inverse distance weighted interpolation is used to calculate personnel location concentration, achieving continuous, all-time, and all-domain personnel location and movement trend perception. Finally, a three-dimensional risk matrix is ​​constructed, triggering tiered early warnings based on regional adaptive dynamic thresholds, and achieving closed-loop optimization of the early warning system. In this way, early warnings can be issued before the gas concentration exceeds the standard, effectively improving the intelligence level and accuracy of early warning for toxic and harmful gases in underground metal and non-metal mines.

[0168] To achieve the above functions, the gas monitoring and early warning device combined with personnel positioning includes corresponding hardware structures and / or software modules for performing each function. Those skilled in the art will readily recognize that, based on the algorithmic steps of the examples described in conjunction with the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0169] This disclosure also provides an embodiment such as Figure 4 The gas monitoring and early warning device shown includes: a gas data processing unit 301, a risk level identification unit 302, a risk assessment unit 303, and a risk early warning unit 304.

[0170] The gas data processing unit 301 is configured to determine the gas trend characteristics of multiple gases in each risk area of ​​the mine based on the time series data of the concentration of multiple gases in each risk area; the multiple gases include carbon monoxide, hydrogen sulfide, nitrogen dioxide and sulfur dioxide.

[0171] The risk level identification unit 302 is configured to determine the target risk level and regional early warning threshold of each risk area based on the risk attribute parameters corresponding to each risk area.

[0172] Risk assessment unit 303 is configured to determine the comprehensive risk value of each risk area based on the target risk level of each risk area, the gas trend characteristics of multiple gases, and the location information of downhole workers.

[0173] Risk warning unit 304 is configured to compare the comprehensive risk value with the preset warning threshold to determine the gas anomaly warning result.

[0174] As one implementation method, the gas data processing unit 301 is specifically configured such that, before determining the target risk level and regional early warning threshold of each risk area based on the risk attribute parameters corresponding to each risk area, the method includes: dividing the underground space of the mine into multiple risk areas according to the actual working area of ​​the mine; the actual working area includes roadways, mining faces and goaf areas; and determining the risk attribute parameters of each risk area based on the ventilation design air volume, space volume and historical gas concentration distribution data of each risk area.

[0175] As one implementation method, risk attribute parameters include regional ventilation coefficient, volume coefficient, and risk warning adjustment factor.

[0176] The risk level identification unit 302 is specifically configured to determine the target risk level of each risk area based on the risk attribute parameters corresponding to each risk area. This includes: comparing the measured concentrations of various gases in each risk area with preset risk level thresholds to determine the initial risk level of each risk area; the preset risk level thresholds include a first risk threshold, a second risk threshold, a third risk threshold, and a fourth risk threshold; and correcting the initial risk level based on the risk attribute parameters corresponding to each risk area to obtain the target risk level of each risk area. Specifically, if the measured concentration is within the range of the first risk threshold, the initial risk level is determined to be a blue warning level; if the measured concentration is within the range of the second risk threshold, the initial risk level is determined to be a yellow warning level; if the measured concentration is within the range of the third risk threshold, the initial risk level is determined to be an orange warning level; and if the measured concentration is within the range of the fourth risk threshold, the initial risk level is determined to be an orange warning level.

[0177] As one implementation method, gas trend characteristics include concentration change rate, concentration acceleration, and diffusion direction vector.

[0178] The risk assessment unit 303 is specifically configured to determine the comprehensive risk value of each risk area based on the target risk level of each risk area, the gas trend characteristics of multiple gases, and the location information of downhole workers. This includes: determining the location information of downhole workers in each risk area; the location information includes the movement direction vector, movement speed, and estimated time to reach the high-risk area; the high-risk area is the risk area corresponding to the target risk level of yellow, orange, or red warning level; determining the current exposure risk, trend evolution risk, movement approach risk, and regional attribute risk correction values ​​based on the gas trend characteristics of multiple gases and the location information of downhole workers; and determining the comprehensive risk value based on the weighted sum of the current exposure risk, trend evolution risk, movement approach risk, and regional attribute risk correction values.

[0179] As one implementation method, the risk warning unit 304 is specifically configured to: determine the regional warning threshold for each risk area based on the risk attribute parameters corresponding to each risk area; compare the comprehensive risk value with the regional warning threshold to determine the gas anomaly warning result for each risk area, including: determining the regional warning threshold for each risk area based on the risk attribute parameters corresponding to each risk area and a preset global benchmark threshold; determining a first warning threshold, a second warning threshold, a third warning threshold, and a fourth warning threshold based on the regional warning threshold; if the comprehensive risk value is detected to be less than the first warning threshold, determining the anomaly warning result as not triggering a warning; if the comprehensive risk value is detected to be greater than or equal to the first warning threshold and less than the second warning threshold, determining the gas anomaly warning result as not triggering a warning. If an abnormal warning result is determined to trigger a blue warning, and the ground control terminal is notified of each risk area corresponding to the blue warning; if the comprehensive risk value is detected to be greater than or equal to the second warning threshold and less than the third warning threshold, the abnormal warning result is determined to trigger a yellow warning; and an alarm is sent to the field terminal in each risk area corresponding to the yellow warning; if the comprehensive risk value is detected to be greater than or equal to the third warning threshold and less than the fourth warning threshold, the abnormal warning result is determined to trigger an orange warning; and an alarm is sent to the personnel terminal in each risk area corresponding to the orange warning; if the comprehensive risk value is detected to be greater than or equal to the fourth warning threshold, the abnormal warning result is determined to trigger a red warning; and an alarm is sent to the personnel terminal in each risk area corresponding to the red warning.

[0180] As one implementation method, the risk warning unit 304 is specifically configured to determine the low-risk evacuation route for the downhole workers based on the location information of the downhole workers and the gas anomaly warning results for each risk area.

[0181] As one implementation method, the risk warning unit 304 is specifically configured to monitor the warning response time, the evacuation efficiency of downhole workers, and the concentration change characteristics of multiple gases in each risk area in real time, and adjust the comprehensive risk value using a Bayesian optimization algorithm; and automatically deactivate the alarm when the comprehensive risk value of each risk area corresponding to the triggering of a blue, yellow, orange, or red warning is less than the first warning threshold.

[0182] As one implementation method, the risk level identification unit 302 is specifically configured to predict the gas concentration and diffusion direction of each risk area based on the environmental factors and gas trend characteristics of each risk area, thereby obtaining the predicted gas concentration value of each risk area; the environmental factors include wind speed, temperature, humidity and production operation status; compare the predicted gas concentration value with the preset risk level threshold to determine the target risk level of each risk area in the future preset time domain; and trigger the field terminal of each risk area to issue an alarm in advance according to the target risk level.

[0183] Regarding the apparatus in the above embodiments, the specific manner in which each unit module performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0184] Figure 5 This is a schematic diagram of a gas monitoring and early warning device that combines personnel positioning, as provided in this application. Figure 5 The gas monitoring and early warning device 50, which combines personnel positioning, includes: a first processor 501, a communication bus 502, a memory 503, a communication interface 504, an output device 505, an input device 506, and a second processor 507.

[0185] The gas monitoring and early warning device 50, which incorporates personnel location tracking, may include at least one first processor 501 and a memory 503 for storing processor-executable instructions. The first processor 501 is configured to execute the instructions in the memory 503 to implement the gas monitoring and early warning method incorporating personnel location tracking as described in the following embodiments.

[0186] In addition, the gas monitoring and early warning device 50 that combines personnel positioning may also include a communication bus 502, at least one communication interface 504, an input device 506, and an output device 505.

[0187] The first processor 501 may be a processor (central processing unit, CPU), a microprocessor unit, an ASIC, or one or more integrated circuits for controlling the execution of programs according to the present application.

[0188] The communication bus 502 may include a path for transmitting information between the aforementioned components.

[0189] Communication interface 504 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0190] Input device 506 is used to receive input signals and output device 505 is used to output signals.

[0191] Memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed discs, laser discs, optical discs, digital universal discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory may exist independently and be connected to the processing unit via a bus. Memory may also be integrated with the processing unit.

[0192] The memory 503 stores instructions for executing the scheme of this application, and the execution is controlled by the first processor 501. The first processor 501 executes the instructions stored in the memory 503 to realize the functions of the method of this application.

[0193] In a specific implementation, as one example, the first processor 501 may include one or more CPUs, for example... Figure 5 CPU0 and CPU1 in the CPU.

[0194] In a specific implementation, as one example, the gas monitoring and early warning device 50 that combines personnel positioning may include multiple processors, such as... Figure 5 The first processor 501 and the second processor 507 are described. Each of these processors can be a single-core processor or a multi-core processor. A processor here can refer to one or more devices, circuits, and / or processing cores used to process data (such as computer program instructions).

[0195] This gas monitoring and early warning device, which combines personnel location tracking, such as Figure 5 The diagram shows a first processor 501 and a memory 503 for storing executable instructions of the first processor 501. The first processor 501 is configured to execute the executable instructions to implement a gas monitoring and early warning method combined with personnel positioning, as described in any of the possible embodiments above. Since the same technical effects can be achieved, further details are omitted here to avoid repetition.

[0196] This application also provides a computer-readable storage medium that, when the instructions in the computer-readable storage medium are executed by the processor of a gas monitoring and early warning device combined with personnel positioning, enables the gas monitoring and early warning device combined with personnel positioning to perform the gas monitoring and early warning method combined with personnel positioning as described in any of the above possible embodiments. And it can achieve the same technical effect; to avoid repetition, it will not be described again here.

[0197] This application also provides a computer program product, including a computer program or instructions, which are executed by a processor as described in any of the possible embodiments above, for a gas monitoring and early warning method combined with personnel positioning. It achieves the same technical effects, and to avoid repetition, will not be described again here.

[0198] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0199] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A gas monitoring and early warning method combining personnel positioning, characterized in that, The method includes: Based on the time-series concentration data of multiple gases in each risk zone of the mine, the gas trend characteristics of the multiple gases in each risk zone are determined; Based on the risk attribute parameters corresponding to each risk area, determine the target risk level and regional early warning threshold for each risk area; Based on the target risk level of each risk area, the gas trend characteristics of the various gases, and the location information of downhole workers, the comprehensive risk value of each risk area is determined. The comprehensive risk value is compared with the regional early warning threshold to determine the gas anomaly early warning result for each risk area.

2. The gas monitoring and early warning method combined with personnel positioning according to claim 1, characterized in that, Before determining the target risk level and regional early warning threshold for each risk area based on the risk attribute parameters corresponding to each risk area, the method includes: Based on the actual working areas underground, the underground space of the mine is divided into multiple risk zones; the actual working areas include roadways, mining faces, and goaf areas. Based on the ventilation design air volume, space volume, and historical gas concentration distribution data of each risk area, the risk attribute parameters of each risk area are determined.

3. The gas monitoring and early warning method combined with personnel positioning according to claim 2, characterized in that, The risk attribute parameters include the regional ventilation coefficient, volume coefficient, and risk warning adjustment factor; The step of determining the target risk level for each risk area based on the risk attribute parameters corresponding to each risk area includes: The measured concentrations of various gases in each risk area are compared with preset risk level thresholds to determine the initial risk level of each risk area; the preset risk level thresholds include a first risk threshold, a second risk threshold, a third risk threshold, and a fourth risk threshold. Based on the risk attribute parameters corresponding to each risk area, the initial risk level is corrected to obtain the target risk level for each risk area; Specifically, if the measured concentration value is within the range of the first risk threshold, the initial risk level is determined to be a blue warning level; if the measured concentration value is within the range of the second risk threshold, the initial risk level is determined to be a yellow warning level; if the measured concentration value is within the range of the third risk threshold, the initial risk level is determined to be an orange warning level; and if the measured concentration value is within the range of the fourth risk threshold, the initial risk level is determined to be an orange warning level.

4. The gas monitoring and early warning method combined with personnel positioning according to claim 3, characterized in that, The gas trend characteristics include the concentration change rate, concentration acceleration, and diffusion direction vector; The determination of the comprehensive risk value for each risk area based on the target risk level of each risk area, the gas trend characteristics of the various gases, and the location information of downhole workers includes: The location information of the downhole workers in each risk area is determined; the location information includes the movement direction vector, movement speed, and estimated time to reach the high-risk area; the high-risk area represents the risk area corresponding to the yellow warning level, the orange warning level, or the red warning level of the target risk level; Based on the gas trend characteristics of the various gases and the location information of the downhole workers, the current exposure risk, trend evolution risk, movement approach risk, and regional attribute risk correction values ​​are determined. The comprehensive risk value is determined by a weighted sum of the current exposure risk, the trend evolution risk, the movement approach risk, and the regional attribute risk correction value.

5. The gas monitoring and early warning method combined with personnel positioning according to claim 4, characterized in that, The regional early warning threshold for each risk area is determined based on the risk attribute parameters corresponding to each risk area. The comprehensive risk value is compared with the regional early warning threshold to determine the gas anomaly early warning result for each risk area, including: Based on the risk attribute parameters corresponding to each risk area and the preset global benchmark threshold, the regional early warning threshold for each risk area is determined; Based on the aforementioned regional early warning thresholds, a first early warning threshold, a second early warning threshold, a third early warning threshold, and a fourth early warning threshold are determined; If the overall risk value is detected to be less than the first warning threshold, the abnormal warning result is determined to be no warning triggered. If the overall risk value is detected to be greater than or equal to the first warning threshold and less than the second warning threshold, the abnormal warning result is determined to trigger a blue warning; and each risk area corresponding to the blue warning is notified to the ground control terminal. If the overall risk value is detected to be greater than or equal to the second warning threshold and less than the third warning threshold, the abnormal warning result is determined to trigger a yellow warning; and an alarm is sent to the field terminal of each risk area corresponding to the yellow warning. If the overall risk value is detected to be greater than or equal to the third warning threshold and less than the fourth warning threshold, the abnormal warning result is determined to trigger an orange warning; and an alarm is sent to the personnel terminals in each risk area corresponding to the orange warning. If the overall risk value is detected to be greater than or equal to the fourth warning threshold, the abnormal warning result is determined to trigger a red warning; and an alarm is sent to the personnel terminals located in each risk area corresponding to the red warning.

6. The gas monitoring and early warning method combined with personnel positioning according to claim 5, characterized in that, The method further includes: Based on the location information provided by the downhole workers and the gas anomaly warning results for each risk area, a low-risk evacuation route for the downhole workers is determined.

7. The gas monitoring and early warning method combining personnel positioning according to any one of claims 1 to 6, characterized in that, The method further includes: The system monitors the early warning response time, the evacuation efficiency of downhole workers, and the concentration change characteristics of the various gases in each risk area in real time, and uses a Bayesian optimization algorithm to adjust the comprehensive risk value. If the overall risk value of each risk area corresponding to the blue, yellow, orange, or red alert is less than the first alert threshold, the alarm will be automatically deactivated.

8. The gas monitoring and early warning method combined with personnel positioning according to claim 3, characterized in that, The method further includes: Based on the environmental factors and gas trend characteristics of each risk area, the gas concentration and diffusion direction of each risk area are predicted to obtain the predicted gas concentration value for each risk area; the environmental factors include wind speed, temperature, humidity, and production operation status; The predicted gas concentration is compared with the preset risk level threshold to determine the target risk level of each risk area in the future preset time domain; Based on the target risk level, the on-site terminals in each risk area are triggered to issue an alarm in advance.

9. A gas monitoring and early warning device combined with personnel positioning, characterized in that, The device includes: The gas data processing unit is configured to determine the gas trend characteristics of the multiple gases in each risk zone of the mine based on the time-series concentration data of multiple gases in each risk zone; the multiple gases include carbon monoxide, hydrogen sulfide, nitrogen dioxide, and sulfur dioxide; The risk level identification unit is configured to determine the target risk level and regional early warning threshold for each risk area based on the risk attribute parameters corresponding to each risk area. The risk assessment unit is configured to determine the comprehensive risk value of each risk area based on the target risk level of each risk area, the gas trend characteristics of the multiple gases, and the location information of the downhole workers. The risk warning unit is configured to compare the comprehensive risk value with a preset warning threshold to determine the gas anomaly warning result.

10. A gas monitoring and early warning system incorporating personnel positioning, characterized in that, The system is configured to perform a gas monitoring and early warning method incorporating personnel location as described in any one of claims 1-8.

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