A method and system for collecting and analyzing mine risk monitoring data based on the Internet of Things

Abstract

The present invention belongs to the technical field of mine risk monitoring and analysis, and specifically discloses a method and system for collecting and analyzing mine risk monitoring data based on the Internet of Things, including: analyzing the gas flow blockage rate of each ventilation roadway layout path in each construction period stage to determine the air environment safety situation inside the mine structure and locate specific abnormal areas. At the same time, based on the correlation between the ore body geological data corresponding to the mine construction wall structure and the coercion of the internal gas composition, the dynamic operation data of the ventilation device in the subsequent project is predicted and regulated in advance; by monitoring the ore body data and geological data of the mine construction wall structure, analyzing the data uncertainty level of the mine construction wall structure, and giving early warnings in a timely manner; by analyzing the change law of the ore body uncertainty data, identifying the correlation between the ore body geological data corresponding to the mine construction wall structure and the coercion of the internal gas composition, and accordingly regulating the subsequent project application data.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine risk monitoring and analysis, and relates to a method and system for collecting and analyzing mine risk monitoring data based on the Internet of Things. Background Art

[0002] Mine operations have always been a key area for safety management and environmental protection due to their complex geological conditions, high-intensity mining activities, and potential safety and environmental risks. With the development of information technology, the collection and analysis of mine risk monitoring data have become a key means to improve mine safety management levels, prevent disaster accidents, and protect the ecological environment.

[0003] Currently, the existing technical means have the following deficiencies in mine risk monitoring: 1. When analyzing mine risks, the existing technology often makes relatively rough optimizations and adjustments to the ventilation network, and cannot specifically solve the problem of poor local ventilation, which affects the ventilation efficiency and the accuracy of air quality control. And often, the operation adjustment of the ventilation device is carried out only after an accident occurs, which belongs to post-event response rather than pre-event prevention, increasing potential safety hazards and economic losses.

[0004] 2. Since the geological conditions of the ore body will change dynamically during the construction process, the pre-collected data may quickly become inaccurate, resulting in the invalidation of decisions made based on these data. The existing monitoring system is unable to handle these real-time changing data effectively and is difficult to update risk assessments and take corresponding measures in a timely manner.

[0005] 3. The existing technology lacks a systematic method to integrate the data law of unstable changes in the ore body and the regulation of engineering application data, making it difficult to achieve rapid response and flexible adjustment in actual operations, which affects the safety and efficiency of the mine. Summary of the Invention

[0006] In view of this, to solve the problems raised in the above background art, a method and system for collecting and analyzing mine risk monitoring data based on the Internet of Things are proposed.

[0007] The object of the present invention can be achieved by the following technical solutions: The present invention provides a method for collecting and analyzing mine risk monitoring data based on the Internet of Things, and the method includes: Step 1: Data collection: Before the construction of the mine construction wall structure, collect its structural characteristics, construct a roadway layout map of the ventilation device, extract the layout paths of each ventilation roadway from it, numbered 1, 2,... j..., C, and collect various ore body data, geological data, and air environment data of the mine construction wall structure. Each ore body data includes the positions of the concave and convex points along the wall contour and their volume ratios, the positions and opening degrees of each rock crack, and the wall settlement amplitude. Each geological data includes the water content characteristics and the groundwater flow rate. Each air environment data includes the wind energy density and the internal dust content.

[0008] Tep2. Environmental data analysis: Extract each construction period stage of the mine construction, and analyze the internal gas composition stress index ψ of the mine construction wall structure in each construction period stage r , where r is the number of the construction period stage, r = 1, 2,..., A.

[0009] Tep3. Ore body geological data analysis: Based on the structure data of the mine construction wall structure, the structure data includes each ore body data and each geological data, analyze the main constraint parameters and auxiliary constraint parameters of each ventilation roadway layout path in the mine construction wall structure in each construction period stage.

[0010] Tep4. Multi-scale data fusion: Fusion of the main constraint parameters and auxiliary constraint parameters, determine the data uncertainty level of the mine construction wall structure, and determine the change law of the ore body uncertainty data.

[0011] Tep5. Risk prediction and data regulation: Analyze the correlation coefficient between the structure data corresponding to each ventilation roadway layout path and the stress of its internal gas composition, and accordingly regulate the application data of the subsequent construction period of the mine construction.

[0012] On the other hand, a mine risk monitoring data acquisition and analysis system based on the Internet of Things provided by the present invention includes: a data acquisition module: used to collect the structural characteristics of the mine construction wall structure in the early stage of construction, construct a roadway layout diagram of the ventilation device, extract each ventilation roadway layout path from it, numbered 1, 2,... j..., C, and collect each ore body data, each geological data and each wind environment data of the mine construction wall structure.

[0013] An environmental data analysis module: used to extract each construction period stage of the mine construction, and analyze the internal gas composition stress index ψ of the mine construction wall structure in each construction period stage r , where r is the number of the construction period stage, r = 1, 2,..., A.

[0014] An ore body geological data analysis module: used to analyze the main constraint parameters and auxiliary constraint parameters of each ventilation roadway layout path in the mine construction wall structure in each construction period stage based on the structure data of the mine construction wall structure, and the structure data includes each ore body data and each geological data.

[0015] A multi-scale data fusion module: used to fuse the main constraint parameters and auxiliary constraint parameters, determine the data uncertainty level of the mine construction wall structure, and determine the change law of the ore body uncertainty data.

[0016] A risk prediction and data regulation module: used to analyze the correlation coefficient between the structure data corresponding to each ventilation roadway layout path and the stress of its internal gas composition, and accordingly regulate the application data of the subsequent construction period of the mine construction.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: By analyzing the gas flow blockage rate of the layout paths of each ventilation roadway in each construction period, the present invention determines the safety of the air environment inside the mine structure and locates the specific abnormal areas, which helps to adjust the ventilation network design targeted, can increase ventilation facilities or change the ventilation flow direction, improve ventilation efficiency, and ensure that the air quality in the roadway meets safety standards. At the same time, based on the correlation between the ore body geological data corresponding to the mine construction wall structure and the coercion of its internal gas composition, the dynamic operation data of the ventilation device in subsequent projects are predicted and regulated in advance, which can significantly improve the safety of the operation environment and reduce the risks brought by the coercion of the gas composition.

[0018] In addition, by monitoring the ore body data and geological data of the mine construction wall structure, the present invention analyzes the data uncertainty level of the mine construction wall structure. When the data fluctuation amplitude is too large, indicating that the surface data uncertainty level exceeds the expectation, timely alarms can prompt immediate measures to avoid the occurrence of safety accidents.

[0019] At the same time, by analyzing the change law of the ore body uncertainty data, the present invention identifies the strength degree of the correlation between the ore body geological data corresponding to the mine construction wall structure and the coercion of its internal gas composition, and accordingly regulates the application data of subsequent projects, establishes a systematic engineering risk warning framework, enables the project to flexibly respond to the specific needs of different applications, improves the stability and success rate of the overall project, and further improves the management efficiency and response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0021] Figure 1 It is a schematic flow chart of the implementation steps of the method of the present invention.

[0022] Figure 2 It is a schematic diagram of the system module structure of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0024] Please refer to Figure 1 As shown, the present invention provides a method for collecting and analyzing mine risk monitoring data based on the Internet of Things. The method includes: Step 1, data collection: Before the construction of the mine construction wall structure, collect its structural characteristics, including the roadway layout grid path of the ventilation device, various geological data of each ventilation roadway layout path, construct a roadway layout map of the ventilation device, extract each ventilation roadway layout path from it, numbered 1, 2,... j..., C, collect various ore body data, various geological data and various wind environment data of the mine construction wall structure. Each ore body data includes the position of the concave and convex points along the wall contour and its volume ratio, the position of each rock crack and its opening, and the wall settlement amplitude. Each geological data includes the water content characteristics and the groundwater flow rate. Each wind environment data includes the wind energy density and the internal dust content.

[0025] Step 2, environmental data analysis: Extract each construction period stage of the mine construction, and analyze the internal gas composition stress index ψ r of the mine construction wall structure in each construction period stage, where r is the number of the construction period stage, r = 1, 2,..., A.

[0026] In a preferred embodiment, the analysis of the internal gas composition stress index of the mine construction wall structure in each construction period stage includes: Extract the ventilation structures corresponding to each ventilation roadway layout path from the roadway layout map of the ventilation device, and then detect the wind energy density and the internal dust content β jr of each ventilation roadway layout path in each construction period stage.

[0027] The wind energy density refers to a comprehensive measurement index of wind speed and air volume; the internal dust content refers to the total content of dust and harmful gases in the air.

[0028] Taking the wind energy density and the internal dust content β′ j collected in the pre-construction period of each ventilation roadway layout path as the control index, compare and analyze the gas flow blockage rate of each ventilation roadway layout path in each construction period stage, and then determine the internal gas composition stress index of the mine construction wall structure in each construction period stage, where e is the natural constant.

[0029] Furthermore, compare the internal gas composition stress index of the layout position of each ventilation structure in the mine construction wall structure in each construction period stage with the preset internal gas composition stress index threshold. When the internal gas composition stress index of a certain ventilation structure layout position in a certain construction period stage exceeds the internal gas composition stress index threshold, give a warning prompt for the corresponding construction period stage of the layout position of this ventilation structure.

[0030] The present invention analyzes the gas flow blockage rate of each ventilation roadway layout path in each construction period stage to determine the air environment safety situation inside the mine structure, locate specific abnormal areas, which helps to adjust the ventilation network design targeted, increase ventilation facilities or change the ventilation flow direction, improve ventilation efficiency, and ensure that the air quality in the roadway meets safety standards.

[0031] Tep3. Ore body geological data analysis: Based on the structural data of the mine construction wall structure, the structural data includes various ore body data and various geological data, analyze the main constraint parameters and auxiliary constraint parameters of each ventilation roadway layout path in the mine construction wall structure in each construction period stage.

[0032] In a preferred embodiment, the process of analyzing the main constraint parameters of each ventilation roadway layout path in the mine construction wall structure in each construction period stage is as follows: Scan the mine construction wall structure through remote sensing technology, construct a three-dimensional model of the mine construction wall structure in each construction period stage, compare it with the control model collected in the early stage of construction of the mine construction wall structure, and extract the position and volume ratio of the concave and convex points of each wall edge contour, the position and opening degree of each rock crack, and the wall settlement amplitude H of each ventilation roadway layout path in the mine construction wall structure in each construction period stage jr .

[0033] The volume ratio refers to the ratio of the concave or convex volume at the position of the concave and convex points of the wall edge contour to the volume of the mine construction wall structure.

[0034] Integrate the volume ratios corresponding to the positions of the concave and convex points of each wall edge contour of each ventilation roadway layout path in the mine construction wall structure in each construction period stage to obtain the comprehensive concave and convex defect volume ratio κ of each ventilation roadway layout path in the mine construction wall structure in each construction period stage jr .

[0035] Integrate the opening degrees corresponding to the positions of each rock crack of each ventilation roadway layout path in the mine construction wall structure in each construction period stage to obtain the comprehensive opening degree op of the rock crack defects of each ventilation roadway layout path in the mine construction wall structure in each construction period stage jr .

[0036] Analyze the main constraint parameters of each ventilation roadway layout path in the mine construction wall structure in each construction period stage where h j is the corresponding constraint influence weight value of the unit settlement amplitude of the jth ventilation roadway layout path of the preset mine construction wall structure.

[0037] In a further preferred embodiment, the analysis process of the auxiliary constraint parameters is as follows: Extract various geological data D of the mine construction wall structure in each construction period stage through geological monitoring instruments ry, where y is the serial number of geological data, and y = 1, 2, …, n.

[0038] Ore grade monitoring instruments are arranged on the layout paths of each flow-through roadway in the wall structure during mine construction to monitor the distribution quantity of ores in different shapes and the distribution content of various ore shapes on the layout paths of each flow-through roadway. Based on this, the richness F of ore type distribution on the layout paths of each flow-through roadway in each construction period stage is determined. jr and the density J of ore content distribution. jr .

[0039] The richness of ore type distribution refers to the ratio between the distribution quantity of ores in different shapes and the reference quantity of the preset reference shape. Different ore shapes include massive, banded, disseminated, etc.

[0040] The density of ore content distribution refers to the ratio between the distribution content of various ore shapes and the reference distribution content of the preset corresponding shape.

[0041] Extract the geological data collected in the early stage of mine construction for the wall structure of the mine construction, denoted as D′. y , and analyze the auxiliary constraint parameters of each flow-through roadway layout path in the wall structure of the mine construction in each construction period stage. In the formula, ΔD y is the preset deviation floating value of the y-th geological data, F j ′, J′ j are respectively the richness of ore type distribution and the density of ore content distribution corresponding to the j-th flow-through roadway layout path collected in the early stage of mine construction for the wall structure of the mine construction, and R is a natural constant greater than 1.

[0042] Step 4, multi-scale data fusion: fuse the dominant constraint parameters and the auxiliary constraint parameters to determine the data uncertainty level of the wall structure of the mine construction and determine the variation law of the ore body uncertainty data.

[0043] In a preferred implementation manner, the determination of the data uncertainty level of the wall structure of the mine construction specifically includes: comparing the dominant constraint parameters corresponding to all adjacent construction period stages of each flow-through roadway layout path in the wall structure of the mine construction with each other, and calculating the average error value δ′ corresponding to the dominant constraint parameters of each flow-through roadway layout path in the wall structure of the mine construction by means of mean value. j_1 .

[0044] Select two median values corresponding to the auxiliary constraint parameters of each flow-through roadway layout path from the auxiliary constraint parameters of each flow-through roadway layout path in each construction period stage of the wall structure of the mine construction, and denote them as

[0045] The two dichotomous medians are specifically as follows: obtain the minimum value, median value, and maximum value in the auxiliary constraint parameters of each flow roadway layout path in each construction period stage, and then record the dichotomy value between the minimum value and the median value as one dichotomous median, and record the dichotomy value between the median value and the maximum value as the other dichotomous median.

[0046] Calculate the data error risk coefficient of the mine construction wall structure Compare it with the preset data error risk coefficient range corresponding to each data uncertainty level to determine the data uncertainty level of the mine construction wall structure. In the formula, Δδ1 and Δδ2 are respectively the set reference error values corresponding to the main constraint parameters and the set reference difference values of the two dichotomous medians corresponding to the auxiliary constraint parameters, and C is the number of flow roadway layout paths.

[0047] Furthermore, compare the data uncertainty level of the mine construction wall structure with the alarm response level. When the data uncertainty level of the mine construction wall structure exceeds the alarm response level, optimize the early warning of the data acquisition accuracy of the mine construction wall structure.

[0048] In addition, the present invention analyzes the data uncertainty level of the mine construction wall structure by monitoring the ore body data and geological data of the mine construction wall structure. When the data fluctuation amplitude is too large, it indicates that the data uncertainty level exceeds the expectation. Timely alarm can prompt immediate measures to avoid the occurrence of safety accidents.

[0049] In a further preferred implementation manner, the determination of the change law of the ore body uncertainty data is specifically as follows: dynamically fuse the three-dimensional models of the mine construction wall structure in each construction period stage through modeling software, and count the defect point information of each flow roadway layout path in the mine construction wall structure in each construction period stage. The defect point information includes the positions of the concave and convex points along the wall contour and their volume ratios, and the positions and opening degrees of each rock crack. Then import the defect point information of each flow roadway layout path in the mine construction wall structure in each construction period stage into the modeling software, and export the concentrated area of the volume of the concave and convex points along the wall contour and the concentrated area of the opening degree of the rock cracks in the mine construction wall structure.

[0050] Tep5, Risk Prediction and Data Regulation: Analyze the correlation coefficient between the structure data corresponding to each flow roadway layout path and the coercion of its internal gas composition, and accordingly regulate the application data in the subsequent construction period of the mine construction. The application data is the power operation data of the ventilation device or the acquisition data of the ore body geology.

[0051] In a preferred embodiment, the correlation coefficient between the corresponding structural data of each ventilation roadway layout path and the coercion of the internal gas composition is specifically as follows: Taking the central positions of the volume concentration regions of the concave and convex points along the wall contour and the crack opening concentration regions of the rock in the mine construction wall structure as reference points, these two reference points are respectively compared with each ventilation roadway layout path, and the shortest distances between these two reference points and each ventilation roadway layout path are extracted and denoted as L1 j , L2 j .

[0052] Extract the gas flow blockage rate bl of each ventilation roadway layout path in each construction period stage jr , and analyze the correlation coefficient between the corresponding structural data of each ventilation roadway layout path and the coercion of the internal gas composition where L 0 is the preset reference distance, bl j(r+1) is the gas flow blockage rate of the jth ventilation roadway layout path in the (r + 1)th construction period stage, bl 0 is the preset reference floating deviation value corresponding to the gas flow blockage rate of adjacent construction period stages, min(L1 j , L2 j ) is the minimum value of the nearest distance between the volume concentration region of the concave and convex points along the wall contour and the crack opening concentration region of the rock in the mine construction wall structure and the location of each ventilation roadway layout path, max[bl j(r+1) - bl jr is the maximum deviation value between the gas flow blockage rates of each ventilation roadway layout path in each construction period stage and its adjacent construction period stages, are respectively the preset first correlation weight and second correlation weight, q0 is the preset correlation difference rate between the gas flow blockage rate deviation rate and the nearest distance deviation rate, and exp() is the base of the natural logarithm.

[0053] In a further preferred embodiment, the application data for regulating the subsequent construction period of the mine construction includes: Summing the correlation coefficients between the corresponding structural data of each ventilation roadway layout path and the coercion of the internal gas composition to obtain the comprehensive correlation coefficient I′ between the ore body geological data corresponding to the mine construction wall structure construction and the coercion of the internal gas composition.

[0054] When I′ ≥ I 0 , it indicates that the correlation between the ore body geological data corresponding to the mine construction wall structure and the coercion of the internal gas composition is relatively large. I 0 is the preset comprehensive correlation coefficient threshold, then extract the power operation data U of the ventilation device 0 , the operation data includes fan speed, air pressure, etc., and extract the coercion index ψ of the internal gas composition of the mine construction wall structure in each construction period stager , thereby regulating the power operation data of the ventilation device A is the number of construction period stages.

[0055] In a further preferred embodiment, the application data for regulating the subsequent construction period of the mine construction further includes: when I′ < I 0 , it indicates that the correlation between the wall structure of the mine construction corresponding to the ore body geological data and its internal gas composition is less coercive. Then, extract the data uncertainty level of the wall structure of the mine construction, and determine the corresponding acquisition accuracy of the ore body geological acquisition data for the subsequent construction period.

[0056] Specifically: match the data uncertainty level of the wall structure of the mine construction with the data acquisition accuracy at each level to obtain the corresponding acquisition accuracy of the ore body geological acquisition data for the subsequent construction period. The data acquisition accuracy refers to the frequency period of data acquisition. As the engineering progress accumulates, the data uncertainty in the later stage will be more complex, so more accurate data extraction is required.

[0057] At the same time, the present invention analyzes the variation law of the ore body uncertainty data to identify the strength of the correlation between the wall structure of the mine construction corresponding to the ore body geological data and its internal gas composition coercion, and accordingly regulates the subsequent engineering application data. For example, when the correlation is large, take the power operation data of the ventilation device as the main focus data and perform power regulation on it, which can significantly improve the safety of the working environment and reduce the risks brought by the coercion of the gas composition; when the correlation is small, take the acquisition data of the ore body geology in the subsequent construction period as the main focus data and regulate its acquisition accuracy, which helps to plan the mining more accurately and avoid structural safety problems caused by inaccurate data. Enable the project to flexibly respond to the specific requirements of different applications, improve the stability and success rate of the overall project, and enhance the management efficiency and response speed.

[0058] Please refer to Figure 2 As shown, an Internet of Things-based mine risk monitoring data acquisition and analysis system provided by another aspect of the present invention includes: a data acquisition module, an environmental data analysis module, an ore body geological data analysis module, a multi-scale data fusion module, and a risk prediction and data regulation module.

[0059] The data acquisition module is connected to the environmental data analysis module, the environmental data analysis module is connected to the ore body geological data analysis module, the ore body geological data analysis module is connected to the multi-scale data fusion module, and the multi-scale data fusion module is connected to the risk prediction and data regulation module.

[0060] The data acquisition module is used to collect the structural characteristics of the mine construction wall structure in the early stage of construction, construct the roadway layout diagram of the ventilation device, extract the layout paths of each ventilation roadway therefrom, numbered 1, 2,... j..., C, and collect the ore body data, geological data and air boundary data of the mine construction wall structure.

[0061] The environmental data analysis module is used to extract each construction period stage of the mine construction and analyze the internal gas composition stress index ψ of the mine construction wall structure in each construction period stage r , where r is the number of the construction period stage, r = 1, 2,..., A.

[0062] The ore body and geological data analysis module is used to analyze the main constraint parameters and auxiliary constraint parameters of each ventilation roadway layout path in the mine construction wall structure based on the structural data of the mine construction wall structure, where the structural data includes each ore body data and geological data.

[0063] The multi-scale data fusion module is used to fuse the main constraint parameters and auxiliary constraint parameters, determine the data uncertainty level of the mine construction wall structure, and determine the variation law of the ore body uncertainty data.

[0064] The risk prediction and data regulation module is used to analyze the correlation coefficient between the structural data corresponding to each ventilation roadway layout path and the stress of its internal gas composition, and accordingly regulate the application data of the subsequent construction period of the mine construction.

[0065] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A mine risk monitoring data collection and analysis method based on the Internet of Things, characterized in that: The method comprises the following steps: Tep1, data collection: In the early stage of the construction of the mine wall structure, the structural characteristics are collected, and the tunnel layout diagram of the ventilation device is constructed, from which the layout paths of each flow tunnel are extracted and numbered. , collect the ore body data, geological data and wind environment data of the mine construction wall structure. The ore body data include the location of the concave and convex points along the wall contour and their volume proportion, the location of each rock crack and its opening, and the wall settlement amplitude. The geological data include water content characteristics and groundwater flow rate. The wind environment data include wind energy density and internal dust accumulation; Tep2, Environmental data analysis: Extract the various construction phases of the mine construction and analyze the internal gas composition threat indicators of the mine construction wall structure at each construction phase , is the number of the construction phase, ; Tep3, ore body geological data analysis: Based on the structural data of the mine construction wall structure, the structural data includes the data of each ore body and each geological data, and analyzes the dominant constraint parameters and auxiliary constraint parameters of each flow tunnel layout path in the mine construction wall structure at each construction stage; Tep4, multi-scale data fusion: integrate the dominant constraint parameters and auxiliary constraint parameters to determine the data uncertainty level of the mine construction wall structure and determine the change law of the ore body uncertainty data; Tep5, ventilation data operation control: Analyze the correlation coefficient between the structural data corresponding to the layout path of each flow tunnel and the coerciveness of the internal gas, and adjust the application data of the subsequent construction period of the mine construction accordingly; The analysis of the internal gas composition of the mine construction wall structure at each construction stage constitutes a coercive index, including: Extract the layout paths of ventilation structures corresponding to each flow tunnel, and then detect the wind energy density of each flow tunnel layout path at each construction stage And the amount of dust inside ; The wind energy density collected in the early stage of construction based on the layout path of each flow tunnel And the amount of dust inside As a control indicator, the gas flow blockage rate of each flow tunnel layout path at each construction stage is compared and analyzed. , and then determine the internal gas composition threat index of the mine construction wall structure at each construction stage , e is a natural constant; The process of analyzing the dominant constraint parameters of the layout paths of each flow tunnel in the mine construction wall structure at each construction stage is as follows: The mine construction wall structure is scanned by remote sensing technology, and a three-dimensional model of the mine construction wall structure at each construction stage is constructed. The model is compared with the control model collected in the early stage of the construction of the mine construction wall structure, and the location and volume proportion of each wall contour of each flow tunnel layout path in the mine construction wall structure at each construction stage, the location and opening of each rock crack, and the wall settlement amplitude are extracted. ; Obtain the comprehensive proportion of the concave and convex defect volumes of each flow tunnel layout path in the mine construction wall structure at each construction stage , Comprehensive opening of rock crack defects ; Analyze the dominant constraint parameters of each flow tunnel layout path in the mine construction wall structure at each construction stage ,in The preset mine construction wall structure The unit settlement amplitude of each flow tunnel layout path corresponds to the constraint influence weight; The data uncertainty level for determining the mine construction wall structure is as follows: The dominant constraint parameters of each flow tunnel layout path in the mine construction wall structure corresponding to all adjacent construction stages are compared with each other, and the average error value corresponding to the dominant constraint parameters of each flow tunnel layout path in the mine construction wall structure is obtained by average calculation. ; From the auxiliary constraint parameters of each flow tunnel layout path in the mine construction wall structure at each construction stage, two binary medians of the auxiliary constraint parameters corresponding to each flow tunnel layout path are selected and recorded as ; Calculating the data error risk coefficient of the wall structure in mine construction , and compare it with the preset data error risk coefficient range corresponding to each data uncertainty level to determine the data uncertainty level of the mine construction wall structure, where The reference error value corresponding to the dominant constraint parameter and the reference difference value corresponding to the two binary medians of the auxiliary constraint parameter are respectively, The number of paths for flow channel layout.

2. According to the method for collecting and analyzing mine risk monitoring data based on the Internet of Things in claim 1, it is characterized in that: The analysis process of the auxiliary constraint parameters is as follows: Extract geological data of the mine construction wall structure at each stage of the construction period through geological monitoring instruments , is the number of geological data, ; Ore grade monitoring instruments are installed on the layout paths of each flow tunnel in the mine construction wall structure to monitor the distribution and abundance of ore types in each flow tunnel layout path at each construction stage. and ore content distribution density ; Extract the geological data collected from the mine construction wall structure in the early stage of construction, recorded as , analyze the auxiliary constraint parameters of each flow tunnel layout path in the mine construction wall structure at each construction stage , where For the Preset deviation floating value of geological data, They are the first The layout path of each through-flow tunnel corresponds to the abundance of ore types and the density of ore content distribution. is a natural constant that is set to be greater than 1.

3. According to the method and system for collecting and analyzing mine risk monitoring data based on the Internet of Things in claim 1, it is characterized in that: The determination of the changing law of the uncertainty data of the ore body is specifically as follows: the three-dimensional model of the mine construction wall structure at each construction stage is dynamically integrated through the modeling software, and the defect point information of each flow tunnel layout path in the mine construction wall structure at each construction stage is statistically analyzed, and the defect point information includes the position of each concave and convex point along the wall contour and its volume proportion, the position of each rock crack and its aperture, and the defect point information of each flow tunnel layout path in the mine construction wall structure at each construction stage is imported into the modeling software, and the volume concentration area of ​​the concave and convex point along the wall contour and the rock crack aperture concentration area in the mine construction wall structure are derived.

4. The method for collecting and analyzing mine risk monitoring data based on the Internet of Things according to claim 3 is characterized in that: The correlation coefficient between the structural data corresponding to the layout path of each flow tunnel and the coerciveness of the gas inside the tunnel is specifically: The center position of the concentrated area of ​​the concave and convex points along the wall contour and the concentrated area of ​​the rock crack opening in the mine construction wall structure are taken as the reference points. The two reference points are compared with the layout paths of each flow tunnel respectively, and the shortest distances between the two reference points and the layout paths of each flow tunnel are extracted and recorded as ; Analyze the correlation coefficient between the structural data corresponding to the layout path of each flow tunnel and the coerciveness of the gas inside it ,in To preset the reference distance, For the The flow tunnel layout path is in the The gas flow resistance rate at each construction period stage, The preset reference floating deviation value corresponds to the gas flow resistance rate of the adjacent construction period stages. are respectively the preset first association weight and the second association weight, , is the preset correlation difference rate between the gas flow resistance rate deviation rate and the close distance deviation rate, is the base of natural logarithms.

5. The method for collecting and analyzing mine risk monitoring data based on the Internet of Things according to claim 1 is characterized in that: The application data for regulating the subsequent construction period of the mine construction includes: obtaining the comprehensive correlation coefficient between the geological data of the ore body corresponding to the construction of the mine wall structure and the coerciveness of the internal gas ; when hour, is the preset comprehensive correlation coefficient threshold, then the power operation data of the ventilation device is extracted , and adjust the power operation data of the ventilation device accordingly , is the number of construction phases.

6. The method for collecting and analyzing mine risk monitoring data based on the Internet of Things according to claim 5 is characterized in that: The application data for regulating the subsequent construction period of the mine construction also includes: When extracting the data uncertainty level of the mine construction wall structure, the corresponding collection accuracy of the ore body geological collection data in the subsequent construction period is determined.

7. A mine risk monitoring data collection and analysis system based on the Internet of Things, used to execute the method according to claim 1, characterized in that: The following steps are included: Data acquisition module: used to collect structural features of the mine wall structure in the early stage of construction, Construct the tunnel layout diagram of the ventilation device, and extract the layout paths of each flow tunnel from it, which are numbered , collect the ore body data, geological data and wind environment data of the mine construction wall structure; Environmental data analysis module: used to extract the various construction phases of mine construction and analyze the internal gas composition threat indicators of the mine construction wall structure at each construction phase , is the number of the construction phase, ; Ore body geological data analysis module: used to analyze the leading and auxiliary constraint parameters of each flow tunnel layout path in the mine construction wall structure at each construction stage based on the structural data of the mine construction wall structure, which includes the ore body data and the geological data of each region; Multi-scale data fusion module: used to fuse the dominant constraint parameters and auxiliary constraint parameters, determine the data uncertainty level of the mine construction wall structure, and determine the change law of the ore body uncertainty data; Risk prediction and data control module: used to analyze the correlation coefficient between the structural data corresponding to the layout path of each flow tunnel and the threat posed by the gas inside it, and to adjust the application data of the subsequent construction period of the mine accordingly.

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