Mine network operation and maintenance management system and method for coal mine development

Abstract

The present invention relates to the field of industrial Internet technology, specifically to a mine network operation and maintenance management system and method for coal mine development, the system comprising: a path access assessment module, an equipment status identification module, a scheduling priority sorting module, an operation path conflict assessment module, and a scheduling task issuing module. In the present invention, a weighted time-consuming model is constructed through task location and path segment access difficulty parameters to achieve dynamic estimation of path time consumption and optimal path combination. Equipment status identification uses operating parameter interval assignment and weighted aggregation to achieve multi-dimensional risk judgment. In task sorting, the time consumption and risk level are normalized to establish a combination interval to dynamically mark the urgency. The scheduling order is adjusted in combination with the distribution of task points. The intersection of the path point set is extracted in path conflict processing, the proportion of overlapping segments is calculated, and the task position is adjusted according to the threshold to ensure scheduling continuity. Task issuance uniformly generates a scheduling instruction set containing the path equipment status and task type to improve scheduling accuracy and execution consistency.

Description

Technical Field

[0001] The present invention relates to the field of industrial Internet technology, and in particular to a mine network operation and maintenance management system and method for coal mine development. Background Art

[0002] The field of Industrial Internet technology encompasses the deep integration and collaboration of cyber-physical systems, involving multiple key aspects such as network communications, perception and recognition, edge computing, and control execution. The core of this field is to interconnect sensors, automated control equipment, and network platforms to achieve real-time perception, intelligent analysis, and dynamic control of production equipment, business processes, and industrial data. Building on traditional industrial foundations, the Industrial Internet introduces digital, networked, and intelligent capabilities. By building a cross-level, cross-system, and cross-regional interconnected platform, it provides precise management and intelligent decision-making support for industries such as manufacturing, energy, transportation, and mining. Its essence is the information integration and data-driven intelligent scheduling of industrial systems.

[0003] The mine network operation and maintenance management system for coal mine development builds an industrial communication network covering all mining operations, integrating it with the needs of operation and maintenance business management to collect, remotely transmit, and centrally manage data such as the operating status of coal mine equipment, environmental parameters, and safety information online. This system addresses the challenges of multi-source heterogeneity, complex geographical distribution, and heavy manual management burdens in coal mine operation and maintenance. It uses wireless communication terminals to access equipment status data, performs protocol conversion and preliminary screening through edge gateways, and then uploads it to a central control platform. The platform then executes equipment operation data archiving, risk information screening, and operation and maintenance task dispatching based on preset rules, completing digital management of the entire process.

[0004] Existing path planning techniques lack dynamic calculations for traffic difficulty, resulting in large deviations in task duration estimates. Equipment identification focuses on changes in a single parameter and fails to reflect the comprehensive risks of the operating status. Task scheduling lacks a task urgency assessment mechanism, making it impossible to rationally allocate scheduling sequences. The overlapping paths between multiple tasks lack a conflict identification process, which can easily lead to equipment congestion and task delays. The scheduling distribution structure is inconsistent, and information transmission suffers from interpretation biases, impacting execution accuracy and response efficiency. These deficiencies can easily lead to command errors and operational conflicts in complex operation and maintenance environments, reducing task scheduling coordination and safety assurance capabilities. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a mine network operation and maintenance management system and method for coal mine development.

[0006] In order to achieve the above objectives, the present invention adopts the following technical solutions: A mine network operation and maintenance management system for coal mine development includes:

[0007] The path assessment module obtains the location of the operation and maintenance unit and the coordinates of the task point, calls the tunnel path segment length and the difficulty parameter, multiplies the two and then sums them, selects the path with the minimum time consumption, and generates the optimal path set for the task;

[0008] The equipment status identification module obtains the temperature, voltage, and vibration parameters of the mining equipment at the task point, compares the multiple data with the risk threshold, assigns values based on the results, and summarizes them weightedly to screen abnormal equipment and generate a list of risky equipment;

[0009] The scheduling priority sorting module calls the optimal pass path set of the task and the path time and equipment risk data in the risk equipment list, normalizes the time consumption and risk level and determines the combined interval. If both exceed the set threshold, it is marked as an urgent task; if both are lower, it is marked as a deferred task. The rest are adjusted and sorted according to the weighted score, the number of task points and the operation and maintenance coverage to generate a coal mine scheduling task priority sequence;

[0010] The operation path conflict assessment module calls multiple task path point sets in the coal mine scheduling task priority sequence, performs path intersection to extract the number and proportion of overlapping segments, marks over-threshold tasks and performs position shifting, and generates task sorting results after conflict adjustment.

[0011] As a further solution of the present invention, the optimal task path set includes path time value, path selection number, task point sequence information, and path difficulty identification; the risk equipment list includes equipment number identification, risk level score, abnormal indicator label, and equipment operation status identification; the coal mine scheduling task priority sequence includes task priority mark, normalized time value, normalized risk value, task point quantity assessment value, and operation and maintenance coverage factor; the task sorting result after conflict adjustment includes task sorting number, path overlap segment statistics, conflict identification label, and adjusted position identification.

[0012] As a further solution of the present invention, the path passability assessment module includes:

[0013] The location extraction submodule uses the location of the operation and maintenance unit and the coordinates of the task point to call the longitude and latitude of the task point and the unit's area number in the scheduling database, selects coordinate point pairs within the same scheduling area, and generates a task coordinate matching set;

[0014] The path calculation and evaluation submodule calls the task coordinate matching centralized coordinate point pairs, calculates the product of the path segment length and the difficulty of passage, the square root of the length difference and the square of the manual intervention amount, and then performs a weighted summation with the path smoothness rate and operation stability, using the formula:

[0015]

[0016] The path time consumption value between the task point and the unit point is obtained by calculation to obtain the path time consumption matrix;

[0017] Among them, TC xy Indicates the time taken to travel from unit x to task point y, L xyz represents the length of the zth path between unit x and task point y, D xyz Indicates the difficulty of the path segment, AI xyz Indicates the amount of manual intervention set on the path segment, ST xyz represents the patency rate of the path segment, SD xyz Indicates the operation stability of the area where the path segment is located, w represents the total number of path segments from the task point to the unit, z is the index number of the path segment from the task point to the unit, x represents the unit number index, and y represents the task point number index;

[0018] The optimal path screening submodule screens the path combination with the minimum travel time according to the multi-path time values in the path travel time matrix, constructs the unit and task point travel sequence, and generates the optimal travel path set for the task.

[0019] As a further solution of the present invention, the device status identification module includes:

[0020] The data acquisition submodule obtains the temperature, voltage, and vibration values of the mining equipment at the task point, classifies and organizes them by equipment number, eliminates abnormal data, and obtains the parameter integration value;

[0021] The interval judgment submodule calls three types of risk threshold intervals based on the parameter integration value, performs interval judgment and classification calculation on multiple types of parameters, and uses the formula:

[0022]

[0023] The abnormal deviation of the parameter is obtained by calculation, and a weighted score is formed according to the deviation value and the sensitivity coefficient to obtain the risk deviation coefficient;

[0024] Among them, RS q Represents the risk offset coefficient of device q, OB qr represents the observation value of device q on parameter r, TR qr represents the risk threshold center value of device q on parameter r, SC r is the risk sensitivity coefficient of the rth type parameter, V qr Indicates the fluctuation intensity of device q on parameter r, where q represents the device number index and r represents the parameter category index;

[0025] The risk screening submodule sets screening limits according to the risk deviation coefficient, eliminates low deviation devices, summarizes the remaining devices and corresponding parameters, and generates a risk device list.

[0026] As a further solution of the present invention, the scheduling priority sorting module includes:

[0027] The path risk normalization submodule calls the path time and equipment risk data in the optimal pass path set of the task and the risk equipment list, normalizes the path time and equipment risk values respectively, obtains the normalized time value and the normalized risk level value, establishes corresponding two-dimensional data points, and generates a path normalized risk data pair;

[0028] The urgency judgment submodule determines whether the time-consuming threshold and the risk level threshold are exceeded at the same time based on the path normalized risk data pair, marks the urgency of the task, establishes three types of task labels, and generates task urgency classification labels;

[0029] The priority sequence generation submodule uses the task emergency classification label, calls the path normalization risk data pair of the intermediate task, and performs weighted calculation based on the number of task points and the operation and maintenance coverage value, using the formula:

[0030]

[0031] Calculate and obtain the comprehensive ranking score of the intermediate tasks, adjust the task order from high to low according to the score, and generate the priority sequence of coal mine scheduling tasks;

[0032] Among them, PG a Indicates the comprehensive ranking score of the intermediate task a, TN a is the normalized time-consuming value of task a, RG a is the risk normalization value of task a, α is the time-consuming weighted index, β is the risk-weighted index, TP a Represents the number of task points for task a, CN a is the operation and maintenance coverage value of task a, |TP a -CN a | is the absolute value of the difference between the two, It is the sum of the product of time and risk of all intermediate tasks, a represents the task number index, e is the intermediate task set index, and m represents the number of intermediate tasks.

[0033] As a further solution of the present invention, the operation path conflict assessment module includes:

[0034] The path point set extraction submodule calls the multi-task path point information based on the coal mine scheduling task priority sequence, extracts the path point numbers and time series data, constructs a structured path point set, and generates a path point number sequence set;

[0035] The overlap segment identification submodule calls the path point number sequence set, compares the numbers of the path points in pairs, calculates the number and ratio of overlap points, and uses the formula:

[0036]

[0037] The calculation obtains the path overlap strength value between multiple task combinations. The combination with the overlap strength exceeding the threshold is marked, and the overlap path strength matrix is obtained.

[0038] Among them, RI uv represents the overlap strength of the paths between tasks u and v, RA uc , RA vc represents the set of path points of tasks u and v on path segment c, |RA u |、|RA v | represents the total number of path points for tasks u and v, TT u TT v Represent the starting time points of tasks u and v respectively, D uvc is the distance difference between the path segments of tasks u and v, d represents the number of path segments in the path point number sequence set, c is the path segment index number in the path point number sequence set, and u and v represent the number index of the task combination.

[0039] The task sequence adjustment submodule extracts the intensity-exceeding-threshold task combinations according to the overlapped path intensity matrix, adjusts the task sequence and rearranges the scheduling order based on the time-shifted task numbers, and generates a conflict-adjusted task sequence result.

[0040] As a further embodiment of the present invention, the system further comprises:

[0041] The scheduling task issuing module calls the task sorting result after the conflict adjustment, generates a scheduling parameter field combination including number, path, equipment and type for the task sorting content, assembles it into an output instruction, and generates a mine network operation and maintenance scheduling instruction set;

[0042] The mine network operation and maintenance scheduling instruction set includes a scheduling task number, a passage path information, associated equipment information, and a scheduling task type label.

[0043] As a further solution of the present invention, the scheduling task issuing module includes:

[0044] The scheduling path calculation submodule calls the task sorting result after conflict adjustment, extracts the start and end point coordinate values and path node numbers, reorganizes the path numbers based on the sorting order identifier, matches the task node numbers with the path node position index, filters the continuous path segments and binds the task numbers, and generates a task path sequence number set;

[0045] The device matching determination submodule calls the path node information in the task path sequence number set, obtains the bound device number and operation status identifier, calculates the device continuous operation matching value and compares it with the node continuous operation matching threshold, selects the matching device number, and generates the path node device matching coefficient;

[0046] The type field fusion submodule extracts the device type field code and the path number according to the device number in the path node device matching coefficient, concatenates the device type field and the path node number, and returns them to the original task number to generate a task field fusion combination value;

[0047] The instruction assembly output submodule calls the task field fusion combination value, arranges it in ascending order by task number, adds the execution priority identifier, scheduling trigger flag and timestamp identifier, sets the output format field order according to the task number and writes it into the template structure to generate a mine network operation and maintenance scheduling instruction set.

[0048] A mine network operation and maintenance management method for coal mine development, which is executed based on the above-mentioned mine network operation and maintenance management system for coal mine development, includes the following steps:

[0049] S1: Obtain the location of the operation and maintenance unit and the coordinates of the task point, call the path segment length and the difficulty coefficient, sum the product of the path segment length and the difficulty coefficient and compare the time values to obtain the path time evaluation value;

[0050] S2: Obtain equipment temperature, voltage, and vibration parameters, perform interval judgment on each parameter and the corresponding risk threshold, assign values, and perform weighted aggregation to obtain the equipment operation risk level value;

[0051] S3: Call the time and risk data in the path time evaluation value and the equipment operation risk level value, perform a normalization process on the two data and determine the combined interval, mark high-time-consuming and high-risk tasks as urgent, and mark low-time-consuming and low-risk tasks as deferred, and sort the remaining tasks according to the weighted score, the number of task points and the coverage range to obtain the scheduling task priority score;

[0052] S4: calling the task path point set in the scheduling task priority score value, performing path intersection extraction and overlapping segment statistics, marking the over-threshold path tasks and moving them backward, and obtaining the path overlap conflict adjustment amount;

[0053] S5: Call the adjusted task order in the path overlap conflict adjustment amount, combine the task number, path point, device number and task type fields, and obtain the scheduling task parameter output.

[0054] Compared with the prior art, the advantages and positive effects of the present invention are:

[0055] In the present invention, a weighted time consumption model is constructed by combining the task location and the path segment difficulty parameters to achieve dynamic path time consumption estimation and select the optimal path combination. Equipment status identification uses multiple operating parameter interval assignments and weighted aggregation to achieve multi-dimensional risk comprehensive judgment. In task sorting, the time consumption and risk level are normalized to establish a combined interval, dynamically mark the task urgency, and adjust the scheduling order based on the distribution of task points. In the path conflict processing stage, the intersection of the path point set is extracted and the proportion of overlapping segments is calculated. The task position is adjusted according to the threshold to ensure scheduling continuity. When tasks are issued, a scheduling instruction set containing the path, equipment status, and task type is uniformly generated to improve scheduling accuracy and execution consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a system flow chart of the present invention;

[0057] Figure 2 This is a flow chart of the path assessment module of the present invention;

[0058] Figure 3 This is a flow chart of the device status identification module of the present invention;

[0059] Figure 4 This is a flow chart of the scheduling priority module of the present invention;

[0060] Figure 5 This is a flow chart of the operation path conflict assessment module of the present invention;

[0061] Figure 6 This is a flowchart of the scheduling task distribution module of the present invention. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0063] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0064] Example 1

[0065] See also Figure 1 The present invention provides a technical solution: a mine network operation and maintenance management system for coal mine development includes:

[0066] The path assessment module obtains the location of the operation and maintenance unit and the coordinates of the task point, calls the tunnel path segment length and the difficulty parameter, multiplies the two and then sums them, selects the path with the minimum time consumption, and generates the optimal path set for the task;

[0067] The equipment status identification module obtains the temperature, voltage, and vibration parameters of the mining equipment at the task point, compares the multiple data with the risk threshold, assigns values based on the results, and summarizes them weightedly to screen abnormal equipment and generate a list of risky equipment;

[0068] The scheduling priority sorting module calls the optimal path set for the task and the path time and equipment risk data in the risk equipment list, normalizes the time and risk level and determines the combined interval. If both exceed the set threshold, it is marked as an urgent task; if both are lower, it is marked as a deferred task. The rest are adjusted and sorted according to the weighted score, the number of task points, and the operation and maintenance coverage to generate a priority sequence for coal mine scheduling tasks;

[0069] The operation path conflict assessment module calls multiple task path point sets in the coal mine scheduling task priority sequence, performs path intersection to extract the number and proportion of overlapping segments, marks over-threshold tasks and moves them backward, and generates the task sorting result after conflict adjustment;

[0070] The scheduling task issuing module calls the task sorting result after conflict adjustment, generates a scheduling parameter field combination including number, path, equipment and type for the task sorting content, assembles it into output instructions, and generates a mine network operation and maintenance scheduling instruction set.

[0071] The optimal task path set includes path time value, path selection number, task point sequence information, and path difficulty identification; the risk equipment list includes equipment number identification, risk level score, abnormal indicator label, and equipment operation status identification; the coal mine scheduling task priority sequence includes task priority mark, normalized time value, normalized risk value, task point quantity assessment value, and operation and maintenance coverage factor; the task sorting result after conflict adjustment includes task sorting number, path overlap segment statistics, conflict identification label, and adjusted position identification; the mine network operation and maintenance scheduling instruction set includes scheduling task number, path information, associated equipment information, and scheduling task type label.

[0072] See also Figure 2 , the path access assessment module includes:

[0073] The location extraction submodule uses the location of the operation and maintenance unit and the coordinates of the task point to call the longitude and latitude of the task point and the unit's area number in the scheduling database, selects coordinate point pairs within the same scheduling area, and generates a task coordinate matching set;

[0074] First, call the scheduling database to obtain the latitude and longitude information of each task point and the area number to which it belongs, so as to clarify the specific location information of each task point; then call the area number and longitude and latitude information of the operation and maintenance unit respectively to form the initial geographical location data combination between each operation and maintenance unit and each task point. At this time, there may be cross-regional situations in the data combination formed; then, based on the area number, compare the area numbers of all initial data combinations one by one, discard the coordinate point pairs with different area numbers, and only retain the operation and maintenance unit and task point combinations with exactly the same area numbers; for example, if unit A is area If the unit A is numbered as region 01 and the task point T1 is also numbered as region 01, this pair of coordinates is retained. If the unit A is numbered as region 01 and the task point T2 is numbered as region 02, this combination is discarded. Then, after the retained combination is reconfirmed by the region number, a coordinate point matching relationship is established within the same scheduling area. For example, unit A (latitude and longitude are 116.40° east longitude and 39.90° north latitude) and task point T1 (latitude and longitude are 116.41° east longitude and 39.91° north latitude) are both located in Haidian District, Beijing. They are determined as a valid coordinate point pair, and finally a task coordinate matching set of the unit and task point is generated.

[0075] The path calculation and evaluation submodule calls the task coordinate matching centralized coordinate point pairs, calculates the product of the path segment length and the difficulty of passage, the square root of the length difference, and the square of the manual intervention amount, and then performs a weighted summation with the path smoothness rate and operation stability, using the formula:

[0076]

[0077] The path time consumption value between the task point and the unit point is obtained by calculation to obtain the path time consumption matrix;

[0078] Among them, TC xy Indicates the time taken to travel from unit x to task point y, L xyz represents the length of the zth path between unit x and task point y, D xyz Indicates the difficulty of the path segment, AI xyz Indicates the amount of manual intervention set on the path segment, ST xyz represents the patency rate of the path segment, SD xyz Indicates the operation stability of the area where the path segment is located, w represents the total number of path segments from the task point to the unit, z is the index number of the path segment from the task point to the unit, x represents the unit number index, and y represents the task point number index;

[0079] Taking the path from unit A to task point T1 as an example, the detailed execution process is as follows: First, call the path segmentation data between unit A and task point T1. Assume that the path is divided into 3 sections, and the length of each section is L. xyz , Difficulty of Passage D xyz , artificial intervention AI xyz Path patency rate ST xyz and operational stability SD xyz The data is obtained through on-site measurement, historical operation record collection or real-time monitoring. The specific data is shown in Table 1:

[0080] Table 1 Data table of the path segment from unit A to task point T1

[0081]

[0082]

[0083] The specific calculation process is carried out section by section: for the first section of the path, the length is multiplied by the difficulty, which is 2.5km×3=7.5; the square root of the absolute value of the difference between the length and the difficulty is The square of the human intervention is 1 2 = 1; the sum of the path patency and the running stability is 95 + 92 = 187; the sum of the above three values is divided by the sum of the patency and the stability, that is, (7.5 + 0.707 + 1) / 187 = 9.207 / 187 = 0.0492. Calculate the second path in the same way: (3.0 × 4 = 12.0; 22=4; (12+1+4) / (88+90)=17 / 178=0.0955). Then calculate the third path: (1.5×2=3; 12=1;

[0084] (3+0.707+1) / (97+95)=4.707 / 192=0.0245). Finally, the values obtained from the above three segments are summed up, that is, TC xy =0.0492+0.0955+0.0245=0.1692. This result indicates that the travel time from unit A to task point T1 is 0.1692, which is relatively small, indicating that the overall traffic condition of the path is good.

[0085] The optimal path screening submodule selects the path combination with the minimum passage time according to the multi-path time values in the path passage time matrix, constructs the passage sequence of units and task points, and generates the optimal passage path set for the task.

[0086] For example, among the three alternative paths from unit A to task point T1, it is assumed that the time value of path P1 is 0.1692, the time value of path P2 is 0.2150, and the time value of path P3 is 0.1845. The execution process is to first call the path time values 0.1692, 0.2150, and 0.1845 one by one, and compare them pairwise. The first comparison is 0.1692 and 0.2150. It is determined that 0.1692 is smaller, so path P2 is discarded. The second call is Path P1's 0.1692 and path P3's 0.1845 are compared again and determined to be smaller, so path P1 is retained and path P3 is discarded. After the above two calls and comparisons of the path travel time values, the time value of path P1, 0.1692, is the smallest, so path P1 is determined to be the optimal path. Finally, the unit and task point coordinates of path P1 are added to the unit and task point travel sequence in sequence, thereby forming the optimal path set for the task.

[0087] See also Figure 3 , the device status identification module includes:

[0088] The data acquisition submodule obtains the temperature, voltage, and vibration values of the mining equipment at the task point, classifies and organizes them by equipment number, eliminates abnormal data, and obtains the parameter integration value;

[0089] Taking the mining equipment No. Q1 as an example, the collected data include the temperature value of 75℃ measured by the temperature sensor T1, the voltage value of 380V measured by the voltage sensor U1, and the vibration value of 15mm / s measured by the vibration sensor Z1. These parameters are marked with the equipment number to form the initial data, and then the acquired data is classified and sorted. The sorting process includes summarizing the data of the same equipment number one by one, and listing the different types of parameters measured by all sensors in the same array or table. For example, the temperature value array corresponding to the Q1 equipment [T1: 75℃, T2: 77℃, T3: 76℃], the voltage value array [U1: 380V, U2: 382V, U3: 378V], and the vibration value array [Z1: 15mm / s, Z2: 16mm / s, Z3: 14mm / s], and then Abnormal data is judged within a reasonable data range. For example, the normal temperature range is set to 60°C to 80°C, the normal voltage range is set to 370V to 390V, and the normal vibration range is set to 10mm / s to 20mm / s. Each value in the array is compared with the upper and lower limits of the interval one by one. If a measurement value, such as T4, is 95°C and exceeds the upper limit of the normal temperature range of 80°C, it is directly eliminated through the judgment action to complete the abnormal data elimination process. Finally, the remaining parameters are numerically integrated. For example, the values 75°C, 77°C, and 76°C in the temperature array are calculated by arithmetic mean, and the temperature integration value of the device Q1 is 76°C. The same method is used to process the voltage and vibration arrays, and the voltage integration value is 380V and the vibration integration value is 15mm / s to obtain the parameter integration value.

[0090] The interval judgment submodule calls three types of risk threshold intervals based on the parameter integration value, performs interval judgment and classification calculation on multiple types of parameters, and uses the formula:

[0091]

[0092] The abnormal deviation of the parameter is obtained by calculation, and a weighted score is formed according to the deviation value and the sensitivity coefficient to obtain the risk deviation coefficient;

[0093] Among them, RS q Represents the risk offset coefficient of device q, OB qr represents the observation value of device q on parameter r, TR qr represents the risk threshold center value of device q on parameter r, SC r is the risk sensitivity coefficient of the rth type parameter, V qr Indicates the fluctuation intensity of device q on parameter r, where q represents the device number index and r represents the parameter category index;

[0094] The specific implementation of this process is as follows: First, refer to the risk threshold intervals of various parameters determined in advance through experiments, such as the temperature risk threshold center value TR q1 Set to 70℃, the voltage risk threshold center value TR q2 Set to 375V, vibration risk threshold center value TR q3 Set to 12mm / s; then determine the risk sensitivity coefficient SC r The sensitivity coefficient is set based on the influence of equipment parameter changes on the fault after multiple tests, and the weight is assigned according to the actual frequency of fault occurrence. For example, temperature change is more sensitive, so it is assigned a higher sensitivity coefficient SC1=1.2, voltage change is second, and is assigned SC2=1.0, and vibration change is the lowest, and is assigned SC3=0.8; then the fluctuation intensity V is determined. qr The fluctuation intensity is obtained by collecting historical data through long-term monitoring and calculating the historical fluctuation variance of each parameter. For example, the historical temperature data variance of Q1 equipment is 4.0, the voltage variance is 6.0, and the vibration variance is 1.0. Based on the above set values and calling the formula:

[0095]

[0096] Explanation of the calculation process by substituting specific values: Taking device Q1 as an example, substituting the above values into the formula in sequence, the calculation process is specifically expressed as follows:

[0097]

[0098] Calculation formula:

[0099]

[0100] The results show that the risk deviation coefficient of device Q1 is 6.81, indicating that the parameters of the device during monitoring have significantly deviated from the set risk threshold center value.

[0101] The risk screening submodule sets the screening limit according to the risk deviation coefficient, eliminates low deviation devices, summarizes the remaining devices and corresponding parameters, and generates a list of risky devices.

[0102] The risk screening boundaries are established based on actual monitoring data. When setting them specifically, after measuring the risk offset coefficient data of all devices through historical data, the median value of the offset coefficient and its fluctuation range are calculated. For example, the risk offset coefficients of the five devices collected historically are: [4.5, 5.0, 6.0, 7.2, 8.5]. Through actual calculation, the median value is 6.0, and the risk offset coefficient threshold is set to 6.0. That is, the threshold is used as the boundary, and the actions are judged by comparison. All devices with risk offset coefficients lower than the threshold, such as 4.5 and 5.0, are directly eliminated. Devices with risk offset coefficients higher than or equal to the threshold, such as 6.0, 7.2 and 8.5, are included in the risk device list. Finally, the device numbers retained by the screen and the corresponding integrated values of temperature, voltage and vibration parameters are summarized to generate a risk device list and form the results.

[0103] Table 2 Historical data table of equipment risk deviation coefficient

[0104]

[0105] As shown in Table 2, the table lists the integrated parameter values and calculated risk offset coefficients of the five devices. Based on the screening threshold of 6.0, devices Q1, Q3, and Q5 are identified as risky devices.

[0106] See also Figure 4 , the scheduling priority sorting module includes:

[0107] The path risk normalization submodule calls the path time and equipment risk data in the task optimal pass path set and the risk equipment list, normalizes the path time and equipment risk values respectively, obtains the normalized time value and the normalized risk level value, establishes corresponding two-dimensional data points, and generates path normalized risk data pairs;

[0108] First, normalization of time consumption and risk is performed separately. The specific process of path time normalization is to calculate the ratio of the actual time consumption data of a path to the maximum time consumption data of all selected paths to obtain a normalized time consumption value. For example, if the actual time consumption of coal mine roadway path A is 25 minutes, and the longest path in the coal mine task set consumes 50 minutes, then the normalized time consumption value of path A is 25 / 50 = 0.5. The normalized risk level value is processed by dividing the risk value of a single risk device by the maximum risk value of all devices in the risk device list of the current task. For example, if the risk value of device X is 30 and the maximum risk value in the risk device list is 100, then the normalized risk level value of device X is 30 / 100 = 0.3. After completing the above calculations, the normalized time consumption value and the normalized risk level value are combined to create a two-dimensional data point. For example, the corresponding combined data point of path A and device X is (0.5, 0.3). This process is repeated for each path in the task set to finally generate a normalized risk data pair for all paths.

[0109] The urgency judgment submodule determines whether the time-consuming threshold and the risk level threshold are exceeded simultaneously based on the path-normalized risk data pair, marks the task urgency, establishes three types of task labels, and generates task urgency classification labels;

[0110] Based on the path normalized risk data, the over-limit judgment operation of the time consumption and risk level thresholds is performed respectively. The time consumption threshold and risk level threshold are specifically set to preset values. The specific settings of these two thresholds refer to the data range of the coal mine task scenario. The time consumption normalization threshold is usually set to 0.7, and the risk level normalization threshold is set to 0.6. For example, if the time consumption normalization value of the corresponding data point of a path is 0.8 and the risk level normalization value is 0.65, a comparison action needs to be performed to compare the values of 0.8 and 0.7 respectively, and 0.65 and 0.6 at the same time. Through comparison, it is found that the above values exceed the set thresholds at the same time. Therefore, the urgency of the task corresponding to the path is marked as high. Similarly, if either the time consumption value or the risk value of the path data point is lower than the threshold, the urgency of the task is judged to be medium, and if both are lower than the threshold, the urgency of the task is marked as low. In this way, the labeling of three types of task labels is achieved, forming a complete task urgency classification label.

[0111] The priority sequence generation submodule uses the task urgency classification label, calls the path normalization risk data pair of the intermediate task, and performs weighted calculation based on the number of task points and the operation and maintenance coverage value. The formula is:

[0112]

[0113] Calculate and obtain the comprehensive ranking score of the intermediate tasks, adjust the task order from high to low according to the score, and generate the priority sequence of coal mine scheduling tasks;

[0114] Among them, PG a Indicates the comprehensive ranking score of the intermediate task a, TN a is the normalized time-consuming value of task a, RG a is the risk normalization value of task a, α is the time-consuming weighted index, β is the risk-weighted index, TP a Represents the number of task points for task a, CN a is the operation and maintenance coverage value of task a, |TP a -CN a | is the absolute value of the difference between the two, It is the sum of the product of time and risk of all intermediate tasks, a represents the task number index, e is the intermediate task set index, and m represents the number of intermediate tasks.

[0115] Set the number of intermediate tasks to 3. The specific parameter information of each intermediate task is shown in Table 3:

[0116] Table 3 Intermediate task parameter information table

[0117] Task Number Normalized time value Risk Normalized Value Number of mission points Operation and maintenance coverage value 1 0.55 0.40 15 8 2 0.65 0.45 12 9 3 0.60 0.50 20 10

[0118] As shown in Table 3, through the formula:

[0119]

[0120] The detailed explanation of each parameter is as follows:

[0121] PG a is the comprehensive ranking score of the intermediate task a;

[0122] TN a The normalized value of the time consumed by task a;

[0123] RG a is the risk normalization value of task a;

[0124] The indexes α and β are set to 2 and 2 respectively. The settings of these two indexes are determined by the actual management experience of coal mines, that is, the sensitivity of risk and time consumption are both squared;

[0125] TP a is the number of task points for task a, obtained through actual statistics;

[0126] CN a is the operation and maintenance coverage value of task a, obtained through statistics on the area covered by the on-site operation and maintenance personnel;

[0127] The summation symbol indicates that the number of all intermediate tasks m = 3 tasks is executed TN e With RG e The multiplication and accumulation operation.

[0128] Taking the task number 1 as an example, the calculation process is as follows:

[0129] First, find the sum of the products of the normalized values of each intermediate task:

[0130]

[0131] Calculate the intermediate expression of Task 1:

[0132]

[0133] Calculate the absolute difference between the task point and the coverage area:

[0134] |TP1-CN1|=|15-8|=7;

[0135] Substitute the above calculation results to get the score value:

[0136]

[0137] Under the same process, the score values of tasks numbered 2 and 3 are calculated respectively, and then sorted from high to low according to the score value. Finally, the coal mine scheduling task priority sequence is adjusted to generate. If the final score value is sorted as Task 2>Task 1>Task 3, the task priority sequence is Task 2→Task 1→Task 3.

[0138] The higher the calculated comprehensive score, the more obvious the imbalance between the comprehensive risk and time consumption of the task and the operation and maintenance coverage and the number of task points, and the higher the urgency and scheduling priority of the task. Therefore, this result shows that the task priority sequence calculated by the comprehensive score is closely related to the operation and maintenance strategy of the actual scheduling scenario, and the score effectively determines the priority level of task processing.

[0139] See also Figure 5 ,The job path conflict assessment module includes:

[0140] The path point set extraction submodule calls the multi-task path point information based on the coal mine scheduling task priority sequence, extracts the path point numbers and time series data, constructs a structured path point set, and generates a path point number sequence set;

[0141] For example, a coal mine needs to execute tasks A, B, and C between 8:00 and 9:00 in the morning. The priority sequence of these tasks is A→B→C. The submodules are executed in sequence according to the priority. First, the path point information of task A is called. Task A includes the path point number set [12,13,14,15] on path segment 1 and the path point number set [16,17,18] on path segment 2. The corresponding starting time of the time series data is 08:00, and the time interval of the path point number is 1 minute per point. Next, the path point information of task B is called. The path point number set of path segment 1 of task B is [14,15,19,20], and the path point number set of path segment 2 is [21,22]. The starting time is 08:05, and the interval between each path point is also 1 minute. The path point number set of task C path segment is [18,23,24]. The path segment starts at 08:10 and the interval is 1 minute; the path point set extraction submodule extracts the above information task by task and path segment by path segment, and forms a structured path point set based on the timing information and the path point number combination. The path point set of each task and its corresponding timing are structured and recorded, thereby obtaining the following structured path point number sequence set: (Task A: [12(08:00), 13(08:01), 14(08:02), 15(08:03), 16(08:04), 17(08:05), 18(08:06)], Task B: [14(08:05), 15(08:06), 19(08:07), 20(08:08), 21(08:09), 22(08:10)], Task C: [18(08:10), 23(08:11), 24(08:12)]), and finally forming the task path point number sequence set.

[0142] The overlap segment identification submodule calls the path point number sequence set, compares the numbers of the path points in pairs, calculates the number and ratio of overlap points, and uses the formula:

[0143]

[0144] The calculation obtains the path overlap strength value between multiple task combinations. The combination with the overlap strength exceeding the threshold is marked, and the overlap path strength matrix is obtained.

[0145] Among them, RI uv represents the overlap strength of the paths between tasks u and v, RA uc , RA vc represents the set of path points of tasks u and v on path segment c, |RA u |、|RA v | represents the total number of path points for tasks u and v, TT u TT v Represent the starting time points of tasks u and v respectively, Duvc is the distance difference between the path segments of tasks u and v, d represents the number of path segments, c is the index number of the path segment, and u and v represent the number index of the task combination.

[0146] For example, when comparing the path point numbers of tasks A and B, it is found that path points 14 and 15 overlap, for a total of 2. The number of path overlaps is calculated to be 2, the total number of path points for task A is 7, and the total number of path points for task B is 6. The submodule then analyzes the ratio of path overlap points, which is calculated as the ratio of the square root of the number of path overlap points and the total number of task path points: Then, the start time difference and the distance difference between the two task paths are calculated respectively. Task A starts at 08:00 and Task B starts at 08:05, with a start time difference of 5 minutes. Then, the distance difference between the path segments is calculated. For example, the distance difference between Task A and Task B path segment 1 is 3 meters, and the distance difference between path segment 2 is 4 meters. The total number of path segments is 2, so the sum of the distance differences between all path segments is 3 + 4 = 7 meters. Then, the submodule calls the formula:

[0147]

[0148] The meaning of each parameter in the formula is: RA Ac Represents the set of path points of task A on path segment c, for example, path segment 1 is [12, 13, 14, 15]; RA Bc is the set of path points for task B on path segment c, for example, path segment 1 is [14, 15, 19, 20]; |RA A |、|RA B | is the number of path points 7, 6; TT A TT B They represent the task start time points 08:00 and 08:05 respectively, and the absolute value of the difference between the two is 5; D ABc is the distance difference between the path segments. Path segment 1 is 3 meters, and path segment 2 is 4 meters. Substituting the actual data into the calculation, we get:

[0149]

[0150] The result shows that the path overlap intensity of tasks A and B is 0.1082. According to the experience of coal mine transportation task management, the path overlap intensity threshold is set to 0.10. Then this combination exceeds the threshold of 0.10 and is marked as a path conflict task combination and recorded in the overlap path intensity matrix.

[0151] The task sequence adjustment submodule extracts the task combinations with intensity exceeding the threshold according to the overlapped path intensity matrix, adjusts the task sequence and rearranges the scheduling order based on the time-shifted task numbers, and generates the task sequence result after conflict adjustment.

[0152] Based on the obtained overlap path strength matrix, task combinations with path overlap strength exceeding the threshold of 0.10, such as tasks A and B, are extracted. Then, the task numbers and task execution start times in the task combinations are analyzed, and adjustments are made by shifting the execution time of the task with the larger task number backward. For example, if task A is numbered 1 and task B is numbered 2, the start time of task B is postponed from 08:05 to 08:10 by 5 minutes. Subsequently, the submodule rearranges the task execution order, and the task order changes from the original [A(08:00), B(08:05), C(08:10)] to [A(08:00), C(08:10), B(08:10 moved back to 08:15)]. The new scheduling order is rearranged accordingly, and finally the conflict-adjusted task order [A→C→B] is generated.

[0153] See also Figure 6 , the scheduling task delivery module includes:

[0154] The scheduling path calculation submodule calls the task sorting result after conflict adjustment, extracts the start and end point coordinate values and path node numbers, reorganizes the path numbers based on the sorting order identifiers, matches the task node numbers with the path node position indexes, filters the continuous path segments and binds the task numbers to generate the task path sequence number set;

[0155] The starting point, end point coordinates and path node numbers of each task in the task sequence are extracted one by one for subsequent processing. Taking task T1 from coordinate point A (15, 20) to coordinate point B (35, 50) as an example, the task path node numbers are extracted as [1, 3, 5, 7, 9], and the sorting order is task number 1. The sorting order identification of these path node numbers is matched with the node position index, that is, the path node number 1 is mapped to the sorting number 1-1, the node number 3 is mapped to the sorting number 1-2, and so on. The reorganization of the sorting number and the node number is completed to form a dual identification of the number and the node; then, the adjacent node numbers are compared continuously. The specific comparison action is when Is the difference between the previous node and the next node number 1? If this condition is met, it is recorded as a continuous node segment and bound to the current task number T1. If the difference is greater than 1, it is considered a new path segment. For example, after continuity comparison of the path nodes [1, 3, 5, 7, 9] in the above task, since the node number difference is 2, it means that the nodes are not continuous. Therefore, each node is treated as a continuous path segment and bound to T1 to form T1-1, T1-2, T1-3, T1-4, and T1-5, a total of 5 task path segments. After repeated execution of the above steps and analysis and processing of each task, the task path sequence number set is finally generated as [T1-1, T1-2, T1-3, T1-4, T1-5].

[0156] The device matching determination submodule calls the path node information in the task path sequence number set, obtains the bound device number and operation status identifier, calculates the device continuous operation matching value and compares it with the node continuous operation matching threshold, selects the matching device number, and generates the path node device matching coefficient;

[0157] The path node information in the task path sequence number set [T1-1, T1-2, T1-3, T1-4, T1-5] is called one by one. For example, for the path segment T1-1 corresponding to the node number 1, the device number it is bound to is the device E101, and the real-time running status of the called device is marked as "idle"; for T1-2 corresponding to the node number 3, the device number is the device E203, and the device status is marked as "operating"; then the matching degree of the device and the node continuous operation is calculated. The execution method of this calculation action is: first obtain the current operation time parameter of the device The number (e.g., the cumulative operation time of device E203 is 180 minutes) and the estimated operation time of the current task segment (assuming that the duration of segment T1-2 is 30 minutes), and then the ratio of the continuous operation time of the device to the task duration is calculated, that is, 180 / 30=6.0, and this value is defined as the device continuous operation matching degree; the calculated matching degree value is then compared with the node continuous operation matching threshold, where the threshold is set to 4.0 (set by actual statistical data on the stable operation time of the device, such as when the continuous operation of the device exceeds 120 minutes and the task duration is 30 minutes, the threshold is 4.0).

[0158] =120 / 30=4.0). At this time, the calculated value 6.0 is greater than the threshold value 4.0, and device E203 is determined to be mismatched. The device screening action is performed to screen out device E203 and find an alternative device. Through the above-mentioned screening action after comparing the task path segments one by one, a valid matching device number is obtained. For example, the matching coefficient of device E101 in segment T1-1 is 0.5 (running time 30 minutes / task time 60 minutes). The matching result is retained, and the formation of the path node device matching coefficient is completed.

[0159] The type field fusion submodule extracts the device type field code and the path number based on the device number in the path node device matching coefficient, concatenates the device type field and the path node number, and returns them to the original task number to generate the task field fusion combination value;

[0160] According to the valid device number of the path node device matching coefficient, such as device E101, the device type field code "TY07" (mining excavation equipment type) is obtained through the device management database call, and the current path number T1-1 is further extracted. The device type field code "TY07" and the path node number "1" are spliced to form a fused combination value TY07-1, and then the fused combination value is returned according to the original task number, and the fused combination value is matched to the original task number T1, that is, the task field fused combination value T1-TY07-1 is obtained; for other path nodes, such as T1-3 corresponding to device E305, the device type field code "TY09", the path node number is 5, and after splicing, the fused combination value TY09-5 is formed. After processing in sequence, a fused combination value set [T1-TY07-1, T1-TY09-5] is formed.

[0161] The instruction assembly output submodule calls the task field fusion combination value, arranges it in ascending order by task number, adds the execution priority identifier, scheduling trigger flag and timestamp identifier, sets the output format field order based on the task number and writes it into the template structure to generate the mine network operation and maintenance scheduling instruction set.

[0162] After calling the task field fusion combination value [T1-TY07-1, T1-TY09-5], rearrange it in ascending order according to the original task number T1, and add the execution priority identifier to each task fusion value such as T1-TY07-1. For example, the execution priority identifier of task T1 is set to "high priority", and then add the scheduling trigger flag bit and set the value to "1". Further call the actual timestamp identifier when the current task is processed. For example, the timestamp of the current processing completion moment is "1701234600" (Uni x timestamp format), and the output format sequence is reset in conjunction with the original task number as follows: task number - fusion combination value - execution priority - trigger flag - timestamp, thus forming the specific instruction entry "T1-TY07-1-high priority-1-1701234600". The above contents are then written into the scheduling template structure item by item, and after executing the template structure parameter mapping action, the final mine network operation and maintenance scheduling instruction set is generated as follows: [T1-TY07-1-high priority-1-1701234600, T1-TY09-5-high priority-1-1701234650].

[0163] A mine network operation and maintenance management method for coal mine development is implemented based on the above-mentioned mine network operation and maintenance management system for coal mine development, and includes the following steps:

[0164] S1: Obtain the location of the operation and maintenance unit and the coordinates of the task point, call the path segment length and the difficulty coefficient, sum the product of the path segment length and the difficulty coefficient and compare the time values to obtain the path time evaluation value;

[0165] S2: Obtain equipment temperature, voltage, and vibration parameters, perform interval judgment on each parameter and the corresponding risk threshold, assign values, and perform weighted aggregation to obtain the equipment operation risk level value;

[0166] S3: Call the time and risk data from the path time evaluation value and the equipment operation risk level value, perform data normalization on the two data, and determine the combined interval. Mark high-time, high-risk tasks as urgent, and low-time, low-risk tasks as deferred. The remaining tasks are sorted according to the weighted score, the number of task points, and the coverage area to obtain the scheduling task priority score.

[0167] S4: Call the task path point set in the scheduling task priority score value, perform path intersection extraction and overlap segment statistics, mark the over-threshold path tasks and move them back, and obtain the path overlap conflict adjustment amount;

[0168] S5: Call the adjusted task sorting in the path overlap conflict adjustment amount, combine the task number, path point, device number and task type fields, and obtain the scheduling task parameter output.

[0169] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A mine network operation and maintenance management system for coal mine development, characterized in that: The system comprises: The path assessment module obtains the location of the operation and maintenance unit and the coordinates of the task point, calls the tunnel path segment length and the difficulty parameter, multiplies the two and then sums them, selects the path with the minimum time consumption, and generates the optimal path set for the task; The equipment status identification module obtains the temperature, voltage, and vibration parameters of the mining equipment at the task point, compares the multiple data with the risk threshold, assigns values based on the results, and summarizes them weightedly to screen abnormal equipment and generate a list of risky equipment; The scheduling priority sorting module calls the optimal pass path set of the task and the path time and equipment risk data in the risk equipment list, normalizes the time consumption and risk level and determines the combined interval. If both exceed the set threshold, it is marked as an urgent task; if both are lower, it is marked as a deferred task. The rest are adjusted and sorted according to the weighted score, the number of task points and the operation and maintenance coverage to generate a coal mine scheduling task priority sequence; The operation path conflict assessment module calls multiple task path point sets in the coal mine scheduling task priority sequence, performs path intersection to extract the number and proportion of overlapping segments, marks over-threshold tasks and performs position shifting, and generates a task sorting result after conflict adjustment; The operation path conflict assessment module includes: The path point set extraction submodule calls the multi-task path point information based on the coal mine scheduling task priority sequence, extracts the path point numbers and time series data, constructs a structured path point set, and generates a path point number sequence set; The overlap segment identification submodule calls the path point number sequence set, compares the numbers of the path points in pairs, calculates the number and ratio of overlap points, and uses the formula: The calculation obtains the path overlap strength value between multiple task combinations. The combination with the overlap strength exceeding the threshold is marked, and the overlap path strength matrix is obtained. Among them, RI uv represents the overlap strength of the paths between tasks u and v, RA uc , RA vc represents the set of path points of tasks u and v on path segment c, |RA u |、|RA v | represents the total number of path points for tasks u and v, TT u TT v Represent the starting time points of tasks u and v respectively, D uvc is the distance difference between the path segments of tasks u and v, d represents the number of path segments in the path point number sequence set, c is the path segment index number in the path point number sequence set, and u and v represent the number index of the task combination; The task sequence adjustment submodule extracts the intensity-exceeding-threshold task combinations according to the overlapped path intensity matrix, adjusts the task sequence and rearranges the scheduling order based on the time-shifted task numbers, and generates a conflict-adjusted task sequence result.

2. The mine network operation and maintenance management system for coal mine development according to claim 1, characterized in that: The optimal task path set includes path time value, path selection number, task point sequence information, and path difficulty identification; the risk equipment list includes equipment number identification, risk level score, abnormal indicator label, and equipment operation status identification; the coal mine scheduling task priority sequence includes task priority mark, normalized time value, normalized risk value, task point quantity assessment value, and operation and maintenance coverage factor; the task sorting result after conflict adjustment includes task sorting number, path overlap segment statistics, conflict identification label, and adjusted position identification.

3. The mine network operation and maintenance management system for coal mine development according to claim 2, characterized in that: The path passability assessment module includes: The location extraction submodule uses the location of the operation and maintenance unit and the coordinates of the task point to call the longitude and latitude of the task point and the unit's area number in the scheduling database, selects coordinate point pairs within the same scheduling area, and generates a task coordinate matching set; The path calculation and evaluation submodule calls the task coordinate matching centralized coordinate point pairs, calculates the product of the path segment length and the difficulty of passage, the square root of the length difference and the square of the manual intervention amount, and then performs a weighted summation with the path smoothness rate and operation stability, using the formula: The path time consumption value between the task point and the unit point is obtained by calculation to obtain the path time consumption matrix; Among them, TC xy Indicates the time taken to travel from unit x to task point y, L xyz represents the length of the zth path between unit x and task point y, D xyz Indicates the difficulty of the path segment, AI xyz Indicates the amount of manual intervention set on the path segment, ST xyz represents the patency rate of the path segment, SD xyz Indicates the operation stability of the area where the path segment is located, w represents the total number of path segments from the task point to the unit, z is the index number of the path segment from the task point to the unit, x represents the unit number index, and y represents the task point number index; The optimal path screening submodule screens the path combination with the minimum travel time according to the multi-path time values in the path travel time matrix, constructs the unit and task point travel sequence, and generates the optimal travel path set for the task.

4. The mine network operation and maintenance management system for coal mine development according to claim 3, characterized in that: The device status identification module includes: The data acquisition submodule obtains the temperature, voltage, and vibration values of the mining equipment at the task point, classifies and organizes them by equipment number, eliminates abnormal data, and obtains the parameter integration value; The interval judgment submodule calls three types of risk threshold intervals based on the parameter integration value, performs interval judgment and classification calculation on multiple types of parameters, and uses the formula: The abnormal deviation of the parameter is obtained by calculation, and a weighted score is formed according to the deviation value and the sensitivity coefficient to obtain the risk deviation coefficient; Among them, RS q Represents the risk offset coefficient of device q, OB qr represents the observation value of device q on parameter r, TR qr represents the risk threshold center value of device q on parameter r, SC r is the risk sensitivity coefficient of the rth type parameter, V qr Indicates the fluctuation intensity of device q on parameter r, where q represents the device number index and r represents the parameter category index; The risk screening submodule sets screening limits according to the risk deviation coefficient, eliminates low deviation devices, summarizes the remaining devices and corresponding parameters, and generates a risk device list.

5. The mine network operation and maintenance management system for coal mine development according to claim 4, characterized in that: The scheduling prioritization module includes: The path risk normalization submodule calls the path time and equipment risk data in the optimal pass path set of the task and the risk equipment list, normalizes the path time and equipment risk values respectively, obtains the normalized time value and the normalized risk level value, establishes corresponding two-dimensional data points, and generates a path normalized risk data pair; The urgency judgment submodule determines whether the time-consuming threshold and the risk level threshold are exceeded at the same time based on the path normalized risk data pair, marks the urgency of the task, establishes three types of task labels, and generates task urgency classification labels; The priority sequence generation submodule uses the task emergency classification label, calls the path normalization risk data pair of the intermediate task, and performs weighted calculation based on the number of task points and the operation and maintenance coverage value, using the formula: Calculate and obtain the comprehensive ranking score of the intermediate tasks, adjust the task order from high to low according to the score, and generate the priority sequence of coal mine scheduling tasks; Among them, PG a Indicates the comprehensive ranking score of the intermediate task a, TN a is the normalized time-consuming value of task a, RG a is the risk normalization value of task a, α is the time-consuming weighted index, β is the risk-weighted index, TP a Represents the number of task points for task a, CN a is the operation and maintenance coverage value of task a, |TP a -CN a | is the absolute value of the difference between the two, It is the sum of the product of time and risk of all intermediate tasks, a represents the task number index, e is the intermediate task set index, and m represents the number of intermediate tasks.

6. The mine network operation and maintenance management system for coal mine development according to claim 1, characterized in that: The system further comprises: The scheduling task issuing module calls the task sorting result after the conflict adjustment, generates a scheduling parameter field combination including number, path, equipment and type for the task sorting content, assembles it into an output instruction, and generates a mine network operation and maintenance scheduling instruction set; The mine network operation and maintenance scheduling instruction set includes a scheduling task number, a passage path information, associated equipment information, and a scheduling task type label.

7. The mine network operation and maintenance management system for coal mine development according to claim 6, characterized in that: The scheduling task issuing module includes: The scheduling path calculation submodule calls the task sorting result after conflict adjustment, extracts the start and end point coordinate values and path node numbers, reorganizes the path numbers based on the sorting order identifier, matches the task node numbers with the path node position index, filters the continuous path segments and binds the task numbers, and generates a task path sequence number set; The device matching determination submodule calls the path node information in the task path sequence number set, obtains the bound device number and operation status identifier, calculates the device continuous operation matching value and compares it with the node continuous operation matching threshold, selects the matching device number, and generates the path node device matching coefficient; The type field fusion submodule extracts the device type field code and the path number according to the device number in the path node device matching coefficient, concatenates the device type field and the path node number, and returns them to the original task number to generate a task field fusion combination value; The instruction assembly output submodule calls the task field fusion combination value, arranges it in ascending order by task number, adds the execution priority identifier, scheduling trigger flag and timestamp identifier, sets the output format field order according to the task number and writes it into the template structure to generate a mine network operation and maintenance scheduling instruction set.

8. A mine network operation and maintenance management method for coal mine development, characterized in that: The mine network operation and maintenance management system for coal mine development according to any one of claims 1 to 7 is implemented, comprising the following steps: S1: Obtain the location of the operation and maintenance unit and the coordinates of the task point, call the path segment length and the difficulty coefficient, sum the product of the path segment length and the difficulty coefficient and compare the time values to obtain the path time evaluation value; S2: Obtain equipment temperature, voltage, and vibration parameters, perform interval judgment on each parameter and the corresponding risk threshold, assign values, and perform weighted aggregation to obtain the equipment operation risk level value; S3: Call the time and risk data in the path time evaluation value and the equipment operation risk level value, perform a normalization process on the two data and determine the combined interval, mark high-time-consuming and high-risk tasks as urgent, and mark low-time-consuming and low-risk tasks as deferred, and sort the remaining tasks according to the weighted score, the number of task points and the coverage range to obtain the scheduling task priority score; S4: calling the task path point set in the scheduling task priority score value, performing path intersection extraction and overlapping segment statistics, marking the over-threshold path tasks and moving them backward, and obtaining the path overlap conflict adjustment amount; S5: Call the adjusted task order in the path overlap conflict adjustment amount, combine the task number, path point, device number and task type fields, and obtain the scheduling task parameter output.

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