A coal yard safety equipment management method and system based on environmental monitoring

Abstract

The present application relates to the technical field of coal yard safety management and environmental monitoring, and discloses a coal yard safety equipment management method and system based on environmental monitoring, comprising: collecting environmental data and equipment operation state data in real time; generating environment-operation state-equipment associated data set; after eliminating interference data caused by shutdown for maintenance and operation plan, marking data exceeding preset safety threshold in any point in the associated data set as abnormal; performing risk index calculation on the abnormally marked data to obtain the risk index; automatically matching the library based on the risk level to generate a safety equipment action list; and performing conflict detection on the action list, equipment maintenance work order and energy scheduling plan, and dynamically adjusting according to the safety priority-production guarantee-energy saving optimization principle. The present application effectively improves the real-time, accuracy, coordination and automation level of coal yard safety management.

Description

Technical Field

[0001] This invention relates to the technical field of coal yard safety management and environmental monitoring, and in particular to a coal yard safety equipment management method and system based on environmental monitoring. Background Technology

[0002] In recent years, intelligent and refined management of coal yards has become an important development trend in the industry. Coal yard management technology has gradually shifted from the traditional manual inspection and passive handling mode to a proactive intelligent management mode based on the Internet of Things, digital twins and big data analysis. For example, grid management technology is used to visualize the spatial information of coal yards to improve the efficiency of coal yard operations; or three-dimensional modeling technology is used to achieve accurate monitoring of coal pile information and optimization of coal blending schemes to improve the overall management efficiency of coal yards.

[0003] CN114841599A discloses a grid-based management method for coal yards, which only focuses on the visualization of coal yard spatial information and coal storage attributes, without involving the correlation analysis of coal yard environmental monitoring parameters and equipment operating status, making it difficult to proactively predict potential safety risks. CN116629779A discloses a three-dimensional model management method for coal yards, which, although providing relatively precise control over coal pile information, lacks the integrated analysis of real-time environmental parameters and safety equipment status, making it unable to timely and proactively identify coal yard safety hazards caused by environmental factors. Therefore, the above solutions are insufficient in terms of real-time monitoring of safety risks, proactive early warning, and the formulation and implementation of emergency response measures, and are unable to fully meet the practical needs of efficient and safe coal yard management.

[0004] In summary, existing coal yard management technologies generally suffer from insufficient integration of environmental data and equipment status, and weak proactive risk warning capabilities, making it difficult to effectively address the issues of rapid identification, response, and elimination of coal yard safety risks. The technical problem addressed by this invention is how to achieve the integrated analysis of coal yard environmental monitoring data and the operating status of safety equipment, thereby proactively identifying and assessing safety risks, and automatically generating safety equipment response measures that match the risk level, in order to achieve proactive, intelligent, and refined management of coal yard safety. Summary of the Invention

[0005] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0006] In view of the aforementioned existing problems, the present invention is proposed.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: multi-source sensor nodes are deployed in a grid pattern inside and outside the coal yard to collect environmental data and equipment operating status data in real time; Using a unified time base, environmental data, device operating status data, and control logs of security devices within 10 minutes before and after the end time of the current sliding window are synchronized and aligned to generate an associated dataset of environment-operating status-device; the control logs include device ID, action type, execution result, and timestamp; Based on the work plans of the production scheduling system and the maintenance management system, after removing interfering data caused by production stoppages, maintenance, and work plans, any data in the associated dataset that exceeds a preset safety threshold is marked as abnormal; including: when And continue When this happens, the data point is marked as an anomaly, where, For the first i Real-time measurements of environmental parameters. To preset a safety threshold, This is the margin coefficient. The duration threshold; for the infrared thermal image grayscale matrix IR Perform target segmentation and grayscale clustering, if continuous n The frame exists at a temperature higher than Aggregates with an area percentage ≥ β% are considered anomalies in their corresponding grid temperatures; among them, β is the threshold for determining high temperature in thermal imaging, and β is the minimum percentage threshold for high-temperature clusters to occupy the entire frame area. Calculate the risk index by performing a risk index calculation on the data marked as an anomaly; Based on an automatic risk level matching library, a list of safety equipment actions is generated, including starting and stopping sprinkler systems, adjusting ventilation volume, speed-limiting conveyor belts, area power outages, and audible and visual alarms. This includes storing rule entries in the matching library in the form of risk level → action sequence. Each rule contains triggering conditions, action queues, execution sequence, and target effects. The action queue format is <equipment ID, action type, target value, duration>. When multiple rules satisfy the same risk level, they are selected based on priority coefficients. Choose to make the weighted residual risk value The minimum solution generates a corresponding action list; among which, To execute the first Risk reduction amount after each action; The action list is checked for conflicts with equipment maintenance work orders and energy dispatch plans. If conflicts exist, adjustments are made dynamically according to the principles of safety priority, production assurance, and energy-saving optimization. This includes: Compare each device action in the action list with the current maintenance isolation list. If the device is under maintenance isolation, skip the action and record the reason. Invoke the energy dispatch plan and calculate the incremental impact of the action sequence on the power load. If |Δ P If the load exceeds the upper limit of the energy dispatch plan, priority will be given to retaining the equipment operation with the highest risk reduction efficiency. Based on the principles of safety priority, production assurance, and energy conservation optimization, the remaining actions are reordered, and the final sequence of execution instructions is output. in, For the first k The power requirements of the equipment when the new operation is running. For the first k The reference power of the equipment under current operating conditions.

[0008] As a preferred embodiment of the coal yard safety equipment management method based on environmental monitoring described in this invention, the step of deploying multi-source sensor nodes in a grid-like manner inside and outside the coal yard includes: A three-dimensional layered point layout method is adopted, with at least one set of temperature-gas composite sensors deployed in the surface, middle and base layers of the coal pile. The sensor nodes are evenly distributed in a 5 m × 5 m grid in the planar direction and form a self-healing topology through a ZigBee-Mesh wireless network; A 360° rotating infrared thermal imager is installed above the coal yard to obtain the temperature field distribution on the surface of the coal pile; Connect all sensor nodes to the IEEE 1588 precision clock synchronization network to ensure that the data timestamp error is less than 1 second. The coal pile surface layer is ≤ 0.5 m, the middle layer is 0.5 m to 2 m, and the coal pile base is ≥ 2 m.

[0009] As a preferred embodiment of the coal yard safety equipment management method based on environmental monitoring described in this invention, the environmental data includes at least temperature, humidity, wind speed, wind direction, dust concentration, carbon monoxide concentration, methane gas concentration, and infrared thermal image grayscale matrix. The equipment operating status data includes at least the winch torque, water pump outlet pressure, ventilator speed, transmission belt linear speed, motor current, and bearing temperature. The equipment operating status data is obtained by collecting data from safety equipment, which includes at least a winch, a water spraying device, a ventilator, and a conveyor belt. The equipment control commands for the safety equipment are issued via industrial Ethernet.

[0010] As a preferred embodiment of the coal yard safety equipment management method based on environmental monitoring described in this invention, the generation of the associated dataset of environment-operating status-equipment includes: Define the set of environment parameters as ; Where T is temperature, H is humidity, WS is wind speed, and WD is wind direction. Dust concentration, This refers to the carbon monoxide concentration. The concentration of methane gas. This is the grayscale matrix of an infrared thermal image; Define the set of running status parameters as follows ; in, For the output torque of the winch, This refers to the outlet pressure of the sprinkler pump. This refers to the fan speed. To transmit the linear speed of the belt, For the drive motor current, For bearing temperature; Define a device control log set L, whose fields include device ID, action type, execution result, and timestamp; Each record is stored in the format <E, O, L, t, ID>, where t is the IEEE 1588 synchronization timestamp and ID is the device number.

[0011] As a preferred embodiment of the coal yard safety equipment management method based on environmental monitoring described in this invention, a risk index R is calculated for the data marked as abnormal, including:

[0012] in, For the first i Real-time measurements of environmental parameters. iThis is an index of environmental parameter categories, where m represents the total number of environmental parameter categories involved in the risk calculation. Set a preset safety threshold for it. For the first i The weighting coefficients of the class environment parameters satisfy the following: ; When R ≥ 30%, it is risk level I, which is high risk. In this case, the machine should be shut down immediately, the area should be powered off, continuous spray cooling should be implemented, and a 110 dB alarm should be triggered. When 10% ≤ R < 30%, it is classified as risk level II, which is medium risk. In this case, sprinkler and ventilation equipment should be activated, belt speed reduced, and an early warning issued. When R < 10%, it is classified as risk level III, which is low-risk. In this case, ventilation equipment will be turned on and risk information will be pushed to the back-end terminal.

[0013] As a preferred embodiment of the coal yard safety equipment management system based on environmental monitoring according to the present invention, it includes: one or more processors; The memory stores operable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, including the flow of the coal yard safety equipment management method based on environmental monitoring as described above.

[0014] As a preferred embodiment of the computer-readable medium for storing software according to the present invention, the software includes instructions executable by one or more computers, the instructions causing the one or more computers to perform operations, the operations including the process of the coal yard safety equipment management method based on environmental monitoring as described above.

[0015] The beneficial effects of this invention are: 1. By deploying multi-source sensor nodes in a grid pattern inside and outside the coal yard, environmental data and equipment operating status data are collected in real time, realizing comprehensive, multi-dimensional, and real-time perception of the coal yard safety environment and equipment operating status. This solves the problems of data lag and low accuracy in traditional manual inspections, thereby providing a rich and accurate data foundation for subsequent safety management and risk assessment, and effectively improving the real-time and comprehensiveness of data acquisition. 2. By synchronizing and aligning environmental data, equipment operating status data, and safety equipment control logs within a 10-minute range before and after the current sliding window ends using a unified time benchmark, precise correlation between environmental parameters and equipment operating status data is achieved. This ensures temporal consistency and logical correlation between data from different sources, solving the problem of poor data correlation and difficulty in accurately identifying causal relationships caused by the lack of a unified benchmark in traditional data collection. This provides accurate and effective data support for subsequent abnormal event analysis and improves the accuracy of correlation analysis between environmental data and equipment status data. 3. By eliminating interference data generated during shutdowns, maintenance, and planned operations, it effectively distinguishes between actual safety risks and interference from planned human events, avoiding false alarms and interference caused by normal maintenance, shutdowns, or planned operations. This effectively solves the problems of high false alarm rates and inaccurate anomaly identification in traditional safety monitoring systems, thereby improving the accuracy of anomaly monitoring and marking, effectively reducing false alarm rates, and enhancing the accuracy of risk assessment. 4. By transforming complex and abstract safety conditions into intuitive and quantifiable risk indicators, the safety risk level of coal yards can be accurately identified and quantitatively assessed, effectively solving the problem of lack of objective basis in traditional subjective judgment of risk levels, and achieving the beneficial effects of objectivity, standardization and refinement of risk assessment. 5. By automatically formulating corresponding safety response measures based on specific risk levels, the traditional safety emergency measures are characterized by slow response, strong reliance on experience, and lack of consistency in plans. This enables the rapid and accurate implementation of safety control actions, achieving the beneficial effects of automation, rapid response, and precise matching of control measures with risks. 6. By performing conflict detection on the generated list of safety equipment actions, equipment maintenance work orders, and energy scheduling plans, and dynamically adjusting them according to the principles of safety priority, production assurance, and energy-saving optimization, the coordination and unification of equipment control commands with actual production conditions and energy scheduling are achieved. This resolves potential conflicts between safety management measures and production tasks and energy use, and avoids excessive impact on production progress or unreasonable energy use due to the implementation of safety measures. Thus, under the premise of ensuring safety, the optimal coordination of production and energy scheduling is achieved, ultimately achieving the beneficial effect of efficient coordination and optimization of safety management measures with production and energy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1This is a flowchart illustrating the coal yard safety equipment management method based on environmental monitoring as described in this invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0018] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0019] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0020] According to an embodiment of the present invention, in combination Figure 1 The flowchart shown illustrates a coal yard safety equipment management method based on environmental monitoring, which specifically includes the following steps: S1. Deploy multi-source sensor nodes in a grid pattern inside and outside the coal yard to collect environmental data and equipment operating status data in real time. Note the following in this step: A three-dimensional layered point layout method is adopted, with at least one set of temperature-gas composite sensors deployed in the surface, middle and base layers of the coal pile. Sensor nodes are evenly distributed in a 5 m × 5 m grid in the planar direction and form a self-healing topology through a ZigBee-Mesh wireless network. A 360° rotating infrared thermal imager is installed above the coal yard to obtain the temperature field distribution on the surface of the coal pile; Connect all sensor nodes to the IEEE 1588 precision clock synchronization network to ensure that the data timestamp error is less than 1 second. The coal pile surface layer is ≤ 0.5 m, the middle layer is 0.5 m to 2 m, and the coal pile base is ≥ 2 m.

[0021] As an example, environmental data includes at least temperature, humidity, wind speed, wind direction, dust concentration, carbon monoxide concentration, methane gas concentration, and infrared thermal image grayscale matrix.

[0022] As an example, equipment operating status data should include at least the winch torque, water pump outlet pressure, fan speed, transmission belt linear speed, motor current, and bearing temperature.

[0023] It should be noted that the equipment operating status data is obtained by collecting data from safety equipment, which includes at least winches, sprinkler systems, ventilators, and conveyor belts. The equipment control commands for the safety equipment are issued via industrial Ethernet.

[0024] S2. Using a unified time base, synchronize and align the environmental data, device operating status data, and control logs of the security device within 10 minutes before and after the end time of the current sliding window, generating a correlated dataset of environment, operating status, and device. Note that the following should be noted in this step: Define the set of environment parameters as ; Where T is temperature, H is humidity, WS is wind speed, and WD is wind direction. Dust concentration, This refers to the carbon monoxide concentration. The concentration of methane gas. This is the grayscale matrix of an infrared thermal image; Define the set of running status parameters as follows ; in, For the output torque of the winch, This refers to the outlet pressure of the sprinkler pump. This refers to the fan speed. To transmit the linear speed of the belt, For the drive motor current, For bearing temperature; Define a device control log set L, whose fields include device ID, action type, execution result, and timestamp; Each record is stored in the format <E, O, L, t, ID>, where t is the IEEE 1588 synchronization timestamp and ID is the device number.

[0025] S3. Based on the work plans of the production scheduling system and maintenance management system, after removing interfering data caused by production stoppages, maintenance, and work plans, mark any data in the associated dataset that exceeds a preset safety threshold as an anomaly. Note that the following should be noted in this step: (1) Perform threshold comparisons for each type of real-time environmental parameter. And continue When this happens, mark the data point as an anomaly; in, For the first i Real-time measurements of environmental parameters. To preset a safety threshold, This is the margin coefficient. Set a duration threshold (e.g., 60 s, to filter out false alarms caused by transient data fluctuations); (2) The infrared thermal image grayscale matrix IR is processed as follows to determine whether there are anomalous temperature clusters: The target segmentation algorithm is used to segment the thermal image grayscale matrix IR to extract the grayscale information of the coal pile area; Then, gray-scale clustering analysis is performed on the segmented coal pile ash-scale information to identify high-temperature regions; If continuous n The frame exists at a temperature higher than If the clusters have an area ratio ≥ β%, then the corresponding grid temperature is considered an anomaly. in, β is the threshold for judging high temperature in thermal imaging (which can be determined based on the critical temperature of coal spontaneous combustion risk), and β is the minimum percentage threshold of high temperature agglomerates occupying the entire frame area (e.g., 5%). The data points that are clearly marked as abnormal will be recorded and transmitted to the next step S4 for risk index calculation, so as to realize the automated risk response and management of subsequent coal yard safety equipment.

[0026] It should be noted that the work plan of the production scheduling system and maintenance management system in this embodiment includes the following: The work plans in the production scheduling system include, but are not limited to, planned tasks related to coal yard production and operation such as coal pile turning work plans, coal transfer work plans, and equipment shutdown and start-up work plans; The equipment maintenance work orders in the maintenance management system include, but are not limited to, routine equipment maintenance work orders, temporary maintenance work orders, and equipment shutdown repair work orders, as well as other information related to equipment maintenance tasks.

[0027] Furthermore, the specific data regarding interference caused by production shutdowns, maintenance, and work schedules include: Abnormal fluctuations in coal yard environmental data caused by human factors during planned turning and transfer operations; Abnormal data fluctuations caused by changes in the operating status of relevant equipment during inspection or maintenance operations; Other production and maintenance activities that are clearly documented in the work plan and are expected to affect environmental and equipment status data.

[0028] In an optional implementation, the method for removing interfering data includes: Compare and analyze the planned task time periods provided in the work plan with the timestamps in the associated dataset; If the timestamps of the environmental data and equipment status data recorded in the associated dataset fall within the time period of the above-mentioned planned task, it is determined that the data point may be subject to human interference. The associated data records that overlap with the planned task time period are automatically marked as interference data and removed from subsequent abnormal data detection and analysis.

[0029] S4. Calculate the risk index R for the data marked as anomaly. Note the following in this step: For example, the mathematical expression of the risk index R is as follows:

[0030] in, For the first i Real-time measurements of environmental parameters. i This is an index of environmental parameter categories, where m represents the total number of environmental parameter categories involved in the risk calculation. Set a preset safety threshold for it. For the first i The weighting coefficients of the class environment parameters satisfy the following: ; When R ≥ 30%, it is risk level I, which is high risk. In this case, the machine should be shut down immediately, the area should be powered off, continuous spray cooling should be implemented, and a 110 dB alarm should be triggered. When 10% ≤ R < 30%, it is classified as risk level II, which is medium risk. In this case, sprinkler and ventilation equipment should be activated, belt speed reduced, and an early warning issued. When R < 10%, it is classified as risk level III, which is low-risk. In this case, ventilation equipment will be turned on and risk information will be pushed to the back-end terminal.

[0031] S5. Based on the risk level automatic matching library, generate a list of safety equipment actions including starting and stopping the sprinkler system, adjusting ventilation volume, speed-limiting conveyor belts, area power outages, and audible and visual alarms. Note that the following should be noted in this step: (1) Construct and maintain an automatic risk level matching library. This matching library stores rule entries in the form of "risk level → action sequence". Each rule entry includes: Triggering conditions: Based on the risk level determined by the risk index R, it is specifically divided into Level I (high risk), Level II (medium risk) and Level III (low risk); Action Queue: Based on the risk level, the specific actions that the corresponding safety devices need to perform are defined. The queue format is <Device ID, Action Type, Target Value, Duration>, where: The device ID is used to identify a specific security device; The action type refers to the action that the safety equipment needs to perform, such as "start / stop", "adjust speed", "adjust ventilation volume", "speed limit", "area power failure", and "activate audible and visual alarm". The target value is the set value that the equipment should achieve after the action is executed, such as the specific value of the belt speed, the pressure value of the water pump, and the speed of the ventilator. Duration is the length of time that the device needs to perform the action. Execution sequence: the logical order and temporal relationship between the actions in the action queue; Target effect: The expected reduction in safety risks or the expected state of safety achieved after the action is executed; (2) Determine the risk level based on the risk index R value: When the risk index R ≥ 30%, it is classified as Risk Level I; When the risk index is 10% ≤ R < 30%, it is classified as risk level II; When the risk index R < 10%, it is classified as risk level III; (3) Based on the risk level determined above, retrieve all rule entries that meet the risk level from the matching database: If only one rule entry satisfies the current risk level, then the action queue corresponding to that entry will be used directly. If multiple rule entries simultaneously satisfy the current risk level, calculate the weighted residual risk value R' for each rule entry, and select the optimal action sequence based on the calculation results. (4) When multiple rule entries meet the same risk level, the process of implementing the preferred solution is as follows: Calculate the weighted residual risk value R' after the execution of each rule entry:

[0032] Where R' represents the weighted residual risk value after the rule is executed. Let j be the priority coefficient of the j-th rule under this risk level. This represents the amount of risk reduction after executing the sequence of actions listed in rule j, i.e., the difference in the risk index before and after the rule is executed; It should be noted that the priority coefficient It is derived from historical risk data and risk control effectiveness evaluation data, and is determined through historical data analysis and review by safety management experts. Compare the R' values ​​of all rule entries and select the rule entry with the smallest R' value as the optimal solution for executing the safety device action in this case; (5) Generate the final list of safety equipment actions based on the preferred rule entries. This list of actions specifically includes: The device ID of the device performing the action; The specific actions that each piece of equipment needs to perform include, for example, starting or stopping the sprinkler system, adjusting the speed of the ventilation fan, limiting the speed of the belt conveyor, causing a partial power outage in the area, and activating the high-decibel alarm or warning lights on site. The specific target values ​​and setting conditions for each action, such as spray pressure, ventilation volume, and conveyor belt linear speed limit; The precise duration for which each action needs to be performed; The sequence of actions and their specific execution relationships; (6) The safety equipment action list generated above is sent to the safety equipment execution control unit via industrial Ethernet in a unified data format, and the equipment execution unit is required to return a confirmation signal for action execution; (7) The action execution feedback results are synchronized back to the safety management platform to form a closed-loop system for coal yard safety management.

[0033] S6. Perform conflict detection between the action list and equipment maintenance work orders and energy dispatch plan. If conflicts exist, dynamically adjust according to the principles of safety priority, production assurance, and energy-saving optimization. Note that the following points should be noted in this step: (1) Perform collision detection, specifically including: Get the list of devices in the maintenance management system that are currently under maintenance isolation. This list clearly shows all devices that have been locked and isolated due to maintenance or repair. Compare the device ID corresponding to each action record in the safety equipment action list with the maintenance and isolation list one by one; When a device ID is detected to exist in both the action list and the maintenance isolation list, it indicates that the device is currently unable to perform the preset action, thus skipping the corresponding action of the device. The system automatically records the specific reason for skipping the action, that is, records that the device is in maintenance isolation and cannot perform the action. (2) Invoking the energy dispatch plan to detect incremental power load, specifically including: Obtain the upper limit of the current power load margin P given in the current energy dispatch system of the coal yard. max As currently permitted limits on energy use; Calculate the overall power load increment after the remaining action sequences in the action list are executed. The calculation formula is shown in the following example:

[0034] in, This represents the power requirement for the k-th device to operate after the action sequence is executed. The baseline power of the k-th device under current operating conditions before the execution of the action sequence; If the calculated absolute value of the overall power load increment is |Δ P |Exceeded the upper limit of the load margin P given by the energy dispatch plan. max Then, all actions to be executed are sorted according to risk reduction efficiency, and the actions of the equipment with the highest risk reduction efficiency are retained first, until the adjusted action sequence meets the load margin constraint of the energy dispatch plan. (3) Dynamically adjust the action execution sequence according to the principle of "safety first - production assurance - energy saving optimization", specifically including: Safety must be the top priority, meaning that the minimum safety requirements for the current coal yard environment must be met. Based on meeting safety requirements, and according to the current production scheduling tasks and production support needs, the execution priority of the remaining actions in the action sequence is adjusted to ensure the normal operation of production tasks. On the basis of ensuring safety and smooth production tasks, energy consumption optimization of action sequence is then considered. Actions with high energy consumption are appropriately adjusted, delayed, or their operating parameters are reduced to achieve energy-saving goals. (4) After the above dynamic adjustment, the final output sequence of execution instructions specifically includes: The specific device ID of the equipment involved in each action; The specific types of actions each piece of equipment performs (such as start / stop, speed adjustment, conveyor belt speed limit, area power failure, alarm activation, etc.). The specific target parameters for each action (such as the specific set values ​​for water spraying pressure, fan speed, belt running speed, etc.); The defined duration of each action; The specific sequence of actions after comprehensive optimization for safety, production, and energy conservation; Each action executes the necessary logical dependencies and timing arrangements; (5) The optimized execution instruction sequence is sent to the coal yard field control unit via industrial Ethernet using a preset data communication protocol, and the equipment field control unit is required to return feedback information confirming execution within a specified time to achieve closed-loop control of safe actions.

[0035] As an example, the original list of security device actions is defined as shown in the table below: Table 1. Original Safety Equipment Action List

[0036] Maintenance and isolation comparison: Equipment D03 is in the maintenance and isolation list → Action A3 skipped, record the reason: "Conveyor belt 2# is under maintenance and isolation"; Load increment calculation: Calculate the load increment ΔP = 25.1 kW for the remaining action sequence, |ΔP| = 25.1 kW > P max =15kW → Energy load constraint optimization needs to be performed; The optimal action under load constraints is shown in the table below: Table 2. Optimal Actions under Load Constraints

[0037] First, retain the action that maximizes the efficiency in reducing unit risk: D05 → D01 → D04; Then calculate the cumulative load: D05: ΔP = +0.1 kW; D01: ΔP = 15.1 kW; It is close to P max After adding D04, ΔP = 13.1 kW ≤ 15 kW; Action D02 will cause ΔP to exceed the limit → execution will be suspended; For example, the order can be sorted as "safety first - production assurance - energy saving optimization": Essential safety actions: D05 (alarm) → D01 (sprinkler pump); In conjunction with safety and load reduction: D04 (Regional power outage); Production safeguard action: D02 (ventilator speed adjustment) is temporarily suspended and will be executed when the load allows; The final sequence of executed instructions is shown in the table below: Table 3. Final Execution Instruction Sequence Table

[0038] The real-time load increment ΔP of execution sequence 1~3 is 13.1 kW, which satisfies P. max ; The system automatically records the reasons and timestamps for skipping D03 and delaying D02, for auditing and traceability.

[0039] It should be noted that, through the aforementioned conflict detection mechanism, energy load calculation method, and comprehensive optimization and adjustment rules, this invention enables precise coordination between equipment safety actions and actual production operations and energy dispatch plans, thereby achieving efficient and feasible coal yard safety management.

[0040] Preferably, through the above steps, the present invention realizes a complete intelligent and automated solution for coal yard safety management, from environmental data collection and risk identification and assessment to the implementation of safety control measures and coordination with production energy, effectively improving the real-time performance, accuracy, coordination and automation level of coal yard safety management.

[0041] The aforementioned method for synchronizing and aligning environmental data, equipment operating status data, and control logs of safety devices within 10 minutes before and after the end time of the current sliding window can be achieved using existing technologies and methods, and will not be elaborated upon in this example.

[0042] In addition to the above embodiments, other aspects of the present invention also propose a coal yard safety equipment management system based on environmental monitoring, including: one or more processors and a memory.

[0043] The memory is used to store operable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, including the flow of the coal yard safety equipment management method based on environmental monitoring of the foregoing embodiments, especially... Figure 1 The flowchart of the method is shown.

[0044] Other aspects disclosed in the embodiments of the present invention also propose a computer-readable medium for storing software including instructions executable by one or more computers, which, upon execution, cause the one or more computers to perform operations including the flow of the coal yard safety equipment management method based on environmental monitoring of the foregoing embodiments, particularly... Figure 1 The flowchart of the method is shown.

[0045] It should be recognized that embodiments of the present invention may be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable storage medium.

[0046] The method can be implemented using standard programming techniques, including a non-transitory computer-readable storage medium configured with a computer program in the computer program, wherein the storage medium is configured such that the computer operates in a specific and predefined manner.

[0047] Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system; however, if required, the program can be implemented in assembly or machine language.

[0048] In any case, the language can be either compiled or interpreted.

[0049] Furthermore, for this purpose, the program can run on programmed application-specific integrated circuits.

[0050] The processes described herein (or variations and / or combinations thereof) can be executed under the control of one or more computer systems configured with executable instructions, and can be implemented by hardware or a combination thereof as code (e.g., executable instructions, one or more computer programs, or one or more applications) that commonly executes on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.

[0051] Furthermore, the method can be implemented in any suitable computing platform, including but not limited to personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, standalone or integrated computer platforms, or in communication with charged particle tools or other imaging devices.

[0052] Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether portable or integrated into a computing platform, such as a hard disk, optical read and / or write storage medium, RAM, ROM, etc., such that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the processes described herein.

[0053] Furthermore, machine-readable code, or parts thereof, can be transmitted via wired or wireless networks.

[0054] When such media includes instructions or programs that combine with a microprocessor or other data processor to implement the steps described above, the invention described herein includes these and other different types of non-transitory computer-readable storage media.

[0055] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for managing safety equipment in coal yards based on environmental monitoring, characterized in that, include: Multi-source sensor nodes are deployed in a grid pattern inside and outside the coal yard to collect environmental data and equipment operating status data in real time. Using a unified time base, environmental data, device operating status data, and control logs of security devices within 10 minutes before and after the end time of the current sliding window are synchronized and aligned to generate an associated dataset of environment-operating status-device; the control logs include device ID, action type, execution result, and timestamp; Based on the work plans of the production scheduling system and maintenance management system, after removing interfering data caused by production stoppages, maintenance, and work plans, any data in the associated dataset that exceeds a preset safety threshold is marked as abnormal; including: when And continue When this happens, the data point is marked as an anomaly, where, For the first i Real-time measurements of environmental parameters. To preset a safety threshold, This is the margin coefficient. The duration threshold; for the infrared thermal image grayscale matrix IR Perform target segmentation and grayscale clustering, if continuous n The frame exists at a temperature higher than If clusters exist and their area percentage is ≥ β%, then the corresponding grid temperature is considered an anomaly; among them, β is the threshold for determining high temperature in thermal imaging, and β is the minimum percentage threshold for high-temperature clusters to occupy the entire frame area. Perform risk index calculation on the data marked as anomalies to obtain the risk index; Based on an automatic risk level matching library, a list of safety equipment actions is generated, including starting and stopping sprinkler systems, adjusting ventilation volume, speed-limiting conveyor belts, area power outages, and audible and visual alarms. This includes storing rule entries in the matching library in the form of risk level → action sequence. Each rule contains triggering conditions, action queues, execution sequence, and target effects. The action queue format is <equipment ID, action type, target value, duration>. When multiple rules satisfy the same risk level, they are selected based on priority coefficients. Choose to make the weighted residual risk value The minimum solution generates a corresponding action list; among which, To execute the first Risk reduction amount after each action; The action list is checked for conflicts with equipment maintenance work orders and energy dispatch plans. If conflicts exist, adjustments are made dynamically according to the principles of safety priority, production assurance, and energy-saving optimization. This includes: Compare each device action in the action list with the current maintenance isolation list. If the device is under maintenance isolation, skip the action and record the reason. Invoke the energy dispatch plan and calculate the incremental impact of the action sequence on the power load. If |Δ P If the load exceeds the upper limit of the energy dispatch plan, priority will be given to retaining the equipment operation with the highest risk reduction efficiency. Based on the principles of safety priority, production assurance, and energy conservation optimization, the remaining actions are reordered, and the final sequence of execution instructions is output. in, For the first k The power requirements of the equipment when the new operation is running. For the first k The reference power of the equipment under current operating conditions.

2. The coal yard safety equipment management method based on environmental monitoring according to claim 1, characterized in that, The deployment of multi-source sensor nodes in a grid pattern inside and outside the coal yard includes: A three-dimensional layered point layout method is adopted, with at least one set of temperature-gas composite sensors deployed in the surface, middle and base layers of the coal pile. The sensor nodes are evenly distributed in a 5 m × 5 m grid in the planar direction and form a self-healing topology through a ZigBee-Mesh wireless network; A 360° rotating infrared thermal imager is installed above the coal yard to obtain the temperature field distribution on the surface of the coal pile; Connect all sensor nodes to the IEEE 1588 precision clock synchronization network to ensure that the data timestamp error is less than 1 second. The coal pile surface layer is ≤ 0.5 m, the middle layer is 0.5 m to 2 m, and the coal pile base is ≥ 2 m.

3. The coal yard safety equipment management method based on environmental monitoring according to claim 1 or 2, characterized in that, The environmental data includes at least temperature, humidity, wind speed, wind direction, dust concentration, carbon monoxide concentration, methane gas concentration, and infrared thermal image grayscale matrix. The equipment operating status data includes at least the winch torque, water pump outlet pressure, ventilator speed, transmission belt linear speed, motor current, and bearing temperature. The equipment operating status data is obtained by collecting data from safety equipment, which includes at least a winch, a water spraying device, a ventilator, and a conveyor belt. The equipment control commands for the safety equipment are issued via industrial Ethernet.

4. The coal yard safety equipment management method based on environmental monitoring according to claim 1, characterized in that, The associated dataset of the generation environment, operating status, and device includes: Define the set of environment parameters as ; Where T is temperature, H is humidity, WS is wind speed, and WD is wind direction. Dust concentration, This refers to the carbon monoxide concentration. The concentration of methane gas. This is the infrared thermal image grayscale matrix; Define the set of running status parameters as follows ; in, For the output torque of the winch, This refers to the outlet pressure of the sprinkler pump. This refers to the fan speed. To transmit the linear speed of the belt, For the drive motor current, For bearing temperature; Define a device control log set L, whose fields include device ID, action type, execution result, and timestamp; Each record is stored in the format <E, O, L, t, ID>, where t is the IEEE 1588 synchronization timestamp and ID is the device number.

5. The coal yard safety equipment management method based on environmental monitoring according to claim 4, characterized in that, A risk index R is calculated by performing a risk index calculation on the data marked as an anomaly, which includes: in, For the first i Real-time measurements of environmental parameters. i This is an index of environmental parameter categories, where m represents the total number of environmental parameter categories involved in the risk calculation. Set a preset safety threshold for it. For the first i The weighting coefficients of the class environment parameters satisfy the following: ; When R ≥ 30%, it is risk level I, which is high risk. In this case, the machine should be shut down immediately, the area should be powered off, continuous spray cooling should be implemented, and a 110 dB alarm should be triggered. When 10% ≤ R < 30%, it is classified as risk level II, which is medium risk. In this case, sprinkler and ventilation equipment should be activated, belt speed reduced, and an early warning issued. When R < 10%, it is classified as risk level III, which is low-risk. In this case, ventilation equipment will be turned on and risk information will be pushed to the back-end terminal.

6. A coal yard safety equipment management system based on environmental monitoring, characterized in that, include: One or more processors; The memory stores operable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, including the flow of the coal yard safety equipment management method based on environmental monitoring as described in any one of claims 1 to 5.

7. A computer-readable medium for storing software, characterized in that: The software includes instructions executable by one or more computers, which, through execution, cause the one or more computers to perform operations, including the flow of the coal yard safety equipment management method based on environmental monitoring as described in any one of claims 1 to 5.

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