Coal mine emergency early warning method and system for preventing emergency accidents

Abstract

The invention relates to the technical field of intelligent emergency, and discloses a coal mine emergency early warning method and system for preventing emergency accidents, and the method comprises the steps: deploying a plurality of sensor nodes in a coal mine; sampling the environmental parameters of the coal mine through the plurality of sensor nodes, and adjusting the sampling rate of the plurality of sensor nodes according to the environmental parameters of the coal mine; sending the environmental parameters of the coal mine to a preset distributed edge computing node; calculating an emergency accident risk index according to the environmental parameters of the coal mine; and when the emergency accident risk index is higher than a preset threshold value, sending an emergency early warning signal to mobile terminals of a plurality of workers in the coal mine. According to the invention, through the reasonable configuration of the sensor nodes and the edge computing nodes and the intelligent data management and analysis process, the resource configuration efficiency in the coal mining process is improved, the waste of manpower and material resources caused by false alarm or late alarm is reduced, and meanwhile, the rescue cost after an accident occurs is also reduced.

Description

Technical Field

[0001] The present invention relates to the field of smart emergency technology, and more specifically, to an emergency warning method and system for coal mines for preventing emergency accidents. Background Art

[0002] Safety is the primary consideration in coal mining. Due to the complexity and danger of the coal mining environment, emergency accidents such as gas explosion, coal dust explosion, roof collapse, etc. pose a huge threat to the life safety of workers.

[0003] Traditional coal mine safety monitoring methods usually rely on single sensors at fixed locations, which can detect environmental parameters in a specific area, such as temperature, humidity, gas concentration, etc. However, this type of monitoring method has certain limitations: first, the location of the sensor arrangement is relatively fixed, making it difficult to fully cover the entire coal mine environment; second, data collection and processing are often concentrated in ground stations or central servers, which may cause data transmission delays and affect the real-time nature of the early warning system; third, the fixed sampling rate may not be able to adapt to the changing requirements for monitoring accuracy in different environments, thereby reducing the accuracy of early warnings.

[0004] Therefore, there is a need for a new emergency warning method and system for coal mines to prevent emergency accidents, which can combine multi-sensor networks, adaptive sampling, edge computing and intelligent warning mechanisms, aiming to overcome the shortcomings of existing technologies and provide more reliable technical support for coal mine safety production. Summary of the invention

[0005] In order to solve the above-mentioned technical problems, the present application is proposed to provide an emergency warning method and system for coal mines to prevent emergency accidents, aiming to overcome the deficiencies in the existing technology and provide more reliable technical support for safe production in coal mines.

[0006] In a first aspect, the present invention provides an emergency warning method for coal mines for preventing emergency accidents, comprising: deploying multiple sensor nodes in a coal mine; sampling the environmental parameters of the coal mine through the multiple sensor nodes, and adjusting the sampling rates of the multiple sensor nodes according to the environmental parameters of the coal mine; sending the environmental parameters of the coal mine to a preset distributed edge computing node through a preset communication protocol; calculating an emergency accident risk index on the distributed edge computing node according to the environmental parameters of the coal mine, the emergency accident risk index indicating the probability of a preset type of emergency accident occurring; when the emergency accident risk index is higher than a preset threshold, sending an emergency warning signal to mobile terminals of multiple staff members in the coal mine.

[0007] Optionally, in the aforementioned coal mine emergency warning method for preventing emergency accidents, adjusting the sampling rate of the multiple sensor nodes according to the environmental parameters of the coal mine includes: calculating the change rate of the environmental parameters of the coal mine, wherein the environmental parameter sampled by the i-th sensor node at time t among the multiple sensor nodes is x i (t), the rate of change of the environmental parameters sampled by the i-th sensor node at time t is Δx i (t); Calculate the sampling rate of the multiple sensor nodes Among them, α is the preset adjustment coefficient, f base is the preset reference sampling rate, N is the number of the multiple sensor nodes, and w i is the preset weight value corresponding to the i-th sensor node, x i (D) is the preset benchmark sampling parameter of the i-th sensor node.

[0008] Optionally, in the aforementioned coal mine emergency warning method for preventing emergency accidents, sampling the environmental parameters of the coal mine through the multiple sensor nodes includes: detecting the data transmission power of the multiple sensor nodes and the distance between the distributed edge computing nodes, wherein the data transmission power of the i-th sensor node at time t is P i (t), and the distance between it and the distributed edge computing node is D i (t); Detect the remaining power of the multiple sensor nodes, wherein the remaining power of the i-th sensor node at time t is S i (t); detecting the load L(t) of the data transmission network to which the plurality of sensor nodes are connected; establishing a power consumption model for the plurality of sensor nodes: Wherein, E(t) represents the total power consumption of the multiple sensor nodes at time t, β and γ are preset balance coefficients; the data transmission power of at least one sensor node among the multiple sensor nodes is adjusted so that the total power consumption E(t) of the multiple sensor nodes at time t does not exceed the preset power upper limit.

[0009] Optionally, in the aforementioned emergency warning method for coal mines for preventing emergency accidents, before adjusting the data transmission power of at least one sensor node among the multiple sensor nodes, the emergency warning method for coal mines for preventing emergency accidents also includes: detecting the power supply situation of the coal mine; detecting the situation of electrical equipment in the coal mine; and setting the power upper limit according to the power supply situation and the situation of electrical equipment in the coal mine.

[0010] Optionally, in the aforementioned emergency warning method for coal mines to prevent emergency accidents, before adjusting the data transmission power of at least one sensor node among the multiple sensor nodes, the emergency warning method for coal mines to prevent emergency accidents also includes: detecting the data transmission quality of the multiple sensor nodes at time t and the data transmission quality at time t-1, wherein the data transmission quality of the i-th sensor node at time t is Q(t), and the data transmission quality at time t-1 is Q(t-1); detecting the instantaneous power consumption of the multiple sensor nodes at time t, wherein the instantaneous power consumption E of the i-th sensor node at time t is i (t); Calculate the pheromone concentration of the multiple sensor nodes at time t, where the pheromone concentration of the i-th sensor node at time t Wherein, T(t-1) is the pheromone concentration of the i-th sensor node at time t-1, the pheromone concentration of the i-th sensor node at the initial time is a fixed value, ρ is a preset information evaporation coefficient, 0<ρ<1, and μ is a preset proportional factor; according to the pheromone concentrations of the multiple sensor nodes at time t, the at least one sensor node is selected from the multiple sensor nodes.

[0011] Optionally, in the aforementioned coal mine emergency warning method for preventing emergency accidents, the data transmission power of at least one sensor node among the multiple sensor nodes is adjusted, including: when the data transmission power of the i-th sensor node needs to be adjusted, calculating the difference ΔE between the total power consumption E(t) of the multiple sensor nodes at time t and the total power consumption E(t-1) at time t-1; calculating the data transmission power of the i-th sensor node at time t+1 Among them, E max represents the power upper limit, A(t) is a preset environmental sensitivity factor, and represents the influence of the environment of the coal mine on the data transmission efficiency.

[0012] Optionally, in the aforementioned coal mine emergency warning method for preventing emergency accidents, when calculating the data transmission power of the i-th sensor node at time t+1, Previously, the emergency warning method for coal mines to prevent emergencies also included: detecting the temperature, humidity and dust concentration of the coal mine at time t; and calculating the value of the environmental sensitivity factor A(t) based on the temperature, humidity and dust concentration of the coal mine at time t.

[0013] Optionally, in the aforementioned emergency warning method for coal mines to prevent emergency accidents, an emergency warning signal is sent to mobile terminals of multiple workers in the coal mine, including: detecting the distance between the multiple workers and potential danger sources in the coal mine; detecting the roles of the multiple workers; sorting the multiple workers according to the distance between the multiple workers and the potential danger sources and the roles of the multiple workers; and sending the emergency warning signal to the multiple workers in sequence according to the sorting results.

[0014] In the second aspect, the present invention provides an emergency warning system for coal mines for preventing emergency accidents, comprising: multiple sensor nodes deployed in the coal mine; a data sampling module, which samples the environmental parameters of the coal mine through the multiple sensor nodes, and adjusts the sampling rate of the multiple sensor nodes according to the environmental parameters of the coal mine; a data transmission module, which sends the environmental parameters of the coal mine to a preset distributed edge computing node through a preset communication protocol; an index calculation module, which calculates an emergency accident risk index on the distributed edge computing node according to the environmental parameters of the coal mine, the high or low emergency accident risk index indicates the high or low probability of an emergency accident of a preset type occurring; a signal sending module, which sends an emergency warning signal to the mobile terminals of multiple staff members in the coal mine when the emergency accident risk index is higher than a preset threshold.

[0015] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0016] According to the technical solution of the present invention, through the reasonable configuration of sensor nodes and edge computing nodes, and intelligent data management and analysis processes, it helps to improve the resource allocation efficiency in the coal mining process, reduce the waste of manpower and material resources caused by false alarms or late reports, and also reduce the rescue costs after accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0018] Figure 1 It is a flow chart of an emergency warning method for coal mines to prevent emergency accidents according to an embodiment of the present application;

[0019] Figure 2 A partial flow chart of an emergency warning method for coal mines for preventing emergency accidents according to an embodiment of the present application;

[0020] Figure 3 Another layout flow chart of an emergency warning method for coal mines to prevent emergency accidents according to an embodiment of the present application;

[0021] Figure 4 It is another partial flow chart of an emergency warning method for coal mines for preventing emergency accidents according to an embodiment of the present application;

[0022] Figure 5 It is another partial flow chart of an emergency warning method for coal mines for preventing emergency accidents according to an embodiment of the present application; Figure 6 The present invention is a block diagram of an emergency warning system for coal mines for preventing emergencies according to an embodiment of the present application. DETAILED DESCRIPTION

[0023] Some embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0024] like Figure 1 As shown, in one embodiment of the present invention, a coal mine emergency warning method for preventing emergency accidents is provided, comprising:

[0025] Step S110, deploying multiple sensor nodes in the coal mine.

[0026] Step S120, sampling the environmental parameters of the coal mine through multiple sensor nodes, and adjusting the sampling rates of the multiple sensor nodes according to the environmental parameters of the coal mine.

[0027] In this embodiment, by deploying multiple sensor nodes in the coal mine and being able to dynamically adjust the sampling rate according to environmental parameters, comprehensive and real-time monitoring of the coal mine is ensured. This adaptive sampling mechanism not only improves the accuracy of data collection, but also effectively reduces unnecessary data transmission, thereby optimizing operational efficiency.

[0028] Step S130, sending the environmental parameters of the coal mine to a preset distributed edge computing node through a preset communication protocol.

[0029] In this embodiment, distributed edge computing nodes are used for data processing, avoiding the delay problem that may be caused by traditional centralized processing methods. Edge computing nodes can quickly analyze and process data from sensors, instantly evaluate the emergency risk index, and respond in the shortest time, greatly shortening the time interval from detection to warning.

[0030] Step S140, on the distributed edge computing node, calculate the emergency accident risk index based on the environmental parameters of the coal mine, and the high or low emergency accident risk index indicates the probability of a preset type of emergency accident occurring.

[0031] In this embodiment, the emergency risk index can be automatically calculated based on the collected environmental parameters, and a reasonable threshold can be set to trigger the warning signal. This mechanism ensures the accuracy and timeliness of the warning information, allowing staff to receive notifications before potential dangers occur, buying valuable time for taking risk avoidance measures.

[0032] Step S150, when the emergency accident risk index is higher than a preset threshold, an emergency warning signal is sent to the mobile terminals of multiple workers in the coal mine.

[0033] According to the technical solution of this embodiment, through the reasonable configuration of sensor nodes and edge computing nodes, as well as intelligent data management and analysis processes, it helps to improve the efficiency of resource allocation in the coal mining process, reduce the waste of manpower and material resources caused by false alarms or late reports, and also reduce the rescue costs after an accident.

[0034] like Figure 2 As shown, another embodiment of the present invention further provides an emergency warning method for coal mines for preventing emergency accidents. Compared with the aforementioned embodiment, the emergency warning method for coal mines for preventing emergency accidents in this embodiment, step S120 includes:

[0035] Step S210, calculating the change rate of the environmental parameters of the coal mine, wherein the environmental parameter sampled by the i-th sensor node at time t among the multiple sensor nodes is x i (t), the rate of change of the environmental parameters sampled by the i-th sensor node at time t is Δx i (t).

[0036] In this embodiment, by calculating the rate of change of environmental parameters (Δx_i(t)) of each sensor node at a specific time point, the instantaneous change trend of environmental parameters in the coal mine can be captured more keenly. This not only helps to identify potential risks earlier, but also provides information about the rate of environmental change, providing more detailed data support for assessing the possibility of emergency accidents.

[0037] Step S220, calculating the sampling rates of multiple sensor nodes Among them, α is the preset adjustment coefficient, f base is the preset benchmark sampling rate, N is the number of sensor nodes, and w i is the preset weight value corresponding to the i-th sensor node, x i (D) is the preset baseline sampling parameter of the i-th sensor node.

[0038] According to the technical solution of this embodiment, a dynamic adjustment formula for the sampling rate based on environmental parameters and their change rates is introduced, which comprehensively considers the importance (weight value) of each sensor node, the current environmental parameters and their changes relative to the reference value, as well as the preset adjustment coefficient and the reference sampling rate. This method ensures that the sampling frequency can be flexibly adjusted according to the actual situation while maintaining data integrity and real-time performance, thereby achieving effective resource utilization and performance maximization.

[0039] like Figure 3 As shown, another embodiment of the present invention further provides an emergency warning method for coal mines for preventing emergency accidents. Compared with the aforementioned embodiment, the emergency warning method for coal mines for preventing emergency accidents in this embodiment, step S120 further includes:

[0040] Step S310, detecting the data transmission power of multiple sensor nodes and the distance between them and the distributed edge computing nodes, wherein the data transmission power of the i-th sensor node at time t is P i (t), and the distance between it and the distributed edge computing node is D i (t).

[0041] Step S320, detecting the remaining power of multiple sensor nodes, wherein the remaining power of the i-th sensor node at time t is S i (t).

[0042] Step S330: Detect the load L(t) of the data transmission network to which the multiple sensor nodes are connected.

[0043] In this embodiment, by considering the distance from the sensor node to the edge computing node and the network load, the data transmission strategy of each node can be optimized without affecting the data integrity. For example, the transmission power can be appropriately reduced during high load or long-distance transmission, and the power can be increased during low load or short-distance transmission, so as to maintain the best data transmission rate and quality while reducing the risk of interference.

[0044] Step S340: Establish a power consumption model for multiple sensor nodes: Wherein, E(t) represents the total power consumption of multiple sensor nodes at time t, and β and γ are preset balance coefficients.

[0045] In this embodiment, the power consumption model takes into account the data transmission power, distance, network load and remaining power, and introduces a balance coefficient to ensure the effectiveness and flexibility of the model. The model can accurately calculate the total power consumption of multiple sensor nodes at any time, thereby achieving refined control of energy consumption. This not only helps to reduce unnecessary power waste, but also effectively extends the endurance of the entire early warning mechanism, especially when power supply is limited.

[0046] Step S350: adjusting the data transmission power of at least one sensor node among the multiple sensor nodes so that the total power consumption E(t) of the multiple sensor nodes at time t does not exceed a preset power upper limit.

[0047] In this embodiment, the data transmission power of the sensor node is dynamically adjusted to ensure that the total power consumption does not exceed the preset power limit, thereby avoiding equipment failure or downtime caused by excessive power consumption. In addition, through real-time monitoring of the power supply and power-consuming equipment conditions, the power limit can be set more scientifically and reasonably to ensure stable and reliable operation in a complex and changing working environment.

[0048] Specifically, the power cap can be calculated as follows:

[0049] (1) Check the power supply situation in coal mines.

[0050] (2) Check the status of electrical equipment in coal mines.

[0051] (3) Set a power limit based on the coal mine’s power supply conditions and electrical equipment.

[0052] In this embodiment, through comprehensive analysis of the power supply and power equipment conditions in the coal mine, the power upper limit can be set more accurately, thereby achieving the optimal configuration of limited resources. This is not only conducive to ensuring the normal operation of the early warning mechanism, but also provides necessary power support for other key equipment, improving the safety and economic benefits of the overall production operation.

[0053] According to the technical solution of this embodiment, by introducing advanced power consumption management and adjustment mechanism, not only the energy consumption problem existing in the traditional early warning solution is solved, but also the reliability, stability and intelligence level of the system are improved, providing a more solid technical guarantee for safe production in coal mines.

[0054] like Figure 4 As shown, another embodiment of the present invention further provides an emergency warning method for coal mines for preventing emergency accidents. Compared with the aforementioned embodiment, the emergency warning method for coal mines for preventing emergency accidents in this embodiment, before step S350, further includes:

[0055] Step S410, detecting the data transmission quality of multiple sensor nodes at time t and the data transmission quality at time t-1, wherein the data transmission quality of the i-th sensor node at time t is Q(t), and the data transmission quality at time t-1 is Q(t-1).

[0056] In this embodiment, by monitoring the data transmission quality of multiple sensor nodes, the data transmission performance of each node can be evaluated in real time, which helps to promptly discover and solve possible data transmission problems, such as signal interference or packet loss, thereby ensuring the accuracy and integrity of data transmission.

[0057] Step S420, detecting the instantaneous power consumption of multiple sensor nodes at time t, wherein the instantaneous power consumption E of the i-th sensor node at time t is i (t).

[0058] In this embodiment, detecting the instantaneous power consumption of each sensor node can provide key parameters for the subsequent pheromone concentration calculation. Combining power consumption data for analysis not only helps to further refine the energy management strategy, but also dynamically adjusts the task allocation of nodes according to the current working status to avoid equipment overheating or failure caused by excessive use of certain nodes.

[0059] Step S430, calculating the pheromone concentrations of multiple sensor nodes at time t, where the pheromone concentration of the i-th sensor node at time t is Among them, T(t-1) is the pheromone concentration of the i-th sensor node at time t-1, the pheromone concentration of the i-th sensor node at the initial time is a fixed value, ρ is the preset information evaporation coefficient, 0<ρ<1, and μ is the preset proportional factor.

[0060] In this embodiment, the concept of pheromone concentration is introduced, and the behavior pattern of ants foraging in nature is simulated through formula calculation. This method can make intelligent decisions based on the historical performance (pheromone concentration) and current performance (data transmission quality and instantaneous power consumption) of the node, and give priority to those nodes with good transmission quality and low energy consumption to participate in key tasks, thus achieving the optimal allocation of resources.

[0061] Step S440: selecting at least one sensor node from the plurality of sensor nodes according to the pheromone concentrations of the plurality of sensor nodes at time t.

[0062] According to the technical solution of this embodiment, by continuously monitoring the data transmission quality and instantaneous power consumption, the best sensor nodes can be quickly screened out at places close to the data source (i.e., edge computing nodes). This not only reduces unnecessary data transmission delays, but also improves the speed and efficiency of overall data processing, ensuring that early warning information can be conveyed to relevant personnel in a timely manner, and buying valuable time for taking effective response measures.

[0063] like Figure 5 As shown, another embodiment of the present invention further provides an emergency warning method for coal mines for preventing emergency accidents. Compared with the aforementioned embodiment, the emergency warning method for coal mines for preventing emergency accidents in this embodiment, step S350 includes:

[0064] Step S510: when the data transmission power of the i-th sensor node needs to be adjusted, the difference ΔE between the total power consumption E(t) of the plurality of sensor nodes at time t and the total power consumption E(t-1) at time t-1 is calculated.

[0065] In this embodiment, by calculating the difference between the total power consumption of multiple sensor nodes, the power consumption change trend can be grasped in real time. This helps to make more accurate decisions when it is necessary to adjust the data transmission power, and avoid system instability or exceeding the preset power limit due to sudden changes in power consumption.

[0066] Step S520, calculate the data transmission power of the i-th sensor node at time t+1 Among them, E max represents the power upper limit, and A(t) is the preset environmental sensitivity factor, which represents the influence of the coal mine environment on the data transmission efficiency.

[0067] In this embodiment, the dynamic adjustment formula allows the data transmission power of each sensor node to be flexibly adjusted according to actual power consumption changes and environmental conditions. This adaptive strategy not only improves energy utilization efficiency, but also minimizes unnecessary power consumption while maintaining communication quality.

[0068] Before step S520, the temperature, humidity and dust concentration of the coal mine at time t may be detected; and the value of the environmental sensitivity factor A(t) may be calculated based on the temperature, humidity and dust concentration of the coal mine at time t.

[0069] In this embodiment, an environmental sensitive factor is introduced and its value is calculated based on parameters such as temperature, humidity and dust concentration in the coal mine, which can better cope with the complex and changeable working environment. For example, under conditions of high humidity or high dust concentration, appropriately reducing the data transmission power can reduce signal interference and improve the stability and accuracy of data transmission; while under suitable environments, the power can be appropriately increased to speed up the data transmission rate.

[0070] According to the technical solution of this embodiment, by introducing the total power consumption difference calculation and environmental sensitivity factors, not only the energy consumption problem and the lack of environmental adaptability in the traditional early warning system are solved, but also the intelligence level, reliability and response speed are improved, providing a more solid technical guarantee for coal mine safety production. This method has opened up a new path for safety management and technological innovation in the coal mining industry, and has important application value and development prospects.

[0071] Another embodiment of the present invention further provides an emergency warning method for coal mines for preventing emergency accidents. Compared with the above-mentioned embodiment, the emergency warning method for coal mines for preventing emergency accidents in this embodiment includes step S150:

[0072] (1) Detect the distance between multiple workers and potential hazards in the coal mine environment; detect the roles of multiple workers.

[0073] In this embodiment, by detecting the distance between multiple workers and potential danger sources and combining their role information, a more detailed and personalized assessment of the degree of danger faced by each worker is performed. This location and role-based assessment method ensures the pertinence of early warning information, allowing people in different roles to take the most appropriate risk avoidance measures according to their own circumstances.

[0074] (2) Sort the multiple workers according to their distances from potential danger sources and their roles.

[0075] (3) The emergency warning signal is sent to multiple staff members in sequence according to the sorting results.

[0076] According to the technical solution of this embodiment, the sorting strategy based on distance and role is endowed with stronger intelligent and humanized features. It not only improves the reliability of the early warning system, but also allows miners to feel more intimate security services, enhancing their trust and satisfaction.

[0077] like Figure 6 As shown, in one embodiment of the present invention, a coal mine emergency warning system for preventing emergency accidents is provided, comprising:

[0078] A plurality of sensor nodes 610 are deployed in a coal mine.

[0079] The data sampling module 620 samples the environmental parameters of the coal mine through multiple sensor nodes, and adjusts the sampling rates of the multiple sensor nodes according to the environmental parameters of the coal mine.

[0080] In this embodiment, by deploying multiple sensor nodes in the coal mine and being able to dynamically adjust the sampling rate according to environmental parameters, comprehensive and real-time monitoring of the coal mine is ensured. This adaptive sampling mechanism not only improves the accuracy of data collection, but also effectively reduces unnecessary data transmission, thereby optimizing operational efficiency.

[0081] The data transmission module 630 sends the environmental parameters of the coal mine to the preset distributed edge computing node through a preset communication protocol.

[0082] In this embodiment, distributed edge computing nodes are used for data processing, avoiding the delay problem that may be caused by traditional centralized processing methods. Edge computing nodes can quickly analyze and process data from sensors, instantly evaluate the emergency risk index, and respond in the shortest time, greatly shortening the time interval from detection to warning.

[0083] The index calculation module 640 calculates the emergency accident risk index on the distributed edge computing node according to the environmental parameters of the coal mine. The high or low emergency accident risk index indicates the probability of a preset type of emergency accident occurring.

[0084] In this embodiment, the emergency risk index can be automatically calculated based on the collected environmental parameters, and a reasonable threshold can be set to trigger the warning signal. This mechanism ensures the accuracy and timeliness of the warning information, allowing staff to receive notifications before potential dangers occur, buying valuable time for taking risk avoidance measures.

[0085] The signal sending module 650 sends an emergency warning signal to the mobile terminals of multiple workers in the coal mine when the emergency accident risk index is higher than a preset threshold.

[0086] According to the technical solution of this embodiment, through the reasonable configuration of sensor nodes and edge computing nodes, as well as intelligent data management and analysis processes, it helps to improve the efficiency of resource allocation in the coal mining process, reduce the waste of manpower and material resources caused by false alarms or late reports, and also reduce the rescue costs after an accident.

[0087] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0088] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0089] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0090] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0091] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A coal mine emergency warning method for preventing emergency accidents, comprising: Deploy multiple sensor nodes in coal mines; Sampling environmental parameters of the coal mine through the multiple sensor nodes, and adjusting sampling rates of the multiple sensor nodes according to the environmental parameters of the coal mine; The environmental parameters of the coal mine are sent to a preset distributed edge computing node through a preset communication protocol; On the distributed edge computing node, an emergency accident risk index is calculated according to the environmental parameters of the coal mine, and the emergency accident risk index indicates the probability of a preset type of emergency accident occurring; When the emergency accident risk index is higher than a preset threshold, an emergency warning signal is sent to mobile terminals of multiple workers in the coal mine.

2. The coal mine emergency warning method for preventing emergency accidents according to claim 1, wherein: Adjusting the sampling rates of the plurality of sensor nodes according to the environmental parameters of the coal mine includes: Calculate the change rate of the environmental parameters of the coal mine, where the environmental parameter sampled by the i-th sensor node among the multiple sensor nodes at time t is x i (t), the rate of change of the environmental parameters sampled by the i-th sensor node at time t is Δx i (t); Calculate the sampling rates of the multiple sensor nodes Among them, α is the preset adjustment coefficient, f base is the preset reference sampling rate, N is the number of the multiple sensor nodes, and w i is the preset weight value corresponding to the i-th sensor node, x i (D) is the preset benchmark sampling parameter of the i-th sensor node.

3. The coal mine emergency warning method for preventing emergency accidents according to claim 2, wherein: Sampling the environmental parameters of the coal mine through the multiple sensor nodes includes: Detect the data transmission power of the multiple sensor nodes and the distance between them and the distributed edge computing node, where the data transmission power of the i-th sensor node at time t is P i (t), and the distance between it and the distributed edge computing node is D i (t); Detect the remaining power of the multiple sensor nodes, where the remaining power of the i-th sensor node at time t is S i (t); Detecting a load L(t) of a data transmission network to which the plurality of sensor nodes are connected; Establish a power consumption model for the multiple sensor nodes: Wherein, E(t) represents the total power consumption of the multiple sensor nodes at time t, and β and γ are preset balance coefficients; The data transmission power of at least one sensor node among the multiple sensor nodes is adjusted so that the total power consumption E(t) of the multiple sensor nodes at time t does not exceed a preset power upper limit.

4. The coal mine emergency warning method for preventing emergency accidents according to claim 3, wherein: Before adjusting the data transmission power of at least one sensor node among the plurality of sensor nodes, the coal mine emergency warning method for preventing emergency accidents further includes: Detecting the power supply situation of the coal mine; Detecting the status of electrical equipment in the coal mine; The power upper limit is set according to the power supply situation and power-consuming equipment situation of the coal mine.

5. The coal mine emergency warning method for preventing emergency accidents according to claim 3, wherein: Before adjusting the data transmission power of at least one sensor node among the plurality of sensor nodes, the coal mine emergency warning method for preventing emergency accidents further includes: Detecting the data transmission quality of the multiple sensor nodes at time t and the data transmission quality at time t-1, wherein the data transmission quality of the i-th sensor node at time t is Q(t), and the data transmission quality at time t-1 is Q(t-1); Detect the instantaneous power consumption of the multiple sensor nodes at time t, wherein the instantaneous power consumption E of the i-th sensor node at time t is i (t); Calculate the pheromone concentration of the multiple sensor nodes at time t, where the pheromone concentration of the i-th sensor node at time t is Wherein, T(t-1) is the pheromone concentration of the i-th sensor node at time t-1, the pheromone concentration of the i-th sensor node at the initial time is a fixed value, ρ is a preset information evaporation coefficient, 0<ρ<1, and μ is a preset proportional factor; The at least one sensor node is selected from the multiple sensor nodes according to the pheromone concentrations of the multiple sensor nodes at time t.

6. The coal mine emergency warning method for preventing emergency accidents according to claim 3, wherein: Adjusting the data transmission power of at least one sensor node among the plurality of sensor nodes comprises: When the data transmission power of the i-th sensor node needs to be adjusted, a difference ΔE between the total power consumption E(t) of the plurality of sensor nodes at time t and the total power consumption E(t-1) at time t-1 is calculated; Calculate the data transmission power of the i-th sensor node at time t+1 Among them, E max represents the power upper limit, A(t) is a preset environmental sensitivity factor, and represents the influence of the environment of the coal mine on the data transmission efficiency.

7. The coal mine emergency warning method for preventing emergency accidents according to claim 6, wherein: When calculating the data transmission power of the i-th sensor node at time t+1 Previously, the coal mine emergency warning method for preventing emergency accidents also includes: detecting environmental parameters of the coal mine at time t, wherein the environmental parameters of the coal mine include temperature, humidity and dust concentration; The value of the environmental sensitivity factor A(t) is calculated based on the environmental parameters of the coal mine at time t.

8. The coal mine emergency warning method for preventing emergency accidents according to claim 1, wherein: Sending an emergency warning signal to the mobile terminals of multiple workers in the coal mine includes: Detecting the distances between the plurality of workers and potential danger sources in the coal mine; detecting roles of the plurality of workers; sorting the multiple workers according to the distances between the multiple workers and the potential danger source and the roles of the multiple workers; The emergency warning signal is sent to the multiple staff members in sequence according to the sorting results.

9. An emergency warning system for coal mines to prevent emergencies, comprising: Multiple sensor nodes are deployed in coal mines; A data sampling module, which samples the environmental parameters of the coal mine through the multiple sensor nodes and adjusts the sampling rates of the multiple sensor nodes according to the environmental parameters of the coal mine; A data transmission module, which sends the environmental parameters of the coal mine to a preset distributed edge computing node through a preset communication protocol; An index calculation module, on the distributed edge computing node, calculates an emergency accident risk index according to the environmental parameters of the coal mine, wherein the emergency accident risk index indicates the probability of a preset type of emergency accident occurring; The signal sending module sends an emergency warning signal to the mobile terminals of multiple workers in the coal mine when the emergency accident risk index is higher than a preset threshold.

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