Multi-node rolling type intelligent dust detection and multi-terminal collaborative protection system under self-adaptive self-healing network

Abstract

The invention provides a multi-node rolling type intelligent dust detection and multi-terminal cooperative protection system under an adaptive self-healing network, which is characterized by comprising a plurality of dust detection sensors, a Wireless HART ultra-narrow band remote wireless communication module for signal transmission, a data storage and processing center and terminal equipment, the terminal equipment comprises an anti-explosion mobile phone and / or an intelligent bracelet; data transmission is carried out between the dust detection sensors through a self-healing network system, and dust concentration distribution in a roadway is obtained based on dust data detected by the dust detection sensors and a rolling scheduling algorithm; and then the dust concentration distribution is transmitted to a data storage and processing center through a Wireless HART ultra-narrow band remote wireless communication module. By using the large-scale wireless sensor network, rolling type intelligent monitoring of dust in the mine laneway is realized, and the system operation power consumption is greatly reduced while the detection precision is improved.

Description

Technical Field

[0001] The present invention relates to a low-power intelligent dust detection and multi-terminal collaborative protection technology for mines, and specifically to a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network. Background Art

[0002] Nowadays, as an important resource mining site, dust pollution has always attracted much attention in mines. Dust in mine tunnels not only affects the health and safety of miners, but also damages equipment and the environment. Therefore, dust detection and protection have become one of the important tasks of mine management. Traditional dust detection methods mainly rely on manual sampling and laboratory analysis, which is time-consuming and labor-intensive and cannot be detected in real time. Summary of the invention

[0003] The present invention aims to provide a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network to solve the problems of high delay in dust detection in tunnels, uneven detection areas, high power consumption of the detection system, inability to perform long-term stable detection, inability to intuitively feedback dust concentration to mine workers, and inability to effectively avoid risks in emergency situations.

[0004] In order to solve the above problems, the present invention proposes a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network, comprising: a dust detection sensor, a WirelessHART ultra-narrowband long-distance wireless communication module for signal transmission, a data storage and processing center, and a terminal device, wherein the terminal device comprises an explosion-proof mobile phone and / or a smart bracelet;

[0005] Dust detection sensors transmit data through a self-healing network system, and obtain the dust concentration distribution in the tunnel based on the dust data detected by the dust detection sensors and the rolling scheduling algorithm; then the dust concentration distribution is transmitted to the data storage and processing center through the WirelessHART ultra-narrowband long-range wireless communication module.

[0006] The dust detection sensors are installed at multiple nodes in the coal mine mining tunnels, and are deployed densely at high-risk locations such as key turns, forks, vents and exits. Each node is responsible for dust concentration detection in its vicinity and has the ability to make independent judgments. The detection frequency can be adjusted according to the rolling scheduling algorithm and the external dust diffusion trend, thereby obtaining the dust concentration distribution in the tunnel.

[0007] Preferably, the transmission of the WirelessHART ultra-narrowband long-range wireless communication module is matched with a self-healing network system of a dynamic routing protocol to transmit data to a data storage and processing center; wherein a regular heartbeat signal is set in the self-healing network system, and the heartbeat signal is sent to adjacent nodes or gateways regularly to confirm that each node can operate normally. If the heartbeat signal is not received in time, the system quickly identifies the faulty node and automatically starts the self-healing mechanism;

[0008] The self-healing mechanism bypasses the faulty node through a dynamic routing protocol (AODV) and a heartbeat signal, thereby enabling each node to periodically send a heartbeat signal to an adjacent node or gateway;

[0009] Among them, the heartbeat signal sending interval T S The node surplus E node , Environmental dust concentration C dust and mine complex dust environment parameters T mine Jointly determined, the calculation formula is:

[0010]

[0011] Where k is the proportionality constant;

[0012] α, β, and γ are empirical coefficients;

[0013] This formula comprehensively considers the impact of node quantity, the effect of dust concentration on signal attenuation, and the impact of complex dust environment parameters in mines on equipment performance.

[0014] When the heartbeat signal of a node is not received within the specified time, the adjacent node will immediately mark it as unavailable and start the self-healing mechanism; the specified time T r According to the heartbeat sending interval T S , Dust concentration C dust and mine complex dust environment parameters T mine Calculation, the calculation formula is as follows:

[0015]

[0016] Among them, δ is the adjustment parameter;

[0017] The above formula takes into account the delay of signal propagation in high dust concentration and complex mine environment, as well as the impact of the number of nodes.

[0018] The system uses the AODV protocol to build a new data transmission path. The source node first broadcasts the RREQ message, which contains the source node address, the destination node address and a unique request identifier. When the affected node forwards the RREQ, it updates the hop count H and the accumulated delay Δ to reflect the current path characteristics; the update formula for the hop count H and the accumulated delay Δ is:

[0019]

[0020] Among them, H new , H current Respectively represent the updated hop count and the current hop count;

[0021] Δ new , Δ current Represent the updated cumulative delay and the current cumulative delay respectively;

[0022] η, φ are weight coefficients;

[0023] L packet is the packet length;

[0024] V transmit is the transmission rate.

[0025] This formula integrates the effects of dust concentration, coal mine dust concentration environment, and node quantity on hop count and delay.

[0026] After receiving the RREQ message, other nodes check whether there is a valid route to the target node in their own routing table. A valid route refers to a path that can stably transmit data, has low latency, high reliability and meets load requirements. If a valid route is found, there is no need to forward it. If no valid route is found, the node broadcasts the RREQ message to find a new path. When forwarding the RREQ message, the above formula is also used to update information such as the number of hops and accumulated delay to reflect the current path characteristics, and establish a reverse route for use when returning the route reply (RREP). If the intermediate node has a valid route or is the target node itself, it will generate a RREP message containing the total number of hops and estimated delay, and send it back to the source node along the reverse route.

[0027] After receiving multiple RREP messages, the source node evaluates the available paths according to the following path evaluation function ψ and selects the path with the highest path evaluation function value:

[0028]

[0029] Among them, α1, β1, and γ1 are evaluation weight coefficients;

[0030] H is the number of hops.

[0031] If the path evaluation function values ​​are the same, the path with the least hops is selected to reduce the number of intermediate nodes, reduce the probability of failure and transmission delay; if the number of hops is still the same, the path with the lowest delay is selected to improve the real-time and stability of data transmission. If there is historical data, the system will also consider the reliability record and remaining energy of the node to select a more stable path. Once the best path is selected, the source node updates the routing table, and the data packet is transmitted along the new path, successfully bypassing the faulty node. The entire process is transparent to the upper-layer application, ensuring the continuity and reliability of communication. In addition, the AODV protocol supports a routing maintenance mechanism. If a node in the new path fails again, the system will repeat the routing discovery and selection process to continuously optimize the data transmission path. In this way, the network can dynamically adapt to node failures and topology changes, ensure that the dust concentration detection data is reliably and timely transmitted to the target node or data processing center, and ensure the normal communication between modules. In addition, due to the congestion of communication channels, ultra-narrowband long-distance wireless transmission technology is required; the data storage and processing center is responsible for storing the received dust concentration and particle size data, and processing the data according to the geographic information data format; the WirelessHART ultra-narrowband long-distance wireless communication module sends the processed information data to multiple portable terminals (smart bracelets and smart explosion-proof mobile phones) of mine workers in the form of wireless data streams;

[0032] When the worker terminal needs to communicate, the AODV protocol temporarily establishes a route on demand to reduce unnecessary network traffic and power consumption; when a node needs to send data to the target node, AODV starts the path discovery mechanism. The source node first broadcasts a route request (RREQ) message, which contains information such as the source node address, the target node address, the sequence number, and the number of hops. After receiving the RREQ message, the intermediate node in the network updates the number of hops and establishes a reverse routing table entry. If the intermediate node has a valid route to the target node, or it is the target node itself, it generates a route reply (RREP) message and returns to the source node along the reverse route. The source node may receive multiple RREP messages, and it selects the best path based on the principle of the least hops and the latest sequence number; when the hops are the same, the target sequence number is compared and the path with the larger sequence number is selected to ensure the freshness and optimality of the route. When a node or link in the route fails, the relevant node will send a routing error (RERR) message to notify the affected source node. After receiving the RERR, the source node immediately starts a new path discovery process, broadcasts a new RREQ message, and searches for an alternate path. If there is a cached alternate route, the source node can also directly switch to the alternate path to ensure uninterrupted communication. Through the dynamic route discovery and maintenance mechanism of the AODV protocol, the system can quickly adapt to changes in network topology, dynamically acquire the best path and alternate paths, and ensure the stability and reliability of communication in the complex environment of the mine.

[0033] Preferably, in order to deal with the dust concentration C in the mine dust The impact on signal propagation and node margin E node , Mine complex dust environment parameters T mine and ventilation rate V f The dynamic changes of environmental parameters such as the time interval T for broadcasting RREQ messages (including the source node and other nodes sending RREQ messages) RREQ Perform adaptive adjustment, the formula is as follows:

[0034]

[0035] Where, k is the proportionality constant;

[0036] δ is the adjustment parameter;

[0037] β cost is the weight coefficient of the moving cost;

[0038] α2 is the empirical coefficient of the number of nodes;

[0039] γ2 is the empirical coefficient of dust concentration;

[0040] V f Indicates ventilation rate;

[0041] C dust Indicates the dust concentration in the mine;

[0042] E node is the node margin.

[0043] According to this formula, when the dust is too high or the mine environment is too harsh, the interval between sending routing requests is appropriately increased to reduce the excessive overhead caused by unstable links; between nodes with good ventilation and sufficient number of nodes, the interval between RREQs can be appropriately shortened to increase the speed of route establishment.

[0044] Preferably, the rolling scheduling algorithm includes:

[0045] At the beginning of each cycle, the system first recalculates the weight values ​​W of all grids i , update the weight value according to the latest real-time dust concentration data, historical records and regional accident statistics; then adjust the node allocation and detection frequency according to the weight to ensure that resources are tilted towards high-weight areas; at the same time, select the node N participating in the rolling scheduling m , and move these nodes to uncovered or low-coverage areas, give priority to covering high-weight areas, and gradually optimize the overall coverage;

[0046] The optimization objective function of rolling scheduling is:

[0047]

[0048] Among them, E i Indicates detection error;

[0049] M j represents the node movement cost;

[0050] β cost is the weight coefficient of the moving cost;

[0051] n is the number of grids;

[0052] N is the total number of nodes.

[0053] Through this process, rolling scheduling achieves dynamic allocation of resources and continuous optimization of full network coverage.

[0054] When the system is first run, the rolling scheduling algorithm is based on the historical data of dust concentration D h (x, y) and the distribution of detection nodes to ensure coverage integrity and resource utilization efficiency in the initial stage of system operation.

[0055] Preferably, the rolling scheduling algorithm further includes:

[0056] The entire detection area is divided into n grids R i (x, y), each grid represents an independent monitoring unit; historical dust concentration data D h (x, y) is used as a reference, and combined with the total number of detection nodes N, all grids are initially allocated with a uniform strategy, that is, each grid is assigned at least one detection node, satisfying the formula:

[0057]

[0058] Among them, N i To assign to grid R i The number of nodes;

[0059] D h (x, y, i) is the historical dust concentration data of the i-th single grid;

[0060] The historical dust concentration data for all grids;

[0061] is the rounding symbol;

[0062] λ is the adjustment coefficient, which is used to dynamically adjust the number of node allocations in each grid according to historical dust concentration data.

[0063] The above formula ensures that node allocation not only evenly covers each grid, but also appropriately tilts resources according to the historical dust concentration to improve the monitoring capability of high dust areas.

[0064] After the initial task allocation is completed, the system enters the rolling detection mode and gradually optimizes the distribution of detection resources through a dynamic weight adjustment mechanism. In the rolling detection mechanism, the rolling interval time T r It is an important parameter of the algorithm, which directly determines the frequency and response speed of the system's dynamic adjustment. The initial default rolling interval of this system is set to 30 minutes. During each rolling cycle, the system will select some nodes to be rescheduled to uncovered or low-coverage areas based on the current detection coverage and regional weight changes to improve detection coverage and flexibility. Specifically, the number of nodes involved in the rolling, N m By the proportional parameter P m OK, the calculation formula is:

[0065]

[0066] Among them, P m Indicates the percentage of nodes involved in scrolling;

[0067] C i is the adjustment demand index within the i-th rolling period;

[0068] m is the number of nodes;

[0069] M is the total number of rolling cycles;

[0070] Indicates rounding up.

[0071] This formula dynamically determines the number of nodes that need to be rescheduled in each rolling cycle by considering the adjustment needs in the historical rolling cycle to ensure the timeliness of system response and the rationality of adjustment.

[0072] The goal of the rolling mechanism is to dynamically schedule nodes according to the regional weight value W. i For the number of detection nodes N i and detection frequency F i Real-time adjustments are made to achieve optimal allocation of detection resources. The monitoring priority of key areas is ensured, and the problem of insufficient coverage in the initial allocation is gradually corrected, thereby enhancing the overall adaptability of the system. In addition, the regional weight is the core indicator of the rolling scheduling algorithm, which is used to measure the priority of each monitoring grid and guide the allocation and scheduling of nodes. Each grid area R i The weight value W of (x,y) i Based on historical dust concentration data D h (x, y), regional accident number A(x, y) and real-time dust concentration data D r (x,y) comprehensive calculation, the formula is:

[0073]

[0074] Among them, α3, β3, and γ3 are the weight coefficients of historical dust concentration, regional accident number, and real-time dust concentration, respectively;

[0075] V f (x,y) is the grid R i ventilation rate;

[0076] The formula takes into account historical dust accumulation, regional safety hazard frequency, and current dust concentration, and combines the ventilation rate to adjust the weight. Historical data reflects the long-term dust accumulation level in the region, the number of accidents represents the frequency of safety hazards in the region, and real-time concentration data reflects the current dust situation.

[0077] According to the weight, the grid is divided into three levels: high weight, medium weight and low weight: i >0.7, classified as high weight; for 0.4≤W i ≤0.7, classified as medium weight; for W i <0.4, it is classified as low weight; high-weight areas are given priority to allocate more detection resources and monitor at a higher frequency. This weight classification mechanism ensures that the allocation of detection resources can reflect actual needs and avoid resource waste by comprehensively considering static historical information and dynamic real-time data.

[0078] The rolling scheduling algorithm uses a dynamic task allocation mechanism to allocate tasks according to the regional weight value W. i For the number of detection nodes N i and detection frequency F i Make real-time adjustments to optimize the allocation of testing resources:

[0079] Number of detection nodes N i Dynamically adjusted by the following formula:

[0080]

[0081] Where W i is the weight value of the grid Ri(x,y);

[0082] is the sum of the weights of all grids;

[0083] N total is the total number of nodes;

[0084] F i is the adjusted detection frequency of the grid Ri(x,y);

[0085] F base As the basic detection frequency;

[0086] αaf is the frequency adjustment coefficient, which is used to adjust the nonlinear relationship between frequency and the number of nodes;

[0087] By introducing the quadratic term of the detection frequency, the dynamic adjustment of the number of nodes is more sensitive when the frequency difference is large, thereby improving the allocation accuracy to high-demand areas.

[0088] Detection frequency F i It is dynamically adjusted through the following formula:

[0089] F i =F base ·(1+k af ·W i )

[0090] where F base As the basic detection frequency;

[0091] k af is the weight adjustment coefficient, which indicates the amplifying effect of the weight on the detection frequency;

[0092] When a grid is continuous T c Second detection concentration value D r When (x, y) are both lower than the detection concentration threshold τ, the system will reduce the detection frequency F in this area. i , the adjustment formula is:

[0093]

[0094] in To reduce the coefficient;

[0095] F min is the minimum detection frequency.

[0096] This dynamic task allocation mechanism ensures priority monitoring of high-risk areas by adjusting node distribution and detection frequency in real time, while avoiding excessive resource investment in low-risk areas. Rolling scheduling updates are the core tasks completed in each rolling cycle, aiming to dynamically optimize the distribution and utilization of detection resources.

[0097] Preferably, the terminal device remotely receives information data on dust concentration and particle size in the tunnel detected by the dust detection sensor, and superimposes the data with the tunnel topographic map to complete visual display, so as to facilitate mine workers to understand the dust conditions in the tunnel in a timely and intuitive manner.

[0098] The terminal device includes a ZT Map GIS map engine module, a WirelessHART ultra-narrowband long-distance wireless communication module supporting a self-healing network, a vibration module, a Python geographic information processing module, an OPENGL graphics rendering module, a gesture recognition module, and a user interaction module. The ZT Map GIS map engine module is responsible for processing the 3D coordinate topographic map of the lane, and the WirelessHART ultra-narrowband long-distance wireless communication module supporting a self-healing network is responsible for receiving information data sent by the data storage and processing center, and sending it to the Python geographic information processing module to complete the superposition with the coordinate topographic map output by the ZT Map GIS map engine module, and after being processed by the user interaction module and the OPENGL graphics rendering module, the visual display is completed on the screen.

[0099] Preferably, the terminal device is equipped with gesture recognition, and the initial interface of the terminal device is a 3D image of the dust concentration distribution in the area where the miner is located. When a specific gesture is recognized, the interface is switched to the optimal evacuation path from the miner's location to a low-concentration dust safety environment. Switching between different display modes through gesture recognition facilitates emergency avoidance for miners in dangerous situations.

[0100] Preferably, the terminal device is equipped with a vibration module:

[0101] Miners are exposed to dust concentrations of 50 mg / m 3 When in the above range, the vibration frequency of the vibration module is 30 times per minute;

[0102] Miners are exposed to dust concentrations of 50 mg / m 3 -20mg / m 3 When in the area, the vibration frequency of the vibration module is 20 times per minute;

[0103] Miners are exposed to dust concentrations ranging from 20 mg / m 3 -5mg / m 3 When in the area, the vibration frequency of the vibration module is 10 times per minute;

[0104] Miners are exposed to dust concentrations of 5 mg / m 3 When in the area, the vibration module does not vibrate.

[0105] Preferably,

[0106] The data storage and processing center stores the received real-time dust concentration, historical dust data, particle size data, etc., and processes them in blocks according to the sensor number; the processing rules are: take the horizontal center of the mining face as the origin, the tunnel as the x-axis, place a sensor every 10m from the origin until the entire tunnel is covered, and number them sequentially along the x-axis direction.

[0107] The data storage and processing center includes a data receiving module equipped with the AODV protocol, a data storage module including the InfluxDB real-time database and the Cassandra historical database, a data processing module, a real-time analysis engine, a decision support and control module, an energy consumption and resource management module, and a system self-healing and fault-tolerant module. The data receiving module of the AODV protocol is responsible for receiving the dynamic routing table; the data storage module is responsible for storing historical dust data, regional accident times, real-time dust concentration and other information in the rolling scheduling algorithm; the real-time analysis engine is responsible for calculating the grid weight in the rolling scheduling algorithm; the decision support and control module is responsible for the implementation of the rolling scheduling algorithm; the energy consumption and resource management module is responsible for the calculation and allocation of the overall power consumption of the system; and the system self-healing and fault-tolerant module is responsible for the implementation of the self-healing network.

[0108] In summary, due to the adoption of the above-mentioned technical solution, the present invention realizes the intelligent rolling monitoring of dust in the mine tunnels by using a large-scale wireless sensor network, which greatly reduces the power consumption of the system operation while improving the detection accuracy. Secondly, by combining the dust data collected by the sensor grid nodes with the geographic information system (GIS), the data can be visualized on the map. In this way, miners or managers can clearly understand the distribution of dust concentrations in different areas, and promptly discover and deal with high-concentration areas. The map visualization system can also provide storage and query functions for historical data, which is convenient for comparing and analyzing dust conditions in different time periods, and providing a more comprehensive reference for mine management. In addition, the terminal device switches modes through gesture recognition, and provides miners with a safe low-concentration dust evacuation route in an emergency, effectively protecting the life, health and safety of the workers. The specific advantages are as follows:

[0109] (1) The system has a self-healing function and is suitable for complex environments such as mines. When a node or link failure is detected, it can quickly switch to an alternative path to ensure uninterrupted communication and improve the reliability and stability of the system.

[0110] (2) By adopting the AODV dynamic routing protocol, the system can automatically adjust the routing paths from sensors to data storage and processing centers, and from data storage and processing centers to multiple miner terminals according to changes in the sensor network topology and node status, thereby reducing unnecessary communication delays and network congestion and improving data transmission efficiency.

[0111] (3) The energy consumption and resource management module in the data storage and processing center introduces energy perception function for the self-healing network. The system can optimize the frequency of sensor use based on the dynamic routing algorithm, which helps to extend the life cycle of the entire network and is particularly suitable for mine environments with limited energy.

[0112] (4) The rolling detection mechanism combined with the self-healing network can dynamically allocate the detection tasks of each node, optimize the detection frequency and regional coverage, and ensure efficient monitoring of dust concentration in mines.

[0113] (5) Through the collaborative protection mechanism of multiple terminal devices, the portable devices carried by workers can automatically vibrate to give a prompt when the dust concentration exceeds the standard, and can guide workers to find the best evacuation route with the lowest dust concentration in case of emergencies, greatly improving the safety of mine operations.

[0114] (6) The system can summarize and store historical dust concentration data and conduct data analysis and statistics. This can help us understand the periodic changes in roadway dust, grasp long-term trends, and provide a scientific basis for dust prevention, control and management.

[0115] (7) When faced with frequent node failures or changes in sensor network topology, the system can still maintain stable operation by quickly starting backup paths and dynamically adjusting. It has strong fault tolerance and ensures the continuity of dust detection and personnel safety protection.

[0116] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0117] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0118] Figure 1 It is the overall system structure diagram of the present invention.

[0119] Figure 2 This is a self-healing network interaction diagram of the present invention using the dynamic routing protocol AODV. DETAILED DESCRIPTION

[0120] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0121] Combination Figure 1-Figure 2As shown, the multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under the adaptive self-healing network is mainly composed of dust detection sensors 2, WirelessHART ultra-narrowband remote wireless communication modules 4, data storage and processing centers 5, explosion-proof mobile phones 6, and smart bracelets 7. The dust detection sensors 2 transmit data through the self-healing network system 1, and based on the dust data detected by the dust detection sensors 2 and the rolling scheduling algorithm 3, the dust concentration distribution in the lane is obtained; then the dust concentration distribution is transmitted to the data storage and processing center 5 through the WirelessHART ultra-narrowband remote wireless communication module 4.

[0122] The dust detection sensor 2 is installed at multiple nodes in the coal mining tunnel. The nodes are reasonably distributed according to the length of the tunnel and important areas, and are densely deployed at high-risk locations such as key turns, forks, vents and exits. Each node is responsible for the dust concentration detection in its vicinity and has the ability to make independent judgments. It can adjust the detection frequency according to the rolling scheduling algorithm and the external dust diffusion trend to obtain the dust concentration distribution in the tunnel; these sensor nodes use modern communication technology and are equipped with the AODV dynamic routing protocol to transmit data stably with low power consumption, and realize ultra-narrowband wireless communication of the centralized control system. In this way, not only can the workload of manual monitoring be reduced, but also the dust situation can be monitored in real time to provide accurate data support.

[0123] The WirelessHART ultra-narrowband long-range wireless communication module 4 transmits the data collected by the sensor network back to the data storage and processing unit in the form of a wireless data stream. The WirelessHART ultra-narrowband long-range wireless communication module 4 connects its TX end to the RX end of the dust concentration sensor 2, and the RX end is connected to the TX end of the dust concentration sensor 2. The sensor sends the collected data to the WirelessHART ultra-narrowband long-range wireless communication module through the UART serial port, and a UART to RF communication device can be obtained. The WirelessHART ultra-narrowband long-range wireless communication module 4 can realize wireless communication between different module units through the built-in low-power RF chip with the HART7.5 protocol. The transmission of the WirelessHART ultra-narrowband long-range wireless communication module 4 is matched with a self-healing network using a dynamic routing protocol (AODV, Ad Hocon-demand distance-vector) to send data to the data storage and processing center. Among them, a regular heartbeat signal is set in the self-healing network. By regularly sending heartbeat signals to adjacent nodes or gateways, it is confirmed that each node can operate normally. If the heartbeat signal is not received in time, the system will quickly identify it and automatically start the self-healing mechanism. The self-healing mechanism bypasses the faulty node through the dynamic routing protocol (AODV) and heartbeat signals, so that each node can send heartbeat signals to adjacent nodes or gateways regularly.

[0124] Among them, the heartbeat signal sending interval T S The node surplus E node , Environmental dust concentration C dust and mine complex dust environment parameters T mine Jointly determined, the calculation formula is:

[0125]

[0126] Where k is the proportionality constant;

[0127] α, β, and γ are empirical coefficients;

[0128] This formula comprehensively considers the impact of the number of nodes, the impact of dust concentration on signal attenuation, and the impact of complex dust environment parameters in mines on equipment performance. When the heartbeat signal of a node is not received within the specified time, the adjacent nodes will immediately mark it as "unavailable" and start the self-healing mechanism.

[0129] The prescribed time T r According to the heartbeat sending interval T S , Dust concentration C dust and mine complex dust environment parameters T mine Calculation, the calculation formula is as follows:

[0130]

[0131] Among them, δ is the adjustment parameter;

[0132] The above formula takes into account the delay of signal propagation in high dust concentration and complex mine environment, as well as the impact of the number of nodes. The system uses the AODV protocol to build a new data transmission path. The affected node (the source node that wants to send data but finds that the current route is unavailable) first broadcasts a route request (RREQ) message containing the source node address, the destination node address, and a unique request identifier. When forwarding the RREQ, the number of hops H and the accumulated delay Δ are updated to reflect the current path characteristics. The update formula for the number of hops H and the accumulated delay Δ is:

[0133]

[0134] Among them, H new , H current Respectively represent the updated hop count and the current hop count;

[0135] Δ new , Δ current Represent the updated cumulative delay and the current cumulative delay respectively;

[0136] η, φ are weight coefficients;

[0137] L packet is the packet length;

[0138] V transmit is the transmission rate.

[0139] This formula combines the effects of dust concentration, coal mine dust concentration environment, and node quantity on hop count and delay. After receiving the RREQ message, other nodes check their own routing tables to determine whether there is a valid route to the target node; when forwarding the RREQ, they update information such as hop count and accumulated delay to reflect the current path characteristics, and establish a reverse route for use when returning a route reply (RREP). If the intermediate node has a valid route or is the target node itself, it will generate a RREP message containing the total hop count and estimated delay, and send it back to the source node along the reverse route.

[0140] After receiving multiple RREP messages, the source node evaluates the available paths according to the following path evaluation function ψ:

[0141]

[0142] Among them, α1, β1, and γ1 are evaluation weight coefficients;

[0143] Prioritize the path with the least hops to reduce the number of intermediate nodes, reduce the probability of failure and transmission delay; when the number of hops is the same, select the path with the lowest delay to improve the real-time and stability of data transmission. If there is historical data, the system will also consider the reliability record and remaining energy of the node to select a more stable path. Once the best path is selected, the source node updates the routing table, and the data packet is transmitted along the new path, successfully bypassing the faulty node. The entire process is transparent to the upper-layer application, ensuring the continuity and reliability of communication. In addition, the AODV protocol supports a routing maintenance mechanism. If a node in the new path fails again, the system will repeat the routing discovery and selection process to continuously optimize the data transmission path. In this way, the network can dynamically adapt to node failures and topology changes, ensure that the dust concentration detection data is reliably and timely transmitted to the target node or data processing center, and ensure the normal communication between modules. In addition, due to the congestion of communication channels, ultra-narrowband remote wireless transmission technology is required; the data storage and processing center 5 is responsible for storing the received dust concentration and particle size data, and processing the data according to the geographic information data format; the WirelessHART ultra-narrowband remote wireless communication module 4 sends the processed information data to multiple portable terminals (smart bracelets and smart explosion-proof mobile phones) of mine workers in the form of wireless data streams;

[0144] The multiple portable terminals remotely receive information data on dust concentration and particle size in the tunnel detected by the dust detection sensor 2, and superimpose the data with the tunnel topographic map to complete the visual display, so that miners can understand the dust status of the tunnel in a timely and intuitive manner. In addition, it is equipped with gesture recognition, which can switch different display modes, so that miners can avoid danger in emergency situations.

[0145] The operation rules of the rolling scheduling algorithm 3 are as follows:

[0146] When the system is first run, the rolling scheduling algorithm is based on the historical data of dust concentration D h (x, y) and the distribution of detection nodes to ensure the coverage integrity and resource utilization efficiency of the system in the early stage of operation. The entire detection area is divided into n grids R i (x, y), records the dust concentration historical data, current monitoring status, detection frequency and other information of n grid areas. Each grid represents an independent monitoring unit. Historical dust concentration data D h (x, y) is used as a reference, and combined with the total number of detection nodes N, all grids are initially allocated with a uniform strategy, that is, each grid is assigned at least one detection node, satisfying the formula

[0147]

[0148] Where N i To assign to grid R i The number of nodes;

[0149] λ is the adjustment coefficient, which is used to dynamically adjust the number of node allocations in each grid according to historical dust concentration data.

[0150] The above formula ensures that node allocation not only evenly covers each grid, but also appropriately tilts resources according to the historical dust concentration to improve the monitoring capability of high dust areas. After the initial task allocation is completed, the system enters the rolling detection mode and gradually optimizes the distribution of detection resources through a dynamic weight adjustment mechanism. In the rolling detection mechanism, the rolling interval time T r It is an important parameter of the algorithm, which directly determines the frequency and response speed of the system's dynamic adjustment. The initial default rolling interval of this system is set to 30 minutes. During each rolling cycle, the system will select some nodes to be rescheduled to uncovered or low-coverage areas based on the current detection coverage and regional weight changes to improve detection coverage and flexibility. Specifically, the number of nodes involved in the rolling, N m By the proportional parameter P m OK, the calculation formula is:

[0151]

[0152] Among them, Pm Indicates the percentage of nodes involved in scrolling;

[0153] C i is the adjustment demand index within the i-th rolling period;

[0154] M is the total number of rolling cycles;

[0155] This formula dynamically determines the number of nodes that need to be rescheduled in each rolling cycle by considering the adjustment needs in the historical rolling cycle to ensure the timeliness of system response and the rationality of adjustment. The goal of the rolling mechanism is to dynamically schedule nodes according to the regional weight value W. i For the number of detection nodes N i and detection frequency F i Real-time adjustments are made to achieve optimal allocation of detection resources. The monitoring priority of key areas is ensured, and the problem of insufficient coverage in the initial allocation is gradually corrected, thereby enhancing the overall adaptability of the system. In addition, the regional weight is the core indicator of the rolling scheduling algorithm, which is used to measure the priority of each monitoring grid and guide the allocation and scheduling of nodes. Each grid area R i The weight value W of (x,y) i Based on historical dust concentration data D h (x, y), regional accident number A(x, y) and real-time dust concentration data D r (x,y) comprehensive calculation, the formula is:

[0156]

[0157] Among them, α3, β3, and γ3 are the weight coefficients of historical dust concentration, regional accident number, and real-time dust concentration, respectively;

[0158] V f (x,y) is the grid R i ventilation rate;

[0159] The formula comprehensively considers historical dust accumulation, regional safety hazard frequency, and current dust concentration, and combines the adjustment effect of ventilation rate on weight. Historical data reflects the long-term dust accumulation level in the region, the number of accidents represents the frequency of safety hazards in the region, and real-time concentration data reflects the current dust situation. According to the weight size, the grid is divided into high weight (W i >0.7), medium weight (0.4≤W i ≤0.7) and low weight (W i<0.4), with higher weight areas being given priority to more detection resources and monitored at a higher frequency. This weight classification mechanism ensures that the allocation of detection resources reflects actual needs and avoids resource waste by comprehensively considering static historical information and dynamic real-time data. The rolling scheduling algorithm uses a dynamic task allocation mechanism to allocate tasks based on the regional weight value W. i For the number of detection nodes N i and detection frequency F i Make real-time adjustments to optimize the allocation of detection resources.

[0160] Number of detection nodes N i Dynamic adjustment through formula:

[0161]

[0162] Where W i For the grid R i The weight value of (x,y), is the sum of the weights of all grids, N total is the total number of nodes, F i is the adjusted detection frequency of the grid Ri(x,y), F base is the basic detection frequency, α af is the frequency adjustment coefficient, which is used to adjust the nonlinear relationship between frequency and the number of nodes. By introducing the quadratic term of the detection frequency, the dynamic adjustment of the number of nodes is more sensitive when the frequency difference is large, thereby improving the allocation accuracy of high-demand areas.

[0163] Detection frequency F i Then dynamically adjust through the formula:

[0164] F i =F base ·(1+k af ·W i )

[0165] where F base As the basic detection frequency;

[0166] k af is the weight adjustment coefficient, which indicates the amplifying effect of the weight on the detection frequency;

[0167] When a grid is continuous T c Second detection concentration value D r When (x, y) are both lower than τ, the system will reduce the detection frequency F in this area. i , the adjustment formula is:

[0168]

[0169] in To reduce the coefficient;

[0170] F min is the minimum detection frequency.

[0171] This dynamic task allocation mechanism ensures priority monitoring of high-risk areas by adjusting node distribution and detection frequency in real time, while avoiding excessive resource investment in low-risk areas. Rolling scheduling update is the core task completed in each rolling cycle, aiming to dynamically optimize the distribution and utilization of detection resources. At the beginning of each cycle, the system first recalculates the weight value W of all grids. i , update the weight value according to the latest real-time dust concentration data, historical records and regional accident statistics. Then, adjust the node allocation and detection frequency according to the weight to ensure that resources are tilted towards high-weight areas. At the same time, select the node N participating in the rolling scheduling m , and move these nodes to uncovered or low-coverage areas, give priority to covering high-weight areas, and gradually optimize the overall coverage. The optimization objective function of rolling scheduling is:

[0172]

[0173] Where E i represents the detection error, M j represents the node movement cost, β cost is the weight coefficient of the mobility cost. Through this process, rolling scheduling realizes the dynamic allocation of resources and the continuous optimization of the whole network coverage.

[0174] The self-healing network system 1 with AODV dynamic routing protocol is adapted to the complex working environment in the mine, and effectively solves the problem of communication interruption caused by sensor failure due to high temperature and high humidity. All nodes (sensors, multi-terminals of workers) in the detection system constitute a self-organizing network, the network is decentralized, all nodes can be used as routers, and multi-hop routing is adopted to complete communication, and the AODV protocol is used to realize dynamic routing. During operation, when the worker terminal needs to communicate, AODV will temporarily establish a route, thereby reducing unnecessary network traffic and power consumption; when a node needs to send data to the target node, AODV will start the path discovery mechanism to find the best path. When a node or link in the route fails, AODV will quickly switch to the backup path to ensure that communication is not interrupted. The operating mechanism of the self-healing network system 1 with AODV (Ad hoc On-Demand Distance Vector) dynamic routing protocol is as follows: All nodes in the detection system (including sensors and multi-terminal devices of workers) constitute a self-organizing network, the network is a decentralized structure, all nodes can be used as routers, and multi-hop routing is adopted to complete communication, and the AODV protocol is used to realize dynamic routing management. In this system, in order to deal with the dust concentration C in the minedust The impact on signal propagation and node margin E node , Mine complex dust environment parameters T mine and ventilation rate V f Dynamic changes in environmental parameters such as RREQ Perform adaptive adjustment, the formula is as follows:

[0175]

[0176] Where k is the proportionality constant;

[0177] δ is the adjustment parameter;

[0178] β cost is the weight coefficient of the moving cost;

[0179] α2 is the empirical coefficient of the number of nodes;

[0180] γ2 is the empirical coefficient of dust concentration;

[0181] V f Indicates ventilation rate;

[0182] C dust Indicates the dust concentration in the mine;

[0183] E node is the node margin.

[0184] According to this formula, when the dust is too high or the mine environment is too harsh, the interval between routing requests is appropriately increased to reduce the excessive overhead caused by unstable links; between nodes with good ventilation and sufficient number of nodes, the interval between RREQs can be appropriately shortened to increase the speed of route establishment. When the worker terminal needs to communicate, the AODV protocol temporarily establishes routes on demand to reduce unnecessary network traffic and power consumption; when a node needs to send data to the target node, AODV starts the path discovery mechanism. The source node first broadcasts a routing request (RREQ) message, which contains information such as the source node address, the target node address, the sequence number and the number of hops. After receiving the RREQ message, the intermediate node in the network updates the number of hops and establishes a reverse routing table entry. If the intermediate node has a valid route to the target node, or it is the target node itself, it generates a routing reply (RREP) message and returns to the source node along the reverse route. The source node may receive multiple RREP messages. It selects the best path based on the principle of the least hops and the latest sequence number; when the hops are the same, the target sequence number is compared and the path with the larger sequence number is selected to ensure the freshness and optimality of the route. When a node or link in the route fails, the relevant node will send a routing error (RERR) message to notify the affected source node. After receiving the RERR, the source node immediately starts a new path discovery process, broadcasts a new RREQ message, and searches for an alternate path. If there is a cached alternate route, the source node can also directly switch to the alternate path to ensure uninterrupted communication. Through the dynamic route discovery and maintenance mechanism of the AODV protocol, the system can quickly adapt to changes in network topology, dynamically acquire the best path and alternate paths, and ensure the stability and reliability of communication in the complex environment of the mine.

[0185] The data storage and processing center 5 stores the received real-time dust concentration, historical dust data, particle size data, etc., and processes them in blocks according to the sensor number. The rule is: take the horizontal center of the mining face as the origin, the lane as the x-axis, and place a sensor every 10m from the origin until the entire lane is covered. The numbering sequence is the origin as ①, and the numbers increase in the x-axis direction. The data storage and processing center 5 includes a data receiving module equipped with the AODV protocol, a data storage module including the InfluxDB real-time database and the Cassandra historical database, a data processing module, a real-time analysis engine, a decision support and control module, an energy consumption and resource management module, and a system self-healing and fault-tolerant module. The data receiving module of the AODV protocol is responsible for receiving the dynamic routing table; the data storage module is responsible for storing historical dust data, regional accident times, real-time dust concentration and other information in the rolling scheduling algorithm; the real-time analysis engine is responsible for calculating the grid weights in the rolling scheduling algorithm; the decision support and control module is responsible for the implementation of the rolling scheduling algorithm; the energy consumption and resource management module is responsible for the calculation and allocation of the overall power consumption of the system; the system self-healing and fault-tolerant module is responsible for the implementation of the self-healing network.

[0186] The portable terminal includes an explosion-proof mobile phone 6 and a smart bracelet 7. The portable terminal includes a ZT Map GIS map engine module, a WirelessHART ultra-narrowband long-distance wireless communication module supporting a self-healing network, a vibration module, a Python geographic information processing module, an OPENGL graphics rendering module, a gesture recognition module, and a user interaction module. The ZT Map GIS map engine module is responsible for processing the 3D coordinate topographic map of the tunnel. The WirelessHART ultra-narrowband long-distance wireless communication module supporting a self-healing network is responsible for receiving the information data sent by the data storage and processing center 5, and sending it to the Python geographic information processing module to complete the superposition with the coordinate topographic map output by the ZTMap GIS map engine module. After being processed by the user interaction module and the OPENGL graphics rendering module, the visual display is completed on the screen. The gesture recognition module realizes the switching of the output content of the explosion-proof mobile phone by recognizing the miner's fist gesture. The initial interface is a 3D image map of the dust concentration distribution in the area where the miner is located. Make a fist once, and the initial interface will be switched to the optimal evacuation path from the miner's location to a low-concentration dust safety environment. According to the dust concentration range of the miner's area: 50mg / m 3 The vibration frequency in the above area is 30 times in 1 minute; 50mg / m 3 -20mg / m 3 The vibration frequency in the area is 20 times in 1 minute; 20mg / m 3 -5mg / m 3 The vibration frequency in the area is 10 times in 1 minute; 5mg / m 3 The above processing is carried out on the basis of the superposition of dust concentration data and topographic map.

[0187] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network, characterized in that: include: Multiple dust detection sensors, WirelessHART ultra-narrowband long-range wireless communication modules for signal transmission, data storage and processing centers, and terminal devices, wherein the terminal devices include explosion-proof mobile phones and / or smart bracelets; Dust detection sensors transmit data through a self-healing network system, and obtain the dust concentration distribution in the tunnel based on the dust data detected by the dust detection sensors and the rolling scheduling algorithm; then the dust concentration distribution is transmitted to the data storage and processing center through the WirelessHART ultra-narrowband long-range wireless communication module.

2. According to the multi-node rolling intelligent dust detection and multi-terminal collaborative protection system in an adaptive self-healing network according to claim 1, it is characterized in that: The transmission of the WirelessHART ultra-narrowband long-range wireless communication module is matched with a self-healing network system with a dynamic routing protocol to transmit data to a data storage and processing center; wherein a regular heartbeat signal is set in the self-healing network system, and the heartbeat signal is sent to adjacent nodes or gateways regularly to confirm that each node can operate normally. If the heartbeat signal is not received in time, the system quickly identifies the faulty node and automatically starts the self-healing mechanism; The self-healing mechanism bypasses the faulty node through a dynamic routing protocol and heartbeat signals, so that each node periodically sends a heartbeat signal to an adjacent node or gateway; Among them, the heartbeat signal sending interval T S The node surplus E node , Environmental dust concentration C dust and mine complex dust environment parameters T mine Jointly determined, the calculation formula is: Where k is the proportionality constant; α, β, and γ are empirical coefficients; When the heartbeat signal of a node is not received within the specified time, the adjacent node will immediately mark it as unavailable and start the self-healing mechanism; the specified time T r According to the heartbeat sending interval T S , Dust concentration C dust and mine complex dust environment parameters T mine Calculation, the calculation formula is as follows: Among them, δ is the adjustment parameter; The system uses the AODV protocol to build a new data transmission path. The source node first broadcasts the RREQ message. The route request message contains the source node address, the destination node address and a unique request identifier. When the affected node forwards the RREQ, it updates the hop count H and the accumulated delay Δ to reflect the current path characteristics. The update formula of the hop count H and the accumulated delay Δ is: Among them, H new , H current Respectively represent the updated hop count and the current hop count; Δ new , Δ current Represent the updated cumulative delay and the current cumulative delay respectively; η, φ are weight coefficients; L packet is the packet length; V transmit is the transmission rate; After receiving the RREQ message, other nodes check their own routing tables to see if there is a valid route to the target node; if a valid route is found, there is no need to forward it; if no valid route is found, the node broadcasts the RREQ message to find a new path; After receiving multiple RREP messages, the source node evaluates the available paths according to the following path evaluation function ψ and selects the path with the highest path evaluation function value: Among them, α1, β1, and γ1 are evaluation weight coefficients; H is the number of hops; If the path evaluation function values ​​are the same, the path with the least hops is selected; if the hop count is still the same, the path with the lowest delay is selected.

3. According to the multi-node rolling intelligent dust detection and multi-terminal collaborative protection system in an adaptive self-healing network according to claim 2, it is characterized in that: The time interval T for broadcasting RREQ messages RREQ Perform adaptive adjustment, the formula is as follows: Where k is the proportionality constant; δ is the adjustment parameter; β cost is the weight coefficient of the moving cost; α2 is the empirical coefficient of the number of nodes; γ2 is the empirical coefficient of dust concentration; V f Indicates ventilation rate; C dust Indicates the dust concentration in the mine; E node is the node margin.

4. According to claim 1, a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network, characterized in that: The rolling scheduling algorithm includes: At the beginning of each cycle, the system first recalculates the weight values ​​W of all grids i , update the weight value according to the latest real-time dust concentration data, historical records and regional accident statistics; then adjust the node allocation and detection frequency according to the weight to ensure that resources are tilted towards high-weight areas; at the same time, select the node N participating in the rolling scheduling m , and move these nodes to uncovered or low-coverage areas; The optimization objective function of rolling scheduling is: Among them, E i Indicates detection error; M j represents the node movement cost; β cost is the weight coefficient of the moving cost; n is the number of grids; N is the total number of nodes.

5. According to claim 1, a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network, characterized in that: The rolling scheduling algorithm (3) also includes: The entire detection area is divided into n grids R i (x, y), each grid represents an independent monitoring unit; historical dust concentration data D h (x, y) is used as a reference, and combined with the total number of detection nodes N, all grids are initially allocated with a uniform strategy, that is, each grid is assigned at least one detection node, satisfying the formula: Among them, N i To assign to grid R i The number of nodes; D h (x, y, i) is the historical dust concentration data of the i-th single grid; The historical dust concentration data for all grids; is the rounding symbol; λ is the adjustment coefficient, which is used to dynamically adjust the number of node allocations in each grid according to historical dust concentration data; After the initial task allocation is completed, the system enters the rolling detection mode, and the number of nodes N participating in the rolling m By the proportional parameter P m OK, the calculation formula is: Among them, P m Indicates the percentage of nodes involved in scrolling; C i is the adjustment demand index within the i-th rolling period; m is the number of nodes; M is the total number of rolling cycles; Indicates rounding up; In addition, each grid area R i The weight value W of (x,y) i Based on historical dust concentration data D h (x, y), regional accident number A(x, y) and real-time dust concentration data D r (x,y) comprehensive calculation, the formula is: Among them, α3, β3, and γ3 are the weight coefficients of historical dust concentration, regional accident number, and real-time dust concentration, respectively; V f (x,y) is the grid R i ventilation rate; According to the weight, the grid is divided into three levels: high weight, medium weight and low weight: i >0.7, classified as high weight; for 0.4≤W i ≤0.7, classified as medium weight; for W i <0.4, classified as low weight; The rolling scheduling algorithm uses a dynamic task allocation mechanism to allocate tasks according to the regional weight value W. i For the number of detection nodes N i and detection frequency F i Make real-time adjustments to optimize the allocation of testing resources: Number of detection nodes N i Dynamically adjusted by the following formula: Where W i is the weight value of the grid Ri(x,y); is the sum of the weights of all grids; N total is the total number of nodes; F i is the adjusted detection frequency of the grid Ri(x,y); F base As the basic detection frequency; α af is the frequency adjustment coefficient, which is used to adjust the nonlinear relationship between frequency and the number of nodes; Detection frequency F i It is dynamically adjusted through the following formula: F i =F base ·(1+k af ·W i ) where F base As the basic detection frequency; k af is the weight adjustment coefficient, which indicates the amplifying effect of the weight on the detection frequency; When a grid is continuous T c Second detection concentration value D r When (x, y) are both lower than the detection concentration threshold τ, the system will reduce the detection frequency F in this area. i , the adjustment formula is: in To reduce the coefficient; F min is the minimum detection frequency.

6. According to claim 1, a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network, characterized in that: The terminal device remotely receives information data on dust concentration and particle size in the tunnel detected by the dust detection sensor (2), and superimposes the data with the tunnel topographic map to complete visual display.

7. According to claim 1, a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system under an adaptive self-healing network, characterized in that: The terminal device is equipped with gesture recognition. The initial interface of the terminal device is a 3D image of the dust concentration distribution in the area where the miner is located. When a specific gesture is recognized, the interface is switched to the optimal evacuation path from the miner's location to a low-concentration dust safety environment.

8. According to claim 1, a multi-node rolling intelligent dust detection and multi-terminal collaborative protection system in an adaptive self-healing network, characterized in that: The terminal device is equipped with a vibration module: Miners are exposed to dust concentrations of 50 mg / m 3 When in the above range, the vibration frequency of the vibration module is 30 times per minute; Miners are exposed to dust concentrations of 50 mg / m 3 -20mg / m 3 When in the area, the vibration frequency of the vibration module is 20 times per minute; Miners are exposed to dust concentrations ranging from 20 mg / m 3 -5mg / m 3 When in the area, the vibration frequency of the vibration module is 10 times per minute; Miners are exposed to dust concentrations of 5 mg / m 3 When in the area, the vibration module does not vibrate.

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