Adaptive intelligent mining anti-explosion lighting system

Abstract

The invention belongs to the technical field of mine lighting, and particularly relates to an adaptive intelligent mining anti-explosion lighting system which comprises a positioning base station, a lighting network, a personnel identification card, a three-dimensional GIS module, an environment monitoring module and a central processing module. According to the system, a visibility compensation component is constructed according to empirical formulas of visibility and smoke, so that the change of the visibility is compensated when the luminous power is adjusted, and additional light sensors and motion sensors are not needed. In addition, the invention also provides a simulation K shortest path algorithm which organically combines a Yen algorithm, fire simulation simulation, a particle swarm algorithm and risk assessment, so that dynamic and comprehensive intelligent escape path planning is realized. And finally, the central processing module controls the light emitting units on the way of the escape path to indicate the escape path in a stroboscopic mode in sequence from far to near according to the distance relative to the end point of the escape path.

Description

Technical Field

[0001] The invention relates to the technical field of mine lighting, and in particular to an adaptive intelligent explosion-proof lighting system for mines. Background Art

[0002] The mine lighting system is an engineering system that provides lighting for the interior of the mine. The system needs to meet the special environmental requirements inside the mine, such as dustproof, waterproof, corrosion-resistant and explosion-proof, to ensure long-term and stable operation in the special environment of the mine. The existing mine intelligent lighting systems generally use a solution of light sensors plus motion sensors to control the brightness and switch of lamps, and generally do not have an escape indication function and do not consider the impact of visibility. The existing escape route planning methods are generally based on static analysis and planning, and do not take into account the dynamic evolution of the fire situation over time and the role of the refuge chamber, nor do they specify how to indicate the escape route. Summary of the invention

[0003] The present invention overcomes the shortcomings of the prior art and provides an adaptive intelligent explosion-proof lighting system for mining, which constructs a visibility compensation component according to an empirical formula of visibility and smoke, and realizes compensating for changes in visibility when adjusting the luminous power, without the need for additional light sensors and motion sensors. In addition, a simulated K shortest path algorithm is proposed, which uses the Yen algorithm to generate K shortest path groups, and uses a particle swarm simulation path verification algorithm and a hazard assessment to perform two rounds of screening to generate a final escape path. In this process, the refuge chamber is also regarded as a potential end point. The simulated K shortest path algorithm organically combines the Yen algorithm, fire simulation, particle swarm algorithm and hazard assessment to realize dynamic and comprehensive intelligent escape path planning. Finally, the central processing module controls the light-emitting units along the escape path to indicate the escape path in a flashing manner from far to near according to the distance relative to the end point of the escape path.

[0004] The adaptive intelligent mining explosion-proof lighting system includes: a positioning base station, a lighting network, a personnel identification card, a three-dimensional GIS module, an environmental monitoring module and a central processing module;

[0005] The three-dimensional GIS module is electrically connected to the central processing module, the environmental monitoring module is electrically connected to the central processing module, the positioning base station is communicatively connected to the three-dimensional GIS module, the lighting network is communicatively connected to the central processing module, the personnel identification card is communicatively connected to the positioning base station, and the lighting network is communicatively connected to the positioning base station;

[0006] The lighting network is installed in the mine, and includes a plurality of lighting groups. Each lane in the mine corresponds to a lighting group. The lighting group includes a first camera, a second camera, and a plurality of lighting modules. The lighting modules are fixedly arranged on the ceiling of the lane at equal intervals. The lighting modules include a device identification card and a light-emitting unit. The first camera and the second camera are respectively located at two ends of the lane, and are arranged diagonally. The device identification card reports the device position to the central processing module.

[0007] The first camera and the second camera collect videos in the lane and upload them to the central processing module and the environment monitoring module;

[0008] The environmental monitoring module collects and processes the gas concentration, smoke concentration and tunnel video in real time to generate an underground environmental report and transmit it to the central processing module, and sends a fire warning to the central processing module based on the underground environmental report;

[0009] The central processing module controls the switch of the light-emitting unit and automatically adjusts the power of the light-emitting unit according to the change of brightness and smoke concentration;

[0010] After receiving the fire warning, the central processing module plans the escape route by using the simulated K shortest path algorithm, and controls the light-emitting units along the escape route to flash in sequence from far to near according to the distance relative to the end point of the escape route.

[0011] Furthermore, the personnel identification card reports the personnel location to the three-dimensional GIS module in real time;

[0012] The central processing module uploads the personnel location and equipment location to the three-dimensional GIS module;

[0013] The three-dimensional GIS module collects the mine design drawings, and constructs a GIS three-dimensional simulation model according to the mine design drawings, personnel positions and equipment positions, and inputs the model into the central processing module.

[0014] Furthermore, the central processing module corrects the illumination of the light-emitting unit to comply with the "Mine Electricity Design Standards", records the power of the light-emitting unit at this time as the benchmark power, the average brightness of the video in the tunnel of the lighting group where the light-emitting unit is located at this time is the benchmark brightness, and the smoke concentration in this tunnel at this time is the benchmark smoke concentration.

[0015] Furthermore, the process of controlling the switch of the light-emitting unit includes the following steps:

[0016] Step E1: The central processing module calculates the displacement vector of the personnel identification card according to the GIS three-dimensional simulation model;

[0017] Step E2: The central processing module uses the displacement vector of the personnel identification card as the angle bisector to delineate a sector area with an angle of 188° and a radius of 100 meters, and turns on the light-emitting units within the sector area.

[0018] Furthermore, the process of automatically adjusting the power of the light-emitting unit according to the brightness change and the smoke concentration change includes the following steps:

[0019] Step T1: The central processing module receives the video of the tunnel of the lighting group where the light-emitting unit in the sector area is located, calculates the average brightness of the tunnel at this time, and extracts the smoke concentration of the tunnel at this time from the underground environment report;

[0020] Step T2: Adjust the power of the light-emitting unit according to the change in brightness and smoke concentration. The power adjustment formula is as follows:

[0021]

[0022]

[0023] Where W is the adjusted light unit power, W' is the reference power, L' is the reference brightness, L is the average brightness at this time, C is the visibility compensation component, ρ' is the reference smoke concentration, and ρ is the smoke concentration at this time.

[0024] Furthermore, the process of planning the escape path using the simulated K shortest path algorithm includes the following steps:

[0025] Step S1: The central processing module constructs an underground undirected weighted graph according to the GIS three-dimensional simulation model, extracts tunnels from the GIS three-dimensional simulation model as the edges of the underground undirected weighted graph, and extracts the intersections between tunnels, mine exits and refuge chambers as the vertices of the underground undirected weighted graph. The distance of the tunnels is extracted from the GIS three-dimensional simulation model as the weight of the edge of the underground undirected weighted graph;

[0026] Step S2: the central processing module uses Pyrosim to deduce the fire situation according to the underground environmental report and the GIS three-dimensional simulation model to generate a deduction result, and constructs a dynamic underground undirected weighted graph for the underground undirected weighted graph according to the deduction result. The elements of the dynamic underground undirected weighted graph include vertices and edges, and each element has an affected attribute, whose value is affected and not affected. The value of the affected attribute changes with time according to the deduction result;

[0027] Step S3: The central processing module marks the location of the personnel identification card in the underground undirected weighted graph according to the GIS three-dimensional simulation model, extracts the location of the mine exit and the refuge chamber as the end point list, and sorts them according to the distance relative to the location of the personnel identification card;

[0028] Step S4: Select a location from the destination list in order as the path destination, take the location of the personnel identification card as the path starting point, and use the Yen algorithm to generate K shortest path groups;

[0029] Step S5: Use the particle swarm simulation path verification algorithm to screen the K shortest path groups and generate the remaining K shortest path groups;

[0030] Step S6: Execute steps S4 to S5 for each position in the destination list, and aggregate all remaining K shortest path groups into an escape path group;

[0031] Step S7: Select the paths in the escape path group whose path lengths differ from the path lengths of the shortest path in the escape path group by no more than 5%, sort them from short to long by path length, summarize them into a set of paths to be evaluated, perform path hazard evaluation on them, and select the final escape path based on the evaluation results.

[0032] Furthermore, the process of constructing a dynamic downhole undirected weighted graph for the downhole undirected weighted graph according to the deduction result in step S2 includes the following steps:

[0033] Step S21: adding a time attribute to the underground undirected weighted graph, and adding a gas concentration attribute, a smoke concentration attribute, and a spread attribute to each element in the underground undirected weighted graph, wherein the gas concentration attribute and the smoke concentration attribute are floating point classes, and their default values ​​are 0, the spread attribute is a string class, and its default value is not spread, and the time attribute is a datetime class, and its default value is 00:00:00;

[0034] Step S22: defining a dynamic update function, which extracts information from the deduction results according to changes in the attribute values ​​of the deduction results over time to update the values ​​of the gas concentration attribute and the smoke concentration attribute;

[0035] Step S23: collecting gas lethal concentration and smoke lethal concentration from the network, defining a spread range function, which updates the value of the spread attribute of the element whose value of at least one of the gas concentration attribute and the smoke concentration attribute reaches its corresponding lethal concentration to be affected;

[0036] Step S24: Obtain a dynamic downhole undirected weighted graph.

[0037] Furthermore, the process of step S5 includes the following steps:

[0038] Step S51: creating a particle for each path in the K shortest path group;

[0039] Step S52: Verification start: extract the fire occurrence time from the deduction results as the time attribute assignment of the dynamic underground undirected weighted graph, and each particle moves along the path at a speed of 10 kilometers per hour;

[0040] Step S53: updating the dynamic downhole undirected weighted graph: using the timedelta function to add 1 second to the time attribute of the dynamic downhole undirected weighted graph, calling the dynamic update function and the affected range function to update the attributes of each element of the dynamic downhole undirected weighted graph;

[0041] Step S54: Update the particle state and perform screening: update the position of each particle at this time, record the value of the smoke concentration attribute of the element to which each particle is located at this time as the instantaneous smoke exposure, record the value of the gas concentration attribute as the instantaneous gas exposure, and delete the path corresponding to the affected particle from the K shortest path group by taking the value of the affected attribute of the element to which the particle is located; and end the movement of the particle;

[0042] Step S55: ending the movement of the particle that has reached the end point and recording data: ending the movement of the particle whose position is the end point, summing up each instantaneous smoke exposure recorded by the particle as the cumulative smoke exposure, and summing up each instantaneous gas exposure recorded by the particle as the cumulative gas exposure;

[0043] Step S56: repeating steps S53 to S55 until all particles created in step S51 have finished moving;

[0044] Step S57: The undeleted part of the K shortest path group is used as the remaining K shortest path group.

[0045] Furthermore, the process of path hazard assessment in step S7 specifically includes the following steps:

[0046] Step S71: Preprocessing of the path set to be evaluated: for all the paths in the path set to be evaluated, extract the slope of each lane in the path from the GIS three-dimensional simulation model, take the absolute value and sum it up as the cumulative path slope, perform Min-Max standardization on the cumulative path slopes of all the paths in the path set to be evaluated and the cumulative smoke exposure and cumulative gas exposure of the corresponding particles, respectively, to generate the standard path slope, standard smoke exposure and standard gas exposure corresponding to each path in the path set to be evaluated;

[0047] Step S72: selecting a path from the set of paths to be evaluated in order;

[0048] Step S73: Calculate the risk index of this path using a risk assessment formula, the risk assessment formula is as follows:

[0049] Where D is the hazard index, I is the standard path slope, S is the standard smoke exposure, and G is the standard gas exposure;

[0050] Step S74: repeating steps S72 to S73 until all paths in the set of paths to be evaluated have a corresponding danger index;

[0051] Step S75: Sorting and final escape path selection: sort all the paths in the path set to be evaluated from small to large according to the danger index, and select the path whose end point is the mine exit and has the lowest danger index as the final escape path. If such a path does not exist, select the path with the lowest danger index as the final escape path.

[0052] The beneficial effects of the present invention are as follows:

[0053] (1) The present invention constructs a visibility compensation component based on the empirical formula of visibility and smoke, thereby compensating for changes in visibility when adjusting the luminous power without the need for additional light sensors and motion sensors. In addition, a simulated K shortest path algorithm is proposed, which uses the Yen algorithm to generate K shortest path groups, and uses a particle swarm simulation path verification algorithm and a hazard assessment to perform two rounds of screening to generate the final escape path. In this process, the refuge chamber is also regarded as a potential end point. The simulated K shortest path algorithm organically combines the Yen algorithm, fire simulation, particle swarm algorithm and hazard assessment to achieve dynamic and comprehensive intelligent escape path planning. Finally, the central processing module controls the light-emitting units along the escape path to flash in sequence from far to near according to the distance relative to the end point of the escape path to indicate the escape path.

[0054] (2) The present invention includes the refuge chamber in the destination list when using the Yen algorithm to generate the K shortest path groups, thus overcoming the industry's long-standing technical bias of ignoring the refuge chamber when planning escape routes, increasing the robustness of escape route planning, and injecting more possibilities into escape route planning.

[0055] (3) The particle swarm simulation path verification algorithm proposed in the present invention realizes the organic combination of dynamic simulation, graph theory and particle swarm algorithm, defines the dynamic update function and the affected range function to reflect the deduction results in the dynamic underground undirected weighted graph, rather than directly simulating in the GIS three-dimensional simulation model. While retaining the characteristics of the dynamic evolution of the fire situation over time, it compresses the computing power expenditure and realizes accurate and fast escape path planning.

[0056] (4) The hazard assessment formula proposed in the present invention measures the ruggedness of the path by the sum of the absolute values ​​of the slope, and sets the weights according to the poisoning concentrations of gas and smoke. The formula is standardized before being introduced to eliminate the differences caused by the dimensions, so as to better measure the impact of different factors on the hazard of the path, and ultimately improve the reliability of the hazard assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1This is a module diagram of an adaptive intelligent explosion-proof lighting system for mining proposed by the present invention;

[0058] Figure 2 A flow chart of the particle swarm simulation path verification algorithm proposed by the present invention;

[0059] Figure 3 A flow chart of the path hazard assessment proposed by the present invention;

[0060] Figure 4 This is a schematic diagram of the sector area in Example 4.

[0061] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the examples given are only used to explain the present invention, and are not used to limit the scope of the present invention.

[0063] Example 1, see Figure 1 ,The present invention provides an adaptive intelligent mining explosion-proof lighting system, including: a positioning base station, a lighting network, a personnel identification card, a three-dimensional GIS module, an environmental monitoring module and a central processing module;

[0064] The three-dimensional GIS module is electrically connected to the central processing module, the environmental monitoring module is electrically connected to the central processing module, the positioning base station is communicatively connected to the three-dimensional GIS module, the lighting network is communicatively connected to the central processing module, the personnel identification card is communicatively connected to the positioning base station, and the lighting network is communicatively connected to the positioning base station;

[0065] The lighting network is installed in the mine, and includes multiple lighting groups. Each lane in the mine corresponds to a lighting group. The lighting group includes a first camera, a second camera, and multiple lighting modules. The lighting modules are fixedly arranged on the ceiling of the lane at equal intervals. The lighting modules include a device identification card and a light-emitting unit. The first camera and the second camera are respectively located at the two ends of the lane, and are arranged diagonally. The device identification card reports the device position to the central processing module. In this embodiment, the spacing between the lighting modules is 4 meters.

[0066] The first camera and the second camera collect videos in the lane and upload them to the central processing module and the environment monitoring module;

[0067] The environmental monitoring module collects and processes the gas concentration, smoke concentration and tunnel video in real time to generate an underground environmental report and transmit it to the central processing module, and sends a fire warning to the central processing module based on the underground environmental report;

[0068] The central processing module controls the switch of the light-emitting unit and automatically adjusts the power of the light-emitting unit according to the change of brightness and smoke concentration;

[0069] After receiving the fire warning, the central processing module plans the escape route by using the simulated K shortest path algorithm, and controls the light-emitting units along the escape route to flash in sequence from far to near according to the distance relative to the end point of the escape route.

[0070] Embodiment 2: This embodiment is based on the above embodiment, and the personnel identification card reports the personnel location to the three-dimensional GIS module in real time;

[0071] The central processing module uploads the personnel location and equipment location to the three-dimensional GIS module;

[0072] The three-dimensional GIS module collects the mine design drawings, and constructs a GIS three-dimensional simulation model according to the mine design drawings, personnel positions and equipment positions, and inputs the model into the central processing module.

[0073] Embodiment three, this embodiment is based on embodiment two, the central processing module corrects the illumination of the light-emitting unit to comply with the "Mine Electricity Design Standards", records the power of the light-emitting unit at this time as the reference power, the average brightness of the video in the tunnel of the lighting group where the light-emitting unit is located at this time is the reference brightness, and the smoke concentration in this tunnel at this time is the reference smoke concentration.

[0074] Example 4, see Figure 4 This embodiment is based on the third embodiment, and the process of controlling the switch of the light-emitting unit includes the following steps:

[0075] Step E1: The central processing module calculates the displacement vector of the personnel identification card according to the GIS three-dimensional simulation model;

[0076] Step E2: The central processing module uses the displacement vector of the personnel identification card as the angle bisector to delineate a sector area with an angle of 188° and a radius of 100 meters, and turns on the light-emitting units within the sector area.

[0077] Embodiment 5, based on Embodiment 4, the process of automatically adjusting the power of the light-emitting unit according to the brightness change and the smoke concentration change includes the following steps:

[0078] Step T1: The central processing module receives the video of the tunnel of the lighting group where the light-emitting unit in the sector area is located, calculates the average brightness of the tunnel at this time, and extracts the smoke concentration of the tunnel at this time from the underground environment report;

[0079] Step T2: Adjust the power of the light-emitting unit according to the change in brightness and smoke concentration. The power adjustment formula is as follows:

[0080]

[0081]

[0082] Wherein W is the adjusted light-emitting unit power, W' is the reference power, L' is the reference brightness, L is the average brightness at this time, C is the visibility compensation component, ρ' is the reference smoke concentration, ρ is the smoke concentration at this time. In this embodiment, the reference power is 25W, the reference brightness is 7 nits, and the reference smoke concentration is 200ppm. At this time, the average brightness is 5 nits, and the smoke concentration is 300ppm. It is concluded that the adjusted light-emitting unit power is 41W.

[0083] Embodiment 6, based on Embodiment 5, the process of planning an escape path using the simulated K shortest path algorithm comprises the following steps:

[0084] Step S1: The central processing module constructs an underground undirected weighted graph according to the GIS three-dimensional simulation model, extracts tunnels from the GIS three-dimensional simulation model as the edges of the underground undirected weighted graph, and extracts the intersections between tunnels, mine exits and refuge chambers as the vertices of the underground undirected weighted graph. The distance of the tunnels is extracted from the GIS three-dimensional simulation model as the weight of the edge of the underground undirected weighted graph;

[0085] Step S2: the central processing module uses Pyrosim to deduce the fire situation according to the underground environmental report and the GIS three-dimensional simulation model to generate a deduction result, and constructs a dynamic underground undirected weighted graph for the underground undirected weighted graph according to the deduction result. The elements of the dynamic underground undirected weighted graph include vertices and edges, and each element has an affected attribute, whose value is affected and not affected. The value of the affected attribute changes with time according to the deduction result;

[0086] Step S3: The central processing module marks the location of the personnel identification card in the underground undirected weighted graph according to the GIS three-dimensional simulation model, extracts the location of the mine exit and the refuge chamber as the end point list, and sorts them according to the distance relative to the location of the personnel identification card;

[0087] Step S4: Select a location from the destination list in order as the path destination, take the location of the personnel identification card as the path starting point, and use the Yen algorithm to generate K shortest path groups;

[0088] Step S5: Use the particle swarm simulation path verification algorithm to screen the K shortest path groups and generate the remaining K shortest path groups;

[0089] Step S6: Execute steps S4 to S5 for each position in the destination list, and aggregate all remaining K shortest path groups into an escape path group;

[0090] Step S7: Select the paths in the escape path group whose path lengths differ from the path lengths of the shortest path in the escape path group by no more than 5%, sort them from short to long by path length, summarize them into a set of paths to be evaluated, perform path hazard evaluation on them, and select the final escape path based on the evaluation results.

[0091] Embodiment 7, based on Embodiment 6, the process of constructing a dynamic downhole undirected weighted graph for the downhole undirected weighted graph according to the deduction result in step S2 comprises the following steps:

[0092] Step S21: adding a time attribute to the underground undirected weighted graph, and adding a gas concentration attribute, a smoke concentration attribute, and a spread attribute to each element in the underground undirected weighted graph, wherein the gas concentration attribute and the smoke concentration attribute are floating point classes, and their default values ​​are 0, the spread attribute is a string class, and its default value is not spread, and the time attribute is a datetime class, and its default value is 00:00:00;

[0093] Step S22: defining a dynamic update function, which extracts information from the deduction results according to changes in the attribute values ​​of the deduction results over time to update the values ​​of the gas concentration attribute and the smoke concentration attribute;

[0094] Step S23: collecting gas lethal concentration and smoke lethal concentration from the network, defining a spread range function, which updates the value of the spread attribute of the element whose value of at least one of the gas concentration attribute and the smoke concentration attribute reaches its corresponding lethal concentration to be affected;

[0095] Step S24: Obtain a dynamic downhole undirected weighted graph.

[0096] Embodiment 8, see Figure 2 This embodiment is based on the seventh embodiment, and the process of step S5 includes the following steps:

[0097] Step S51: creating a particle for each path in the K shortest path group;

[0098] Step S52: Verification start: extract the fire occurrence time from the deduction results as the time attribute assignment of the dynamic underground undirected weighted graph, and each particle moves along the path at a speed of 10 kilometers per hour;

[0099] Step S53: updating the dynamic downhole undirected weighted graph: using the timedelta function to add 1 second to the time attribute of the dynamic downhole undirected weighted graph, calling the dynamic update function and the affected range function to update the attributes of each element of the dynamic downhole undirected weighted graph;

[0100] Step S54: Update the particle state and perform screening: update the position of each particle at this time, record the value of the smoke concentration attribute of the element to which each particle is located at this time as the instantaneous smoke exposure, record the value of the gas concentration attribute as the instantaneous gas exposure, and delete the path corresponding to the affected particle from the K shortest path group by taking the value of the affected attribute of the element to which the particle is located; and end the movement of the particle;

[0101] Step S55: ending the movement of the particle that has reached the end point and recording data: ending the movement of the particle whose position is the end point, summing up each instantaneous smoke exposure recorded by the particle as the cumulative smoke exposure, and summing up each instantaneous gas exposure recorded by the particle as the cumulative gas exposure;

[0102] Step S56: repeating steps S53 to S55 until all particles created in step S51 have finished moving;

[0103] Step S57: The undeleted part of the K shortest path group is used as the remaining K shortest path group.

[0104] Embodiment 9, see Figure 3 This embodiment is based on the eighth embodiment, and the process of path hazard assessment in step S7 specifically includes the following steps:

[0105] Step S71: Preprocessing of the path set to be evaluated: for all the paths in the path set to be evaluated, extract the slope of each lane in the path from the GIS three-dimensional simulation model, take the absolute value and sum it up as the cumulative path slope, perform Min-Max standardization on the cumulative path slopes of all the paths in the path set to be evaluated and the cumulative smoke exposure and cumulative gas exposure of the corresponding particles, respectively, to generate the standard path slope, standard smoke exposure and standard gas exposure corresponding to each path in the path set to be evaluated;

[0106] Step S72: selecting a path from the set of paths to be evaluated in order;

[0107] Step S73: Calculate the risk index of this path using a risk assessment formula, the risk assessment formula is as follows:

[0108] Wherein D is the danger index, I is the standard path slope, S is the standard smoke exposure, and G is the standard gas exposure. In this embodiment, the standard path slope is 0.8, the standard smoke exposure is 0.21, and the standard gas exposure is 0.23, and the danger index is 0.026;

[0109] Step S74: repeating steps S72 to S73 until all paths in the set of paths to be evaluated have a corresponding danger index;

[0110] Step S75: Sorting and final escape path selection: sort all the paths in the path set to be evaluated from small to large according to the danger index, and select the path whose end point is the mine exit and has the lowest danger index as the final escape path. If such a path does not exist, select the path with the lowest danger index as the final escape path.

[0111] Embodiment 10, based on embodiment 9, runs in Windows operating system environment, relies on Anacond3 environment, and uses NetworkX to construct underground undirected weighted graph and dynamic underground undirected weighted graph as the framework of particle swarm simulation path verification algorithm, uses Pandas library and Numpy tool to complete data processing, uses sklearn library to complete Min-Max standardization, three-dimensional GIS module is implemented by KJ2236J, environmental monitoring module is implemented by KJ2427, positioning base station is implemented by KJ2236-F1, personnel identification card is implemented by KJ2236-K1, central processing module is implemented by SIMATI C industrial PC is adopted, the first camera and the second camera are implemented by KBA-127, the light-emitting unit is implemented by DGS51 / 127L(A), the equipment identification card is implemented by KJ2236-K2, the smoke concentration, gas concentration, instantaneous gas exposure and instantaneous smoke exposure are in ppm, the cumulative smoke exposure and cumulative gas exposure are in ppm·s, the slope and cumulative path slope are in degrees, the standard path slope, standard smoke exposure and standard gas exposure are dimensionless quantities due to Min-Max standardization, and the average brightness and reference brightness are obtained by processing the video using the cv2.mean() function in the OpenCV library.

[0112] Although 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 appended claims and their equivalents.

[0113] The present invention and its implementation methods are described above. Such description is not restrictive. What is shown in the accompanying drawings is only one of the implementation methods of the present invention. The actual structure is not limited thereto. In short, if ordinary technicians in this field are inspired by the present invention and do not deviate from the purpose of the invention, they can creatively design structural methods and embodiments similar to the technical scheme, which should all fall within the scope of protection of the present invention.

Claims

1. An adaptive intelligent explosion-proof lighting system for mines, characterized by: The adaptive intelligent mining explosion-proof lighting system includes: a positioning base station, a lighting network, a personnel identification card, a three-dimensional GIS module, an environmental monitoring module and a central processing module; The three-dimensional GIS module is electrically connected to the central processing module, the environmental monitoring module is electrically connected to the central processing module, the positioning base station is communicatively connected to the three-dimensional GIS module, the lighting network is communicatively connected to the central processing module, the personnel identification card is communicatively connected to the positioning base station, and the lighting network is communicatively connected to the positioning base station; The lighting network includes a plurality of lighting groups, each lighting group includes a plurality of lighting modules, each lighting module includes a device identification card and a light-emitting unit, and the device identification card reports the location of the lighting module to the central processing module; The lighting group collects videos in the lane and uploads them to the central processing module and the environmental monitoring module; The environmental monitoring module collects and processes the gas concentration, smoke concentration and tunnel video in real time to generate an underground environmental report and transmit it to the central processing module, and sends a fire warning to the central processing module based on the underground environmental report; The central processing module controls the switch of the light-emitting unit and automatically adjusts the power of the light-emitting unit according to the change of brightness and smoke concentration; The central processing module plans an escape route using a simulated K shortest path algorithm after receiving a fire warning.

2. The adaptive intelligent explosion-proof lighting system for mines according to claim 1 is characterized in that: The personnel identification card reports the personnel location to the three-dimensional GIS module in real time; The central processing module uploads the positions of the personnel and the lighting module to the three-dimensional GIS module; The three-dimensional GIS module collects the mine design drawing, and constructs a GIS three-dimensional simulation model according to the mine design drawing, personnel positions and the position of the lighting module, and inputs it into the central processing module.

3. The adaptive intelligent explosion-proof lighting system for mines according to claim 2 is characterized in that: The process of the central processing module planning the escape path includes the following steps: Step S1: The central processing module constructs an underground undirected weighted graph according to the GIS three-dimensional simulation model, extracts tunnels from the GIS three-dimensional simulation model as the edges of the underground undirected weighted graph, and extracts the intersections between tunnels, mine exits and refuge chambers as the vertices of the underground undirected weighted graph. The distance of the tunnels is extracted from the GIS three-dimensional simulation model as the weight of the edge of the underground undirected weighted graph; Step S2: the central processing module uses Pyrosim to deduce the fire situation according to the underground environmental report and the GIS three-dimensional simulation model to generate a deduction result, and constructs a dynamic underground undirected weighted graph for the underground undirected weighted graph according to the deduction result. The elements of the dynamic underground undirected weighted graph include vertices and edges, and each element has an affected attribute, whose value is affected and not affected. The value of the affected attribute changes with time according to the deduction result; Step S3: The central processing module marks the location of the personnel identification card in the underground undirected weighted graph according to the GIS three-dimensional simulation model, extracts the location of the mine exit and the refuge chamber as the end point list, and sorts them according to the distance relative to the location of the personnel identification card; Step S4: Select a location from the destination list in order as the path destination, take the location of the personnel identification card as the path starting point, and use the Yen algorithm to generate K shortest path groups; Step S5: Use the particle swarm simulation path verification algorithm to screen the K shortest path groups and generate the remaining K shortest path groups; Step S6: Execute steps S4 to S5 for each position in the destination list, and aggregate all remaining K shortest path groups into an escape path group; Step S7: Select the paths in the escape path group whose path lengths differ from the path lengths of the shortest path in the escape path group by no more than 5%, sort them from short to long by path length, summarize them into a set of paths to be evaluated, perform path hazard evaluation on them, and select the final escape path based on the evaluation results.

4. The adaptive intelligent explosion-proof lighting system for mines according to claim 3 is characterized in that: The central processing module corrects the illumination of the light-emitting unit to meet the standard, records the power of the light-emitting unit at this time as the reference power, the average brightness of the video in the lane of the lighting group where the light-emitting unit is located at this time as the reference brightness, and the smoke concentration in this lane at this time as the reference smoke concentration.

5. The adaptive intelligent explosion-proof lighting system for mines according to claim 4 is characterized in that: The process of controlling the switch of the light emitting unit comprises the following steps: Step E1: The central processing module calculates the displacement vector of the personnel identification card according to the GIS three-dimensional simulation model; Step E2: The central processing module uses the displacement vector of the personnel identification card as the angle bisector to delineate a sector area with an angle of 188° and a radius of 100 meters, and turns on the light-emitting units within the sector area.

6. The adaptive intelligent explosion-proof lighting system for mines according to claim 5 is characterized in that: The process of automatically adjusting the power of the light-emitting unit according to the brightness change and the smoke concentration change comprises the following steps: Step T1: The central processing module receives the video of the tunnel of the lighting group where the light-emitting unit in the sector area is located, calculates the average brightness of the tunnel at this time, and extracts the smoke concentration of the tunnel at this time from the underground environment report; Step T2: Adjust the power of the light-emitting unit according to the change in brightness and smoke concentration. The power adjustment formula is as follows: Where W is the adjusted light unit power, W' is the reference power, L' is the reference brightness, L is the average brightness at this time, C is the visibility compensation component, ρ' is the reference smoke concentration, and ρ is the smoke concentration at this time.

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