Fire detection method and device for belt trestle, electronic equipment and storage medium

Abstract

The application discloses a belt trestle fire detection method and device, an electronic device and a storage medium, which can capture various environmental parameters and on-site image data of each area of a coal belt trestle in real time, dynamically adapt a smoke concentration monitoring threshold value in combination with a dust concentration to weaken the interference of dust on a detection signal, acquire a fire probability through image feature analysis, complementarily verify multiple source data such as smoke concentration and environmental temperature to realize accurate fire determination, and cooperate with fixed partition and movable tracking fire extinguishing devices to make up for the coverage limitation of a fire source point in a narrow space, so that the technical effects of improving fire identification accuracy, accelerating fire extinguishing response efficiency, improving fire extinguishing operation accuracy, effectively containing fire spread and reducing equipment damage are achieved.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a fire detection method, apparatus, electronic device, and storage medium for a belt conveyor bridge. Background Technology

[0002] Coal conveyor belt trestle bridges, as a key channel in coal transportation systems, are widely used in the fuel supply stages of industries such as power and metallurgy. Related technologies utilize the coordinated operation of smoke detection, temperature monitoring, and fixed-zone sprinkler systems to construct a basic fire protection system.

[0003] Existing fire prevention methods for coal conveyor belt trestle bridges rely on single smoke or temperature thresholds for detection. However, high concentrations of dust can interfere with sensor signals, potentially leading to false or missed fire detections. Additionally, fixed-zone sprinklers may not be able to cover fire sources within narrow spaces, thus affecting the speed and accuracy of fire suppression response and increasing the risk of fire spread and equipment damage. Summary of the Invention

[0004] This disclosure provides a fire detection method, apparatus, electronic device, and storage medium for belt conveyor bridges.

[0005] According to a first aspect of this disclosure, a fire detection method for a belt conveyor bridge is provided, comprising:

[0006] Real-time acquisition of various environmental parameters and on-site image data of each monitoring area of ​​the coal conveyor belt trestle; Based on the collected dust concentration data, the monitoring threshold for smoke concentration in the corresponding area is dynamically corrected. Feature analysis is performed on the collected on-site image data to obtain the fire probability, and a comprehensive fire judgment is made based on the fusion results of multi-source data such as smoke concentration, fire probability and ambient temperature to identify the area to be extinguished. For the identified fire-prone areas, coordinate the use of fixed zone fire extinguishing devices and mobile tracking fire extinguishing devices to perform fire extinguishing operations simultaneously.

[0007] Optionally, the multiple environmental parameters include at least one of dust concentration, smoke concentration, and ambient temperature.

[0008] Optionally, the dynamic correction of the smoke concentration monitoring threshold for the corresponding area based on the collected dust concentration data includes: Based on the difference between the baseline dust concentration and the real-time monitoring value in each monitoring area, the smoke concentration monitoring threshold for the corresponding area is adjusted.

[0009] Optionally, the step of performing feature analysis on the collected on-site image data to obtain the fire probability, and making a comprehensive fire determination based on the multi-source data fusion results of smoke concentration, fire probability, and ambient temperature, to identify the area to be extinguished includes: If, in the same monitoring area, the smoke concentration exceeds the corrected threshold, the fire probability is higher than the preset value, and the ambient temperature shows an abnormal upward trend, and the aforementioned three judgment results are consistent with each other, the area is judged as a fire-fighting area.

[0010] Optionally, the step of coordinating fixed zone fire extinguishing devices and mobile tracking fire extinguishing devices to simultaneously perform fire extinguishing operations for the identified fire-to-be-extinguished area includes: Based on the location information of the area to be extinguished, the fixed zone fire extinguishing devices in the corresponding area are activated to carry out area spraying fire extinguishing, while the mobile tracking fire extinguishing devices are controlled to aim at the fire target for directional and precise spraying fire extinguishing.

[0011] According to a second aspect of this disclosure, a fire detection device for a belt conveyor bridge is provided, comprising: The multi-source acquisition unit is used to collect various environmental parameters and on-site image data in real time from each monitoring area of ​​the coal conveyor belt trestle. The threshold correction unit is used to dynamically correct the smoke concentration monitoring threshold of the corresponding area based on the collected dust concentration data. The fusion judgment unit is used to perform feature analysis on the collected on-site image data to obtain the fire probability, and to make a comprehensive fire judgment based on the fusion results of multi-source data such as smoke concentration, fire probability and ambient temperature, and identify the area to be extinguished. The linkage fire suppression control unit is used to coordinate fixed zone fire suppression devices and mobile tracking fire suppression devices to perform fire suppression operations synchronously in the identified fire suppression area.

[0012] Optionally, the environmental parameters collected by the multi-source acquisition unit include at least one of dust concentration, smoke concentration, and ambient temperature.

[0013] Optionally, the threshold correction unit is further configured to: Based on the difference between the baseline dust concentration and the real-time monitoring value in each monitoring area, the smoke concentration monitoring threshold for the corresponding area is adjusted.

[0014] Optionally, the fusion determination unit is further configured to: If, in the same monitoring area, the smoke concentration exceeds the corrected threshold, the fire probability is higher than the preset value, and the ambient temperature shows an abnormal upward trend, and the aforementioned three judgment results are consistent with each other, the area is judged as a fire-fighting area.

[0015] Optionally, the linkage fire suppression control unit is also used for: Based on the location information of the area to be extinguished, the fixed zone fire extinguishing devices in the corresponding area are activated to carry out area spraying fire extinguishing, while the mobile tracking fire extinguishing devices are controlled to aim at the fire target for directional and precise spraying fire extinguishing.

[0016] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0017] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0018] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0019] The fire detection method, device, electronic equipment, and storage medium for conveyor belt trestle provided in this application can capture various environmental parameters and on-site image data of different areas of the coal conveyor belt trestle in real time. By combining the dynamic adaptation of dust concentration and smoke concentration monitoring threshold to reduce the interference of dust on the detection signal, and obtaining the fire probability through image feature analysis, the fire can be accurately determined by forming a multi-source data complementarity with smoke concentration and ambient temperature. Furthermore, by coordinating the operation of fixed zones and mobile tracking fire extinguishing devices to compensate for the limited coverage of fire sources in narrow spaces, this application can solve the technical problems in the prior art where single threshold detection is affected by high concentration dust interference, resulting in false fire detection and missed detection, and the incomplete coverage of fixed zone spraying affecting the fire extinguishing response speed and accuracy. This achieves the technical effects of improving the accuracy of fire identification, accelerating the fire extinguishing response efficiency, improving the accuracy of fire extinguishing operations, effectively curbing the spread of fire, and reducing equipment damage.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0021] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 A schematic flowchart illustrating a fire detection method for a belt conveyor bridge provided in this embodiment of the present disclosure; Figure 2 This is a schematic diagram of the structure of a fire detection device for a belt conveyor bridge provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0022] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0023] The following description, with reference to the accompanying drawings, outlines a fire detection method, apparatus, electronic device, and storage medium for belt conveyor bridges according to embodiments of the present disclosure.

[0024] Figure 1 This is a schematic flowchart illustrating a fire detection method for a belt conveyor bridge provided in an embodiment of this disclosure.

[0025] like Figure 1 As shown, the method includes the following steps: Step 101: Real-time acquisition of various environmental parameters and on-site image data for each monitoring area of ​​the coal conveyor belt trestle; The various environmental parameters encompass, but are not limited to, all physical or chemical quantities that can reflect early signs of a fire. Their specific types can be flexibly configured according to the actual working conditions and protection requirements of the trestle. Real-time on-site image data is simultaneously acquired for each monitoring area to obtain visual information reflecting the on-site condition of the area. The aforementioned environmental parameter data and image data together form the multi-source information foundation for subsequent comprehensive fire assessment. The acquired data are transmitted to the control host in real time via wired or wireless communication, providing raw data support for subsequent data preprocessing and fusion assessment.

[0026] In some embodiments, the various environmental parameters may include dust concentration, smoke concentration and ambient temperature. The data acquisition device may integrate a dust monitoring module, a smoke monitoring module, a temperature monitoring module and an image acquisition module, which are deployed in each monitoring area of ​​the trestle to realize parallel real-time acquisition and converged transmission of the above four types of data.

[0027] Step 102: Based on the collected dust concentration data, dynamically correct the smoke concentration monitoring threshold of the corresponding area; Dust concentration and smoke concentration have a physical relationship that interferes with each other. In high-dust environments, the measured values ​​of smoke sensors will be deflected. If a fixed smoke concentration threshold is used for discrimination, false alarms or missed alarms are easily generated due to the influence of dust. Therefore, this solution establishes a correction model between dust concentration and smoke monitoring threshold based on the correspondence between the benchmark reference value and the real-time monitoring value of dust concentration in different areas. The smoke concentration monitoring threshold for each area is dynamically adjusted in a targeted manner, so that the corrected threshold can truly reflect the reasonable judgment boundary of smoke concentration in the current dust environment, thereby effectively eliminating the interference of dust factors on the accuracy of smoke detection.

[0028] In some embodiments, the control host can calculate the deviation between the preset dust concentration benchmark value of each area and the real-time collected dust concentration data, and adjust the smoke concentration threshold of the corresponding area upward or downward according to the preset correction rules to ensure that an accurate and reliable smoke judgment benchmark can be obtained under different dust concentration conditions.

[0029] Step 103: Perform feature analysis on the collected on-site image data to obtain the fire probability, and make a comprehensive fire judgment based on the multi-source data fusion results of smoke concentration, fire probability and ambient temperature to identify the area to be extinguished. The control host performs intelligent feature analysis on the on-site image data collected from each monitoring area. It extracts fire-related visual features using image recognition algorithms, calculates and outputs the fire probability value for each monitoring area. The fire probability reflects the likelihood of a fire occurring in the current area based on visual information and serves as one of the important criteria for comprehensive fire assessment. The control host then initiates a multi-source data fusion assessment process, comprehensively analyzing the dynamically corrected smoke concentration data obtained in the preceding steps, the fire probability data derived from image analysis, and the ambient temperature monitoring data.

[0030] When a monitoring area simultaneously meets the following conditions—smoke concentration exceeding a corrected threshold, fire probability obtained from image analysis higher than a preset judgment threshold, and ambient temperature showing an abnormally rising trend consistent with the judgment results of the aforementioned two data points—the control host determines that area to be designated as a fire-fighting zone. This multi-source data fusion judgment method requires that various types of data corroborate and synergistically represent fire characteristics, rather than relying on data from a single dimension for judgment, thereby ensuring the accuracy and reliability of fire identification.

[0031] In some embodiments, the control host can independently determine the smoke concentration, fire probability and temperature data in sequence, and then compare the consistency of the three determination results. Only when all three determination results point to the occurrence of a fire will the area be marked as a fire-fighting area and the subsequent fire-fighting response be triggered.

[0032] Step 104: For the identified fire-fighting area, coordinate the fixed zone fire extinguishing devices and the mobile tracking fire extinguishing devices to perform fire extinguishing operations simultaneously.

[0033] Fixed zone fire suppression systems, based on the location information of the area to be extinguished, implement regional coverage fire suppression in corresponding preset zones to achieve rapid and wide-area fire suppression coverage of the target area. Mobile tracking fire suppression systems, upon receiving instructions, autonomously adjust their spray direction and angle according to the spatial location of the area to be extinguished and the real-time situation of the fire target, implementing directional and precise concentrated fire suppression. The synergistic effect of these two types of fire suppression systems ensures both comprehensive coverage and precise strikes. Fixed zone fire suppression systems are responsible for rapidly suppressing the spread of the fire, while mobile tracking fire suppression systems target the core area of ​​the fire with precision. The two systems work in tandem, complementing each other to form a complete coordinated fire suppression response. Fire suppression operations continue until the fire is extinguished, after which the system automatically returns to normal monitoring status.

[0034] In some embodiments, the fixed zone fire extinguishing device may be a sprinkler assembly pre-installed in each area of ​​the trestle, and the mobile tracking fire extinguishing device may be an automatic tracking water cannon. The control host sends instructions to both at the same time. The sprinkler assembly sprays water to cover the zone at a fixed point, while the automatic tracking water cannon tracks the fire target in real time and sprays it accurately until the fire is extinguished and the system returns to the monitoring state.

[0035] In some embodiments, the plurality of environmental parameters includes at least one of dust concentration, smoke concentration, and ambient temperature.

[0036] Dust concentration is collected through a dust monitoring module, which uses a dust concentration sensor based on optical scattering or charge induction principles. This sensor is installed at locations where dust tends to accumulate in each monitoring area of ​​the trestle, detecting the mass concentration or number concentration of suspended particulate matter in the air in real time and converting the detection signal into dust concentration data. Smoke concentration is collected through a smoke monitoring module, which can use a photoelectric smoke sensor or an ionization smoke sensor. This sensor is installed at the top of each monitoring area of ​​the trestle or in areas where smoke tends to accumulate. By detecting the scattering of light signals by smoke particles or the attenuation of ion current, it outputs monitoring data reflecting the current smoke concentration in the area. Ambient temperature is collected through a temperature monitoring module, which can use thermocouples, resistance temperature detectors (RTDs), or infrared temperature sensors. These sensors are installed along the conveyor belt and at locations where equipment heats up in concentrated areas of the trestle, continuously sensing changes in ambient temperature and outputting temperature values.

[0037] The above three types of monitoring modules can be deployed individually, or two or three can be combined and deployed simultaneously. The specific configuration method is determined according to the actual fire risk characteristics and protection level requirements of each area of ​​the trestle. The data collected by each module is uniformly collected in real time to the fire extinguishing control host through the data transmission channel for subsequent data preprocessing and fusion judgment.

[0038] In some embodiments, dynamically correcting the smoke concentration monitoring threshold for the corresponding area based on the collected dust concentration data includes: Based on the difference between the baseline dust concentration and the real-time monitoring value in each monitoring area, the smoke concentration monitoring threshold for the corresponding area is adjusted.

[0039] Dust concentration benchmark values ​​are established for each monitoring area of ​​the trestle. These benchmark values ​​reflect the inherent dust concentration levels of each area under normal operating conditions and without fire. They can be preset and determined by statistical analysis of dust concentration monitoring data of each area over a certain period of time. Due to differences in coal type, ventilation conditions, and belt conveyor node locations, the dust concentration benchmark values ​​of different areas are different.

[0040] During system operation, the fire extinguishing control host continuously receives real-time dust concentration monitoring values ​​uploaded by dust monitoring modules in each area, compares these real-time monitoring values ​​with the corresponding dust concentration benchmark values ​​for that area, and calculates the difference between the two.

[0041] When the real-time monitoring value is higher than the benchmark value, it indicates that the current dust concentration in the area is high, and the interference of dust particles on the smoke sensor is increased. At this time, the fire suppression control host adjusts the smoke concentration monitoring threshold of the area upward according to the preset correspondence, so that the smoke sensor can be judged as a valid smoke signal only at a higher output level, thereby avoiding false alarms caused by dust particles scattering light signals or attenuating ion current in high dust environments. Conversely, when the real-time monitoring value is lower than the benchmark value, it indicates that the current dust concentration in the area is low, and the degree of dust interference is reduced. In this case, the smoke concentration monitoring threshold is appropriately lowered to ensure that the sensitivity of smoke detection does not decrease due to an excessively high threshold, avoiding the risk of missed alarms. The mapping relationship between this difference and the threshold adjustment can be realized through a pre-calibrated correction model or correction coefficient table to ensure that a smoke judgment threshold matching the current actual working conditions can be obtained under different dust concentration deviation conditions.

[0042] In some embodiments, the step of performing feature analysis on the collected on-site image data to obtain the fire probability, and making a comprehensive fire determination based on the multi-source data fusion results of smoke concentration, fire probability, and ambient temperature to identify the area to be extinguished includes: If, in the same monitoring area, the smoke concentration exceeds the corrected threshold, the fire probability is higher than the preset value, and the ambient temperature shows an abnormal upward trend, and the aforementioned three judgment results are consistent with each other, the area is judged as a fire-fighting area.

[0043] In some embodiments, after completing the feature analysis of the on-site image data of each monitoring area and outputting the corresponding fire probability value, the fire suppression control host initiates a multi-source data fusion-based comprehensive fire determination process. This determination process applies four determination conditions to the same monitoring area simultaneously, and requires that all four conditions be met at the same time for the area to be determined as a fire-fighting area.

[0044] The first criterion is whether the real-time smoke concentration monitoring value of the area exceeds the smoke concentration threshold after dynamic correction by the aforementioned steps. This criterion aims to confirm whether there is a real smoke signal in the area after eliminating dust interference factors. The second criterion is whether the fire probability value obtained from image feature analysis of the area is higher than a pre-set probability threshold. This criterion uses visual information to confirm whether there are fire-related image features such as flames or high-temperature heat radiation in the area. The third criterion is whether the ambient temperature of the area shows an abnormally rising trend, that is, whether the temperature change rate exceeds the normal fluctuation range. This criterion confirms the presence of fire-related features in the area from a thermodynamic perspective. The fourth criterion is whether the above three criterion results are consistent with each other, that is, whether the three results of excessive smoke concentration, excessive fire probability, and abnormal temperature rise simultaneously point to the occurrence of fire in the same area. This consistency check ensures that the fire signals represented by the three different physical quantities can corroborate each other rather than be isolated. Only when the area simultaneously meets the conditions of smoke concentration exceeding the corrected threshold, fire probability higher than the preset value, and ambient temperature showing an abnormal upward trend, and the three criterion results are consistent with each other in the spatiotemporal dimension, will the fire extinguishing control host officially determine the area as a fire-fighting area and trigger the subsequent collaborative fire extinguishing execution procedure.

[0045] In some embodiments, coordinating fixed zone fire extinguishing devices and mobile tracking fire extinguishing devices to simultaneously perform fire extinguishing operations for the identified fire-to-be-extinguished area includes: Based on the location information of the area to be extinguished, the fixed zone fire extinguishing devices in the corresponding area are activated to carry out area spraying fire extinguishing, while the mobile tracking fire extinguishing devices are controlled to aim at the fire target for directional and precise spraying fire extinguishing.

[0046] After identifying a monitored area as a fire-fighting zone, the fire control host immediately extracts the location code information of that area and generates two fire-fighting commands, which are sent to the fixed zone fire extinguishing device and the mobile tracking fire extinguishing device respectively. The fixed zone fire extinguishing device is the automatic fire water extinguishing system. This system divides the area into several independent sprinkler zones along the longitudinal direction of the trestle bridge. Each zone is equipped with a sprinkler assembly controlled by a solenoid valve. Each sprinkler assembly is connected to the fire water source through a water supply network. After determining the sprinkler zone to which the fire-fighting zone belongs based on the location code of the area to be extinguished, the fire control host sends an opening signal to the solenoid valve of the corresponding zone. Fire water is then transported to the sprinkler assembly of that zone through the water supply network. The nozzles spray the area with a certain pressure and diffusion angle to achieve overall humidification and cooling of the fire area and suppression of the fire.

[0047] At the same time, the fire extinguishing control host sends a directional control command containing the spatial coordinates of the area to be extinguished to the mobile tracking fire extinguishing device, namely the automatic tracking water cannon. After receiving the command, the automatic tracking water cannon uses its built-in horizontal rotation mechanism and pitch adjustment mechanism to drive the cannon barrel to quickly turn to the target position. After locking the precise location of the fire target through infrared detection or image tracking, it uses high-pressure concentrated water flow to carry out directional and precise spraying on the core area of ​​the fire, forming a high-intensity concentrated strike on the fire source.

[0048] The two fire extinguishing systems operate synchronously at the same time. The fixed zone sprinkler provides large-area fire extinguishing coverage to prevent the fire from spreading to adjacent areas, while the automatic tracking water cannon precisely targets the core of the fire to quickly suppress its intensity. The two systems complement each other and work synergistically. The fire extinguishing operation continues until the data from all monitoring sensors return to normal ranges and the fire is confirmed to be extinguished. At this point, the fire extinguishing control host sends a stop command to both fire extinguishing systems, and the system returns to normal monitoring status.

[0049] Corresponding to the fire detection method for belt conveyor bridges described above, this invention also proposes a fire detection device for belt conveyor bridges. Since the device embodiments of this invention correspond to the method embodiments described above, details not disclosed in the device embodiments can be referred to in the method embodiments described above, and will not be repeated here.

[0050] Figure 2 This is a schematic diagram of the structure of a fire detection device for a belt conveyor bridge provided in an embodiment of this disclosure, as shown below. Figure 2 As shown, it includes: The multi-source acquisition unit 21 is used to collect various environmental parameters and on-site image data in real time from each monitoring area of ​​the coal conveyor belt trestle. The threshold correction unit 22 is used to dynamically correct the smoke concentration monitoring threshold of the corresponding area based on the collected dust concentration data. The fusion judgment unit 23 is used to perform feature analysis on the collected on-site image data to obtain the fire probability, and to make a comprehensive fire judgment based on the fusion results of multi-source data such as smoke concentration, fire probability and ambient temperature, and identify the area to be extinguished. The linkage fire suppression control unit 24 is used to coordinate the fixed zone fire suppression devices and the mobile tracking fire suppression devices to perform fire suppression operations synchronously for the identified fire suppression area.

[0051] Furthermore, in one possible implementation of this disclosure embodiment, the multiple environmental parameters collected by the multi-source acquisition unit 21 include at least one of dust concentration, smoke concentration, and ambient temperature.

[0052] Furthermore, in one possible implementation of this disclosure embodiment, the threshold correction unit 22 is further configured to: Based on the difference between the baseline dust concentration and the real-time monitoring value in each monitoring area, the smoke concentration monitoring threshold for the corresponding area is adjusted.

[0053] Furthermore, in one possible implementation of this disclosure embodiment, the fusion determination unit 23 is further configured to: If, in the same monitoring area, the smoke concentration exceeds the corrected threshold, the fire probability is higher than the preset value, and the ambient temperature shows an abnormal upward trend, and the aforementioned three judgment results are consistent with each other, the area is judged as a fire-fighting area.

[0054] Furthermore, in one possible implementation of this disclosure embodiment, the linkage fire extinguishing control unit 24 is further configured to: Based on the location information of the area to be extinguished, the fixed zone fire extinguishing devices in the corresponding area are activated to carry out area spraying fire extinguishing, while the mobile tracking fire extinguishing devices are controlled to aim at the fire target for directional and precise spraying fire extinguishing.

[0055] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0056] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0057] Figure 3A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0058] like Figure 3 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0059] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0060] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the fire detection method for a belt conveyor. For example, in some embodiments, the fire detection method for a belt conveyor can be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program can be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above can be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned fire detection method for the belt conveyor bridge by any other suitable means (e.g., by means of firmware).

[0061] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0062] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0063] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0064] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0065] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0066] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0067] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0068] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0069] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A fire detection method for a belt conveyor bridge, characterized in that, include: Real-time acquisition of various environmental parameters and on-site image data of each monitoring area of ​​the coal conveyor belt trestle; Based on the collected dust concentration data, the monitoring threshold for smoke concentration in the corresponding area is dynamically corrected. Feature analysis is performed on the collected on-site image data to obtain the fire probability, and a comprehensive fire judgment is made based on the fusion results of multi-source data such as smoke concentration, fire probability and ambient temperature to identify the area to be extinguished. For the identified fire-prone areas, coordinate the use of fixed zone fire extinguishing devices and mobile tracking fire extinguishing devices to perform fire extinguishing operations simultaneously.

2. The method according to claim 1, characterized in that, The various environmental parameters include at least one of dust concentration, smoke concentration, and ambient temperature.

3. The method according to claim 1, characterized in that, The dynamic correction of the smoke concentration monitoring threshold for the corresponding area based on the collected dust concentration data includes: Based on the difference between the baseline dust concentration and the real-time monitoring value in each monitoring area, the smoke concentration monitoring threshold for the corresponding area is adjusted.

4. The method according to claim 1, characterized in that, The process of performing feature analysis on the collected on-site image data to obtain the fire probability, and making a comprehensive fire determination based on the multi-source data fusion results of smoke concentration, fire probability, and ambient temperature, to identify the area to be extinguished includes: If, in the same monitoring area, the smoke concentration exceeds the corrected threshold, the fire probability is higher than the preset value, and the ambient temperature shows an abnormal upward trend, and the aforementioned three judgment results are consistent with each other, the area is judged as a fire-fighting area.

5. The method according to claim 1, characterized in that, The coordinated firefighting operations, involving both fixed zone fire suppression systems and mobile tracking fire suppression systems, for the identified fire-prone areas include: Based on the location information of the area to be extinguished, the fixed zone fire extinguishing devices in the corresponding area are activated to carry out area spraying fire extinguishing, while the mobile tracking fire extinguishing devices are controlled to aim at the fire target for directional and precise spraying fire extinguishing.

6. A fire detection device for a belt conveyor bridge, characterized in that, include: The multi-source acquisition unit is used to collect various environmental parameters and on-site image data in real time from each monitoring area of ​​the coal conveyor belt trestle. The threshold correction unit is used to dynamically correct the smoke concentration monitoring threshold of the corresponding area based on the collected dust concentration data. The fusion judgment unit is used to perform feature analysis on the collected on-site image data to obtain the fire probability, and to make a comprehensive fire judgment based on the fusion results of multi-source data such as smoke concentration, fire probability and ambient temperature, and identify the area to be extinguished. The linkage fire suppression control unit is used to coordinate fixed zone fire suppression devices and mobile tracking fire suppression devices to perform fire suppression operations synchronously in the identified fire suppression area.

7. The apparatus according to claim 6, characterized in that, The multi-source acquisition unit collects various environmental parameters, including at least one of dust concentration, smoke concentration, and ambient temperature.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-5.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-5.

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