Intelligent fire-fighting inspection system and method

Abstract

The invention discloses an intelligent fire-fighting inspection system and an intelligent fire-fighting inspection method, which are applied to the technical field of fire fighting, reduce the workload of manual inspection through automatic data acquisition and analysis, improve the inspection frequency and efficiency, and timely find fire hazards and equipment faults. According to the system and the method, a plurality of fire-fighting equipment is collected, the collected data is processed and analyzed by utilizing an advanced data algorithm, the accuracy of fire judgment and equipment fault diagnosis is improved, the situations of false alarm and missing alarm are reduced, the system can comprehensively monitor a plurality of areas and various fire-fighting equipment in a building in real time, the overall guarantee capability of fire-fighting safety is improved, and the system is suitable for popularization and application. And meanwhile, a mode of combining local storage and cloud storage is adopted, so that quick query and analysis of local data are facilitated, backup and multi-site access of important data are ensured, and long-term management and utilization of the data are facilitated.

Description

Technical Field

[0001] The present invention belongs to the technical field of fire protection, and in particular relates to an intelligent fire protection inspection system and method. Background Art

[0002] With the development of society and the advancement of science and technology, fire safety has received more and more attention from people. Firefighting facilities, as important urban infrastructure, play an important role in ensuring the normal and safe operation of the city. It is particularly important to ensure their normal operation.

[0003] Traditional fire inspection work mainly relies on manual inspection, which has many disadvantages. Manual inspection is prone to negligence, missed inspections, etc., and the inspection efficiency is low. At the same time, for some complex fire environments and a large number of fire equipment, it is difficult for manual inspection to achieve real-time and accurate monitoring. As the scale of modern buildings continues to expand and their functions become increasingly complex, traditional fire inspection methods have been unable to meet the needs of fire safety.

[0004] Combining the above-mentioned problems, we can find that it is difficult to avoid the above-mentioned problems when using the existing inspection methods, thus failing to achieve the desired results. Therefore, we propose an intelligent fire inspection system and method that can reduce the workload of manual inspections, improve the frequency and efficiency of inspections, and detect fire hazards and equipment failures in a timely manner through automated data collection and analysis during use. Summary of the invention

[0005] The purpose of the present invention is to propose an intelligent fire inspection system and method, which has the advantages of reducing the workload of manual inspections and improving the frequency and efficiency of inspections through automated data collection and analysis, being able to promptly discover fire hazards and equipment failures, and utilizing advanced data algorithms to process and analyze the collected data, thereby improving the accuracy of fire judgment and equipment fault diagnosis, and reducing false alarms and missed alarms. Moreover, the system can conduct comprehensive and real-time monitoring of multiple areas and various fire-fighting equipment within a building, thereby improving the overall protection capability of fire safety. At the same time, a combination of local and cloud storage is adopted, which not only facilitates the rapid query and analysis of local data, but also ensures the backup and multi-location access of important data, which is beneficial to the long-term management and utilization of data.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: an intelligent fire inspection system, comprising an intelligent fire inspection system and a power supply module, the input end of the intelligent fire inspection system is unidirectionally electrically connected to the power supply module, the intelligent fire inspection system comprises a central processing module, the input end of the central processing module is bidirectionally electrically connected to a data acquisition module, a inspection execution module and an equipment status monitoring module, the output end of the central processing module is bidirectionally electrically connected to a data processing and analysis module and a communication module, the output end of the central processing module is unidirectionally electrically connected to an alarm module, the output end of the communication module is bidirectionally electrically connected to a remote monitoring and management module, and the output end of the data processing and analysis module is unidirectionally electrically connected to a data storage module.

[0007] The above technical solution reduces the workload of manual inspections through automated data collection and analysis, improves the frequency and efficiency of inspections, can promptly detect fire hazards and equipment failures, and uses advanced data algorithms to process and analyze the collected data, thereby improving the accuracy of fire judgment and equipment fault diagnosis and reducing false alarms and missed alarms. The system can conduct comprehensive and real-time monitoring of multiple areas and various fire-fighting equipment within a building, thereby improving the overall fire safety protection capability. At the same time, the combination of local and cloud storage facilitates the rapid query and analysis of local data, ensures the backup of important data and multi-location access, and is conducive to the long-term management and utilization of data.

[0008] The present invention is further configured as follows: the data acquisition module includes a first central control unit, and the output end of the first central control unit is bidirectionally electrically connected to a temperature monitoring unit, a smoke monitoring unit, a flame monitoring unit and a pressure monitoring unit.

[0009] By adopting the above technical solution and setting up a data acquisition module, the temperature monitoring unit, smoke monitoring unit, flame monitoring unit and pressure monitoring unit can be respectively controlled by the first central control unit, so that the temperature monitoring unit, smoke monitoring unit, flame monitoring unit and pressure monitoring unit can respectively monitor the ambient temperature changes, the ambient smoke concentration, whether there is a fire, and monitor the pressure changes of the fire extinguishing system, thereby facilitating timely understanding of the fire protection situation inside the building.

[0010] The present invention is further configured as follows: the equipment status monitoring module includes a second central control unit, and the output end of the second central control unit is bidirectionally electrically connected to the electrical equipment status monitoring unit and the fire equipment status monitoring unit.

[0011] By adopting the above technical solution, by setting up an equipment status monitoring module, the electrical equipment status monitoring unit and the fire equipment status monitoring unit can be controlled separately through the second central control unit, and the electrical equipment status monitoring unit and the fire equipment status monitoring unit can respectively measure the operating current and voltage of the electrical equipment and the operating status and parameters of the fire equipment and other information, so as to monitor whether there are problems such as equipment failures.

[0012] The present invention is further configured such that: the electrical equipment status monitoring unit uses a current transformer and a voltage transformer to monitor the operating current and voltage of the electrical equipment, and the fire equipment status monitoring unit uses a pressure sensor, a water pressure sensor, a flow sensor, a temperature sensor, a vibration sensor and a blockage detection sensor to monitor the fire equipment;

[0013] The pressure sensor and flow sensor are arranged at the key positions of the sprinkler system pipe network, and the blockage detection sensor is arranged at the nozzle of the sprinkler system to measure the flow, pressure and blockage of the sprinkler system. The water pressure sensor is arranged inside the fire hydrant to measure the water pressure of the fire hydrant. The temperature sensor and vibration sensor are arranged on the motor housing and bearing of the fire pump to detect the real-time data of the fire pump.

[0014] By adopting the above technical solution, by using a sensor group to detect electrical equipment and fire-fighting equipment, the operating current of the electrical equipment can be measured, and the safety status of the electrical equipment can be judged by detecting whether the current is overloaded, short-circuited, or there is an abnormal situation such as leakage, and the operating parameters of the fire-fighting equipment can be detected based on the real-time data and status of the fire-fighting equipment.

[0015] The present invention is further configured as follows: the inspection execution module is composed of an inspection robot, a drone, etc., and uses a high-definition camera and an infrared thermal imager to collect the appearance and internal data of the equipment.

[0016] By adopting the above technical solution, the inspection execution module is composed of inspection robots, drones, etc., and high-definition cameras and infrared thermal imagers can be used to conduct all-round and multi-angle inspections of the equipment. It can clearly capture the appearance and internal structure of the equipment, and detect the heating conditions and potential fault hazards of the equipment.

[0017] The present invention is further configured as follows: the data processing and analysis module includes a data processing unit, the output end of the data processing unit is unidirectionally electrically connected to the data analysis unit, and the output end of the data analysis unit is unidirectionally electrically connected to the data feature extraction unit, the output end of the data feature extraction unit is unidirectionally electrically connected to the fault detection unit, the output end of the data processing unit is bidirectionally electrically connected to the algorithm storage unit, and the output end of the algorithm storage unit is bidirectionally electrically connected to the data analysis unit.

[0018] By adopting the above technical solution and setting up a data processing and analysis module, the data processing unit can obtain the corresponding algorithm from the algorithm storage unit to pre-process the collected original data, and the data analysis unit can obtain the corresponding algorithm from the algorithm storage unit to analyze the data and establish a model. The data feature extraction unit can then extract feature information to determine whether there is an abnormal situation, and then the fault detection unit can determine whether there is an equipment failure.

[0019] The present invention is further configured as follows: the alarm module comprises a microprocessor, and the output end of the microprocessor is electrically connected to the sound and light alarm, the SMS alarm unit and the network alarm unit in a unidirectional manner.

[0020] By adopting the above technical solution, an alarm module is set up. When abnormal situations and equipment failures are found, the sound and light alarms are used to attract the attention of people around, and SMS alarm information is sent to a pre-set mobile phone number and an alarm message is sent to a remote center through the SMS alarm unit and the network alarm unit, respectively, so that the staff can deal with the alarm information in time.

[0021] The present invention is further configured as follows: the temperature monitoring unit is installed in a distributed manner and is arranged in key locations such as a machine room and an electrical equipment room; the smoke monitoring unit is arranged above vents, stairwells, crowded areas, etc.; the flame monitoring unit is arranged in power distribution rooms, chemical storage depots and other high-risk fire areas; and the pressure monitoring unit is arranged at key nodes of the gas fire extinguishing system pipeline network.

[0022] By adopting the above technical solution, by installing the temperature monitoring unit, smoke monitoring unit, flame monitoring unit and pressure monitoring unit at the corresponding positions, data collection can be automatically performed, the workload of manual inspection is reduced, and the frequency and efficiency of inspection are improved.

[0023] The present invention is further configured to: use median filtering, mean filtering and other algorithms to filter the collected raw data, use artificial intelligence algorithms based on neural networks, decision trees and other artificial intelligence algorithms or traditional threshold judgment algorithms to judge the occurrence of fire, and use model-based diagnosis algorithms or signal processing-based diagnosis algorithms to judge whether there is a fault in the equipment.

[0024] By adopting the above technical solution, the collected data can be processed and analyzed by using various algorithms, which improves the accuracy of fire judgment and equipment fault diagnosis and reduces false alarms and missed alarms.

[0025] A method for using an intelligent fire inspection system comprises the following steps:

[0026] S1. Use the data acquisition module, inspection execution module, and equipment status monitoring module to obtain the original data of the equipment and the scene;

[0027] S2. The data processing and analysis module performs pre-processing such as cleaning, denoising and calibration on the acquired raw data, and analyzes the data and establishes a model based on the algorithm, and extracts feature information based on the model to determine whether there is equipment failure and abnormal situation;

[0028] S3. If abnormal conditions and equipment failures are found, the alarm module will attract the attention of people around, and send SMS alarm information to the pre-set mobile phone number and send alarm messages to the remote center;

[0029] S4. After the inspection task is completed, the inspection results are fed back to the user, and the data and information during the inspection process are recorded and stored.

[0030] In summary, the present invention has the following beneficial effects:

[0031] Through automated data collection and analysis, the workload of manual inspections is reduced, the frequency and efficiency of inspections are improved, fire hazards and equipment failures can be discovered in a timely manner, and advanced data algorithms are used to process and analyze the collected data, which improves the accuracy of fire judgment and equipment fault diagnosis and reduces false alarms and missed alarms. The system can conduct comprehensive and real-time monitoring of multiple areas and various fire-fighting equipment in a building, improving the overall protection capability of fire safety. At the same time, the combination of local and cloud storage facilitates the rapid query and analysis of local data, ensures the backup of important data and multi-location access, which is conducive to the long-term management and utilization of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the overall structure of the present invention;

[0033] Figure 2 It is a schematic diagram of a data acquisition module of the present invention;

[0034] Figure 3 is a schematic diagram of a device status monitoring module of the present invention;

[0035] Figure 4 is a schematic diagram of a data processing and analysis module of the present invention;

[0036] Figure 5 is a schematic diagram of an alarm module of the present invention;

[0037] Figure 6 It is a flow chart of the intelligent fire inspection method of the present invention.

[0038] Figure numerals: 1. Fire intelligent patrol system; 2. Power supply module; 3. Central processing module; 4. Data acquisition module; 41. First central control unit; 42. Temperature monitoring unit; 43. Smoke monitoring unit; 44. Flame monitoring unit; 45. Pressure monitoring unit; 5. Patrol execution module; 6. Equipment status monitoring module; 61. Second central control unit; 62. Electrical equipment status monitoring unit; 63. Fire equipment status monitoring unit; 7. Data processing and analysis module; 71. Data processing unit; 72. Data analysis unit; 73. Data feature extraction unit; 74. Fault detection unit; 75. Algorithm storage unit; 8. Communication module; 9. Alarm module; 91. Microprocessor; 92. Sound and light alarm; 93. SMS alarm unit; 94. Network alarm unit; 10. Remote monitoring and management module; 11. Data storage module. DETAILED DESCRIPTION

[0039] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0040] Embodiment 1:

[0041] refer to Figure 1-5 , an intelligent fire inspection system, comprising an intelligent fire inspection system 1 and a power supply module 2, the input end of the intelligent fire inspection system 1 is unidirectionally electrically connected to the power supply module 2, the intelligent fire inspection system 1 comprises a central processing module 3, the input end of the central processing module 3 is bidirectionally electrically connected to a data acquisition module 4, an inspection execution module 5 and an equipment status monitoring module 6, the output end of the central processing module 3 is bidirectionally electrically connected to a data processing and analysis module 7 and a communication module 8, the output end of the central processing module 3 is unidirectionally electrically connected to an alarm module 9, the output end of the communication module 8 is bidirectionally electrically connected to a remote monitoring and management module 10, the output end of the data processing and analysis module 7 is unidirectionally electrically connected to a data acquisition module 4, an inspection execution module 5 and an equipment status monitoring module 6, the output end of the central processing module 3 is bidirectionally electrically connected to a data processing and analysis module 7 and a communication module 8, According to the storage module 11, through automated data collection and analysis, the workload of manual inspections is reduced, the frequency and efficiency of inspections are improved, fire hazards and equipment failures can be discovered in a timely manner, and advanced data algorithms are used to process and analyze the collected data, thereby improving the accuracy of fire judgment and equipment fault diagnosis, reducing false alarms and missed alarms, and the system can conduct comprehensive and real-time monitoring of multiple areas and various fire-fighting equipment in a building, thereby improving the overall protection capability of fire safety. At the same time, a combination of local and cloud storage is adopted, which not only facilitates the rapid query and analysis of local data, but also ensures the backup and multi-location access of important data, which is conducive to the long-term management and utilization of data.

[0042] like Figure 2As shown, the data acquisition module 4 includes a first central control unit 41, and the output end of the first central control unit 41 is bidirectionally electrically connected to a temperature monitoring unit 42, a smoke monitoring unit 43, a flame monitoring unit 44 and a pressure monitoring unit 45. By setting the data acquisition module 4, the temperature monitoring unit 42, the smoke monitoring unit 43, the flame monitoring unit 44 and the pressure monitoring unit 45 can be controlled respectively by the first central control unit 41, so that the temperature monitoring unit 42, the smoke monitoring unit 43, the flame monitoring unit 44 and the pressure monitoring unit 45 can respectively monitor the ambient temperature change, the ambient smoke concentration, whether there is a fire, and the pressure change of the fire extinguishing system, so as to facilitate timely understanding of the fire protection situation inside the building.

[0043] like Figure 3 As shown, the equipment status monitoring module 6 includes a second central control unit 61, and the output end of the second central control unit 61 is bidirectionally electrically connected to the electrical equipment status monitoring unit 62 and the fire equipment status monitoring unit 63. By setting the equipment status monitoring module 6, the electrical equipment status monitoring unit 62 and the fire equipment status monitoring unit 63 can be controlled respectively by the second central control unit 61, and the electrical equipment status monitoring unit 62 and the fire equipment status monitoring unit 63 can respectively measure the operating current and voltage of the electrical equipment and the operating status and parameters of the fire equipment and other information, so as to monitor whether the equipment has problems such as faults.

[0044] The electrical equipment status monitoring unit 62 uses a current transformer and a voltage transformer to monitor the operating current and voltage of the electrical equipment, and the fire equipment status monitoring unit 63 uses a pressure sensor, a water pressure sensor, a flow sensor, a temperature sensor, a vibration sensor and a blockage detection sensor to monitor the fire equipment;

[0045] Pressure sensors and flow sensors are installed at key positions of the sprinkler system pipeline, and blockage detection sensors are installed at the nozzles of the sprinkler system to measure the flow, pressure and blockage of the sprinkler system. Water pressure sensors are installed inside fire hydrants to measure the water pressure of fire hydrants. Temperature sensors and vibration sensors are installed on the motor housing and bearings of fire pumps to detect real-time data of fire pumps. By using sensor groups to detect electrical equipment and fire-fighting equipment, the operating current of electrical equipment can be measured. The safety status of electrical equipment can be judged by detecting abnormal conditions such as overload, short circuit or leakage of current, and the operating parameters of fire-fighting equipment can be detected according to the real-time data and status of fire-fighting equipment.

[0046] The inspection execution module 5 is composed of inspection robots, drones, etc., and uses high-definition cameras and infrared thermal imagers to collect the appearance and internal data of the equipment. The inspection execution module 5 is composed of inspection robots, drones, etc., and can use high-definition cameras and infrared thermal imagers to conduct all-round and multi-angle inspections on the equipment, and can clearly capture the appearance and internal structure of the equipment, and detect the heating conditions and potential fault hazards of the equipment.

[0047] like Figure 4 As shown, the data processing and analysis module 7 includes a data processing unit 71, the output end of the data processing unit 71 is unidirectionally electrically connected to the data analysis unit 72, and the output end of the data analysis unit 72 is unidirectionally electrically connected to the data feature extraction unit 73, the output end of the data feature extraction unit 73 is unidirectionally electrically connected to the fault detection unit 74, the output end of the data processing unit 71 is bidirectionally electrically connected to the algorithm storage unit 75, and the output end of the algorithm storage unit 75 is bidirectionally electrically connected to the data analysis unit 72. By setting up the data processing and analysis module 7, the data processing unit 71 can obtain the corresponding algorithm from the algorithm storage unit 75 to pre-process the collected original data, and the data analysis unit 72 can obtain the corresponding algorithm from the algorithm storage unit 75 to analyze the data and establish a model, and then the data feature extraction unit 73 extracts feature information to determine whether there is an abnormal situation, so as to determine whether there is an equipment failure through the fault detection unit 74.

[0048] like Figure 5 As shown, the alarm module 9 includes a microprocessor 91, and the output end of the microprocessor 91 is unidirectionally electrically connected to an audible and visual alarm 92, a text message alarm unit 93 and a network alarm unit 94. By setting the alarm module 9, when an abnormal situation or equipment failure is found, the sound and light alarm 92 is used to attract the attention of people around, and the text message alarm unit 93 and the network alarm unit 94 are used to send text message alarm information to a pre-set mobile phone number and send an alarm message to a remote center, so that the staff can handle the alarm information in time.

[0049] The temperature monitoring unit 42 is installed in a distributed manner and is set in key locations such as the machine room and electrical equipment room. The smoke monitoring unit 43 is set above the vents, stairwells, and crowded areas. The flame monitoring unit 44 is set in the power distribution room, chemical storage area and other high-risk fire areas. The pressure monitoring unit 45 is set at key nodes of the gas fire extinguishing system pipeline network. By installing the temperature monitoring unit 42, smoke monitoring unit 43, flame monitoring unit 44 and pressure monitoring unit 45 in corresponding positions, data collection can be performed automatically, reducing the workload of manual inspections and improving the frequency and efficiency of inspections.

[0050] The collected raw data is filtered using algorithms such as median filtering and mean filtering. Artificial intelligence algorithms based on neural networks, decision trees, or traditional threshold judgment algorithms are used to determine the occurrence of fire. Model-based diagnosis algorithms or signal processing-based diagnosis algorithms are used to determine whether the equipment is faulty. By adopting various algorithms, the collected data can be processed and analyzed, which improves the accuracy of fire judgment and equipment fault diagnosis and reduces false alarms and missed alarms.

[0051] Brief description of the use process: The temperature monitoring unit 42, the smoke monitoring unit 43, the flame monitoring unit 44 and the pressure monitoring unit 45 can respectively monitor the changes in ambient temperature, the ambient smoke concentration, whether there is a fire, and the pressure changes of the fire extinguishing system. At the same time, the inspection execution module 5 and the equipment status monitoring module 6 cooperate to monitor the operating status of the electrical equipment and the fire-fighting equipment. Then, the data processing unit 71 obtains the corresponding algorithm from the algorithm storage unit 75 to pre-process the collected original data, and obtains the corresponding algorithm from the algorithm storage unit 75 through the data analysis unit 72 to analyze the data and establish a model. Then, the data feature extraction unit 73 extracts feature information to determine whether there is an abnormal situation, and then determines whether there is an equipment failure through the fault detection unit 74. If an abnormal situation and equipment failure are found, the sound and light alarm 92 will attract the attention of the surrounding personnel, and the SMS alarm unit 93 and the network alarm unit 94 will send SMS alarm information to the pre-set mobile phone number and send an alarm message to the remote center. After the inspection task is completed, the inspection result will be fed back to the user, and the data and information in the inspection process will be recorded and stored.

[0052] Embodiment 2:

[0053] like Figure 6 As shown, the present invention also provides a method for using the intelligent fire inspection system, comprising the following steps:

[0054] S1. Use the data acquisition module 4, the inspection execution module 5, and the equipment status monitoring module 6 to obtain the original data of the equipment and the scene;

[0055] S2. The acquired raw data is cleaned, denoised and calibrated by the data processing and analysis module 7, and the data is analyzed and a model is established according to the algorithm, and feature information is extracted according to the model to determine whether there is equipment failure and abnormal situation;

[0056] S3. If abnormal conditions and equipment failures are found, the alarm module 9 will attract the attention of people around, and send a text message alarm to a preset mobile phone number and send an alarm message to the remote center;

[0057] S4. After the inspection task is completed, the inspection results are fed back to the user, and the data and information during the inspection process are recorded and stored.

[0058] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. An intelligent fire inspection system, comprising an intelligent fire inspection system (1) and a power supply module (2), characterized in that: The input end of the fire intelligent patrol inspection system (1) is unidirectionally electrically connected to the power supply module (2). The fire intelligent patrol inspection system (1) comprises a central processing module (3). The input end of the central processing module (3) is bidirectionally electrically connected to a data acquisition module (4), a patrol execution module (5) and an equipment status monitoring module (6). The output end of the central processing module (3) is bidirectionally electrically connected to a data processing and analysis module (7) and a communication module (8). The output end of the central processing module (3) is unidirectionally electrically connected to an alarm module (9). The output end of the communication module (8) is bidirectionally electrically connected to a remote monitoring and management module (10). The output end of the data processing and analysis module (7) is unidirectionally electrically connected to a data storage module (11).

2. The intelligent fire inspection system according to claim 1, characterized in that: The data acquisition module (4) comprises a first central control unit (41), and the output end of the first central control unit (41) is bidirectionally electrically connected to a temperature monitoring unit (42), a smoke monitoring unit (43), a flame monitoring unit (44) and a pressure monitoring unit (45).

3. The intelligent fire inspection system according to claim 1, characterized in that: The equipment status monitoring module (6) comprises a second central control unit (61), and the output end of the second central control unit (61) is bidirectionally electrically connected to an electrical equipment status monitoring unit (62) and a fire fighting equipment status monitoring unit (63).

4. The intelligent fire inspection system according to claim 3, characterized in that: The electrical equipment status monitoring unit (62) uses a current transformer and a voltage transformer to monitor the operating current and voltage of the electrical equipment, and the fire equipment status monitoring unit (63) uses a pressure sensor, a water pressure sensor, a flow sensor, a temperature sensor, a vibration sensor and a blockage detection sensor to monitor the fire equipment; The pressure sensor and flow sensor are arranged at the key positions of the sprinkler system pipe network, and the blockage detection sensor is arranged at the nozzle of the sprinkler system to measure the flow, pressure and blockage of the sprinkler system. The water pressure sensor is arranged inside the fire hydrant to measure the water pressure of the fire hydrant. The temperature sensor and vibration sensor are arranged on the motor housing and bearing of the fire pump to detect the real-time data of the fire pump.

5. The intelligent fire inspection system according to claim 1, characterized in that: The inspection execution module (5) is composed of an inspection robot, a drone, etc., and uses a high-definition camera and an infrared thermal imager to collect data on the appearance and internal structure of the equipment.

6. The intelligent fire inspection system according to claim 1, characterized in that: The data processing and analysis module (7) comprises a data processing unit (71), the output end of the data processing unit (71) is unidirectionally electrically connected to a data analysis unit (72), and the output end of the data analysis unit (72) is unidirectionally electrically connected to a data feature extraction unit (73), the output end of the data feature extraction unit (73) is unidirectionally electrically connected to a fault detection unit (74), the output end of the data processing unit (71) is bidirectionally electrically connected to an algorithm storage unit (75), and the output end of the algorithm storage unit is bidirectionally electrically connected to the data analysis unit (72).

7. The intelligent fire inspection system according to claim 1, characterized in that: The alarm module (9) comprises a microprocessor (91), and the output end of the microprocessor (91) is unidirectionally electrically connected to an audible and visual alarm (92), a short message alarm unit (93) and a network alarm unit (94).

8. The intelligent fire inspection system according to claim 2, characterized in that: The temperature monitoring unit (42) is installed in a distributed manner and is arranged in key locations such as a machine room and an electrical equipment room. The smoke monitoring unit (43) is arranged above ventilation openings, stairwells, crowded areas, etc. The flame monitoring unit (44) is arranged in high-risk fire areas such as a power distribution room and a chemical storage depot. The pressure monitoring unit (45) is arranged at key node locations of a gas fire extinguishing system pipe network.

9. The intelligent fire inspection system according to claim 6, characterized in that: The collected raw data is filtered using algorithms such as median filtering and mean filtering. Artificial intelligence algorithms such as neural networks and decision trees or traditional threshold judgment algorithms are used to determine the occurrence of fire. Model-based diagnosis algorithms or signal processing-based diagnosis algorithms are used to determine whether the equipment is faulty.

10. A method for using an intelligent fire inspection system according to any one of claims 1 to 9, characterized in that: The following steps are involved: S1. Use the data acquisition module (4), the inspection execution module (5), and the equipment status monitoring module (6) to obtain the original data of the equipment and the scene; S2. The acquired raw data is cleaned, denoised and calibrated by the data processing and analysis module (7), and the data is analyzed and a model is established according to the algorithm. Feature information is extracted according to the model to determine whether there is equipment failure and abnormal situation; S3. If an abnormal situation or equipment failure is found, the alarm module (9) will draw the attention of people around and send a text message alarm to a preset mobile phone number and an alarm message to a remote center; S4. After the inspection task is completed, the inspection results are fed back to the user, and the data and information during the inspection process are recorded and stored.

Images