Smoke detector validity verification method and device, storage medium and processor

Abstract

The invention discloses a smoke detector validity verification method and device, a storage medium and a processor. According to the scheme, fire scene data corresponding to a to-be-verified smoke detector are acquired; based on the fire scene data, constructing a three-dimensional fire scene model by using FDS software; and dynamically simulating a fire occurrence process by using the model to obtain response data of the to-be-verified smoke detector, and verifying the validity of the to-be-verified smoke detector based on the response data. The method is different from the prior art that an experiment is carried out by building a real fire scene, and the working state of the smoke detector in the fire process is judged. Compared with the prior art that the experiment cost is high, and in the experiment process, some experiment conditions such as the ventilation condition are poor in controllability, so that the accuracy of verification data obtained through the experiment is low, the method has obvious advantages.

Description

Technical Field

[0001] The present application relates to the field of fire detection technology, and in particular to a method, device, storage medium and processor for verifying the effectiveness of a smoke detector. Background Art

[0002] Fire detection technology is an important part of modern building fire protection systems. Its core goal is to minimize the damage to life and property caused by fire through early warning mechanisms. Among the many fire detection devices, smoke detectors have become a key component in building fire protection systems due to their high sensitivity to smoke and wide applicability. Smoke detectors can sound an alarm by detecting changes in smoke concentration at the early stage of a fire, thereby buying precious time for personnel evacuation and fire extinguishing. However, the working status and performance of smoke detectors under actual fire conditions are directly related to the reliability of their alarm function, which is of great significance for fire investigation and responsibility tracing.

[0003] During the investigation process after a fire, the performance evaluation of smoke detectors is often an important task. On the one hand, whether the smoke detector issues an alarm in time at the early stage of the fire directly affects the efficiency of fire response; on the other hand, its working status also provides an important basis for judging the cause of the fire and tracing responsibility. However, the extreme environment at the fire scene (such as high temperature, smoke erosion, physical damage, etc.) usually causes serious damage to the smoke detector or even complete failure. In this case, the traditional method is to conduct an actual fire experiment. The actual fire experiment often requires the construction of a specific experimental environment and consumes a lot of materials and resources to repeat different experimental scenarios. However, this method is costly, and in the actual experimental process, some experimental conditions such as ventilation conditions are poorly controllable, which makes the verification data obtained from the experiment low in accuracy.

[0004] Therefore, when the cost of verifying the effectiveness of smoke detectors is high, how to improve the accuracy of verification is a technical problem that needs to be solved urgently. Summary of the invention

[0005] Based on the above problems, the present application provides a method, device, storage medium and processor for verifying the effectiveness of a smoke detector, the purpose of which is to improve the accuracy of verification and reduce the cost of verifying the effectiveness of a smoke detector.

[0006] The embodiments of the present application disclose the following technical solutions:

[0007] The first aspect of the present application provides a method for verifying the effectiveness of a smoke detector, the method comprising:

[0008] Obtain the fire scene data corresponding to the smoke detector to be verified;

[0009] Based on the fire scene data, a three-dimensional fire scene model is constructed using FDS software;

[0010] The process of fire occurrence is dynamically simulated using the model to obtain the response data of the smoke detector to be verified. Based on the response data, the effectiveness of the smoke detector to be verified is verified.

[0011] Optionally, the process of using the model to dynamically simulate the fire occurrence process, obtaining the response data of the smoke detector to be verified, and verifying the effectiveness of the smoke detector to be verified based on the response data includes:

[0012] The process of smoke diffusion after fire occurrence is dynamically simulated using the model, and the simulated alarm time of the smoke detector to be verified is recorded;

[0013] The actual alarm time of the smoke detector to be verified is compared and analyzed with the simulated alarm time to verify the effectiveness of the smoke detector to be verified; the actual alarm time is obtained based on the fire scene data.

[0014] Optionally, the process of comparing and analyzing the actual alarm time of the smoke detector to be verified with the simulated alarm time to verify the effectiveness of the smoke detector to be verified includes:

[0015] The actual alarm time is compared and analyzed with the simulated alarm time to determine whether the time difference between the actual alarm time and the simulated alarm time meets a preset condition, and a first judgment result is obtained;

[0016] If the first judgment result is yes, it indicates that the smoke detector to be verified effectively responds in the initial stage of the fire;

[0017] If the first judgment result is no, an analysis of the abnormal reasons for the smoke detector to be verified is performed.

[0018] Optionally, the process of using the model to dynamically simulate the process of smoke diffusion after fire occurrence and recording the simulated alarm time of the smoke detector to be verified includes:

[0019] The process of smoke diffusion after fire occurrence is dynamically simulated using the model, and the change curve of smoke concentration over time is recorded;

[0020] When the smoke concentration reaches the alarm threshold of the smoke detector to be verified, the simulated alarm time of the detector to be verified is recorded.

[0021] Optionally, after using the model to dynamically simulate the process of fire occurrence, obtaining the response data of the smoke detector to be verified, and verifying the effectiveness of the smoke detector to be verified based on the response data, it further includes:

[0022] Adjust the parameters of the three-dimensional fire scene model multiple times to obtain the three-dimensional fire scene model after multiple adjustments; the parameters include the heat release rate of the fire source, the smoke generation rate, and / or the ventilation conditions;

[0023] Use the three-dimensional fire scene model after multiple adjustments to obtain multiple response data of the smoke detector to be verified;

[0024] Based on the multiple response data, confirm the effectiveness of the smoke detector to be verified.

[0025] The second aspect of the present application provides a device for verifying the effectiveness of a smoke detector, and the device includes:

[0026] A data acquisition module for acquiring fire scene data corresponding to the smoke detector to be verified;

[0027] A model construction module for constructing a three-dimensional fire scene model using FDS software based on the fire scene data;

[0028] A verification module for dynamically simulating the process of a fire occurring using the model to obtain the response data of the smoke detector to be verified, and verifying the effectiveness of the smoke detector to be verified based on the response data.

[0029] Optionally, the verification module is specifically configured to:

[0030] Dynamically simulate the smoke diffusion process after a fire occurs using the model, and record the simulated alarm time of the smoke detector to be verified;

[0031] Compare and analyze the actual alarm time of the smoke detector to be verified with the simulated alarm time, and verify the effectiveness of the smoke detector to be verified; the actual alarm time is obtained based on the fire scene data.

[0032] Optionally, the verification module is specifically configured to:

[0033] Compare and analyze the actual alarm time with the simulated alarm time, determine whether the time difference between the actual alarm time and the simulated alarm time meets a preset condition, and obtain a first judgment result;

[0034] If the first judgment result is yes, it indicates that the smoke detector to be verified effectively responds in the initial stage of the fire;

[0035] If the first judgment result is no, analyze the abnormal reasons for the smoke detector to be verified.

[0036] The third aspect of the present application provides a computer-readable storage medium, in which a computer program is stored. When the program is run by a processor, it implements the method for verifying the effectiveness of a smoke detector provided in any implementation manner of the first aspect.

[0037] The fourth aspect of the present application provides a processor, which is used to run a computer program. When the program runs, it executes the method for verifying the effectiveness of a smoke detector provided in any implementation manner of the first aspect.

[0038] Compared with the prior art, the present application has the following beneficial effects:

[0039] The method for verifying the effectiveness of a smoke detector provided by the present application obtains the fire scene data corresponding to the smoke detector to be verified, and based on the fire scene data, uses the FDS software to construct a three-dimensional fire scene model. Through the virtual reconstruction of the fire scene by the FDS software, the whole process of the occurrence and development of the fire can be reproduced. Compared with the actual fire experiment, the demand for physical experiments is greatly reduced, and the costs of constructing experimental devices and preparing experimental materials are saved. The process of the fire occurrence is dynamically simulated using the model to obtain the response data of the smoke detector to be verified, and based on the response data, the effectiveness of the smoke detector to be verified is verified. This method can ensure the richness of experimental data and the repeatability of the experiment by precisely controlling experimental conditions such as the position of the fire source, the characteristics of the combustion material, and the environmental ventilation conditions, and the verification results obtained thereby are also more accurate. Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0041] Figure 1 It is a flowchart of a method for verifying the effectiveness of a smoke detector provided by an embodiment of the present application;

[0042] Figure 2 It is a flowchart of another method for verifying the effectiveness of a smoke detector provided by an embodiment of the present application;

[0043] Figure 3 It is a curve graph showing the change of smoke concentration over time during the combustion of a polyurethane material provided by an embodiment of the present application;

[0044] Figure 4 It is a curve graph showing the change of smoke concentration over time during the combustion of another urethane material provided by an embodiment of the present application;

[0045] Figure 5 Another graph showing the change of smoke concentration over time when the polyurethane material provided in the embodiment of the present application burns;

[0046] Figure 6 A graph showing the change of smoke concentration over time when the n - heptane material provided in the embodiment of the present application burns;

[0047] Figure 7 A schematic structural diagram of a smoke detector effectiveness verification device provided in the embodiment of the present application. Detailed implementation manners

[0048] As described above, the current method is to conduct experiments by setting up real fire scenarios to determine the working state of the smoke detector during a fire. However, this method is costly, and during the experiment, some experimental conditions such as ventilation conditions are weakly controllable, resulting in low accuracy of the verification data obtained from the experiment.

[0049] In view of the above problems, through research, the inventor has proposed a method, device, storage medium, and processor for verifying the effectiveness of a smoke detector, which includes obtaining fire scene data corresponding to the smoke detector to be verified; based on the fire scene data, constructing a three - dimensional fire scene model using FDS software; using the model to dynamically simulate the process of a fire occurring to obtain the response data of the smoke detector to be verified, and based on the response data, verifying the effectiveness of the smoke detector to be verified.

[0050] To enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0051] See Figure 1 , this figure is a flowchart of a method for verifying the effectiveness of a smoke detector provided in the embodiment of the present application. This method is applied after a fire occurs and can extract the alarm record of the smoke detector to be verified. If the alarm record cannot be extracted, it proves that the smoke detector to be verified has failed during the fire. As Figure 1 shown, this method includes the following steps:

[0052] S101. Obtain fire scene data corresponding to the smoke detector to be verified.

[0053] Conduct a comprehensive investigation of the fire scene corresponding to the smoke detector to be verified, and the fire scene data obtained includes the igniting substance, the location of the ignition source, the building structure, the ventilation conditions, the alarm records of the smoke detector to be verified, and the installation location of the smoke detector to be verified, etc. These data will provide the basis for subsequent simulations.

[0054] S102. Based on the fire scene data, use FDS software to construct a three-dimensional fire scene model.

[0055] Fire Dynamics Simulator (FDS) is a simulation software based on Computational Fluid Dynamics (CFD) developed by the National Institute of Standards and Technology (NIST) in the United States, which can accurately simulate the occurrence and development of fires and the diffusion process of smoke. FDS can reproduce complex fire scenes in a virtual environment by solving fluid dynamics equations and combining heat transfer and chemical reaction models.

[0056] In an implementable embodiment, according to the geometric structure of the fire scene, the combustion characteristics of the igniting substance (such as heat release rate, smoke generation rate, etc.) and environmental conditions, use FDS software to construct a three-dimensional fire scene model. Among them, constructing the three-dimensional fire scene model also includes setting the spatial range, boundary conditions, initial conditions, and fire source characteristics of the simulation. This model needs to accurately reflect various parameters in the actual environment. By using FDS software to virtually reconstruct the fire scene, the whole process of the occurrence and development of the fire can be reproduced, which greatly reduces the cost of verifying the effectiveness of the smoke detector compared with actual fire experiments.

[0057] S103. Use the model to dynamically simulate the process of the fire occurrence, obtain the response data of the smoke detector to be verified, and verify the effectiveness of the smoke detector to be verified based on the response data.

[0058] Among them, the response data includes the alarm threshold and alarm time of the smoke detector to be verified during the smoke diffusion process.

[0059] Run FDS software for simulation, observe the whole process of the fire from the start to the development, including smoke generation, smoke diffusion path, and temperature change, etc., record the response data of the smoke detector to be verified, and verify the effectiveness of the smoke detector to be verified by analyzing the alarm threshold and alarm time in the response data.

[0060] The method for validating the effectiveness of a smoke detector provided by an embodiment of the present application obtains the fire scene data corresponding to the smoke detector to be validated, and constructs a three-dimensional fire scene model using FDS software based on the fire scene data. Through the virtual reconstruction of the fire scene by FDS software, the whole process of fire occurrence and development can be reproduced. Compared with actual fire experiments, the demand for physical experiments is greatly reduced. This method can not only save the cost of constructing experimental devices and preparing experimental materials, but also reduce the safety risks that may occur during the experiment. The process of fire occurrence is dynamically simulated using the model to obtain the response data of the smoke detector to be validated, and the effectiveness of the smoke detector to be validated is verified based on the response data. By precisely controlling experimental conditions such as the position of the fire source, the characteristics of the combustion material, and the environmental ventilation conditions, this method can ensure the richness of experimental data and the repeatability of the experiment, and the verification results obtained are more accurate.

[0061] Based on the previous embodiment, the method for validating the effectiveness of a smoke detector is further described. After constructing a three-dimensional fire scene model using FDS software based on the fire scene data, the response data of the smoke detector to be validated is obtained by dynamically simulating the smoke diffusion process after the fire occurs, and the effectiveness of the smoke detector to be validated is verified based on the response data.

[0062] See Figure 2 , which is a flowchart of another method for validating the effectiveness of a smoke detector provided by an embodiment of the present application. As Figure 2 shown, the method includes the following steps:

[0063] S201. Obtain the fire scene data corresponding to the smoke detector to be validated.

[0064] Conduct a comprehensive investigation of the fire scene corresponding to the smoke detector to be validated. The obtained fire scene data includes the ignition substance, the position of the fire source, the building structure, the ventilation conditions, the alarm records of the smoke detector to be validated, and the installation position of the smoke detector to be validated, etc. These data will provide a basis for subsequent simulations.

[0065] S202. Construct a three-dimensional fire scene model using FDS software based on the fire scene data.

[0066] Among them, the three-dimensional fire scene model is obtained after correction; the correction process of the three-dimensional fire scene model includes:

[0067] Construct a standard combustion laboratory for combustion tests to obtain the experimental data of the smoke detector to be validated;

[0068] Based on the standard combustion laboratory, use FDS software to construct a three-dimensional fire scene model in proportion to obtain the simulation data of the smoke detector to be validated;

[0069] Based on the comparison and analysis of the experimental data and the simulation data, the model parameters of the three-dimensional fire scene model are corrected until the difference between the experimental data and the simulation data is within a preset range.

[0070] In an implementable embodiment, an experiment is conducted with a polyurethane board as the combustion material.

[0071] A standard combustion laboratory is constructed for the combustion test. The size is 10 meters long, 10 meters wide, and 4 meters high. The ceiling is a horizontal plane, and there is a 36 cm × 36 cm ventilation opening to maintain the balance inside the combustion chamber. Nine smoke detectors are installed on the ceiling of the standard combustion laboratory. Three layers of polyurethane boards are selected as the combustion material. The board size is 500 mm × 500 mm × 30 mm, which is placed in the center of the laboratory at a height position of 15 cm. An electric spark is arranged at the lower right corner to ignite the polyurethane board. Before the experiment, the specimen is allowed to work stably for 15 minutes to ensure that the ambient temperature is (23 ± 5) °C and the smoke concentration m value is less than 2% / m. An electric spark is arranged at the lower right corner, and four heaters with a surface temperature of 1000 °C are used as ignition particles and placed on the bottom cushion to ignite the polyurethane board. The time from the start of ignition to the alarm signal sent by the smoke detector for each specimen is recorded as the experimental data of the smoke detector. Usually, the smoke concentration in the fire is measured by a smoke density meter, and the experimental data is recorded. A thermocouple is used to measure the temperature changes at different heights and positions to reflect the heat transfer and distribution during the fire development process.

[0072] Based on the standard combustion laboratory, a three-dimensional fire scene model is constructed proportionally in the FDS software. Parameters such as polyurethane material and pyrolysis reaction are input. The environmental area grid size is set to 0.04 m × 0.04 m × 0.04 m, and the grid cell size at the position of 96 cm × 96 cm × 176 cm in the central combustion area is 0.02 m × 0.02 m × 0.02 m. The reaction rate of the polyurethane material is set to 1: where, ρ s，i is the density of the reaction solid in the current state, ρ s0 is the density of the reaction solid in the initial state, n s is the mass fraction exponent, which controls the influence degree of density change on the pyrolysis rate and is set to 1. A is the pre-exponential factor (frequency factor) in the Arrhenius formula equation, which represents the collision frequency leading to the reaction. E is the activation energy of the reaction, R is the universal gas constant, T s is the surface temperature of the material, T thr is the threshold temperature below which the reaction does not occur, n t is the threshold exponent, which adjusts the influence of temperature exceeding the threshold on the reaction rate and is set to 0. This item represents the Arrhenius equation, which describes the dependence of the reaction rate on temperature. The boundary conditions and initial conditions of the fire simulation are set for calculation to obtain the simulation data of the smoke detector to be verified.

[0073] Based on the comparison and analysis of the experimental data and the simulation data, the experimental results are as Figure 3 shown. The horizontal axis Time represents time in seconds, and the vertical axis S represents the smoke concentration in percentage per meter. The black solid line FDS represents the change of the smoke concentration with time obtained by numerical simulation through FDS, and the gray shaded area EXP represents the change of the smoke concentration with time measured in the actual experiment. It can be seen from the figure that the smoke generated by the combustion of polyurethane spreads rapidly within 30 seconds, and the growth trend of the smoke layer thickness is obvious. There is a large difference between the simulation data and the experimental data, and the smoke change obtained by verifying with this model does not match the actual situation, so further improvement is needed.

[0074] The model parameters of the three-dimensional fire scene model are corrected for the first time. The grid division remains unchanged. At the position of 96cm×96cm×176cm in the combustion area, the grid cell size is 0.02m×0.02m×0.02m. Four heaters with a surface temperature of 1000°C are used as ignition particles and placed on the bottom cushion for ignition. As Figure 4 shown is the curve of the change in the smoke concentration measured using the model corrected for the first time. Among them, the horizontal axis Time represents time in seconds, and the vertical axis S represents the smoke concentration in percentage per meter. The black solid line FDS represents the change of the smoke concentration with time obtained by numerical simulation through the FDS software, and the gray shaded area EXP represents the change of the smoke concentration with time measured in the actual experiment. It can be seen from the figure that the overall trend of the simulation data is relatively close to the experimental data, but the smoke generation rate is too fast in the initial stage of combustion, with a large deviation from the experimental data. These improvements indicate that the corrected model can more accurately reflect the actual combustion process, and further correction is considered.

[0075] The model parameters of the three-dimensional fire scene model are corrected for the second time. Considering that the grid setting in the polyurethane combustion area in FDS was slightly large during the first correction, overestimating the initial ignition, smoke diffusion, and formation process of polyurethane, FDS may not be able to fully capture the dynamic changes in smoke diffusion and formation in the early stage of the experiment. The grid division of the combustion area is changed to be more refined. The grid cell size at the position of 96cm×96cm×176cm in the combustion area is 0.01m×0.01m×0.01m; the reaction rate of the polyurethane material and the ignition method use four heaters with a surface temperature of 1000°C as ignition particles and place them on the bottom cushion for ignition. As Figure 5The figure shows the curve of the change in smoke concentration measured using the model after the second correction. Here, the horizontal axis "Time" represents time, with the unit of seconds, and the vertical axis "S" represents the smoke concentration, with the unit of percentage per meter. The black solid line "FDS" represents the change in smoke concentration over time obtained through numerical simulation by FDS, and the gray shaded area "EXP" represents the change in smoke concentration over time measured in the actual experiment. As can be seen from the figure, the simulation data not only shows a better fit with the experimental data in terms of the overall trend, but also demonstrates higher prediction accuracy in terms of fluctuations, peak values, and plateau periods. These improvements indicate that the further corrected model can more accurately reflect the actual combustion process, providing reliable data support for further fire research and fire investigation.

[0076] In this embodiment, there is no limit on the number of corrections until the difference between the experimental data and the simulation data is within a preset range.

[0077] FDS numerical simulation simulates the behavior of a fire through computer modeling, greatly reducing the need for physical experiments. This method not only saves the cost of constructing experimental devices and preparing experimental materials, but also reduces the safety risks that may occur during the experiment. In addition, FDS numerical simulation also allows researchers to easily adjust parameters to test the fire behavior under different conditions, which is very valuable for understanding fire dynamics and developing fire prevention strategies.

[0078] In an implementable embodiment, an experiment is conducted using n - heptane as the combustion material.

[0079] A standard combustion laboratory is constructed for the combustion test. The size is 10 meters in length, 10 meters in width, and 4 meters in height. The ceiling is a horizontal plane, and a ventilation opening of 36 cm × 36 cm is provided to maintain the balance inside the combustion chamber. n - heptane is selected as the combustion material, and the oil pan has dimensions of 330 mm × 330 mm × 50 mm and is placed in the center of the laboratory. Before the test, the specimen is allowed to operate stably for 15 minutes to ensure that the ambient temperature is (23 ± 5)°C and the smoke concentration m value is less than 0.02 dB / m. The n - heptane is ignited, and the time from ignition to the alarm signal sent by the smoke detector for each specimen is recorded as the experimental data of the smoke detector. Usually, the smoke density meter is used to measure the smoke concentration in the fire, the experimental data is recorded, and the thermocouple is used to measure the temperature changes at different heights and positions to reflect the heat transfer and distribution during the fire development process.

[0080] Based on the above standard combustion laboratory, a three-dimensional fire scenario model is constructed proportionally in the FDS software. Input parameters such as polyurethane materials and pyrolysis reactions, and input parameters such as n-heptane materials and pyrolysis reactions. The grid size of the environmental area is set to 0.04m×0.04m×0.04m, and the grid cell size at the position of 96cm×96cm×176cm in the central combustion area is 0.01m×0.01m×0.01m. Set the boundary conditions and initial conditions of the fire simulation for calculation to obtain the simulation data of the smoke detector to be verified.

[0081] Based on the comparison and analysis of the experimental data and the simulation data, the experimental results are as Figure 6 shown. Among them, the horizontal axis Time represents time, with the unit of seconds, and the vertical axis S represents the smoke concentration, with the unit of percentage per meter. The black solid line FDS represents the change of the smoke concentration over time obtained by numerical simulation through FDS, and the gray shaded area EXP represents the change of the smoke concentration over time measured in the actual experiment. The changes in the smoke concentration of the experimental data and the simulation data are similar. The initial smoke concentration rapidly rises from 0% / m to about 5% / m. This increase in this section is attributed to the rapid ignition and combustion of n-heptane, generating a large amount of smoke. The smoke concentration continues to increase steadily within the time range of 20 - 60s, showing a fluctuating upward trend; at 60 seconds, the smoke concentration reaches about 10% / m; within the time range of 60 - 85 seconds, the smoke concentration tends to be stable, showing a continuous upward trend but with smaller fluctuations, approaching 15% / m; around 85s, it reaches the alarm threshold, verifying the accuracy of the FDS model.

[0082] Both the experimental data and the simulation data show that at the beginning of the combustion process, the smoke concentration increases rapidly. This indicates that the FDS model accurately captures the initial combustion dynamics and the smoke generation rate. The fluctuations observed in the experimental data may be caused by changes in the combustion intensity and transient effects in the laboratory environment. The FDS simulation captures the overall trend, but it may not be able to capture all the transient phenomena observed in the experiment. The consistent increase in the smoke concentration during the steady-state stage in the experimental data and the FDS simulation indicates that the FDS model effectively simulates the continuous combustion and continuous smoke generation, indicating that the data obtained by the FDS model for simulating the smoke diffusion process during the n-heptane combustion process is reliable.

[0083] S203. Use the model to dynamically simulate the smoke diffusion process after a fire occurs, and record the simulated alarm time of the smoke detector to be verified.

[0084] In an achievable implementation, use the model to dynamically simulate the smoke diffusion process after a fire occurs, and record the change curve of the smoke concentration over time;

[0085] When the smoke concentration reaches the alarm threshold of the smoke detector to be verified, record the simulated alarm time of the detector to be verified.

[0086] Each smoke detector has its specific alarm threshold. When the detected smoke concentration reaches a certain value, the smoke detector will trigger an alarm. The alarm threshold is usually provided by the smoke detector manufacturer or set according to relevant safety standards.

[0087] The simulated alarm time of the smoke detector to be verified obtained through this step is crucial for subsequent verification of the effectiveness of the smoke detector to be verified.

[0088] S204. Compare and analyze the actual alarm time of the smoke detector to be verified with the simulated alarm time to verify the effectiveness of the smoke detector to be verified.

[0089] Among them, the actual alarm time is obtained based on the fire scene data.

[0090] In an implementable embodiment, compare and analyze the actual alarm time with the simulated alarm time, and determine whether the time difference between the actual alarm time and the simulated alarm time meets a preset condition to obtain a first judgment result;

[0091] If the first judgment result is yes, it indicates that the smoke detector to be verified effectively responds in the initial stage of the fire;

[0092] If the first judgment result is no, analyze the abnormal reasons for the smoke detector to be verified.

[0093] Among them, the preset condition is a preset time range. When the time difference between the actual alarm time and the simulated alarm time is within the preset range (for example, 5%), it indicates that the smoke detector to be verified effectively responds in the initial stage of the fire and its working state is normal; if the time difference exceeds the preset range, analyze the abnormal reasons for the smoke detector to be verified, and the abnormal reasons include detector failure, alarm threshold deviation, or unreasonable installation position, etc.

[0094] Using FDS can accurately simulate the smoke diffusion process after a fire occurs, and combined with the alarm threshold of the detector, dynamically analyze the response behavior of the detector. This method not only avoids the difficulty of performance verification caused by detector damage, but also provides a scientific basis for fire cause analysis and liability tracing.

[0095] In an alternative embodiment, after using the model to dynamically simulate the process of a fire occurring, obtaining the response data of the smoke detector to be verified, and verifying the effectiveness of the smoke detector to be verified based on the response data, it further includes:

[0096] Adjust the parameters of the three-dimensional fire scene model multiple times to obtain the three-dimensional fire scene model after multiple adjustments; the parameters include the heat release rate of the fire source, the smoke generation rate, and / or the ventilation conditions;

[0097] Use the three-dimensional fire scene model after multiple adjustments to obtain multiple response data of the smoke detector to be verified;

[0098] Based on the multiple response data, confirm the effectiveness of the smoke detector to be verified.

[0099] This method simulates different fire scenes by adjusting the model parameters multiple times, and verifies the effectiveness of the smoke detector based on the response data obtained under these different scenarios, aiming to cover as many actual fire scenarios as possible to ensure that the smoke detector can work effectively under various conditions.

[0100] Another method for verifying the effectiveness of a smoke detector provided by an embodiment of the present application is to obtain the fire scene data corresponding to the smoke detector to be verified, and based on the fire scene data, use FDS software to construct a three-dimensional fire scene model. Through the virtual reconstruction of the fire scene by FDS software, the whole process of the occurrence and development of the fire can be reproduced. Compared with actual fire experiments, the cost of verifying the effectiveness of the smoke detector is greatly reduced. Use the model to dynamically simulate the smoke diffusion process after the fire occurs, record the simulated alarm time of the smoke detector to be verified, and compare and analyze the actual alarm time of the smoke detector to be verified with the simulated alarm time to verify the effectiveness of the smoke detector to be verified. This method accurately simulates the smoke diffusion process after the fire occurs by precisely controlling experimental conditions, such as the fire source position, the characteristics of the combustion material, and the environmental ventilation conditions, etc., can ensure the richness of experimental data and the repeatability of the experiment, and the verification results obtained are more accurate and reliable. It not only avoids the difficulty of performance verification caused by detector damage, but also provides a scientific basis for fire cause analysis and liability tracing.

[0101] Based on the method for verifying the effectiveness of a smoke detector introduced in the foregoing embodiments, correspondingly, the present application also provides a device for verifying the effectiveness of a smoke detector. Figure 7 It is a schematic structural diagram of the device.

[0102] As Figure 7 shown, the device for verifying the effectiveness of a smoke detector includes:

[0103] A data acquisition module 701, configured to acquire fire scene data corresponding to the smoke detector to be verified;

[0104] A model construction module 702, configured to construct a three-dimensional fire scene model using FDS software based on the fire scene data;

[0105] A verification module 703, configured to dynamically simulate the process of a fire occurring by using the model, obtain response data of the smoke detector to be verified, and verify the effectiveness of the smoke detector to be verified based on the response data.

[0106] Optionally, the verification module is specifically configured to:

[0107] Dynamically simulate the smoke diffusion process after a fire occurs by using the model, and record the simulated alarm time of the smoke detector to be verified;

[0108] Compare and analyze the actual alarm time of the smoke detector to be verified with the simulated alarm time, and verify the effectiveness of the smoke detector to be verified; the actual alarm time is obtained based on the fire scene data.

[0109] Optionally, the verification module is specifically configured to:

[0110] Compare and analyze the actual alarm time with the simulated alarm time, determine whether the time difference between the actual alarm time and the simulated alarm time meets a preset condition, and obtain a first judgment result;

[0111] If the first judgment result is yes, it indicates that the smoke detector to be verified effectively responds in the initial stage of the fire;

[0112] If the first judgment result is no, analyze the reasons for the abnormality of the smoke detector to be verified.

[0113] Optionally, the verification module is specifically configured to:

[0114] Dynamically simulate the smoke diffusion process after a fire occurs by using the model, and record the change curve of the smoke concentration over time;

[0115] When the smoke concentration reaches the alarm threshold of the smoke detector to be verified, record the simulated alarm time of the detector to be verified.

[0116] Optionally, the device further includes a confirmation module;

[0117] The confirmation module is configured to adjust the parameters of the three-dimensional fire scene model multiple times to obtain the three-dimensional fire scene model after multiple adjustments; the parameters include the heat release rate of the fire source, the smoke generation rate, and / or the ventilation condition; use the three-dimensional fire scene model after multiple adjustments to obtain multiple response data of the smoke detector to be verified; and confirm the effectiveness of the smoke detector to be verified based on the multiple response data.

[0118] In addition, an embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the program is run by a processor, the method for verifying the effectiveness of a smoke detector introduced in any manner of the method embodiment is implemented.

[0119] In addition, an embodiment of the present application further provides a processor, which is used to run a computer program. When the program runs, the method for verifying the effectiveness of a smoke detector introduced in any implementation manner of the foregoing method embodiment is executed.

[0120] It should be noted that the embodiments in this specification are all described in a progressive manner. The same or similar parts between the embodiments can be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components prompted as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0121] As described above, only a specific implementation manner of the present application is provided, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for verifying the effectiveness of a smoke detector, characterized in that: include: Obtain the fire scene data corresponding to the smoke detector to be verified; Based on the fire scene data, a three-dimensional fire scene model is constructed using FDS software; The model is used to dynamically simulate the process of fire occurrence to obtain response data of the smoke detector to be verified, and the effectiveness of the smoke detector to be verified is verified based on the response data.

2. The method according to claim 1, characterized in that: The method of dynamically simulating the process of fire occurrence by using the model to obtain response data of the smoke detector to be verified, and verifying the validity of the smoke detector to be verified based on the response data, includes: The model is used to dynamically simulate the smoke diffusion process of a fire, and the simulated alarm time of the smoke detector to be verified is recorded; The actual alarm time of the smoke detector to be verified is compared and analyzed with the simulated alarm time to verify the effectiveness of the smoke detector to be verified; the actual alarm time is obtained based on the fire scene data.

3. The method according to claim 2, characterized in that The comparing and analyzing the actual alarm time of the smoke detector to be verified with the simulated alarm time to verify the validity of the smoke detector to be verified includes: Comparing and analyzing the actual alarm time with the simulated alarm time, determining whether the time difference between the actual alarm time and the simulated alarm time meets a preset condition, and obtaining a first determination result; If the first judgment result is yes, it means that the smoke detector to be verified effectively responds at the initial stage of the fire; If the first judgment result is no, then an abnormality cause analysis is performed on the smoke detector to be verified.

4. The method according to claim 2, characterized in that: The method of dynamically simulating the smoke diffusion process of a fire by using the model and recording the simulated alarm time of the smoke detector to be verified includes: The model is used to dynamically simulate the smoke diffusion process of a fire, and the smoke concentration variation curve over time is recorded; When the smoke concentration reaches the alarm threshold of the smoke detector to be verified, the simulated alarm time of the detector to be verified is recorded.

5. The method according to claim 1, characterized in that The method of dynamically simulating the fire occurrence process by using the model to obtain the response data of the smoke detector to be verified, and verifying the validity of the smoke detector to be verified based on the response data, further includes: The parameters of the three-dimensional fire scene model are adjusted multiple times to obtain the three-dimensional fire scene model after multiple adjustments; the parameters include a fire source heat release rate, a smoke generation rate and / or ventilation conditions; Using the three-dimensional fire scene model after the multiple adjustments, obtaining multiple response data of the smoke detector to be verified; Based on the multiple response data, the validity of the smoke detector to be verified is confirmed.

6. A smoke detector effectiveness verification device, characterized in that: include: A data acquisition module, used to acquire fire scene data corresponding to the smoke detector to be verified; A model building module, used to build a three-dimensional fire scene model using FDS software based on the fire scene data; The verification module is used to dynamically simulate the process of fire occurrence by using the model to obtain the response data of the smoke detector to be verified, and verify the validity of the smoke detector to be verified based on the response data.

7. The device according to claim 6, characterized in that The verification module is specifically used for: The model is used to dynamically simulate the smoke diffusion process of a fire, and the simulated alarm time of the smoke detector to be verified is recorded; The actual alarm time of the smoke detector to be verified is compared and analyzed with the simulated alarm time to verify the effectiveness of the smoke detector to be verified; the actual alarm time is obtained based on the fire scene data.

8. The device according to claim 7, characterized in that The verification module is specifically used for: Comparing and analyzing the actual alarm time with the simulated alarm time, determining whether the time difference between the actual alarm time and the simulated alarm time meets a preset condition, and obtaining a first determination result; If the first judgment result is yes, it means that the smoke detector to be verified effectively responds at the initial stage of the fire; If the first judgment result is no, then an abnormality cause analysis is performed on the smoke detector to be verified.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the program is executed by a processor, the method for verifying the effectiveness of a smoke detector according to any one of claims 1 to 5 is implemented.

10. A processor, characterized in that: Used to run a computer program, which, when running, executes the smoke detector validity verification method according to any one of claims 1 to 5.

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