BIM (Building Information Modeling)-based building weak current system design assisting method

Abstract

The invention discloses a BIM-based building weak current system design auxiliary method, and relates to the technical field of weak current systems.The method comprises the steps that firstly, a building is modeled through the BIM technology, weak current system equipment is embedded into a BIM model, the BIM model is connected with a central control system through the Internet of Things technology, and fire detection data are collected in real time; the method comprises the following steps: transmitting fire detection data to a central control system, calculating, outputting fire analysis data, storing the fire analysis data, calculating in real time according to the fire analysis data, outputting a fire dangerous area Alanger (t) and an emergency lighting priority Lprioritization, calculating and evaluating the fire dangerous area Alanger (t) and the emergency lighting priority Lprioritization to ensure that the lighting is preferentially concentrated in a required area, and when a fire occurs, the emergency lighting priority Lprioritization Lprioritization Lprioritization Lprioritization Lprioritization Lprioritization Lprioritization Illumination in a fire hazard area can be intelligently turned off, people are prevented from being misguided to enter a high-risk area, and meanwhile sufficient illumination brightness is provided in a safe area. An intelligent regulation and control mechanism optimizes resource allocation during design of emergency lighting.

Description

Technical Field

[0001] The present invention relates to the technical field of weak current systems, and in particular to a BIM-based building weak current system design auxiliary method. Background Art

[0002] BIM technology is widely used in the design, construction and management of construction projects, integrating the geometric structure, equipment and system information of buildings through three-dimensional models. The weak current system is one of the important subsystems of the building, involving facilities such as fire alarm, emergency lighting, and monitoring systems, which are mainly used to ensure the safety and normal operation of the building. By combining the weak current system with BIM technology, not only can efficient building management be achieved, but also real-time monitoring and emergency response can be carried out for emergencies such as fires.

[0003] At present, emergency lighting systems in current buildings usually operate independently, lacking linkage and intelligent management with other subsystems. Traditional emergency lighting systems are mainly based on static presets, that is, when a fire occurs, the lighting system will light up the evacuation passage according to a fixed logic. However, this model does not take into account the dynamic changes of fire spread, and cannot dynamically adjust the design of emergency lighting based on factors such as real-time fire hazard areas, crowded conditions, and congestion in evacuation passages. The limitations of the existing system are reflected in its inability to flexibly respond to sudden fire scenarios, resulting in the possibility that emergency lighting may fail to guide people to evacuate safely in a timely manner. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a BIM-based building weak current system design auxiliary method, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented by the following technical scheme: a BIM-based building weak current system design auxiliary method, comprising the following steps:

[0006] S1. Use BIM technology to build a BIM model for high-rise buildings in three dimensions, integrate it with the weak current system inside the high-rise building, embed the weak current system equipment into the BIM model, and collect fire detection data in high-rise buildings in real time through the weak current system equipment;

[0007] S2. Use the Internet of Things technology to connect the weak current system equipment with the central control system of emergency lighting, transmit the collected fire detection data to the central control system, process and analyze it to obtain fire analysis data, and store the fire analysis data in the database of the central control system, and synchronize it with the BIM model through the database interface to dynamically present it in the BIM model;

[0008] S3, based on the fire analysis data in the BIM model, calculate and output the fire hazard area Adangr(t) in real time, and then calculate the emergency lighting priority Lpriority of different areas of the high-rise building based on the fire hazard area Adangr(t);

[0009] S4, presetting the priority threshold F1 and the fire risk threshold F2 to respectively conduct preliminary comparative evaluation with the emergency lighting priority Lpriority and the fire hazard area Adangr(t), analyzing the fire development and the emergency lighting priority, and generating a dynamic brightness adjustment mechanism based on the preliminary comparative evaluation results;

[0010] S5. Reconstruct the channel congestion prediction algorithm formula, calculate and output the channel congestion coefficient Ccong, and preset the congestion threshold F3 and the obtained channel congestion coefficient Ccong to perform congestion assessment, analyze the congestion situation of each channel, and based on the assessment results, execute the evacuation path optimization mechanism to output the path priority Padj;

[0011] S6. During the evacuation process, the overall evacuation efficiency Eeva is calculated and output by constructing an evacuation efficiency algorithm formula, and the emergency evacuation threshold F4 is compared and evaluated with the obtained overall evacuation efficiency Eeva for the second time, the effects of emergency lighting and evacuation paths are analyzed, and based on the results of the second comparison evaluation, early warning prompts and optimization measures are generated.

[0012] Preferably, S1 includes S11 and S12;

[0013] S11. Use laser scanning technology or drone aerial photography, combined with existing building plan data, and use BIM software to perform three-dimensional modeling of the geometric structure, evacuation passages, and emergency exits of high-rise buildings to build a BIM model. Then integrate the weak current system in the high-rise building with the BIM model. Use BIM software to embed the weak current system equipment on each floor of the high-rise building into the BIM model. At the same time, each weak current system equipment in the BIM model is consistent with the actual installation location, and the functional attributes of the weak current system equipment are configured. The functional attributes of the weak current system equipment include detection range, response time, and sensor accuracy;

[0014] S12, after the BIM model is constructed, a fire simulation is performed, and the fire detection data of each high-rise building is collected in real time through the weak current system equipment;

[0015] Weak current system equipment includes smoke detectors, temperature sensors, infrared sensors and timers;

[0016] The fire detection data include smoke concentration C, ambient temperature T, number of people on the floor N, time tala when the fire alarm signal is issued, and time tsta when people start to move.

[0017] Preferably, S2 includes S21, S22 and S23;

[0018] S21. Various sensors and devices installed in the weak current system are connected to the central control system of emergency lighting through the Internet of Things devices. The Internet of Things devices transmit fire detection data to the central control system through the LoRa wireless communication protocol.

[0019] S22, receiving fire detection data in real time in the central control system, and calculating and processing the fire detection data to obtain fire analysis data, the fire analysis data including fire smoke diffusion rate SDS, floor temperature rise rate TGR, population density PMD and evacuation response delay RED;

[0020] The fire smoke diffusion rate SDS is calculated by combining the smoke concentration C with the change in the time interval △t. The specific calculation formula is: In the formula, C(t) represents the smoke concentration at the current time, and C(t+1) represents the smoke concentration at the previous moment. The diffusion direction and speed of smoke are analyzed by combining the data of multiple smoke detectors through the smoke concentration gradient.

[0021] The floor temperature rise rate TGR is calculated by detecting the ambient temperature T of each floor through the temperature sensor. The specific calculation formula is: In the formula, T(t) represents the ambient temperature at the current time, and T(t-△t) represents the ambient temperature at the previous moment;

[0022] The population density PMD is calculated by collecting the number of people N entering the floor through infrared sensors and combining it with the floor area A. The specific calculation formula is:

[0023] The evacuation response delay RED collects the time when personnel start to move tsta and the time when the fire alarm signal is issued tala through infrared sensors and timers, and calculates and obtains them. The specific calculation formula is RED = tsta-tala;

[0024] S23. Build a relational database in the central control system, and set a write port and an output port. Write the fire analysis data into the relational database through the write port for storage, and connect with the output port through the API application program interface to map the fire analysis data to the BIM model in real time, dynamically update the fire analysis, and dynamically present it in the BIM model.

[0025] Preferably, S3 includes S31 and S32;

[0026] S31, extracting fire analysis data through the write port of the relational database, performing calculation output, calculating and outputting the fire danger area Adangr(t) in real time, and analyzing the dynamic spread of the fire over time t;

[0027] The fire hazard area Adangr(t) is calculated by the following algorithm formula;

[0028]

[0029] Where θ represents the smoke diffusion angle, which is obtained by combining and analyzing multiple groups of smoke detectors, cos(θ) represents the diffusion direction, k represents the temperature diffusion coefficient, and dt represents the time differential variable.

[0030] Preferably, S32, based on the acquired fire hazard area Adangr(t), calculate and output the emergency lighting priority Lpriority, and set priorities for emergency lighting equipment in different areas;

[0031] The emergency lighting priority Lpriority is calculated by the following algorithm formula;

[0032]

[0033] In the formula, tend represents the time it takes for evacuees to reach the safe area. It represents the relationship between the total evacuation time and the response delay of personnel. a1, a2, a3 and a4 represent the preset weight values ​​of personnel density PMD, the relationship between the total evacuation time and the response delay of personnel, the fire smoke diffusion rate SDS and the floor temperature rise rate TGR respectively, which are used to represent the weight of different factors on the priority, and a1+a2a+a3+a4=1, and the specific value is set by the user.

[0034] Preferably, S4 includes S41;

[0035] S41. Professionals shall determine the building's function and average population density. The priority threshold F1 and the fire risk threshold F2 are initially set with the fire prevention assessment, and a preliminary comparative assessment is conducted with the emergency lighting priority Lpriority and the fire hazard area Adangr(t), the fire development and emergency lighting priority are analyzed, and a dynamic brightness adjustment mechanism is generated based on the preliminary comparative assessment results. The specific assessment contents are as follows;

[0036] When the fire hazard area Adangr(t)>fire risk threshold F2, it means that the fire spread on the current floor is abnormal, and the emergency lighting on the current floor will not be turned on;

[0037] When the fire hazard area Adangr(t) ≤ the fire risk threshold F2, it means that the fire spread on the current floor is within the controllable range. At this time, the emergency lighting strategy of the current floor is maintained, and the lighting optimization is performed for the evacuation passage;

[0038] Lighting optimization compares and evaluates the emergency lighting priority Lpriority with the priority threshold F1, and dynamically adjusts the emergency lighting brightness based on the priority of the emergency lighting equipment on each floor;

[0039] When the emergency lighting priority Lpriority>priority threshold F1, a first dynamic brightness adjustment mechanism is generated, and the first dynamic brightness adjustment mechanism adjusts the emergency lighting brightness of the evacuation passage on the current floor to the highest through the central control system;

[0040] When the emergency lighting priority Lpriority≤priority threshold F1, a second dynamic brightness adjustment mechanism is generated, and the second dynamic brightness adjustment mechanism adjusts the emergency lighting brightness of the evacuation passage on the current floor to 30% through the central control system.

[0041] Preferably, S5 includes S51, S52 and S53;

[0042] S51. After dynamically adjusting the emergency lighting, construct a channel congestion prediction algorithm formula, calculate and output the channel congestion coefficient Ccong, and predict the congestion situation of each evacuation channel on the floor;

[0043] The channel congestion coefficient Ccong is calculated and output by the following algorithm formula;

[0044]

[0045] In the formula, HD represents the thermal density of personnel, which is collected by infrared sensors;

[0046] S52, the user presets a congestion threshold F3 based on the number and layout of evacuation channels, and then performs congestion assessment with the obtained channel congestion coefficient Ccong. The specific assessment content is as follows;

[0047] When the channel congestion coefficient Ccong> the congestion threshold F3, it indicates that there is a congestion risk in the predicted evacuation channel. At the same time, an alarm is issued through the central control system to indicate channel congestion. At this time, the evacuation path is optimized to guide personnel diversion;

[0048] When the channel congestion coefficient Ccong ≤ the congestion threshold F3, it indicates that the channel is predicted to be unobstructed, and the unobstructed channel is continuously illuminated.

[0049] Preferably, S53, when it is predicted that there is a risk of congestion in the evacuation channel, the evacuation path optimization mechanism is automatically triggered, and the evacuation path optimization mechanism calculates and outputs the path priority Padj based on the change in the area of ​​the fire hazard zone Adangr(t), and dynamically adjusts the evacuation path;

[0050] The path priority Padj is calculated using the following algorithm formula:

[0051]

[0052] Where min represents the lower limit, Dexit represents the distance from the evacuation passage to the emergency exit, Vsped represents the speed of personnel movement, and the movement of personnel is sensed by infrared sensors detecting the infrared thermal radiation emitted by the human body. Adanger(t-1) represents the area of ​​the fire hazard zone at the previous moment, Adanger(t)-Adanger(t-1) represents the change in the danger zone caused by the spread of fire, and Atotal represents the total area of ​​the floor.

[0053] Preferably, S6 includes S61 and S62;

[0054] S61. After the evacuation path optimization mechanism is executed, the overall evacuation efficiency Eeva is calculated and output by constructing an evacuation efficiency algorithm formula, and the effects of emergency lighting and evacuation paths are analyzed in real time;

[0055] The overall evacuation efficiency Eeva is calculated and output by the following evacuation efficiency algorithm formula;

[0056]

[0057] Preferably, S62, presetting an emergency evacuation threshold F4 based on the average evacuation time of the emergency drill, and then performing a secondary comparative evaluation with the obtained overall evacuation efficiency Eeva to evaluate the effects of the emergency lighting and the evacuation path, and the specific evaluation contents are as follows;

[0058] When the overall evacuation efficiency Eeva ≥ emergency evacuation threshold F4, it means that the evacuees reach the safe area within the standard evacuation time, the emergency lighting and evacuation path design are normal, and no adjustment is required at this time;

[0059] When the overall evacuation efficiency Eeva is less than the emergency evacuation threshold F4, it indicates that there is an abnormality in the evacuation process. At this time, an early warning is generated to prompt the administrator to adjust the design position of the emergency lighting equipment and adjust the setting of the evacuation channel.

[0060] Beneficial Effects

[0061] The present invention provides a BIM-based building weak current system design auxiliary method, which has the following beneficial effects:

[0062] (1) This method uses BIM technology to accurately model the building, embeds the weak current system equipment into the BIM model, and connects it to the central control system through the Internet of Things technology to realize real-time collection of fire detection data. After the fire detection data is transmitted to the central control system, the fire analysis data is calculated and output and stored. Then, the fire hazard area Adanger(t) and the emergency lighting priority Lpriority are calculated and evaluated in real time based on the fire analysis data to ensure that the lighting is prioritized in the required areas. In this way, when a fire occurs, the lighting in the fire hazard area can be intelligently turned off to avoid misleading people into high-risk areas, while providing sufficient lighting brightness in the safe area. This intelligent control mechanism optimizes the resource allocation of emergency lighting and improves the efficiency and safety of personnel evacuation.

[0063] (2) This method is based on real-time collected fire analysis data, and uses the BIM model to calculate the dynamic situation of fire spread, such as the fire danger zone area Adanger(t), to accurately determine the development trend of the fire. Through the preset fire risk threshold F2 and emergency lighting priority threshold F1, the system can quickly identify the severity of the fire and respond. In the case of rapid fire spread, the system automatically optimizes emergency lighting, focusing on protecting the lighting brightness of the evacuation channel to ensure smooth evacuation of personnel. By calculating the channel congestion coefficient Ccong and path priority Padj, the system can predict the congestion of the evacuation channel in real time to avoid channel blockage caused by the concentration of people. This path optimization mechanism based on data analysis significantly reduces the congestion problems that may occur during the evacuation process and improves the safety and reliability of the evacuation path;

[0064] (3) This method further expands the system's improvement of evacuation efficiency. By constructing the evacuation efficiency algorithm formula Eeva, the system can evaluate the effect of the entire evacuation process. Specifically, the system dynamically adjusts emergency lighting and evacuation paths through real-time fire data and congestion prediction analysis. When the channel congestion coefficient Ccong exceeds the congestion threshold F3, the system will immediately generate an early warning prompt to notify the manager or automatically adjust the evacuation path to guide personnel to choose a more unobstructed channel. At the same time, the system can continuously optimize the evacuation path based on data such as personnel density, evacuation response delay RED, and fire hazard areas to ensure that evacuees can reach a safe area in the shortest time. By comparing the overall evacuation efficiency with the preset evacuation threshold F4, the system can quickly detect anomalies in the evacuation process and make adjustments. This mechanism not only improves the safety of personnel evacuation, but also ensures the global optimal design configuration of the weak current system of emergency lighting and evacuation paths, minimizing the risk of casualties in fires. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1It is a schematic diagram of the steps of the BIM-based building weak current system design auxiliary method of the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Example 1

[0068] The present invention provides a BIM-based building weak current system design auxiliary method, please refer to Figure 1 , including the following steps:

[0069] S1. Use BIM technology to build a BIM model for high-rise buildings in three dimensions, integrate it with the weak current system inside the high-rise building, embed the weak current system equipment into the BIM model, and collect fire detection data in high-rise buildings in real time through the weak current system equipment;

[0070] S2. Use the Internet of Things technology to connect the weak current system equipment with the central control system of emergency lighting, transmit the collected fire detection data to the central control system, process and analyze it to obtain fire analysis data, and store the fire analysis data in the database of the central control system, and synchronize it with the BIM model through the database interface to dynamically present it in the BIM model;

[0071] S3, based on the fire analysis data in the BIM model, calculate and output the fire hazard area Adangr(t) in real time, and then calculate the emergency lighting priority Lpriority of different areas of the high-rise building based on the fire hazard area Adangr(t);

[0072] S4, presetting the priority threshold F1 and the fire risk threshold F2 to respectively conduct preliminary comparative evaluation with the emergency lighting priority Lpriority and the fire hazard area Adangr(t), analyzing the fire development and the emergency lighting priority, and generating a dynamic brightness adjustment mechanism based on the preliminary comparative evaluation results;

[0073] S5. Reconstruct the channel congestion prediction algorithm formula, calculate and output the channel congestion coefficient Ccong, and preset the congestion threshold F3 and the obtained channel congestion coefficient Ccong to perform congestion assessment, analyze the congestion situation of each channel, and based on the assessment results, execute the evacuation path optimization mechanism to output the path priority Padj;

[0074] S6. During the evacuation process, the overall evacuation efficiency Eeva is calculated and output by constructing an evacuation efficiency algorithm formula, and the emergency evacuation threshold F4 is compared and evaluated with the obtained overall evacuation efficiency Eeva for the second time, the effects of emergency lighting and evacuation paths are analyzed, and based on the results of the second comparison evaluation, early warning prompts and optimization measures are generated.

[0075] In this embodiment, the method uses BIM technology to construct a high-rise building for three-dimensional modeling to construct a BIM model, and the weak current system equipment is embedded in the BIM model to collect fire detection data in real time. Then, with the help of Internet of Things technology, the fire detection data is transmitted to the central control system for processing to generate fire analysis data. These data are synchronized with the BIM model to achieve dynamic presentation of fire information. Based on real-time fire analysis data, the area of ​​the fire hazard area Adanger(t) can be calculated and the emergency lighting priority Lpriority can be allocated to different areas in the building according to the area of ​​the area. Through the preset priority threshold F1 and the fire risk threshold F2, the lighting priority Lpriority and the area of ​​the fire hazard area Adanger(t) are compared and evaluated to generate a dynamic brightness adjustment mechanism. For example, when the area of ​​the fire hazard area exceeds F2, the emergency lighting of the area will be turned off to prevent misleading people from entering the dangerous area; and when the priority exceeds the priority threshold F1, the lighting brightness will be increased first. During the evacuation process, the channel congestion coefficient Ccong is calculated through the channel congestion prediction algorithm and compared with the congestion threshold F3. When the channel congestion coefficient Ccong exceeds the congestion threshold F3, an alarm will be issued and the evacuation path will be optimized. By calculating the path priority Padj, the use of the evacuation channel will be dynamically adjusted to ensure that personnel are diverted into an unobstructed evacuation channel. In addition, by constructing an evacuation efficiency algorithm, the overall evacuation efficiency Eeva is calculated, and a secondary comparative evaluation is performed with the emergency evacuation threshold F4 to ensure that the design of the evacuation path and emergency lighting is operating well. If the evacuation efficiency is lower than the emergency evacuation threshold F4, an early warning prompt will be generated and the lighting equipment and evacuation path will be optimized. Compared with the traditional emergency lighting system, this method achieves a more efficient emergency response through real-time data collection, fire dynamic analysis and congestion prediction. It can flexibly adjust the lighting brightness and evacuation path according to the actual spread of the fire and the congestion level of the evacuation channel, thereby improving the efficiency and accuracy of the safe evacuation of personnel.

[0076] Example 2

[0077] This embodiment is explained in Example 1, please refer to Figure 1 , specifically: S1 includes S11 and S12;

[0078] S11. Use laser scanning technology or drone aerial photography, combined with existing building plan data, and use BIM software to perform three-dimensional modeling of the geometric structure, evacuation passages, and emergency exits of high-rise buildings to build a BIM model. Then integrate the weak current system in the high-rise building with the BIM model. Use BIM software to embed the weak current system equipment on each floor of the high-rise building into the BIM model. At the same time, each weak current system equipment in the BIM model is consistent with the actual installation location, and the functional attributes of the weak current system equipment are configured. The functional attributes of the weak current system equipment include detection range, response time, and sensor accuracy;

[0079] S12, after the BIM model is constructed, a fire simulation is performed, and the fire detection data of each high-rise building is collected in real time through the weak current system equipment;

[0080] Weak current system equipment includes smoke detectors, temperature sensors, infrared sensors and timers;

[0081] The fire detection data include smoke concentration C, ambient temperature T, number of people on the floor N, time tala when the fire alarm signal is issued, and time tsta when people start to move.

[0082] In this embodiment, the method uses BIM software to perform three-dimensional modeling of the geometric structure, evacuation passages, and emergency exits of high-rise buildings by utilizing laser scanning technology or drone aerial photography, and combining existing building plan data. It can accurately construct a BIM model and integrate weak current system equipment into the model to ensure that the equipment installation location is consistent with the actual building. At the same time, the functional properties of the equipment, such as detection range, response time, and sensor accuracy, are configured, which greatly improves the accuracy and efficiency of fire detection. Through the integration of BIM models and weak current system equipment, fire detection data can be collected in real time. Compared with traditional methods, this method not only achieves high-precision three-dimensional modeling and equipment integration, but also enhances the accuracy and timeliness of fire emergency response through fire simulation and real-time data collection.

[0083] Example 3

[0084] This embodiment is explained in Example 2. Please refer to Figure 1 , specifically: S2 includes S21, S22 and S23;

[0085] S21. Various sensors and devices installed in the weak current system are connected to the central control system of emergency lighting through the Internet of Things devices. The Internet of Things devices transmit fire detection data to the central control system through the LoRa wireless communication protocol.

[0086] S22, receiving fire detection data in real time in the central control system, and calculating and processing the fire detection data to obtain fire analysis data, the fire analysis data including fire smoke diffusion rate SDS, floor temperature rise rate TGR, population density PMD and evacuation response delay RED;

[0087] The fire smoke diffusion rate SDS is calculated by combining the smoke concentration C with the change in the time interval △t. The specific calculation formula is: In the formula, C(t) represents the smoke concentration at the current time, and C(t+1) represents the smoke concentration at the previous moment. The diffusion direction and speed of smoke are analyzed by combining the data of multiple smoke detectors through the smoke concentration gradient.

[0088] The floor temperature rise rate TGR is calculated by detecting the ambient temperature T of each floor through the temperature sensor. The specific calculation formula is: In the formula, T(t) represents the ambient temperature at the current time, and T(t-△t) represents the ambient temperature at the previous moment;

[0089] The population density PMD is calculated by collecting the number of people N entering the floor through infrared sensors and combining it with the floor area A. The specific calculation formula is:

[0090] The evacuation response delay RED collects the time when personnel start to move tsta and the time when the fire alarm signal is issued tala through infrared sensors and timers, and calculates and obtains them. The specific calculation formula is RED = tsta-tala;

[0091] S23. Build a relational database in the central control system, and set a write port and an output port. Write the fire analysis data into the relational database through the write port for storage, and connect with the output port through the API application program interface to map the fire analysis data to the BIM model in real time, dynamically update the fire analysis, and dynamically present it in the BIM model.

[0092] In this embodiment, through this method, various sensors in the weak current system equipment and the central control system of emergency lighting are seamlessly connected through the Internet of Things technology, and the LoRa wireless communication protocol is used to quickly transmit the fire detection data to the central control system to ensure the real-time and stability of information transmission. After receiving the fire detection data, the central control system generates fire analysis data through calculation and processing. These data provide a comprehensive assessment of the dynamic development of the fire through real-time collection and formula calculation of sensors. By building a relational database, the fire analysis data can be stored and updated in real time with the BIM model to ensure that the dynamic changes of the fire development in the building can be intuitively presented in the BIM model. Compared with traditional methods, this integration method significantly improves the efficiency of data transmission and the accuracy of fire analysis. Not only can the specific location, scale and development trend of the fire be quickly identified, but also the emergency lighting and evacuation routes can be optimized according to real-time data, which greatly improves the response speed and accuracy of fire emergency management.

[0093] Example 4

[0094] This embodiment is explained in Example 3, please refer to Figure 1 , specifically: S3 includes S31 and S32;

[0095] S31, extracting fire analysis data through the write port of the relational database, performing calculation output, calculating and outputting the fire danger area Adangr(t) in real time, and analyzing the dynamic spread of the fire over time t;

[0096] The fire hazard area Adangr(t) is calculated by the following algorithm formula;

[0097]

[0098] Where θ represents the smoke diffusion angle, which is obtained by combining and analyzing multiple groups of smoke detectors, cos(θ) represents the diffusion direction, k represents the temperature diffusion coefficient, and dt represents the time differential variable.

[0099] S32, based on the obtained fire hazard area Adangr(t), calculate and output the emergency lighting priority Lpriority, and set priorities for emergency lighting equipment in different areas;

[0100] The emergency lighting priority Lpriority is calculated by the following algorithm formula;

[0101]

[0102] In the formula, tend represents the time it takes for evacuees to reach the safe area. It represents the relationship between the total evacuation time and the response delay of personnel. a1, a2, a3 and a4 represent the preset weight values ​​of personnel density PMD, the relationship between the total evacuation time and the response delay of personnel, the fire smoke diffusion rate SDS and the floor temperature rise rate TGR respectively, which are used to represent the weight of different factors on the priority, and a1+a2a+a3+a4=1, and the specific value is set by the user.

[0103] Example 5

[0104] This embodiment is explained in Example 4. Please refer to Figure 1 , specifically: S4 includes S41;

[0105] S41. Professionals shall determine the building's function and average population density. The priority threshold F1 and the fire risk threshold F2 are initially set with the fire prevention assessment, and a preliminary comparative assessment is conducted with the emergency lighting priority Lpriority and the fire hazard area Adangr(t), the fire development and emergency lighting priority are analyzed, and a dynamic brightness adjustment mechanism is generated based on the preliminary comparative assessment results. The specific assessment contents are as follows;

[0106] When the fire hazard area Adangr(t)>fire risk threshold F2, it means that the fire spread on the current floor is abnormal, and the emergency lighting on the current floor will not be turned on;

[0107] When the fire hazard area Adangr(t) ≤ the fire risk threshold F2, it means that the fire spread on the current floor is within the controllable range. At this time, the emergency lighting strategy of the current floor is maintained, and the lighting optimization is performed for the evacuation passage;

[0108] Lighting optimization compares and evaluates the emergency lighting priority Lpriority with the priority threshold F1, and dynamically adjusts the emergency lighting brightness based on the priority of the emergency lighting equipment on each floor;

[0109] When the emergency lighting priority Lpriority>priority threshold F1, a first dynamic brightness adjustment mechanism is generated, and the first dynamic brightness adjustment mechanism adjusts the emergency lighting brightness of the evacuation passage on the current floor to the highest through the central control system;

[0110] When the emergency lighting priority Lpriority≤priority threshold F1, a second dynamic brightness adjustment mechanism is generated, and the second dynamic brightness adjustment mechanism adjusts the emergency lighting brightness of the evacuation passage on the current floor to 30% through the central control system.

[0111] In this embodiment, the method can calculate the area of ​​the fire danger zone Adanger(t) in real time through an algorithm based on fire detection data, and analyze the spread trend of the fire in combination with the time dimension. This dynamic assessment can accurately identify the severity of the fire development. Next, based on the area of ​​the danger zone and the response time of the evacuees, the emergency lighting priority Lpriority of each area is calculated to ensure that the lighting of the evacuation passage in the danger zone is prioritized. Through the preset priority threshold F1 and fire risk threshold F2, intelligent comparison can be performed. When the fire risk exceeds the threshold, the emergency lighting in a specific area is turned off to prevent people from mistakenly entering the danger zone; when the risk is within a controllable range, the lighting brightness is maintained or dynamically adjusted to optimize the evacuation efficiency. Compared with the traditional static emergency lighting system, this method significantly improves the intelligence level and response speed of emergency management through real-time fire analysis and dynamic lighting adjustment. It can flexibly adjust the lighting brightness according to data such as the spread of the fire and the density of people, thereby ensuring the safety and effectiveness of the evacuation passage. This technical improvement greatly reduces the risks caused by insufficient lighting or incorrect lighting guidance during the evacuation process, and ultimately significantly improves the efficiency of fire emergency response and personnel safety.

[0112] Example 6

[0113] This embodiment is explained in Example 5. Please refer to Figure 1 , specifically: S5 includes S51, S52 and S53;

[0114] S51. After dynamically adjusting the emergency lighting, construct a channel congestion prediction algorithm formula, calculate and output the channel congestion coefficient Ccong, and predict the congestion situation of each evacuation channel on the floor;

[0115] The channel congestion coefficient Ccong is calculated and output by the following algorithm formula;

[0116]

[0117] In the formula, HD represents the thermal density of personnel, which is collected by infrared sensors;

[0118] S52, the user presets a congestion threshold F3 based on the number and layout of evacuation channels, and then performs congestion assessment with the obtained channel congestion coefficient Ccong. The specific assessment content is as follows;

[0119] When the channel congestion coefficient Ccong> the congestion threshold F3, it indicates that there is a congestion risk in the predicted evacuation channel. At the same time, an alarm is issued through the central control system to indicate channel congestion. At this time, the evacuation path is optimized to guide personnel diversion;

[0120] When the channel congestion coefficient Ccong ≤ the congestion threshold F3, it indicates that the channel is predicted to be unobstructed, and the unobstructed channel is continuously illuminated.

[0121] S53, when it is predicted that there is a risk of congestion in the evacuation channel, the evacuation path optimization mechanism is automatically triggered, and the evacuation path optimization mechanism calculates and outputs the path priority Padj based on the change in the area of ​​the fire hazard zone Adangr(t), and dynamically adjusts the evacuation path;

[0122] The path priority Padj is calculated using the following algorithm formula:

[0123]

[0124] Where min represents the lower limit, Dexit represents the distance from the evacuation passage to the emergency exit, Vsped represents the speed of personnel movement, and the movement of personnel is sensed by infrared sensors detecting the infrared thermal radiation emitted by the human body. Adanger(t-1) represents the area of ​​the fire hazard zone at the previous moment, Adanger(t)-Adanger(t-1) represents the change in the danger zone caused by the spread of fire, and Atotal represents the total area of ​​the floor.

[0125] In this embodiment, the method realizes real-time prediction and path optimization of the congestion of the evacuation channel. According to the dynamic adjustment of emergency lighting, a channel congestion prediction algorithm is constructed, and the infrared sensor is used to collect the thermal density HD data of personnel in real time, and the channel congestion coefficient Ccong is calculated. By evaluating the relationship between the congestion coefficient and the preset congestion threshold F3, the congestion risk can be discovered in time, and an alarm is issued to prompt personnel to divert and ensure that the evacuation channel remains unobstructed. When the congestion risk is detected, the evacuation path optimization mechanism is automatically triggered, and the evacuation path is dynamically adjusted based on the change of the area of ​​the fire hazard area Adanger(t). By calculating the path priority Padj, the optimal evacuation path can be intelligently selected to ensure that personnel reach the safe area at the fastest speed. Compared with the traditional static evacuation path planning, this method significantly improves the intelligence and response speed of evacuation management through real-time congestion prediction and path adjustment. Not only can the congestion of the evacuation channel be discovered in time, but also the evacuation path can be flexibly adjusted according to the fire dynamics and personnel distribution to optimize the flow of personnel. Compared with traditional methods, this improvement reduces delays and risks in the evacuation process, improves the efficiency and safety of personnel evacuation, and ensures more accurate and intelligent fire emergency management.

[0126] Example 7

[0127] This embodiment is explained in Example 6. Please refer to Figure 1 , specifically: S6 includes S61 and S62;

[0128] S61. After the evacuation path optimization mechanism is executed, the overall evacuation efficiency Eeva is calculated and output by constructing an evacuation efficiency algorithm formula, and the effects of emergency lighting and evacuation paths are analyzed in real time;

[0129] The overall evacuation efficiency Eeva is calculated and output by the following evacuation efficiency algorithm formula;

[0130]

[0131] S62, presetting the emergency evacuation threshold F4 based on the average evacuation time of the emergency drill, and then performing a secondary comparative evaluation with the obtained overall evacuation efficiency Eeva to evaluate the effects of the emergency lighting and evacuation path. The specific evaluation contents are as follows;

[0132] When the overall evacuation efficiency Eeva ≥ emergency evacuation threshold F4, it means that the evacuees reach the safe area within the standard evacuation time, the emergency lighting and evacuation path design are normal, and no adjustment is required at this time;

[0133] When the overall evacuation efficiency Eeva is less than the emergency evacuation threshold F4, it indicates that there is an abnormality in the evacuation process. At this time, an early warning is generated to prompt the administrator to adjust the design position of the emergency lighting equipment and adjust the setting of the evacuation channel.

[0134] In this embodiment, after the evacuation path optimization is completed through the above method steps, an evacuation efficiency evaluation mechanism is further constructed to analyze the effects of emergency lighting and evacuation paths in real time. Through the evacuation efficiency algorithm, the overall evacuation efficiency Eeva can be calculated and compared with the preset emergency evacuation threshold F4. When the overall evacuation efficiency Eeva exceeds or is equal to the emergency evacuation threshold F4, it means that the evacuees can reach the safe area within the standard evacuation time and the operation is normal; when the overall evacuation efficiency Eeva is lower than the emergency evacuation threshold F4, an early warning prompt will be generated to remind the administrator to adjust the emergency lighting equipment and evacuation channel layout to optimize the evacuation process. Different from traditional evacuation path planning and emergency lighting systems, this method greatly improves the flexibility and response speed of the system by introducing real-time evacuation efficiency evaluation and automatic adjustment mechanism.

[0135] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A BIM-based building weak current system design auxiliary method, characterized by: The following steps are involved: S1. Use BIM technology to build a BIM model for high-rise buildings in three dimensions, integrate it with the weak current system inside the high-rise building, embed the weak current system equipment into the BIM model, and collect fire detection data in high-rise buildings in real time through the weak current system equipment; S2. Use the Internet of Things technology to connect the weak current system equipment with the central control system of emergency lighting, transmit the collected fire detection data to the central control system, process and analyze it to obtain fire analysis data, and store the fire analysis data in the database of the central control system, and synchronize it with the BIM model through the database interface to dynamically present it in the BIM model; S3, based on the fire analysis data in the BIM model, calculate and output the fire hazard area Adangr(t) in real time, and then calculate the emergency lighting priority Lpriority of different areas of the high-rise building based on the fire hazard area Adangr(t); S4, presetting the priority threshold F1 and the fire risk threshold F2 to respectively conduct preliminary comparative evaluation with the emergency lighting priority Lpriority and the fire hazard area Adangr(t), analyzing the fire development and the emergency lighting priority, and generating a dynamic brightness adjustment mechanism based on the preliminary comparative evaluation results; S5. Reconstruct the channel congestion prediction algorithm formula, calculate and output the channel congestion coefficient Ccong, and preset the congestion threshold F3 and the obtained channel congestion coefficient Ccong to perform congestion assessment, analyze the congestion situation of each channel, and based on the assessment results, execute the evacuation path optimization mechanism to output the path priority Padj; S6. During the evacuation process, the overall evacuation efficiency Eeva is calculated and output by constructing an evacuation efficiency algorithm formula, and the emergency evacuation threshold F4 is compared and evaluated with the obtained overall evacuation efficiency Eeva for the second time, the effects of emergency lighting and evacuation paths are analyzed, and based on the results of the second comparison evaluation, early warning prompts and optimization measures are generated.

2. The BIM-based building weak current system design auxiliary method according to claim 1 is characterized in that: Said S1 includes S11 and S12; S11. Use BIM software to perform three-dimensional modeling on the geometric structure, evacuation passages, and emergency exits of high-rise buildings to build a BIM model, then integrate the weak current system in the high-rise building with the BIM model, and embed the weak current system equipment on each floor of the high-rise building into the BIM model through the BIM software. At the same time, each weak current system equipment in the BIM model is consistent with the actual installation location, and the functional attributes of the weak current system equipment are configured, and the functional attributes of the weak current system equipment include detection range, response time, and sensor accuracy; S12, after the BIM model is constructed, a fire simulation is performed, and the fire detection data of each high-rise building is collected in real time through the weak current system equipment; The weak current system equipment includes smoke detectors, temperature sensors, infrared sensors and timers; The fire detection data includes smoke concentration C, ambient temperature T, number of people on a floor N, time tala when a fire alarm signal is issued, and time tsta when people start to move.

3. The BIM-based building weak current system design auxiliary method according to claim 2 is characterized in that: The S2 includes S21, S22 and S23; S21. Various sensors and devices installed in the weak current system are connected to the central control system of emergency lighting through Internet of Things devices, and the Internet of Things devices transmit fire detection data to the central control system through the LoRa wireless communication protocol; S22, receiving fire detection data in real time in the central control system, and performing calculation and processing on the fire detection data to obtain fire analysis data, wherein the fire analysis data includes fire smoke diffusion rate SDS, floor temperature rise rate TGR, population density PMD and evacuation response delay RED; The fire smoke diffusion rate SDS is calculated by combining the smoke concentration C with the change in the time interval △t. The specific calculation formula is: In the formula, C(t) represents the smoke concentration at the current time, and C(t+1) represents the smoke concentration at the previous moment; The floor temperature rise rate TGR is calculated by detecting the ambient temperature T of each floor through a temperature sensor. The specific calculation formula is: In the formula, T(t) represents the ambient temperature at the current time, and T(t-△t) represents the ambient temperature at the previous moment; The population density PMD is obtained by collecting the number of people N entering the floor through infrared sensors and calculating it in combination with the floor area A. The specific calculation formula is: The evacuation response delay RED is obtained by collecting the personnel start movement time tsta and the fire alarm signal sending time tala through infrared sensors and timers, and calculating the time. The specific calculation formula is RED=tsta-tala; S23. Build a relational database in the central control system, and set a write port and an output port. Write the fire analysis data into the relational database through the write port for storage, and connect with the output port through the API application program interface to map the fire analysis data to the BIM model in real time, dynamically update the fire analysis, and dynamically present it in the BIM model.

4. The BIM-based building weak current system design auxiliary method according to claim 3 is characterized by: The S3 includes S31 and S32; S31, extracting fire analysis data through the write port of the relational database, performing calculation output, calculating and outputting the fire danger area Adangr(t) in real time, and analyzing the dynamic spread of the fire over time t; The fire hazard area Adangr(t) is calculated by the following algorithm formula: Where θ represents the smoke diffusion angle, which is obtained by combining and analyzing multiple groups of smoke detectors, cos(θ) represents the diffusion direction, k represents the temperature diffusion coefficient, and dt represents the time differential variable.

5. The BIM-based building weak current system design auxiliary method according to claim 4 is characterized in that: S32, based on the obtained fire hazard area Adangr(t), calculate and output the emergency lighting priority Lpriority, and set priorities for emergency lighting equipment in different areas; The emergency lighting priority Lpriority is calculated by the following algorithm formula: In the formula, tend represents the time it takes for evacuees to reach the safe area. It represents the relationship between the total evacuation time and the response delay of personnel. a1, a2, a3 and a4 represent the preset weight values ​​of personnel density PMD, the relationship between the total evacuation time and the response delay of personnel, the fire smoke diffusion rate SDS and the floor temperature rise rate TGR respectively, which are used to represent the weight of different factors on the priority, and a1+a2a+a3+a4=1, and the specific value is set by the user.

6. The BIM-based building weak current system design auxiliary method according to claim 4 is characterized in that: The S4 includes S41; S41. Professionals will initially set the priority threshold F1 and the fire risk threshold F2 based on the building's function, average population density PMD and fire prevention assessment, and make a preliminary comparative assessment with the emergency lighting priority Lpriority and the fire hazard area Adangr(t), analyze the fire development and emergency lighting priority, and generate a dynamic brightness adjustment mechanism based on the preliminary comparative assessment results. The specific assessment contents are as follows; When the fire hazard area Adangr(t)>fire risk threshold F2, it means that the fire spread on the current floor is abnormal, and the emergency lighting on the current floor will not be turned on; When the fire hazard area Adangr(t) ≤ the fire risk threshold F2, it means that the fire spread on the current floor is within the controllable range. At this time, the emergency lighting strategy of the current floor is maintained, and the lighting optimization is performed for the evacuation passage; The lighting optimization compares and evaluates the emergency lighting priority Lpriority with the priority threshold F1, and dynamically adjusts the emergency lighting brightness based on the priority of the floor emergency lighting equipment; When the emergency lighting priority Lpriority>priority threshold F1, a first dynamic brightness adjustment mechanism is generated, and the first dynamic brightness adjustment mechanism adjusts the emergency lighting brightness of the evacuation passage on the current floor to the highest through the central control system; When the emergency lighting priority Lpriority≤priority threshold F1, a second dynamic brightness adjustment mechanism is generated, and the second dynamic brightness adjustment mechanism adjusts the emergency lighting brightness of the evacuation passage on the current floor to 30% through the central control system.

7. The BIM-based building weak current system design auxiliary method according to claim 6 is characterized in that: The S5 includes S51, S52 and S53; S51. After dynamically adjusting the emergency lighting, construct a channel congestion prediction algorithm formula, calculate and output the channel congestion coefficient Ccong, and predict the congestion situation of each evacuation channel on the floor; The channel congestion coefficient Ccong is calculated and output by the following algorithm formula; In the formula, HD represents the thermal density of personnel, which is collected by infrared sensors; S52, the user presets a congestion threshold F3 based on the number and layout of evacuation channels, and then performs congestion assessment with the obtained channel congestion coefficient Ccong. The specific assessment content is as follows; When the channel congestion coefficient Ccong> the congestion threshold F3, it indicates that there is a risk of congestion in the predicted evacuation channel. At the same time, an alarm is issued through the central control system to indicate channel congestion. At this time, the evacuation path is optimized to guide personnel diversion; When the channel congestion coefficient Ccong ≤ the congestion threshold F3, it indicates that the channel is predicted to be unobstructed, and the unobstructed channel is continuously illuminated.

8. The BIM-based building weak current system design auxiliary method according to claim 7 is characterized in that: S53, when it is predicted that there is a risk of congestion in the evacuation channel, the evacuation path optimization mechanism is automatically triggered, and the evacuation path optimization mechanism dynamically adjusts the evacuation path by calculating and outputting the path priority Padj based on the change in the area of ​​the fire hazard zone Adangr(t); The path priority Padj is calculated and obtained by the following algorithm formula; Where min represents the lower limit, Dexit represents the distance from the evacuation passage to the emergency exit, Vsped represents the personnel movement speed, Adanger(t-1) represents the area of ​​the fire danger zone at the previous moment, Adanger(t)-Adanger(t-1) represents the change in the danger zone caused by the spread of fire, and Atotal represents the total area of ​​the floor.

9. The BIM-based building weak current system design auxiliary method according to claim 8, characterized in that: The S6 includes S61 and S62; S61. After the evacuation path optimization mechanism is executed, the overall evacuation efficiency Eeva is calculated and output by constructing an evacuation efficiency algorithm formula, and the effects of emergency lighting and evacuation paths are analyzed in real time; The overall evacuation efficiency Eeva is calculated and output by the following evacuation efficiency algorithm formula; 10. The BIM-based building weak current system design auxiliary method according to claim 9, characterized in that: S62, presetting the emergency evacuation threshold F4 based on the average evacuation time of the emergency drill, and then performing a secondary comparative evaluation with the obtained overall evacuation efficiency Eeva to evaluate the effects of the emergency lighting and evacuation path. The specific evaluation contents are as follows; When the overall evacuation efficiency Eeva ≥ emergency evacuation threshold F4, it means that the evacuees reach the safe area within the standard evacuation time, the emergency lighting and evacuation path design are normal, and no adjustment is required at this time; When the overall evacuation efficiency Eeva is less than the emergency evacuation threshold F4, it indicates that there is an abnormality in the evacuation process. At this time, an early warning is generated to prompt the administrator to adjust the design position of the emergency lighting equipment and adjust the setting of the evacuation channel.

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