An electrical fire prevention method and system for ancient buildings

Abstract

The present invention provides an electrical fire prevention method and system for ancient buildings, which relates to the field of electrical fire prevention technology. According to the type and distribution of building materials, multiple first fire hazard coefficients are obtained, according to the type and distribution of electrical equipment, multiple second fire hazard coefficients are obtained, multiple fire hazard coefficients are calculated, multiple fire facility configuration parameters are obtained according to a fire facility configuration analysis model, and fire facilities are arranged. According to a fire prevention monitoring model, multiple monitoring frequencies and multiple alarm thresholds are obtained, so as to monitor and prevent fires in multiple building areas. The present invention solves the technical problem in the prior art that the final electrical fire prevention effect is poor due to insufficient control of the monitoring frequency and alarm threshold of environmental monitoring and insulator detection in ancient buildings, realizes the rational configuration of the monitoring frequency and alarm threshold of environmental monitoring and insulator detection, and achieves the technical effect of improving the electrical fire prevention effect.

Description

Technical Field

[0001] The invention relates to the technical field of electrical fire prevention, and in particular to an electrical fire prevention method and system for ancient buildings. Background Art

[0002] Ancient architecture generally refers to buildings that have been built for a long time and exist on the ground in various historical periods. They generally have high historical value and cultural relic value. Ancient architecture represents the ancient social, political, economic, cultural and artistic aspects. It is a valuable asset of the nation and also a precious historical and cultural heritage. Most of my country's ancient buildings are brick and wood structures, and fire is a major hazard. Therefore, it is urgent to strengthen the fire safety of ancient buildings. Applying modern science and technology to the fire protection work of ancient buildings to ensure fire safety has become one of the important tasks of the fire department. However, the electrical fire protection methods commonly used in ancient buildings still have certain drawbacks, and there is still room for improvement in the electrical fire protection of ancient buildings.

[0003] In the prior art, due to the insufficient design accuracy of the monitoring frequency and alarm threshold of the internal environment monitoring and insulator detection of ancient buildings, it is impossible to adaptively design electrical fire protection schemes according to the characteristics of ancient buildings, resulting in poor final electrical fire protection effect. Summary of the invention

[0004] The embodiments of the present application provide an electrical fire prevention method and system for ancient buildings, which are used to solve the technical problem in the prior art that the final electrical fire prevention effect is poor due to insufficient control of the monitoring frequency and alarm threshold of the internal environment monitoring and insulator detection of ancient buildings.

[0005] In view of the above problems, an embodiment of the present application provides an electrical fire prevention method and system for ancient buildings.

[0006] In a first aspect, an embodiment of the present application provides an electrical fire prevention method for ancient buildings, the method comprising: dividing the target ancient building to obtain multiple building areas; performing a fire hazard analysis based on the types and distribution of building materials in the multiple building areas to obtain multiple first fire hazard coefficients; performing a fire hazard analysis based on the types and distribution of electrical equipment in the multiple building areas to obtain multiple second fire hazard coefficients, and calculating and obtaining multiple fire hazard coefficients in combination with the multiple first fire hazard coefficients; inputting the multiple fire hazard coefficients into a fire protection facility configuration analysis model to obtain multiple fire protection facility configuration parameters, and arranging fire protection facilities for the multiple building areas; inputting the multiple fire hazard coefficients into a fire protection monitoring model to obtain multiple monitoring frequencies and multiple alarm thresholds, wherein the fire protection monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit; based on the multiple monitoring frequencies and the multiple alarm thresholds, monitoring the electrical, environmental conditions and insulation facilities in the multiple building areas for fire prevention.

[0007] In a second aspect, an embodiment of the present application provides an electrical fire protection system for ancient buildings, the system comprising: a building area acquisition module, the building area acquisition module is used to divide the target ancient building to obtain multiple building areas; a first fire hazard coefficient acquisition module, the first fire hazard coefficient acquisition module is used to perform a fire hazard analysis based on the types and distribution of building materials in the multiple building areas, and obtain multiple first fire hazard coefficients; a second fire hazard coefficient acquisition module, the second fire hazard coefficient acquisition module is used to perform a fire hazard analysis based on the types and distribution of electrical equipment in the multiple building areas, and obtain multiple second fire hazard coefficients, and calculate and obtain multiple fire hazard coefficients in combination with the multiple first fire hazard coefficients. number; a fire protection facility configuration parameter acquisition module, the fire protection facility configuration parameter acquisition module is used to input the multiple fire hazard factors into a fire protection facility configuration analysis model, obtain multiple fire protection facility configuration parameters, and arrange fire protection facilities for the multiple building areas; an alarm threshold acquisition module, the alarm threshold acquisition module is used to input the multiple fire hazard factors into a fire protection monitoring model, obtain multiple monitoring frequencies and multiple alarm thresholds, wherein the fire protection monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit; a monitoring fire protection module, the monitoring fire protection module is used to monitor the electrical, environmental conditions and insulation facilities in the multiple building areas for fire protection based on the multiple monitoring frequencies and the multiple alarm thresholds.

[0008] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0009] The electrical fire prevention method for ancient buildings provided in the embodiment of the present application relates to the field of electrical fire prevention technology. According to the types and distribution of building materials in multiple building areas, multiple first fire hazard coefficients are obtained. According to the types and distribution of electrical equipment in multiple building areas, multiple second fire hazard coefficients are obtained. Multiple fire hazard coefficients are calculated and obtained. According to the fire protection facility configuration analysis model, multiple fire protection facility configuration parameters are obtained. Fire protection facilities are arranged in multiple building areas. According to the fire protection monitoring model, multiple monitoring frequencies and multiple alarm thresholds are obtained. The fire protection monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit. Based on multiple monitoring frequencies and multiple alarm thresholds, the electrical, environmental conditions and insulation facilities in multiple building areas are monitored for fire prevention. The technical problem that the final electrical fire prevention effect is poor due to insufficient control of the monitoring frequency and alarm threshold of environmental monitoring and insulator detection in the prior art is solved. By analyzing the proportion and flammability of materials in ancient buildings, the rational configuration of the monitoring frequency and alarm threshold of environmental monitoring and insulator detection is realized, thereby achieving the technical effect of improving the electrical fire prevention effect of ancient buildings.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic flow chart of an electrical fire prevention method for ancient buildings is provided for the embodiment of the present application;

[0012] Figure 2 A schematic flow chart of obtaining multiple first fire hazard coefficients in an electrical fire prevention method for ancient buildings is provided for an embodiment of the present application;

[0013] Figure 3 A schematic flow chart of obtaining multiple fire risk factors in an electrical fire prevention method for ancient buildings is provided for an embodiment of the present application;

[0014] Figure 4 A schematic diagram of the structure of an electrical fire protection system for ancient buildings is provided for an embodiment of the present application.

[0015] Explanation of the reference numerals: building area acquisition module 10 , first fire hazard factor acquisition module 20 , second fire hazard factor acquisition module 30 , fire protection facility configuration parameter acquisition module 40 , alarm threshold acquisition module 50 , fire prevention monitoring module 60 . DETAILED DESCRIPTION

[0016] The embodiments of the present application provide an electrical fire prevention method for ancient buildings, aiming to solve the technical problem in the prior art that the final electrical fire prevention effect is poor due to insufficient control over the monitoring frequency and alarm threshold of the internal environment monitoring and insulator detection of ancient buildings.

[0017] Embodiment 1

[0018] like Figure 1 As shown, an embodiment of the present application provides an electrical fire prevention method for ancient buildings, the method comprising:

[0019] Step S100: Divide the target ancient building to obtain multiple building areas;

[0020] Specifically, an electrical fire protection method for ancient buildings provided in an embodiment of the present application is applied to the electrical fire protection system of ancient buildings.

[0021] First of all, the group combination of ancient buildings has its common regularity. A single building is formed with a room as a unit, which is generally a regular rectangle. Then, according to the different functional needs of various types of buildings, a courtyard is formed with a single building, and then a group of buildings of various types and sizes is formed with the courtyard as a unit. The target ancient buildings are divided according to the building function. The building function is the most important factor among the three elements of the building. The building is built to meet specific purposes and usage requirements, which is called function in architecture. Due to the different uses of ancient buildings, different buildings have been produced, such as residential buildings, palace buildings, altar buildings, garden buildings, mausoleum buildings, urban buildings, facility buildings and other buildings. The building function often has a direct impact on the structural materials, plane space composition, and spatial scale of the building. Buildings with the same building function are divided into a building area to obtain multiple building areas. In addition, corridors, pavilions, windows, etc. in ancient buildings can also be divided to obtain multiple building areas.

[0022] Step S200: performing a fire hazard analysis according to the types and distribution of building materials in the multiple building areas to obtain multiple first fire hazard coefficients;

[0023] Specifically, ancient building materials can be divided into structural materials, decorative materials and certain special materials. Structural materials include wood, bamboo, stone, bricks and tiles, ceramics, etc. Decorative materials include green tiles, green bricks, square bricks, glazed tiles, etc.

[0024] Analyze the building materials in multiple building areas, obtain the types of building materials used in the building areas, such as wood, stone, bricks and tiles, obtain the ignition point of each building material, and analyze its flammability according to the ignition point. The lower the ignition point, the higher the flammability. For example, the ignition point of wood is very low. Usually, wood will start to burn at 100-200°C. Therefore, once the wooden structure catches fire, it is very easy to burn and lose its supporting capacity in a short time, which greatly shortens the time for people to escape from the burning building and leaves hidden dangers to safety. Therefore, the flammability of wood is relatively high. Relatively speaking, the flammability of stone is very low. For example, the flammability parameter of wood is set to 90% and the flammability parameter of stone is set to 10%. The distribution of each building material in the building area is counted, and the material proportion information is obtained according to the distribution quantity of various materials. For example, 80% wood and 20% stone are used in a certain stone and wood structure building.

[0025] The flammability parameters are weighted and calculated according to the material proportion information. Specifically, the product of the proportion of any building material in the building area and its flammability parameter is calculated as the fire hazard coefficient of the material in the building area. The fire hazard coefficients of all materials are calculated and summed to obtain the first fire hazard coefficient of the building area. The higher the first fire hazard coefficient, the higher the flammability of the building materials in the building area, or the higher the proportion of flammable building materials in the building area, the higher the fire hazard of the building area.

[0026] Step S300: performing a fire hazard analysis according to the types and distribution of electrical equipment in the multiple building areas to obtain multiple second fire hazard coefficients, and combining the multiple first fire hazard coefficients to calculate and obtain multiple fire hazard coefficients;

[0027] Specifically, electrical equipment is a general term for generators, transformers, power lines, circuit breakers and other equipment in the power system. The types of electrical equipment installed in multiple building areas are analyzed to obtain the types of electrical equipment used in the building areas, and the possibility of fire in each electrical equipment is analyzed and evaluated. Electrical fires are generally caused by electrical energy as a fire source, which can easily develop into serious fire accidents. Among them, the source of most electrical fires is wires and cables. Fires caused by wires and cables are roughly divided into four types: short circuit, excessive resistance, leakage and overload. Therefore, the possibility of fire in wires and cables is relatively high. For example, the possibility of fire in wires and cables is set to 60%, which is used as the possibility parameter of fire in wires and cables, and the possibility parameters of fire in multiple electrical equipment in multiple building areas are obtained.

[0028] The distribution of each type of electrical equipment in the building area is counted, and the electrical equipment ratio information is obtained according to the distribution quantity of various electrical equipment, so as to obtain a set of electrical equipment ratio information in multiple building areas.

[0029] The probability parameter of electrical equipment fire is weightedly calculated based on the proportion of electrical equipment. Specifically, the product of the proportion of any electrical equipment in the building area and its probability parameter is calculated as the second fire hazard coefficient of the electrical equipment in the building area. The second fire hazard coefficients of all electrical equipment are calculated and summed to obtain the second fire hazard coefficient of the building area. The higher the second fire hazard coefficient, the higher the possibility of electrical fire in the building area, or the higher the proportion of electrical equipment that may cause fire in the building area, the higher the fire hazard of the building area.

[0030] Step S400: inputting the multiple fire risk factors into a fire protection facility configuration analysis model, obtaining multiple fire protection facility configuration parameters, and arranging fire protection facilities for the multiple building areas;

[0031] Specifically, the firefighting facility configuration data of other ancient buildings are obtained, including the fire hazard coefficients and firefighting facility configuration parameters of other buildings. The firefighting facility configuration parameters include the types and quantities of firefighting facilities, so as to obtain multiple sample fire hazard coefficients and multiple sample firefighting facility configuration parameters. The fire hazard coefficient is used as the characteristic data for division, and a multi-level decision node is constructed with multiple sample fire hazard coefficients. The characteristic data is divided into multiple levels according to the multi-level decision nodes to obtain multiple fire hazard coefficient intervals as multiple division results, and multiple firefighting facility configuration parameters corresponding to the multiple fire hazard coefficient intervals are obtained as multiple decision results. According to the corresponding relationship between the division results and the firefighting facility configuration parameters, a firefighting facility configuration analysis model is constructed.

[0032] The fire hazard coefficient is input into the fire protection facility configuration analysis model, the corresponding fire hazard coefficient interval is matched, and the fire protection facility configuration parameters corresponding to the fire hazard coefficient interval are obtained, and these are used as the fire protection facility configuration parameters of the fire hazard coefficient. For example, the fire hazard coefficient of a building area is 83%, which is input into the fire protection facility configuration analysis model, and a multi-level division decision is made. The matched fire hazard coefficient interval is 80%-85%, and the fire protection facility configuration parameters corresponding to the building area with a fire hazard coefficient interval of 80%-85% are obtained, such as configuring 2 fire extinguishers for every 50 square meters, which are used as the fire protection facility configuration data set for the building area with a fire hazard coefficient of 83%.

[0033] Step S500: inputting the multiple fire risk factors into a fire prevention monitoring model to obtain multiple monitoring frequencies and multiple alarm thresholds, wherein the fire prevention monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit;

[0034] Specifically, the fire protection facility configuration data of other ancient buildings, including the fire hazard coefficients of other buildings, are obtained as multiple sample fire hazard coefficients. Based on the monitoring of electrical, environmental, and insulating facilities in the ancient building area under multiple sample fire hazard coefficients, multiple sample electrical monitoring frequencies, multiple sample environmental monitoring frequencies, multiple sample insulating facility monitoring frequencies, multiple sample electrical alarm thresholds, multiple sample environmental alarm thresholds, and multiple sample insulating facility alarm thresholds are set to obtain.

[0035] Based on the feedforward neural network, the electrical monitoring frequency and electrical alarm threshold corresponding to the sample fire hazard factor are used as sample data for supervised training to construct an electrical monitoring and analysis unit. In the same way, the environmental monitoring and analysis unit and the insulation facility monitoring and analysis unit are constructed for the sample environment and sample insulation facilities. The feedforward neural network is a type of artificial neural network, which adopts a unidirectional multi-layer structure, in which the 0th layer is called the input layer, the last layer is called the output layer, and the other intermediate layers are called hidden layers. The hidden layer can be one layer or multiple layers. Each hidden layer contains several neurons. Each neuron can receive the signal of the previous layer of neurons and generate output to the next layer. There is no feedback in the entire network, and the signal propagates unidirectionally from the input layer to the output layer.

[0036] Input any fire hazard factor into the fire prevention monitoring model, obtain the electrical monitoring frequency and electrical alarm threshold through the electrical monitoring and analysis unit, obtain the environmental monitoring frequency and environmental alarm threshold through the environmental monitoring and analysis unit, and obtain the insulation facility monitoring frequency and insulation facility alarm threshold through the insulation facility monitoring and analysis unit.

[0037] Step S600: Based on the multiple monitoring frequencies and the multiple alarm thresholds, the electrical, environmental conditions and insulation facilities in the multiple building areas are monitored for fire prevention.

[0038] Specifically, the higher the fire hazard factor of the building area, the higher the monitoring frequency and the lower the alarm threshold. The electrical, environmental conditions and insulation facilities in the building area are monitored according to the obtained monitoring frequency. For example, if the electrical monitoring frequency is once an hour, the environmental monitoring frequency is once two hours, and the insulation facility monitoring frequency is once a week, the electrical, environmental conditions and insulation facilities in the building area are monitored once an hour, once two hours, and once a week, respectively. When the monitored value reaches the alarm threshold, it means that the electrical, environmental conditions or insulation facilities in the current building area have reached the critical value for fire, and fire prevention information is generated and sent to the management personnel, so as to manage the electrical, environmental conditions or insulation facilities that exceed the threshold and prevent the occurrence of fire.

[0039] Furthermore, step S100 of the present application also includes:

[0040] Step S110: Acquire multiple building functions;

[0041] Step S120: Divide the target ancient building according to the multiple building functions to obtain the multiple building areas.

[0042] Specifically, building function refers to the specific purpose and use requirements when building a house. For example, residential buildings are residential buildings built to meet the most basic living needs. Residential buildings are influenced by factors such as environment, climate, folk culture, economy, etiquette, etc., and have strong regional characteristics in style and craftsmanship. Temple buildings are places for various sacrificial activities to express respect and gratitude to heaven, earth, and ancestors, such as the Altar of Land and Grain, the Imperial Ancestral Temple, and the Temple of Heaven in Beijing, as well as various ancestral temples in various places, such as the Bao Gong Temple in Anhui, the Wuhou Temple in Sichuan, and the Qu Yuan Temple in Hunan, as well as the clan ancestral temples and ancestral temples. The functional issues of buildings mainly include spatial composition, functional zoning, organization and evacuation of people, and the measurement, shape and physical environment of space. By dividing the functions of ancient buildings, we can control each building area and lay the foundation for the subsequent calculation of the fire hazard factor in the building area.

[0043] Furthermore, if Figure 2 As shown, step S200 of the present application also includes:

[0044] Step S210: obtaining a variety of ancient building materials;

[0045] Step S220: obtaining a plurality of flammability parameters corresponding to the plurality of ancient building materials according to the flammability of the plurality of ancient building materials;

[0046] Step S230: Obtaining the proportions of the multiple ancient building materials in the multiple building areas, and obtaining multiple material proportion information sets;

[0047] Step S240: performing weighted calculation on the multiple flammability parameters according to the multiple material proportion information sets respectively to obtain the multiple first fire hazard coefficients.

[0048] Specifically, ancient building materials can be divided into structural materials, decorative materials and certain special materials. Structural materials include wood, bamboo, stone, bricks and tiles, ceramics, etc. Decorative materials include green tiles, green bricks, square bricks, glazed tiles, etc.

[0049] The flammability of the above-mentioned materials is analyzed. Flammability refers to the property of being easy to ignite and maintain combustion, so as to obtain non-combustible materials, flame-retardant materials, combustible materials and flammable materials. The easier the building material is to ignite, the higher the flammability. The flammability of each building material is evaluated. For example, wood has a low ignition point and is easy to ignite, and it will continue to burn after ignition. Therefore, the flammability of wood is very high. The flammability parameter of wood is set to 90%. In this way, multiple flammability parameters of various ancient building materials are obtained according to the flammability of each ancient building material.

[0050] The above-mentioned multiple materials of ancient buildings in multiple building areas are counted separately to obtain the usage quantity of each material, and the ratio of the usage quantity of a material to the total material quantity is used as the proportion of the material in the ancient building materials. The higher the proportion, the more the material is used. The proportion of multiple materials in the same building area is counted to obtain a material proportion information set in the building area, and the material proportion information sets in multiple building areas are obtained to obtain multiple material proportion information sets.

[0051] The flammability parameters are weightedly calculated according to the material proportion information set in a certain building area to obtain the first fire hazard coefficient of the building area. For example, the flammability parameter of wood is set to 90%, and the flammability parameter of stone is set to 10%. For a stone-wood structure building using 80% wood and 20% stone, its first fire hazard coefficient W1=80%*90%+20%*10%=92%. It can be seen that the first fire hazard coefficient of this stone-wood structure is very high, which means that it is very easy to catch fire and the damage caused by fire is also very large.

[0052] Furthermore, if Figure 3 As shown, step S300 of the present application also includes:

[0053] Step S310: Acquire multiple electrical components and multiple possibility parameters of the possibility of fire occurring in the multiple electrical components;

[0054] Step S320: obtaining a plurality of electrical component proportion information sets according to the proportions of the plurality of electrical components in the plurality of building areas;

[0055] Step S330: performing weighted calculation on the plurality of possibility parameters according to the plurality of electrical component proportion information sets respectively, to obtain the plurality of second fire risk coefficients;

[0056] Step S340: performing weighted calculation on the plurality of first fire hazard coefficients and the plurality of second fire hazard coefficients to obtain the plurality of fire hazard coefficients.

[0057] Specifically, electrical equipment is a general term for generators, transformers, power lines, circuit breakers and other equipment in the power system. Electrical equipment includes primary equipment and secondary equipment. Primary equipment is mainly equipment that directly generates, transmits and consumes electrical energy, such as power generation, transformation, transmission, distribution and consumption, such as generators, transformers, overhead lines, distribution cabinets, switch cabinets, etc. Secondary equipment is equipment that plays a role in control, protection and measurement, such as cables, distribution cabinets, motors, switches and sockets, lamps, air conditioners, electric water heaters, electric meters, cameras, telephones, computers, etc.

[0058] Fires in electrical components generally refer to fires caused by faulty release of heat energy from electrical circuits, electrical equipment, appliances, and power supply equipment, such as high temperature, electric arcs, and electric sparks, as well as non-faulty release of heat energy, such as the hot surface of electric heating appliances, which ignites the main body or other combustibles under combustion conditions. The possibility of fire is analyzed based on the conditions of electrical equipment in the building area. For example, the better the line condition and the better the fire prevention measures, the lower the possibility. If the line is damaged or aged, or combustibles are piled around the equipment, the higher the possibility, and the possibility parameters are obtained.

[0059] The above-mentioned multiple electrical equipment in ancient buildings in multiple building areas are counted separately to obtain the number of each electrical equipment in use, and the ratio of the number of electrical equipment in use to the total number of electrical equipment is used as the proportion of the electrical equipment in the ancient building. The higher the proportion, the more the electrical equipment is used. The proportion of multiple electrical equipment in the same building area is counted to obtain a set of electrical equipment proportion information in the building area, and the electrical equipment proportion information sets in multiple building areas are obtained to obtain multiple electrical equipment proportion information sets.

[0060] A weighted calculation is performed on the possibility parameters according to a set of information on the proportion of electrical equipment in a certain building area to obtain the second fire hazard coefficient W2 of the building area, thereby obtaining multiple second fire hazard coefficients in multiple building areas. The higher the second fire hazard coefficient, the more likely a fire is to occur in the building area, and the greater the harm caused by the fire.

[0061] For any ancient building area, the fire hazard coefficient of the ancient building area is calculated according to its first fire hazard coefficient and the second fire hazard coefficient, and the fire hazard coefficient of the ancient building area is obtained as W=50%W1+50%W2, thereby obtaining multiple fire hazard coefficients in multiple building areas. The higher the fire hazard coefficient, the easier it is for a fire to occur in the building area, and the greater the harm caused by the fire.

[0062] Furthermore, step S400 of the present application also includes:

[0063] Step S410: Based on the fire protection facility configuration data of other ancient buildings, a plurality of sample fire risk factors and a plurality of sample fire protection facility configuration parameters are obtained;

[0064] Step S420: Based on the fire hazard coefficient as a decision feature, the plurality of sample fire hazard coefficients are used to construct a multi-level decision node, wherein each level of decision node performs binary classification on the input fire hazard coefficient and inputs the binary classification result into the upper level decision node;

[0065] Step S430: obtaining a plurality of division results obtained by performing multi-level binary classification by the multi-level decision nodes;

[0066] Step S440: using the multiple sample fire protection facility configuration parameters as multiple decision results, marking the multiple division results, and obtaining the fire protection facility configuration model.

[0067] Specifically, the firefighting facility configuration data includes the fire hazard coefficients and firefighting facility configuration parameters of other ancient buildings, among which firefighting facilities include fire alarm systems, fire extinguishers, safe evacuation systems, etc. The firefighting facility configuration parameters are the protection distance and configuration benchmark of firefighting facilities determined according to factors such as the hazard level and fire type of the firefighting facility configuration site. For example, one fire extinguisher is configured for every 50-100 square meters in a building area with a normal fire hazard coefficient, and the area where the fire extinguisher is set is reduced by one level for each increase in the fire hazard coefficient. Using this as sample data, multiple sample fire hazard coefficients and multiple sample firefighting facility configuration parameters are obtained.

[0068] The fire hazard coefficient is used as the characteristic data for division, and a multi-level decision node is constructed with multiple sample fire hazard coefficients. For example, the interval of the fire hazard coefficient is [0, 100%]. The first sample fire hazard coefficient is 80%. The first-level decision node is constructed with this fire hazard coefficient, and the interval of [0, 80%] and the interval of [80%, 100%] can be divided. The second sample fire hazard coefficient is 85%. According to the sample fire hazard coefficient 85%, the interval of [80%, 100%] is further divided into the interval of [80%, 85%] and the interval of [85%, 100%]. In this way, after the division of the multi-level decision nodes, multiple final divided intervals can be obtained, and the obtained multiple intervals are used as the division results. In this way, a multi-level decision node is constructed, and the fire hazard coefficient is divided into multiple levels according to the multi-level decision nodes to obtain multiple division results.

[0069] The firefighting facility configuration parameters corresponding to the fire hazard coefficient in each division result are obtained and marked. For example, the firefighting facility configuration parameters corresponding to the sample fire hazard coefficient of 85% are marked as the firefighting facility configuration parameters corresponding to the interval [85%, 100%]. According to the mapping relationship between multiple fire hazard coefficient intervals and the firefighting facility configuration parameters corresponding to each fire hazard coefficient interval, a firefighting facility configuration model is constructed.

[0070] Furthermore, step S500 of the present application includes:

[0071] Step S510: obtaining multiple sample fire hazard coefficients based on the fire protection facility configuration data of other ancient buildings;

[0072] Step S520: Based on the multiple sample fire hazard factors, multiple sample electrical monitoring frequencies, multiple sample environmental monitoring frequencies, multiple sample insulation facility monitoring frequencies, multiple sample electrical alarm thresholds, multiple sample environmental alarm thresholds, and multiple sample insulation facility alarm thresholds are set and obtained;

[0073] Step S530: constructing the electrical monitoring and analysis unit by using the plurality of sample electrical monitoring frequencies and the plurality of sample electrical alarm thresholds;

[0074] Step S540: constructing the environment monitoring and analysis unit by using the multiple sample environment monitoring frequencies and the multiple sample environment alarm thresholds;

[0075] Step S550: constructing the insulation facility monitoring and analysis unit by using the plurality of sample insulation facility monitoring frequencies and the plurality of sample insulation facility alarm thresholds;

[0076] Step S560: Based on the electrical monitoring and analysis unit, the environmental monitoring and analysis unit and the insulation facility monitoring and analysis unit, the fire protection monitoring model is obtained.

[0077] Specifically, the fire protection facility configuration data of other ancient buildings, including the fire hazard coefficients of other buildings, are obtained as multiple sample fire hazard coefficients. Common causes of electrical fires include short circuit, excessive resistance, leakage and overload. Among them, the most prominent cause of short circuit is ground fault, aging and damage of insulation layer is the main cause of ground fault, and long-term overload or poor contact of line is a common situation of insulation aging; leakage fire is mainly caused by high temperature and arc after aging and damage of line, causing nearby combustibles and accumulated combustible dust to catch fire. Therefore, based on the monitoring of electrical, environmental and insulation facilities in the ancient building area under multiple sample fire hazard coefficients, multiple sample electrical monitoring frequencies, multiple sample environmental monitoring frequencies, multiple sample insulation facility monitoring frequencies, multiple sample electrical alarm thresholds, multiple sample environmental alarm thresholds and multiple sample insulation facility alarm thresholds are set.

[0078] Based on the feedforward neural network, the electrical monitoring frequency and electrical alarm threshold corresponding to the sample fire hazard factor are used as sample data for supervised training to construct the electrical monitoring and analysis unit. In the same way, the environmental monitoring and analysis unit and the insulation facility monitoring and analysis unit are constructed for the sample environment and sample insulation facilities. Based on the electrical monitoring and analysis unit, the environmental monitoring and analysis unit and the insulation facility monitoring and analysis unit, the fire prevention monitoring model is obtained.

[0079] Furthermore, step S530 of the present application also includes:

[0080] Step S531: constructing the electrical monitoring and analysis unit based on a feedforward neural network, wherein the input data of the electrical monitoring and analysis unit is the fire risk factor, and the output data is the electrical monitoring frequency and the electrical alarm threshold;

[0081] Step S532: performing supervised data labeling on the multiple sample electrical monitoring frequencies and the multiple sample electrical alarm thresholds, and dividing them to obtain a training set, a validation set, and a test set;

[0082] Step S533: Use the training set, validation set and test set to perform supervised training, validation and testing on the electrical monitoring and analysis unit to obtain the electrical monitoring and analysis unit whose accuracy meets the preset accuracy requirement.

[0083] Specifically, multiple sample electrical monitoring frequencies and multiple sample electrical alarm thresholds are used as training data, and the training data is randomly divided into a training set, a validation set, and a test set according to a certain ratio. For example, the preferred ratio of this application is 8:1:1, wherein the training set is used to train the model, that is, to determine the learning parameters such as the weight and bias of the model; the validation set is used to verify each model using the validation set data after training multiple models in the training set, and record the model accuracy, and then select the best model and its corresponding parameters; the test set is only used once, that is, when evaluating the final model after the training is completed, and it does not participate in the process of learning parameters or the process of hyperparameter selection, but is only used for the evaluation of the model. Based on the feedforward neural network, the model is supervised and trained through the training set, the obtained model is verified through the validation set, and the trained model is evaluated through the test set, and the hyperparameters are continuously adjusted until the accuracy meets the preset requirements to obtain the electrical monitoring and analysis unit.

[0084] Embodiment 2

[0085] Based on the same inventive concept as the electrical fire prevention method for ancient buildings in the aforementioned embodiment, Figure 4 As shown, the present application provides an electrical fire protection system for ancient buildings, the system comprising:

[0086] A building area acquisition module 10, wherein the building area acquisition module 10 is used to divide the target ancient building to obtain multiple building areas;

[0087] A first fire hazard coefficient acquisition module 20, the first fire hazard coefficient acquisition module 20 is used to perform fire hazard analysis according to the types and distribution of building materials in the multiple building areas to obtain multiple first fire hazard coefficients;

[0088] A second fire hazard coefficient acquisition module 30, the second fire hazard coefficient acquisition module 30 is used to perform fire hazard analysis according to the types and distribution of electrical equipment in the multiple building areas, obtain multiple second fire hazard coefficients, and calculate and obtain multiple fire hazard coefficients in combination with the multiple first fire hazard coefficients;

[0089] A firefighting facility configuration parameter acquisition module 40, the firefighting facility configuration parameter acquisition module 40 is used to input the multiple fire risk factors into a firefighting facility configuration analysis model, obtain multiple firefighting facility configuration parameters, and arrange firefighting facilities for the multiple building areas;

[0090] An alarm threshold acquisition module 50, the alarm threshold acquisition module 50 is used to input the multiple fire risk factors into a fire monitoring model to obtain multiple monitoring frequencies and multiple alarm thresholds, wherein the fire monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit;

[0091] The fire prevention monitoring module 60 is used to monitor the electrical, environmental conditions and insulation facilities in the multiple building areas for fire prevention based on the multiple monitoring frequencies and the multiple alarm thresholds.

[0092] Furthermore, the system also includes:

[0093] Building function acquisition module, used to obtain various building functions;

[0094] The building division module is used to divide the target ancient building according to the multiple building functions to obtain the multiple building areas.

[0095] Furthermore, the system also includes:

[0096] Ancient building material acquisition module, used to obtain a variety of ancient building materials;

[0097] A flammability parameter acquisition module, used to obtain a plurality of flammability parameters corresponding to the plurality of ancient building materials according to the flammability of the plurality of ancient building materials;

[0098] A material proportion acquisition module is used to acquire the proportions of the multiple ancient building materials in the multiple building areas, and obtain multiple material proportion information sets;

[0099] The first weighted calculation module is used to perform weighted calculations on the multiple flammability parameters according to the multiple material proportion information sets respectively, so as to obtain the multiple first fire hazard coefficients.

[0100] Furthermore, the system also includes:

[0101] A possibility parameter acquisition module, used to acquire multiple electrical components and multiple possibility parameters of the possibility of fire occurring in the multiple electrical components;

[0102] An electrical component proportion information acquisition module, configured to obtain a plurality of electrical component proportion information sets according to proportions of the plurality of electrical components in the plurality of building areas;

[0103] A second weighted calculation module, configured to perform weighted calculations on the plurality of possibility parameters according to the plurality of electrical component proportion information sets, respectively, to obtain the plurality of second fire hazard coefficients;

[0104] The third weighted calculation module is used to perform weighted calculation on the multiple first fire hazard coefficients and the multiple second fire hazard coefficients to obtain the multiple fire hazard coefficients.

[0105] Furthermore, the system also includes:

[0106] A sample configuration parameter acquisition module is used to acquire multiple sample fire risk factors and multiple sample fire facility configuration parameters based on the fire facility configuration data of other ancient buildings;

[0107] A multi-level decision node construction module, which is used to construct a multi-level decision node based on the fire hazard coefficient as a decision feature and adopt the multiple sample fire hazard coefficients, wherein each level of decision node performs binary classification on the input fire hazard coefficient and inputs the binary classification result into the upper level decision node;

[0108] A partitioning result acquisition module, used to acquire multiple partitioning results obtained by performing multi-level binary classification partitioning on the multi-level decision nodes;

[0109] The marking module is used to use the multiple sample fire protection facility configuration parameters as multiple decision results, mark the multiple division results, and obtain the fire protection facility configuration model.

[0110] Furthermore, the system also includes:

[0111] A sample fire hazard coefficient acquisition module is used to obtain multiple sample fire hazard coefficients based on the fire protection facility configuration data of other ancient buildings;

[0112] An alarm threshold acquisition module is used to set and obtain multiple sample electrical monitoring frequencies, multiple sample environmental monitoring frequencies, multiple sample insulation facility monitoring frequencies, multiple sample electrical alarm thresholds, multiple sample environmental alarm thresholds, and multiple sample insulation facility alarm thresholds based on the multiple sample fire hazard coefficients;

[0113] An electrical monitoring and analysis unit construction module, configured to construct the electrical monitoring and analysis unit using the plurality of sample electrical monitoring frequencies and the plurality of sample electrical alarm thresholds;

[0114] An environment monitoring and analysis unit construction module, used to construct the environment monitoring and analysis unit by using the multiple sample environment monitoring frequencies and the multiple sample environment alarm thresholds;

[0115] A monitoring and analysis unit construction module, used to construct the insulation facility monitoring and analysis unit by using the plurality of sample insulation facility monitoring frequencies and the plurality of sample insulation facility alarm thresholds;

[0116] The fire prevention monitoring model acquisition module is used to obtain the fire prevention monitoring model based on the electrical monitoring and analysis unit, the environmental monitoring and analysis unit and the insulation facility monitoring and analysis unit.

[0117] Furthermore, the system also includes:

[0118] A monitoring and analysis unit construction module, used to construct the electrical monitoring and analysis unit based on a feedforward neural network, wherein the input data of the electrical monitoring and analysis unit is a fire hazard coefficient, and the output data is an electrical monitoring frequency and an electrical alarm threshold;

[0119] A data labeling module, used for performing supervised data labeling on the multiple sample electrical monitoring frequencies and the multiple sample electrical alarm thresholds, and dividing them to obtain a training set, a validation set, and a test set;

[0120] The supervised training module is used to use the training set, verification set and test set to perform supervised training, verification and testing on the electrical monitoring and analysis unit to obtain the electrical monitoring and analysis unit whose accuracy meets the preset accuracy requirements.

[0121] Through the above detailed description of an electrical fire prevention method for ancient buildings in this specification, those skilled in the art can clearly know an electrical fire prevention method and system for ancient buildings in this embodiment. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0122] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An electrical fire prevention method for ancient buildings, characterized in that: The method comprises: Divide the target ancient building into multiple building areas; Performing a fire hazard analysis based on the types and distribution of building materials in the multiple building areas to obtain multiple first fire hazard coefficients; Performing a fire hazard analysis according to the types and distribution of electrical equipment in the multiple building areas to obtain multiple second fire hazard coefficients, and calculating and obtaining multiple fire hazard coefficients in combination with the multiple first fire hazard coefficients; Inputting the plurality of fire risk factors into a fire protection facility configuration analysis model to obtain a plurality of fire protection facility configuration parameters, and arranging fire protection facilities for the plurality of building areas; Inputting the multiple fire risk factors into a fire prevention monitoring model to obtain multiple monitoring frequencies and multiple alarm thresholds, wherein the fire prevention monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit; Based on the multiple monitoring frequencies and the multiple alarm thresholds, monitor the electrical, environmental conditions and insulation facilities in the multiple building areas for fire prevention; Conduct fire hazard analysis based on the types and distribution of building materials in the multiple building areas, including: Acquire a variety of ancient building materials; According to the flammability of the plurality of ancient building materials, obtaining a plurality of flammability parameters corresponding to the plurality of ancient building materials; Obtaining the proportions of the plurality of ancient building materials in the plurality of building areas, and obtaining a plurality of material proportion information sets; The multiple flammability parameters are weightedly calculated according to the multiple material proportion information sets respectively to obtain the multiple first fire hazard coefficients.

2. The method according to claim 1, characterized in that Divide the target ancient building into multiple building areas, including: Get multiple building features; According to the multiple building functions, the target ancient building is divided to obtain the multiple building areas.

3. The method according to claim 1, characterized in that According to the types and distribution of electrical equipment in the multiple building areas, a fire hazard analysis is performed to obtain multiple second fire hazard coefficients, and multiple fire hazard coefficients are calculated and obtained in combination with the multiple first fire hazard coefficients, including: Acquire multiple electrical components and multiple possibility parameters of the possibility of fire occurring in the multiple electrical components; According to the proportions of the multiple electrical components in the multiple building areas, obtaining a set of information on proportions of multiple electrical components; According to the plurality of electrical component proportion information sets, respectively, weighted calculation is performed on the plurality of possibility parameters to obtain the plurality of second fire hazard coefficients; The plurality of first fire hazard coefficients and the plurality of second fire hazard coefficients are weightedly calculated to obtain the plurality of fire hazard coefficients.

4. The method according to claim 1, characterized in that: The construction process of the fire protection facility configuration analysis model includes: Based on the fire protection facility configuration data of other ancient buildings, multiple sample fire risk factors and multiple sample fire protection facility configuration parameters are obtained; Based on the fire hazard coefficient as a decision feature, the plurality of sample fire hazard coefficients are used to construct a multi-level decision node, wherein each level of decision node performs binary classification on the input fire hazard coefficient and inputs the binary classification result into the upper level decision node; Obtain multiple division results obtained by performing multi-level binary classification division on the multi-level decision nodes; The multiple sample fire protection facility configuration parameters are used as multiple decision results, the multiple division results are marked, and the fire protection facility configuration model is obtained.

5. The method according to claim 1, characterized in that: The construction process of the fire monitoring model includes: Based on the fire protection facility configuration data of other ancient buildings, multiple sample fire hazard coefficients were obtained; Based on the multiple sample fire hazard factors, multiple sample electrical monitoring frequencies, multiple sample environmental monitoring frequencies, multiple sample insulation facility monitoring frequencies, multiple sample electrical alarm thresholds, multiple sample environmental alarm thresholds, and multiple sample insulation facility alarm thresholds are set to obtain; Using the plurality of sample electrical monitoring frequencies and the plurality of sample electrical alarm thresholds, constructing the electrical monitoring and analysis unit; The environment monitoring and analysis unit is constructed by using the multiple sample environment monitoring frequencies and the multiple sample environment alarm thresholds; The insulation facility monitoring and analysis unit is constructed by using the plurality of sample insulation facility monitoring frequencies and the plurality of sample insulation facility alarm thresholds; The fire protection monitoring model is obtained based on the electrical monitoring and analysis unit, the environmental monitoring and analysis unit and the insulation facility monitoring and analysis unit.

6. The method according to claim 5, characterized in that The electrical monitoring and analysis unit is constructed by using the multiple sample electrical monitoring frequencies and the multiple sample electrical alarm thresholds, including: Based on a feedforward neural network, the electrical monitoring and analysis unit is constructed, wherein the input data of the electrical monitoring and analysis unit is a fire risk factor, and the output data is an electrical monitoring frequency and an electrical alarm threshold; Performing supervised data labeling on the multiple sample electrical monitoring frequencies and the multiple sample electrical alarm thresholds, and dividing them to obtain a training set, a validation set, and a test set; The training set, validation set and test set are used to perform supervised training, validation and testing on the electrical monitoring and analysis unit to obtain the electrical monitoring and analysis unit whose accuracy meets the preset accuracy requirement.

7. An electrical fire protection system for ancient buildings, characterized in that: The system comprises: A building area acquisition module, which is used to divide the target ancient building into multiple building areas; a first fire hazard coefficient acquisition module, the first fire hazard coefficient acquisition module being used to perform fire hazard analysis according to the types and distribution of building materials in the plurality of building areas, and to obtain a plurality of first fire hazard coefficients; a second fire hazard coefficient acquisition module, the second fire hazard coefficient acquisition module being used to perform fire hazard analysis according to the types and distribution of electrical equipment in the plurality of building areas, obtain a plurality of second fire hazard coefficients, and calculate and obtain a plurality of fire hazard coefficients in combination with the plurality of first fire hazard coefficients; a fire protection facility configuration parameter acquisition module, the fire protection facility configuration parameter acquisition module being used to input the plurality of fire risk factors into a fire protection facility configuration analysis model, obtain a plurality of fire protection facility configuration parameters, and arrange fire protection facilities for the plurality of building areas; an alarm threshold acquisition module, the alarm threshold acquisition module is used to input the multiple fire risk factors into a fire prevention monitoring model to obtain multiple monitoring frequencies and multiple alarm thresholds, wherein the fire prevention monitoring model includes an electrical monitoring and analysis unit, an environmental monitoring and analysis unit, and an insulation facility monitoring and analysis unit; a monitoring fire prevention module, the monitoring fire prevention module is used to monitor the electrical, environmental conditions and insulation facilities in the multiple building areas for fire prevention based on the multiple monitoring frequencies and the multiple alarm thresholds; The system also includes: Building function acquisition module, used to obtain various building functions; A building division module, used for dividing the target ancient building according to the multiple building functions to obtain the multiple building areas; Ancient building material acquisition module, used to obtain a variety of ancient building materials; A flammability parameter acquisition module, used to obtain a plurality of flammability parameters corresponding to the plurality of ancient building materials according to the flammability of the plurality of ancient building materials; A material proportion acquisition module is used to acquire the proportions of the multiple ancient building materials in the multiple building areas, and obtain multiple material proportion information sets; The first weighted calculation module is used to perform weighted calculations on the multiple flammability parameters according to the multiple material proportion information sets respectively, so as to obtain the multiple first fire hazard coefficients.

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