CN117197986A - Fire alarm system for building floor - Google Patents
Fire alarm system for building floor Download PDFInfo
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- CN117197986A CN117197986A CN202311475938.4A CN202311475938A CN117197986A CN 117197986 A CN117197986 A CN 117197986A CN 202311475938 A CN202311475938 A CN 202311475938A CN 117197986 A CN117197986 A CN 117197986A
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- 230000005611 electricity Effects 0.000 claims abstract description 19
- 238000011156 evaluation Methods 0.000 claims abstract description 13
- 230000010365 information processing Effects 0.000 claims abstract description 5
- 238000004458 analytical method Methods 0.000 claims description 13
- 239000003517 fume Substances 0.000 claims description 4
- 238000000034 method Methods 0.000 description 10
- 238000004364 calculation method Methods 0.000 description 9
- 239000000779 smoke Substances 0.000 description 9
- 239000002245 particle Substances 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 3
- 238000007796 conventional method Methods 0.000 description 3
- 238000010411 cooking Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 125000005575 polycyclic aromatic hydrocarbon group Chemical group 0.000 description 2
- 238000011002 quantification Methods 0.000 description 2
- 230000004913 activation Effects 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 239000006233 lamp black Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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Abstract
The application relates to the technical field of fire safety alarm, in particular to a fire alarm system of a building floor, an information acquisition module, a control module and a control module, wherein the information acquisition module is used for acquiring the temperature and the power of a main cable of each room; the information processing module is used for obtaining fire risk coefficients of different rooms through the change of the cable temperature and the active power; calculating the electricity habit distance according to the cable temperature, the active power and the fire risk coefficient, so as to obtain an object set; judging the sizes of each outlier factor and a set fire risk coefficient threshold value in the object set, if the outlier factor is smaller than the set fire risk coefficient threshold value, the data point of the outlier factor is normal, otherwise, the outlier factor is high-risk data, and according to the high-risk data, the fire is evaluated to obtain a real-time evaluation index; and the alarm system is used for alarming according to the real-time evaluation index. The application can alarm the fire safety of the building floor.
Description
Technical Field
The application relates to the technical field of fire safety alarm, in particular to a fire alarm system for building floors.
Background
With the development of information society, buildings are becoming an increasingly constituent of the human environment, and from industrial society to the concept of modern buildings, intelligent buildings are being vigorously developed worldwide, and have achieved remarkable results in a large number of building practices. Practice proves that with the development of society and economy, the importance of fire-fighting work is more and more prominent. Thus, the fire alarm is particularly effective in fire-fighting operation, but there are cases where detection is inaccurate.
Disclosure of Invention
In order to solve the technical problems, the application aims to provide an intelligent video safety monitoring method and system based on gridding management and control, and the adopted technical scheme is as follows:
a fire alarm system for a building floor, comprising:
the information acquisition module is used for acquiring the temperature and the power of the main cable of each room;
the information processing module is used for obtaining fire risk coefficients of different rooms through the change of the cable temperature and the active power; calculating the electricity habit distance according to the cable temperature, the active power and the fire risk coefficient, so as to obtain an object set; judging the sizes of each outlier factor and a set fire risk coefficient threshold value in the object set, if the outlier factor is smaller than the set fire risk coefficient threshold value, the data point of the outlier factor is normal, otherwise, the outlier factor is high-risk data, and according to the high-risk data, the fire is evaluated to obtain a real-time evaluation index;
and the alarm system is used for alarming according to the real-time evaluation index.
Preferably, the fire risk factor is:
wherein U is a fire risk coefficient of a room,maximum temperature reached for the cable temperature within one minute of the current analysis, +.>For the highest temperature reached by the cable in the last minute, T is the real-time temperature, < >>Is the average value of the active power in one minute of the current analysis, +.>For the maximum value of active power within one minute of the current analysis,is the median of the active power within one minute of the current analysis.
Preferably, the electricity habit distance is as follows:
wherein,representing active power +.>Above rated power +.>Duty cycle of>Representative is cable temperature +.>Above the expected temperature->Duty cycle of>For the distance of the electricity usage habit,for use mode->Fire risk factor->And usage pattern->Downfire windRisk factor->Is a difference in (a) between the two.
Preferably, the real-time evaluation index is:
wherein,to determine if the main line power usage characteristic is a Boolean function of the sample in a high risk usage mode with a high risk factor for fire in a short period of time +.>For setting the fire risk factor threshold, < >>For each outlier factor, +.>Is natural constant (18)>For the temperature of the room main cable, +.>As a result of the reference temperature,is fume factor (L)>Is a real-time evaluation index.
The application has the beneficial effects that:
according to the fire alarm system for the building floor, the information acquisition module, the information processing module and the alarm template are designed, so that the fire safety of the building floor can be alarmed.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the application, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a system schematic diagram of the fire alarm system of the building floor of the present application.
Detailed Description
In order to further describe the technical means and effects adopted by the present application for achieving the preset purpose, the following detailed description of the specific embodiments, structures, features and effects thereof according to the present application is given with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
Specifically, referring to fig. 1, the fire alarm system for building floors provided by the present application includes:
the information acquisition module is used for acquiring the temperature and the power of the main cable of each room;
the information processing module is used for obtaining fire risk coefficients of different rooms through the change of the cable temperature and the active power; calculating the electricity habit distance according to the cable temperature, the active power and the fire risk coefficient, so as to obtain an object set; judging the sizes of each outlier factor and a set fire risk coefficient threshold value in the object set, if the outlier factor is smaller than the set fire risk coefficient threshold value, the data point of the outlier factor is normal, otherwise, the outlier factor is high-risk data, and according to the high-risk data, the fire is evaluated to obtain a real-time evaluation index;
and the alarm system is used for alarming according to the real-time evaluation index.
And detecting the temperature of the main cable by using an on-line main cable temperature detector to obtain the cable temperature T of the room. When the cable ages or is overloaded, the temperature can rise suddenly, the cable can be heated by a high-power electric appliance, and a plurality of false alarms can occur when the temperature of the cable is directly measured.
The active power is the main active power of all electric appliances when each room is powered, namely, the instantaneous power is obtained based on the product of the voltage sampled each time and the current sampled each time, and the instantaneous power is integrated by using the fixed time, so that the average value of the instantaneous power, namely, the active power, is obtained, and the active power W is obtained. Wherein, W is active power, the active power can represent real-time power consumption of pure resistor, for example, cable has short circuit, pure resistor power of household electrical appliance heating device or other short circuit condition and intermittent short circuit condition can be analyzed by active power.
And setting the duration of the short time period to be 1min, and synchronously recording the trunk cable temperature and the trunk active power of each time period by 5 Hz.
The fire risk factor in this embodiment is:
wherein U is a fire risk coefficient of a room,maximum temperature reached for the cable temperature within one minute of the current analysis, +.>For the highest temperature reached by the cable in the last minute, T is the real-time temperature, < >>Is the average value of the active power in one minute of the current analysis, +.>For the maximum value of active power within one minute of the current analysis,is the median of the active power within one minute of the current analysis.
It should be noted that ReLU is a commonly used activation function in artificial neural networks. The role of the ReLU is: when the current one minute is higher than the previous one, the cable temperature is considered to be still rising, so that the cable has a certain fire hazard, whereas when the current one minute is lowered relative to the previous one, the abnormal heat generating factor disappears, so that the cable has a certain fire hazard0,U is also 0; is->Is considered to be generated at the start-up of the high-power electric appliance if +.>If the fire is in a larger state, the fire is considered to have a certain hidden danger. Thus (S)>Can be used as an index of whether the room has fire hidden danger or not.
The method for acquiring the electricity consumption habit distance comprises the following steps:
constructing a data set based on short-period main line electricity utilization characteristics of each room asFirst, a sample with U of 0 is filtered, because it is difficult to have a fire hazard when U is 0 and classification of fire category is impossible, so it is not considered. The analysis of the power usage pattern is performed below for samples with potential U greater than 0.
The user data volume isI.e. the number of rooms, the minimum number of data in the outlier neighborhood is set to +.>The method comprises the steps of carrying out a first treatment on the surface of the The practitioner should make reasonable settings in connection with the electricity usage pattern of the building.
Setting a calculation objectIs->Distance neighborhood is->Computing object->Reference object in electric quantity data set>The distance between them is->；
The constraint conditions are as follows: at least exist inPersonal object->So that->The method comprises the steps of carrying out a first treatment on the surface of the At least there is->Personal object->So that->；
Wherein the distance between objects is the distance by using electricityThe representation is:
when the potential power utilization hazards have the following differences, the power utilization risks of the representative rooms have the differences; wherein,representing active power +.>Above rated power +.>Duty cycle of>Representative is cable temperature +.>Above the expected temperature->Duty cycle of>For the distance of the electricity habit +.>For use mode->Fire risk factor->And usage pattern->Lower fire risk factor->Is used for the purpose of determining the difference in (2),a risk value representing the user's overrun in using the appliance for a period of time, wherein rated power +.>And the expected temperature->It is necessary for the practitioner to manually determine a value of a conservative estimate, thus representing the mode of excess electricity use, +.>The difference of fire risk coefficients under different use modes is that U covers the temperature T of the cable when sampling is performed, and when the difference of the cable temperatures is large, the cable temperature of one sample is in a high state, so that the samples with risks and low risks are separated.
Calculation ofIs->Distance to object in neighborhood->Is no greater than +.>Is marked asI.e. +.>。
Computing objectAbout object->Is>Setting the right->Distance->Far (+)>At->Is->Within the distance neighborhood), the reachable distance is +.>And->The actual distance of (2) otherwise the reachable distance is +.>Is->A distance neighborhood;
calculating the reachable distance:；
calculating the reachable densityAnd outlier factor->；
Calculating the reachable density；
Computing outliersDot factor。
Setting the fire risk factor threshold in the present embodimentIntroducing all short-time period main line electricity utilization characteristics, and judging each outlier factor +.>Whether a threshold range is exceeded; if not, the data point is normal; if the set threshold value is exceeded, the sample is determined to be a sample in a high-risk use mode in which the fire risk coefficient is high. And sorting the data set into samples in a high-risk use mode, and taking the samples as a high-risk sample set E.
In this embodiment, since too much high power load does not exist in the normal power consumption process to cause the cable to have too high temperature rise, once the outlier factor occursSamples greater than the fire risk factor thresholdThe power of the sample is not too low, i.e. the cable is still considered to be subjected to a large load, so that a temperature rise occurs.
When outlier factors occurSamples that are greater than the fire risk factor threshold,the cable temperature in the high-risk sample set E is always a dangerous temperature rise state.
Reference cable temperature using lower temperatures of the resulting anomaly class as dangerous usage characteristics；
Reference cable temperature for critical use featuresExpressed on the basis of the lower temperature of the cable in dangerous electrical behaviour, the practitioner obtains a reference cable temperature by setting a reference ratio L>；
ObtainingThe method comprises the steps of carrying out incremental sequencing on the cable temperature average value in the high-risk sample set E, and taking the average value of Top-L, wherein L is a percentage.
To this end, a reference cable temperature of the room cable in the building is determined based on the high-risk sample；
Because the scene of high-power use in the building is almost used as cooking, larger oil smoke particles or water drops floating in the air can be generated during cooking, and the value R of fire risk is estimated for abnormal electricity consumption conditions by combining oil smoke factors:
and for the electricity utilization characteristics of the main circuit in the short time period in the room at any moment, the corresponding collected oil smoke factor F exists.
The method for estimating the fire risk according to the oil smoke factor generated during cooking in a room is characterized in that the calculation formula of the oil smoke factor is as follows:
quantification fraction for the concentration of the similar polycyclic aromatic hydrocarbon, the unit is; wherein the concentration of polycyclic aromatic hydrocarbon in the room can be calculated by PM2.5 concentration signal and PM10 concentration signal, and the practitioner can also combine the temperature of kitchen wareThe calculation module is a calculator or a module with a calculation function, which can be used as the calculation module of the present application, and the calculation module of this type is a common knowledge of the calculation module in industrial production, and a person skilled in the art should know that the calculation module is not described herein.
The light loss quantization fraction is given in units of; since the method of detecting the concentration of smoke based on the light loss of the tube is a conventional method of smoke alarms, a detailed description thereof will be omitted.
The wet metric fraction is given in units of; since photoelectric and MEMS-based sensors are conventional methods of relative humidity detection, no further description is given.
A large particle diameter particle concentration sensor quantification fraction in units of; since detection based on large particle size particles is a conventional method of smoke detection technology, no further description is given.
Wherein k1, k2, k3, k4 are oil quality weight coefficients, and k1+k2+k3+k4=1, and k1, k2, k3, k4 are positive numbers.
Obtaining real-time evaluation index
Wherein the method comprises the steps ofIn order to judge whether the electricity utilization characteristic of the main line in the short time period is a Boolean function of a sample in a high-risk use mode with a high fire risk coefficient, if the electricity utilization characteristic is not exceeded, the Boolean function is 0, otherwise, the Boolean function is 1./>Is natural constant (18)>For the temperature of the room main cable, +.>For reference temperature, +.>Is fume factor (L)>For real-time evaluation of indicators
Wherein the method comprises the steps ofIs the distance of any room trunk cable relative to the reference temperature, and if the distance exceeds the reference temperature, the value is negative,can be increased drastically.
Is fume factor->For scaling factor in implementation, it is set to 1 in the embodiment of the present application, as appropriate. When the oil smoke factor is large, the risk can be increased to a certain extent, so that when a user uses some unconventional kitchen appliances, even if the electricity utilization behavior is possibly abnormal, the cable temperature is increased, and the possibility of false alarm can be restrained.
And an implementer designs an alarm threshold value by himself, and can judge whether the power utilization characteristic of the main circuit in a short time period is a high-risk use mode with a high fire risk coefficient or not under the condition that a heavy-load electric appliance generates enough load to a cable, and the risk estimation is carried out by combining the estimation of the cable temperature, and meanwhile, false alarm is restrained based on lampblack.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents.
Claims (4)
1. Fire alarm system of building floor, its characterized in that includes:
the information acquisition module is used for acquiring the temperature and the active power of the main cable of each room;
the information processing module is used for obtaining fire risk coefficients of different rooms through the change of the cable temperature and the active power; calculating the electricity habit distance according to the cable temperature, the active power and the fire risk coefficient, so as to obtain an object set; judging the sizes of each outlier factor and a set fire risk coefficient threshold value in the object set, if the outlier factor is smaller than the set fire risk coefficient threshold value, the data point of the outlier factor is normal, otherwise, the outlier factor is high-risk data, and according to the high-risk data, the fire is evaluated to obtain a real-time evaluation index;
and the alarm system is used for alarming according to the real-time evaluation index.
2. The fire alarm system of claim 1, wherein the fire risk factor is:
wherein U is a fire risk coefficient of a room,the highest temperature reached by the cable temperature within one minute of the current analysis,for the highest temperature reached by the cable in the last minute, T is the real-time temperature, < >>Is the average value of the active power in one minute of the current analysis, +.>For the maximum value of active power within one minute of the current analysis,is the median of the active power within one minute of the current analysis.
3. The fire alarm system of claim 2, wherein the electricity usage habit distance is:
wherein,representing active power +.>Above rated power +.>Duty cycle of>Representative is cable temperature +.>Above the expected temperature->Duty cycle of>For the distance of the electricity habit +.>For use mode->Fire risk factor->And usage pattern->Lower fire risk factor->Is a difference in (a) between the two.
4. The fire alarm system of claim 2, wherein the real-time assessment indicator is:
wherein,to determine if the main line power usage characteristic is a Boolean function of the sample in a high risk usage mode with a high risk factor for fire in a short period of time +.>In order to set the fire risk factor threshold,for each outlier factor, +.>Is natural constant (18)>For the temperature of the room main cable, +.>For reference temperature, +.>Is fume factor (L)>Is a real-time evaluation index.
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| CN116665393A (en) * | 2023-05-30 | 2023-08-29 | 营口天成消防设备有限公司 | Electrical fire monitoring method and system |
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- 2023-11-08 CN CN202311475938.4A patent/CN117197986B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114021501A (en) * | 2021-11-09 | 2022-02-08 | 华东理工大学 | Fire temperature field reconstruction method, system, computer equipment, medium and terminal |
| CN114386845A (en) * | 2022-01-13 | 2022-04-22 | 江苏柯创城市技术有限公司 | Intelligent mall fire fighting monitoring processing system based on BIM |
| CN114511243A (en) * | 2022-02-22 | 2022-05-17 | 哈尔滨工业大学（深圳） | Method and system for dynamically evaluating fire risk based on Internet of things monitoring |
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