CN114937338A - Fire alarm identification method and related components - Google Patents
Fire alarm identification method and related components Download PDFInfo
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- CN114937338A CN114937338A CN202210621610.8A CN202210621610A CN114937338A CN 114937338 A CN114937338 A CN 114937338A CN 202210621610 A CN202210621610 A CN 202210621610A CN 114937338 A CN114937338 A CN 114937338A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
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- A—HUMAN NECESSITIES
- A62—LIFE-SAVING; FIRE-FIGHTING
- A62C—FIRE-FIGHTING
- A62C31/00—Delivery of fire-extinguishing material
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- A—HUMAN NECESSITIES
- A62—LIFE-SAVING; FIRE-FIGHTING
- A62C—FIRE-FIGHTING
- A62C37/00—Control of fire-fighting equipment
- A62C37/36—Control of fire-fighting equipment an actuating signal being generated by a sensor separate from an outlet device
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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Abstract
The invention discloses a fire alarm identification method and related components, which are applied to the field of servers and used for acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises alarm time, alarm position and alarm type; acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system; inputting alarm data and linkage data into a pre-trained fire alarm recognition model constructed by using a long-short term memory recurrent neural network to obtain space-time alarm information; and generating a corresponding fire alarm grade according to the time-space alarm information. Through the fire alarm recognition model, the acquired alarm data are better processed, more accurate space-time alarm information is obtained, the probability of false alarm is reduced, the fire alarm grades are divided, and the efficiency of fire treatment is improved.
Description
Technical Field
The invention relates to the field of servers, in particular to a fire alarm identification method and a related component.
Background
In the prior art, a fire detector detects physical characteristic quantities of a location, such as temperature, smoke, light and gas, for example, when the temperature of the current location exceeds a temperature threshold, the temperature is converted into an electric signal, and an alarm signal is sent to a server. Considering that the temperature of the current environment may rise, the air quality is poor, artificial light exists, and gas which is generated when part of similar fire occurs can influence the normal work of detectors of different types, so that the fire detectors report mistakenly and send alarm signals to a server, but actually, fire does not occur. A great deal of misinformation information can cause resource waste and influence the timely treatment of fire.
Disclosure of Invention
The invention aims to provide a fire alarm identification method and a related component. The acquired alarm data are better processed to obtain more accurate space-time alarm information, the probability of occurrence of false alarm is reduced, the fire alarm grades are divided, and the efficiency of fire treatment is improved.
In order to solve the technical problem, the invention provides a fire alarm identification method, which comprises the following steps:
acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises alarm time, alarm position and alarm type;
acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system;
inputting the alarm data and the linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-short term memory recurrent neural network to obtain space-time alarm information;
and generating a corresponding fire alarm grade according to the time-space alarm information.
Preferably, the fire alarm system comprises a smoke detector, a temperature detector, a flame detector, a manual alarm button and a fire hydrant alarm button;
acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises:
receiving alarm data sent by the smoke detector, the temperature detector, the flame detector, the manual alarm button and the fire hydrant alarm button;
taking the time when the alarm data is received as the alarm time;
determining a serial number of the fire alarm system which sends the alarm data, and determining the alarm position according to the serial number and the corresponding relation between a preset serial number and the position;
determining the alarm type, wherein the alarm type comprises the type of a detector and/or a button which sends alarm data in the fire alarm system.
Preferably, the fire-fighting linkage control system comprises an automatic water-spraying fire-extinguishing system, a fire-fighting water supply system, a smoke-preventing and exhausting system, a fire-preventing separation system and the like;
obtain the linkage data that fire control linkage control system sent, include:
and acquiring the type of the fire-fighting linkage control system for sending the linkage data.
Preferably, the time-space alarm information is the probability of fire occurrence;
generating a corresponding fire alarm grade according to the time-space alarm information, comprising:
and determining fire alarm classification levels according to the preset probability range where the space-time alarm information is located, wherein the fire alarm classification levels corresponding to different preset probability ranges are different.
Preferably, after generating the corresponding fire alarm level according to the space-time alarm information, the method further includes:
and executing a preset alarm mode corresponding to the fire alarm level according to the fire alarms of different levels.
Preferably, the fire alarm identification model comprises a time sequence submodel, a space sequence submodel and a linkage sequence submodel;
inputting the alarm data and the linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-term and short-term memory cyclic neural network to obtain space-time alarm information, wherein the space-time alarm information comprises the following steps:
inputting the alarm time of the current period and the time-space alarm information of the previous period in the alarm data into an input layer of the time sequence sub-model so as to obtain first conversion data after first weight matrix conversion;
inputting the alarm position of the current period in the alarm data to an input layer of the space sequence submodel so as to obtain second conversion data after second weight matrix conversion;
inputting the alarm type of the current period in the alarm data and the linkage data into an input layer of the linkage sequence sub-model so as to obtain third conversion data after the second weight matrix conversion;
and carrying out neuron combination on the first conversion data, the second conversion data and the third conversion data in a hidden layer to obtain the time-space alarm information of the current period.
In order to solve the above technical problem, the present invention further provides a fire alarm recognition system, including:
the fire alarm system comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring alarm data sent by the fire alarm system, and the alarm data comprises alarm time, alarm position and alarm type; acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system;
the input unit is used for inputting the alarm data and the linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-term and short-term memory cyclic neural network, so as to obtain space-time alarm information;
and the generating unit is used for generating a corresponding fire alarm grade according to the time-space alarm information.
In order to solve the technical problem, the invention also provides a fire system which comprises the fire alarm recognition system, a fire alarm system and a fire-fighting linkage control system.
In order to solve the above technical problem, the present invention further provides a fire alarm recognition device, including:
a memory for storing a computer program;
a processor for implementing the steps of the above fire alarm identification method when executing the computer program.
In order to solve the technical problem, the invention also provides a server which comprises the fire alarm recognition device.
The application provides a fire alarm identification method and related components, which are applied to the field of servers and used for acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises alarm time, alarm position and alarm type; acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system; inputting alarm data and linkage data into a pre-trained fire alarm recognition model constructed by using a long-short term memory recurrent neural network to obtain space-time alarm information; and generating a corresponding fire alarm grade according to the time-space alarm information. Through the fire alarm recognition model, the acquired alarm data are better processed, more accurate space-time alarm information is obtained, the probability of occurrence of false alarm is reduced, the fire alarm grades are divided, and the efficiency of fire treatment is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required in the prior art and the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart of a fire alarm identification method according to the present invention;
FIG. 2 is a schematic diagram of a fire alarm recognition model according to the present invention;
FIG. 3 is a data processing diagram of a fire alarm recognition model according to the present invention;
FIG. 4 is a schematic diagram of a fire alarm identification system according to the present invention;
FIG. 5 is a schematic diagram of a fire system according to the present invention;
fig. 6 is a schematic structural diagram of a fire alarm recognition device provided by the invention.
Detailed Description
The core of the invention is to provide a fire alarm identification method and related components. The acquired alarm data are better processed to obtain more accurate space-time alarm information, the probability of occurrence of false alarm is reduced, the fire alarm grades are divided, and the efficiency of fire treatment is improved.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a fire alarm identification method provided by the present invention, which includes:
s11: acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises alarm time, alarm position and alarm type;
when the server receives alarm data sent by a fire alarm system, the server preliminarily judges that a fire disaster occurs at present, and can obtain alarm time, namely the time of the fire disaster, according to the alarm data; obtaining the position of alarm, namely the position of fire; the type of alarm is obtained, i.e. what the cause of the fire is. And acquiring the time and the position of the fire and the factors causing the fire to perform subsequent processing.
S12: acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system;
after receiving the fire alarm system, the fire-fighting linkage control system can automatically carry out fire-fighting related operations, and can send linkage data to the server when carrying out fire-fighting related operations. And the server determines the type of the fire-fighting linkage control system according to the linkage data. Specifically, when the type of the fire-fighting linkage control system is the automatic water-spraying fire-fighting linkage control system, the linkage data is that the water pump is opened.
S13: inputting alarm data and linkage data into a pre-trained fire alarm recognition model constructed by using a long-short term memory recurrent neural network to obtain space-time alarm information;
the fire alarm recognition model is trained in advance, so that the pre-constructed fire alarm recognition model can process input data, and the data is combined through the long-term and short-term memory cyclic neural network to obtain more accurate time-space alarm information, thereby reducing the possibility of false alarm.
S14: and generating a corresponding fire alarm grade according to the time-space alarm information.
Different fire alarm grades are generated according to the time-space alarm information, and subsequent fire treatment can be carried out according to the different fire alarm grades. Specifically, when the fire alarm level is high, there is a greater possibility of a fire occurring, and when the fire alarm level is low, there is a lesser possibility of a fire occurring. And subsequent operators on duty can carry out different operations according to the fire alarm level.
In summary, it is considered that in the prior art, the fire detector detects physical characteristic quantities such as temperature, smoke, light, and gas of a place where the fire detector is located. Considering that the temperature of the current environment may rise, the air quality is poor, artificial light exists, and gas which is generated when part of similar fire occurs can influence the normal work of detectors of different types, so that the fire detectors report mistakenly and send alarm signals to a server, but actually, fire does not occur. A great deal of misinformation information can cause resource waste and influence the timely treatment of fire.
The application provides a fire alarm identification method, which is applied to the field of servers and used for acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises alarm time, alarm position and alarm type; acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system; inputting alarm data and linkage data into a pre-trained fire alarm recognition model constructed by using a long-short term memory recurrent neural network to obtain space-time alarm information; and generating a corresponding fire alarm grade according to the time-space alarm information. Through the fire alarm recognition model, the acquired alarm data are better processed, more accurate space-time alarm information is obtained, the probability of occurrence of false alarm is reduced, the fire alarm grades are divided, and the efficiency of fire treatment is improved.
On the basis of the above-described embodiment:
as a preferred embodiment, the fire alarm system comprises a smoke detector, a temperature detector, a flame detector, a manual alarm button and a fire hydrant alarm button;
acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises:
receiving alarm data sent by a smoke detector, a temperature detector, a flame detector, a manual alarm button and a fire hydrant alarm button;
taking the time of receiving the alarm data as alarm time;
determining a serial number of a fire alarm system for sending alarm data, and determining an alarm position according to the serial number and the corresponding relation between a preset serial number and the position;
an alarm type is determined, the alarm type including the type of detector and/or button in the fire alarm system that sent the alarm data.
In consideration of the fact that various detectors such as a smoke detector, a temperature detector, a flame detector, a manual alarm button, a fire hydrant alarm button and the like exist in the fire alarm system, after alarm data sent by the fire alarm system are obtained, alarm time is determined according to the sending time of the alarm data. The serial number of the fire alarm system represents the position of the fire alarm system, the server is preset with the corresponding relation between the serial number and the position of the fire alarm system, and the alarm position is determined according to the serial number of the fire alarm system of the alarm data sender. And determining the alarm type according to the type of the fire alarm system of the alarm data sender.
Specifically, after receiving the alarm data sent by the smoke detector, the server receives the alarm data for 16:00, the alarm time is 16:00, and the server can obtain the position of the temperature detector by obtaining the serial number of the temperature detector, so as to determine the position of the fire. And if the fire alarm system sending alarm data is a smoke detector, the alarm type is smoke alarm.
In conclusion, according to the time when the fire alarm system sends the alarm data and the type and the serial number of the fire alarm system sending the alarm data, the alarm time, the alarm type and the alarm position can be determined so as to perform subsequent processing on the alarm data.
In addition, the server also receives fault data, feedback data and the like sent by the fire alarm system, for example, when the fire alarm system fails, a signal is sent to the server to inform the server of the failure, so that the server can perform subsequent processing.
As a preferred embodiment, the fire-fighting linkage control system comprises an automatic water-spraying fire-extinguishing system, a fire-fighting water supply system, a smoke-preventing and discharging system, a fire-preventing separation system, an electrical fire monitoring system and the like;
obtain the linkage data that fire control linkage control system sent, include:
and acquiring the type of the fire-fighting linkage control system for sending the linkage data.
Considering that the fire-fighting linkage control system can perform response operation after receiving the alarm data, different types of fire-fighting linkage control systems can perform different types of operation. After receiving the linkage data sent by the fire-fighting linkage control system, the server can determine the relationship between the fire-fighting linkage control system and the fire system according to the linkage data. Specifically, for example, after receiving an alarm from the temperature detector, the automatic fire sprinkler system turns on the water pump, and at this time, the water pump turning-on event is sent to the server as linkage data.
Linkage relation between the fire alarm system and the fire-fighting linkage control system can be obtained through linkage data sent by different types of fire-fighting linkage control systems after the alarm data are received, and further subsequent processing is carried out on the linkage data.
As a preferred embodiment, the time-space alarm information is the probability of fire occurrence;
generating a corresponding fire alarm grade according to the space-time alarm information, comprising:
and determining fire alarm classification levels according to the preset probability range of the time-space alarm information, wherein the fire alarm classification levels corresponding to different preset probability ranges are different.
Considering that the probability of fire occurrence is different, the reaction time of the person on duty to the fire is not used, so the fire alarm is divided into different grades in advance, and the person on duty can carry out different processing modes according to the different grades.
Specifically, when the probability of fire occurrence is lower than 30%, the fire occurrence is a blue fire alarm, the possibility of fire occurrence is extremely low, and the possibility of false alarm is provided; when the probability of fire occurrence is 30% -60%, the fire occurrence is yellow fire alarm, and the possibility of fire occurrence is small; when the probability of fire is 60% -90%, the fire is an orange fire alarm, and the possibility of fire is high; when the probability of fire occurrence is more than 90%, the fire is a red fire alarm, and it can be considered that the fire occurs, and an attendant needs to immediately deal with the fire.
The fire alarm is divided according to the probability range of the space-time alarm information output by the fire alarm identification model, and the space-time alarm data are converted into colors, so that operators on duty can process the fire alarm in different modes according to the colors, and the processing efficiency of the fire alarm is higher.
As a preferred embodiment, after generating the corresponding fire alarm level according to the space-time alarm information, the method further includes:
and executing a preset alarm mode corresponding to the fire alarm level according to the fire alarms of different levels.
In consideration of the fact that the prompt of the operator on duty through the alarm data of different levels is not obvious enough, the operator on duty may miss the alarm of the alarm data, and different alarm modes are carried out according to the fire alarms of different levels. The alarm mode includes, but is not limited to, the sound and frequency of the sending of the alarm sound, specifically, the red fire alarm has the highest alarm volume and the highest frequency, and the blue fire alarm has the lowest alarm volume and the lowest frequency.
The fire alarms of different grades are subjected to alarm modes of corresponding grades, so that different alarms are given to the attendant aiming at the fire alarms of different grades, and the attendant can perform different processing modes after receiving the alarms.
FIG. 2 is a schematic structural diagram of a fire alarm recognition model according to the present invention; FIG. 3 is a data processing diagram of a fire alarm recognition model according to the present invention;
as a preferred embodiment, the fire alarm recognition model comprises a time sequence sub-model, a space sequence sub-model and a linkage sequence sub-model;
inputting alarm data and linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-term and short-term memory cyclic neural network to obtain space-time alarm information, wherein the space-time alarm information comprises the following steps:
inputting the alarm time of the current period and the time-space alarm information of the previous period in the alarm data into an input layer of a time sequence sub-model so as to obtain first conversion data after the first weight matrix conversion;
inputting the alarm position of the current period in the alarm data to an input layer of the space sequence sub-model so as to obtain second conversion data after second weight matrix conversion;
inputting the alarm type of the current period in the alarm data and the linkage data into an input layer of the linkage sequence sub-model so as to obtain third conversion data after the second weight matrix conversion;
and carrying out neuron combination on the first conversion data, the second conversion data and the third conversion data in the hidden layer to obtain the time-space alarm information of the current period.
Considering that the acquired alarm data and linkage data mainly aim at time, space and linkage, the fire alarm identification model comprises three submodels, namely a time sequence submodel, a space sequence submodel and a linkage sequence submodel, and respectively processes alarm time, alarm position, alarm type and linkage data.
Specifically, the first weight matrix is generated based on three dimensions, namely, a proximity relationship, a periodic relationship and a trend relationship. The proximity relation represents a time interval of reporting time of two adjacent alarm data, for example, a 16:00 temperature detector sends alarm data, a 16:01 smoke detector sends alarm data, and the time interval is one minute. The periodic relation represents the interval relation of periodic reporting of the alarm data, and fixed dates and fixed interval days of each month. Considering that the fire alarm system can be operated and maintained in a preset period, namely, the operation and maintenance personnel can simulate the occurrence of a fire and further test whether the fire alarm system works normally. Therefore, the periodic relationship needs to be considered in the time sequence submodel to assist in confirming whether the current fire alarm is artificially set or actually occurs. The trend relation represents the alarm time interval trend judged based on the fire spreading trend, and the server predicts the trend of fire development according to the received alarm data.
The second weight matrix is generated based on three dimensions, namely a topological relation, an explicit relation and an implicit relation. And the topological relation representation deduces the spatial relation among all the alarm devices of the whole area according to the position information. And determining the current position where the fire is possible to happen according to the serial number of the fire alarm system, and further determining the spatial relationship among all current devices for sending alarm data. Explicit relationships characterize the exact spatial relationships derived from the location information, as in a campus, a building, a floor, and a room. The position of the detector is determined according to the serial number, and the room number of a room on a certain floor in a certain building of a certain park can be specified. The implicit relationship represents a spatial relationship deduced according to the position information, and if the spatial relationship is an upper-lower layer relationship, a left-right adjacent relationship.
And converting the alarm time of the current period and the space-time alarm data of the previous period through a first weight matrix to obtain first conversion data. And converting the alarm position of the current period through a second weight matrix to obtain second conversion data, converting the alarm type of the current period and the linkage data of the current period through the second weight matrix to obtain third conversion data, and carrying out neuron combination on the first conversion data, the second conversion data and the third conversion data to finally obtain the space-time alarm information of the current period.
And the subsequent time-space alarm information of the current period is also combined with the alarm time of the next period, so that the time-space alarm information of the next period is output.
The time-space alarm information of the current period is circularly generated in the time-space alarm information of the next period, and meanwhile, the alarm time, the alarm position, the alarm type and the linkage data are processed on the basis of the weight matrix generated by multiple dimensions, so that the fire alarm identification model can more accurately output the time-space alarm information.
It should be noted that the combination method adopted in the present application is based on the LSTM-RNN (Long Short-Term Memory-secure neural network) technology.
FIG. 4 is a schematic diagram of a fire alarm identification system according to the present invention; the method comprises the following steps:
an obtaining unit 41, configured to obtain alarm data sent by a fire alarm system, where the alarm data includes alarm time, alarm position, and alarm type; acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system;
the input unit 42 is used for inputting alarm data and linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-short term memory recurrent neural network, so as to obtain space-time alarm information;
and the generating unit 43 is used for generating a corresponding fire alarm grade according to the space-time alarm information.
Please refer to the above embodiments for the introduction of the fire alarm identification system provided in the present application, which will not be described herein again.
FIG. 5 is a schematic diagram of a fire system according to the present invention; the fire alarm system comprises the fire alarm recognition system 1, and further comprises a fire alarm system 2 and a fire-fighting linkage control system 3.
For the introduction of the fire system provided in the present application, please refer to the above embodiments, which are not described herein.
FIG. 6 is a schematic structural diagram of a fire alarm recognition device according to the present invention; the method comprises the following steps:
a memory 61 for storing a computer program;
a processor 62 for implementing the steps of the above-described fire alarm identification method when executing a computer program.
Please refer to the above embodiments for the introduction of the fire alarm recognition device provided in the present application, which will not be described herein.
The invention also provides a server which comprises the fire alarm recognition device.
Please refer to the above embodiments for the introduction of the server provided in the present application, which is not described herein again.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
It is further noted that, in the present specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. A fire alarm identification method, comprising:
acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises alarm time, alarm position and alarm type;
acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system;
inputting the alarm data and the linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-short term memory cyclic neural network to obtain space-time alarm information;
and generating a corresponding fire alarm grade according to the space-time alarm information.
2. The fire alarm recognition method of claim 1, wherein the fire alarm system includes a smoke detector, a temperature detector, a flame detector, a manual alarm button, and a hydrant alarm button;
acquiring alarm data sent by a fire alarm system, wherein the alarm data comprises:
receiving alarm data sent by the smoke detector, the temperature detector, the flame detector, the manual alarm button and the fire hydrant alarm button;
taking the time when the alarm data is received as the alarm time;
determining a serial number of the fire alarm system which sends the alarm data, and determining the alarm position according to the serial number and the corresponding relation between a preset serial number and the position;
determining the alarm type, wherein the alarm type comprises the type of a detector and/or a button which transmits alarm data in the fire alarm system.
3. A fire alarm identification method according to claim 1, wherein the fire-fighting coordinated control system includes an automatic water-spraying fire-extinguishing system, a fire-fighting water supply system, a smoke-preventing and exhausting system, a fire-preventing partition system, and the like;
obtain the linkage data that fire control linkage control system sent, include:
and acquiring the type of the fire-fighting linkage control system for sending the linkage data.
4. A fire alarm recognition method according to claim 1, wherein the spatiotemporal alarm information is a probability of occurrence of a fire;
generating a corresponding fire alarm grade according to the time-space alarm information, comprising:
and determining fire alarm classification levels according to the preset probability range where the space-time alarm information is located, wherein the fire alarm classification levels corresponding to different preset probability ranges are different.
5. The fire alarm recognition method of claim 1, after generating the corresponding fire alarm level based on the spatio-temporal alarm information, further comprising:
and executing a preset alarm mode corresponding to the fire alarm level according to the fire alarms of different levels.
6. The fire alarm recognition method according to any one of claims 1 to 5, wherein the fire alarm recognition model includes a time series sub-model, a space series sub-model, and a linkage series sub-model;
inputting the alarm data and the linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-term and short-term memory recurrent neural network to obtain space-time alarm information, wherein the space-time alarm information comprises the following steps:
inputting the alarm time of the current period and the space-time alarm information of the previous period in the alarm data into an input layer of the time sequence submodel so as to obtain first conversion data after first weight matrix conversion;
inputting the alarm position of the current period in the alarm data to an input layer of the space sequence sub-model so as to obtain second conversion data after second weight matrix conversion;
inputting the alarm type of the current period in the alarm data and the linkage data into an input layer of the linkage sequence sub-model so as to obtain third conversion data after the second weight matrix conversion;
and carrying out neuron combination on the first conversion data, the second conversion data and the third conversion data in a hidden layer to obtain the time-space alarm information of the current period.
7. A fire alarm identification system, comprising:
the fire alarm system comprises an acquisition unit, a processing unit and a control unit, wherein the acquisition unit is used for acquiring alarm data sent by the fire alarm system, and the alarm data comprises alarm time, alarm position and alarm type; acquiring linkage data sent by a fire-fighting linkage control system, wherein the linkage data comprises the type of the fire-fighting linkage control system;
the input unit is used for inputting the alarm data and the linkage data into a fire alarm recognition model which is trained in advance and constructed by using a long-term and short-term memory cyclic neural network, so as to obtain space-time alarm information;
and the generating unit is used for generating a corresponding fire alarm grade according to the space-time alarm information.
8. A fire alarm system comprising the fire alarm recognition system of claim 7, and further comprising a fire alarm system and a fire-fighting coordinated control system.
9. A fire alarm identification device, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the fire alarm identification method according to any of claims 1 to 6 when executing the computer program.
10. A server, characterized by comprising the fire alarm identifying device according to claim 9.
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| CN202210621610.8A Pending CN114937338A (en) | 2022-06-02 | 2022-06-02 | Fire alarm identification method and related components |
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| JPH08329378A (en) * | 1995-05-29 | 1996-12-13 | Shimizu Corp | Disaster prevention information processor |
| CA2605060A1 (en) * | 2006-10-05 | 2008-04-05 | Christopher M. Campion, Jr. | Method and apparatus for authenticated on-site testing, imspection, servicing and control of life-safety equipment and reporting of same using a remote accessory |
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