CN107230329B - Fire detector calibration method, device and equipment - Google Patents
Fire detector calibration method, device and equipment Download PDFInfo
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- CN107230329B CN107230329B CN201710453320.6A CN201710453320A CN107230329B CN 107230329 B CN107230329 B CN 107230329B CN 201710453320 A CN201710453320 A CN 201710453320A CN 107230329 B CN107230329 B CN 107230329B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/18—Prevention or correction of operating errors
- G08B29/20—Calibration, including self-calibrating arrangements
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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
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Abstract
The invention provides a calibration method of a fire detector, which comprises the following steps: acquiring environmental parameters corresponding to the installation position of the fire detector; determining an alarm threshold corresponding to the fire detector according to the corresponding relation between the preset environmental parameters and the alarm threshold of the fire detector; and calibrating the fire detector according to the alarm threshold value. Because the calibration operation of the fire detector can be automatically completed, the fire detector is not required to be placed in a specific smoke environment for calibration, the operation is simpler, the calibration can be carried out according to a specific scene environment, and the calibration accuracy is higher.
Description
Technical Field
The invention belongs to the field of fire detection, and particularly relates to a calibration method, a calibration device and calibration equipment for a fire detector.
Background
The fire detector is a device for detecting the scene and finding out the fire in the fire-fighting automatic fire alarm system. The fire detector converts the characteristic physical quantity of fire, such as temperature, smoke, gas and radiation light intensity, into an electric signal and immediately acts to send an alarm signal to the fire alarm controller. The fire detector for collecting and analyzing the smoke in the scene has better sensitivity and lower cost, and is widely applied.
In the use process of the fire detector, the sensitivity of the fire detector is changed due to the influence of installation environment or environmental pollution factors. In order to avoid false alarm caused by the sensitivity change of the fire detector, the fire detector is generally required to be calibrated. The calibration operation of the existing fire detector is generally to uniformly set the fire detector in a smoke box, the smoke concentration in the smoke box is a constant value, after a period of time, the smoke concentration in a detector labyrinth is the same as the smoke concentration in the smoke box, the detector detects that the smoke concentration value is in a stable state, and records the current concentration value as the alarm value of the detector. Although the calibrated fire detector can obtain more universal flexibility, the calibration operation is troublesome, and the requirements of sensitivity differentiation of installation scenes or positions cannot be effectively met.
Disclosure of Invention
In view of this, embodiments of the present invention provide a calibration method, an apparatus, and a device for a fire detector, so as to solve the problems that the operation of the fire detector is troublesome and the sensitivity differentiation requirement of an installation scene or a location cannot be effectively met when the fire detector in the prior art is calibrated.
The first aspect of the embodiments of the present invention provides a calibration method for a fire detector, which is characterized in that the calibration method for a fire detector includes:
acquiring environmental parameters corresponding to the installation position of the fire detector;
determining an alarm threshold corresponding to the fire detector according to the corresponding relation between the preset environmental parameters and the alarm threshold of the fire detector;
and calibrating the fire detector according to the alarm threshold value.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the step of acquiring an environmental parameter corresponding to an installation location of the fire detector includes:
acquiring the installation position of the fire detector;
and determining one or more of a gas temperature value, a gas pressure value, a dryness value, a vibration intensity value or a magnetic field intensity value corresponding to the installation position of the fire detector according to the installation position.
With reference to the first aspect or the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, before the step of determining the alarm threshold corresponding to the fire detector according to the preset correspondence between the environmental parameter and the alarm threshold of the fire detector, the method further includes:
acquiring statistical data of alarm thresholds corresponding to various environmental parameters under preset smoke concentration when the environmental parameters are different in value;
and training to obtain a neural network model comprising the corresponding relation between the environmental parameters and the alarm threshold value by taking the various environmental parameters and the alarm threshold value as neural network nodes according to the statistical data.
With reference to the first aspect or the first possible implementation manner of the first aspect, in a third possible implementation manner of the first aspect, after the step of calibrating the fire detector according to the alarm threshold, the method further includes:
counting to obtain a periodic variation curve of an alarm threshold corresponding to the installation position of the fire detector;
and according to the counted periodic variation curve of the alarm threshold value, carrying out fire monitoring on the field environment.
With reference to the first aspect, in a fourth possible implementation manner of the first aspect, the alarm threshold is a concentration threshold of particles, the fire detector includes a darkroom, and a camera and a light source that are disposed in the darkroom, the camera acquires an image of a light beam emitted by the light source, identifies a type and a concentration of scattered particles in the image, and determines whether an abnormality occurs according to a comparison between the concentration of the particles and the concentration threshold of the particles.
In a second aspect, an embodiment of the present invention provides a calibration apparatus for a fire detector, where the calibration apparatus for a fire detector includes:
the environment parameter acquisition unit is used for acquiring environment parameters corresponding to the installation position of the fire detector;
the alarm threshold value determining unit is used for determining an alarm threshold value corresponding to the fire detector according to the corresponding relation between the preset environment parameter and the alarm threshold value of the fire detector;
and the calibration unit is used for calibrating the fire detector according to the alarm threshold value.
With reference to the second aspect, in a first possible implementation manner of the second aspect, the environment parameter obtaining unit includes:
an installation position acquisition subunit for acquiring an installation position of the fire detector;
and the parameter determining subunit is used for determining one or more of a gas temperature value, a gas pressure value, a dryness value, a vibration strength value or a magnetic field strength value corresponding to the installation position of the fire detector according to the installation position.
With reference to the second aspect or the first possible implementation manner of the second aspect, in a second possible implementation manner of the second aspect, the apparatus further includes:
the device comprises a statistical data acquisition unit, a data processing unit and a data processing unit, wherein the statistical data acquisition unit is used for acquiring statistical data of alarm thresholds corresponding to various environmental parameters under preset smoke concentration when the environmental parameters are different in value;
and the training unit is used for training to obtain a neural network model comprising the corresponding relation between the environmental parameters and the alarm threshold value by taking the various environmental parameters and the alarm threshold value as neural network nodes according to the statistical data.
In a third aspect, an embodiment of the present invention provides a calibration apparatus for a fire detector, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor executes the computer program to implement the steps of the calibration method for a fire detector according to any one of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium, which stores a computer program, wherein the computer program is configured to, when executed by a processor, implement the steps of the calibration method for a fire detector according to any one of the first aspect.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: the method comprises the steps of obtaining an environmental parameter corresponding to the installation position of the fire detector, finding an alarm threshold corresponding to the fire detector according to the corresponding relation between a preset environmental parameter and the alarm threshold of the fire detector, and calibrating the fire detector through the alarm threshold, so that the calibration operation of the fire detector can be automatically completed without being placed in a specific smoke environment for calibration, the operation is simpler, the calibration can be carried out according to a specific scene environment, and the calibration accuracy is higher.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions 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 based on these drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a calibration method for a fire detector according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating an interaction flow of a calibration method for a fire detector according to another embodiment of the present invention;
FIG. 3 is a flowchart of an implementation of a calibration method for a fire detector according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a calibration apparatus for a fire detector provided in an embodiment of the present invention;
fig. 5 is a schematic diagram of a calibration device of a fire detector according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
Fig. 1 is a flow chart of a method for calibrating a fire detector according to an embodiment of the present invention, which is detailed as follows:
in step S101, an environmental parameter corresponding to the installation position of the fire detector is acquired.
Specifically, the fire detector can be a smoke detector, a temperature-sensitive detector, a flame detector and a special gas detector. Different fire detectors are concerned with different environmental parameters that affect the accuracy or alarm sensitivity of the fire detector. For a smoke sensor, the corresponding environmental parameter may include one or more of an air temperature value, an air pressure value, a dryness value, a vibration intensity value, or a magnetic field intensity value in the environment of the installation location of the fire detector.
Wherein, the higher the temperature value under the environment of the installation position of the fire detector is, the more water vapor molecules are likely to be included in the air, and the more colloid substances are formed with the water vapor molecules. The air pressure value under the environment of the installation position of the fire detector can influence the mobility of smoke and dust, and the better the mobility is, the more sensitive the sensitivity to the environment of the installation position is. The dryness of the environment in which the fire detector is installed can affect the density of airborne dust or other particles, the drier the air, the greater the number of airborne particles. In addition, the vibration intensity and the magnetic field intensity in the environment of the installation position of the fire detector can both influence the quantity and the type of particles in the air. Therefore, different environmental parameters lead the fire detector to generate different calibration results.
The acquiring of the environmental parameter corresponding to the installation position of the fire detector may include various manners. Wherein, a sensor corresponding to the required environmental parameter can be arranged at the installation position. For example, the air pressure value can be acquired by installing an air pressure sensor, the air temperature value can be acquired by installing a temperature sensor, the dryness value can be acquired by a humidity sensor, and the vibration sensing sensor and the magnetic field detector can be respectively installed for acquiring vibration strength, magnetic field strength and the like.
Of course, the environmental parameters corresponding to the installation position can be inquired in the server by reporting the installation position of the fire detector. The environmental parameters stored in the server are acquired by other satellite equipment, weather servers and other equipment.
In step S102, an alarm threshold corresponding to the fire detector is determined according to a preset correspondence between the environmental parameter and the alarm threshold of the fire detector.
After the environmental parameters corresponding to the installation positions of the fire detectors are obtained, the alarm threshold values of the fire detectors corresponding to the data can be searched according to the numerical values of the environmental parameters. When the environmental parameters comprise a plurality of environmental parameters, the normal numerical value range corresponding to each environmental parameter can be set, and when the numerical value of the environmental parameter belongs to the corresponding normal numerical value range, the matching or searching of the environmental parameter can be avoided, so that the environmental parameter of the alarm threshold of the fire detector can be focused and searched according to the abnormal environmental parameter or the influence, and the searching and matching speed and efficiency can be improved.
For example, the environmental parameter a1 and the environmental parameter a2 are determined by comparison to be two parameters detected in the current fire detector and exceeding the normal numerical range of the parameters, and the alarm threshold X1 matched with the parameters can be found by the numerical value of the environmental parameter a1 and the numerical value of the environmental parameter a2 without comparing and searching other environmental parameters one by one, which is beneficial to improving the calibration efficiency.
In step S103, the fire detector is calibrated according to the alarm threshold.
And performing calibration operation according to the alarm threshold corresponding to the fire detector searched in the step S102, that is, setting the alarm threshold as a calibration value of the fire detector at the current position, and performing fire monitoring at the current position.
For example, for a smoke detector, the alarm threshold is a concentration threshold of particles, the fire detector comprises a darkroom, and a camera and a light source which are arranged in the darkroom, the camera acquires an image of a light beam emitted by the light source, identifies the type and concentration of the scattered particles in the image, and determines whether an abnormality occurs according to the comparison between the concentration of the particles and the concentration threshold of the particles.
The method comprises the steps of obtaining an environmental parameter corresponding to the installation position of the fire detector, finding an alarm threshold corresponding to the fire detector according to the corresponding relation between a preset environmental parameter and the alarm threshold of the fire detector, and calibrating the fire detector through the alarm threshold, so that the calibration operation of the fire detector can be automatically completed without being placed in a specific smoke environment for calibration, the operation is simpler, the calibration can be carried out according to a specific scene environment, and the calibration accuracy is higher.
Fig. 2 is a flowchart of an implementation of a calibration method for a fire detector according to an embodiment of the present invention, which is detailed as follows:
in step S201, statistical data of alarm thresholds corresponding to various environmental parameters at different values under a predetermined smoke concentration is obtained.
The statistical data can be obtained by statistics in an experimental environment. For example, an experimental scenario may be set in which the value of any one of the environmental parameters may be varied to obtain an alarm threshold value detected by the fire detector at a predetermined smoke concentration (standard alarm smoke concentration). The alarm threshold may be the concentration of a particular particle in the smoke, etc.
Of course, the actual alarm data may be counted, and the corresponding alarm threshold value may be determined according to the parameter value of the environmental parameter when the alarm occurs.
In step S202, according to the statistical data, the plurality of environmental parameters and the alarm threshold are used as neural network nodes, and a neural network model including a corresponding relationship between the environmental parameters and the alarm threshold is obtained through training.
After a large amount of sample data is obtained, the sample data can be substituted into a preset neural network model, the environment parameters are learned through the neural network model, and the corresponding relations between the numerical values of different environment parameters and different early warning threshold values are obtained.
In step S203, an environmental parameter corresponding to the installation position of the fire detector is acquired.
In step S204, an alarm threshold corresponding to the fire detector is determined according to a preset correspondence between the environmental parameter and the alarm threshold of the fire detector.
In step S205, the fire detector is calibrated according to the alarm threshold.
Steps S203-S205 are substantially the same as steps S101-S103 in fig. 1.
Fig. 2 introduces a method for establishing a corresponding relationship between the value of the environmental parameter and the alarm and early warning on the basis of fig. 1, and a more and more accurate corresponding relationship can be obtained through a neural network learning method, so that a more accurate fire monitoring message can be provided.
Fig. 3 is a flow chart of implementing a calibration method for a fire detector according to another embodiment of the present invention, which is detailed as follows:
in step S301, an environmental parameter corresponding to the installation position of the fire detector is acquired.
In step S302, an alarm threshold corresponding to the fire detector is determined according to a preset correspondence between the environmental parameter and the alarm threshold of the fire detector.
In step S303, the fire detector is calibrated according to the alarm threshold.
In step S304, a periodic variation curve of the alarm threshold corresponding to the installation position of the fire detector is obtained through statistics.
Specifically, the environmental parameters may have a certain variation period, for example, the environmental parameters such as air temperature, air pressure, dryness, etc. may vary with the period of one day, one year, etc. Therefore, the obtained alarm threshold value curve also has certain periodicity, and the alarm threshold value curve in a future period of time can be predicted according to the periodic curve.
In step S305, a fire is monitored in the field environment based on the counted periodic variation curve of the alarm threshold.
According to the predicted alarm threshold curve, the abnormity in the environment can be automatically monitored, when the monitored abnormal value of the site exceeds the alarm threshold, the environmental parameters of the site can be obtained, the alarm threshold is confirmed again, and if the abnormal value of the current scene is confirmed to exceed the alarm threshold, the alarm is given out. Of course, the alarm may be issued directly when the abnormal value in the field exceeds the predicted alarm threshold.
Fig. 3 can reduce the calculation work of the alarm threshold value by a prediction mode, which is beneficial to reducing the consumption of system resources.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 4 is a schematic structural diagram of a calibration device of a fire detector according to an embodiment of the present invention, which is detailed as follows:
the calibration device of the fire detector comprises:
an environmental parameter obtaining unit 401, configured to obtain an environmental parameter corresponding to an installation location of the fire detector;
an alarm threshold determining unit 402, configured to determine an alarm threshold corresponding to a fire detector according to a preset correspondence between the environmental parameter and the alarm threshold of the fire detector;
a calibration unit 403, configured to calibrate the fire detector according to the alarm threshold.
Preferably, the environment parameter acquiring unit includes:
an installation position acquisition subunit for acquiring an installation position of the fire detector;
and the parameter determining subunit is used for determining one or more of a gas temperature value, a gas pressure value, a dryness value, a vibration strength value or a magnetic field strength value corresponding to the installation position of the fire detector according to the installation position.
Preferably, the apparatus further comprises:
the device comprises a statistical data acquisition unit, a data processing unit and a data processing unit, wherein the statistical data acquisition unit is used for acquiring statistical data of alarm thresholds corresponding to various environmental parameters under preset smoke concentration when the environmental parameters are different in value;
and the training unit is used for training to obtain a neural network model comprising the corresponding relation between the environmental parameters and the alarm threshold value by taking the various environmental parameters and the alarm threshold value as neural network nodes according to the statistical data.
The calibration arrangement of the fire detector shown in fig. 4 corresponds to the calibration method of the fire detector shown in fig. 1-3.
Fig. 5 is a schematic diagram of a calibration apparatus for a fire detector according to an embodiment of the present invention. As shown in fig. 5, the calibration device 5 of the fire detector of this embodiment includes: a processor 50, a memory 51 and a computer program 52 stored in said memory 51 and operable on said processor 50, such as a calibration program for a fire detector. The processor 50, when executing the computer program 52, implements the steps in the above-described embodiments of the calibration method for each fire detector, such as the steps 101 to 104 shown in fig. 1. Alternatively, the processor 50, when executing the computer program 52, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 51 to 54 shown in fig. 5.
Illustratively, the computer program 52 may be partitioned into one or more modules/units that are stored in the memory 51 and executed by the processor 50 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions describing the execution of the computer program 52 in the calibration device 5 of the fire detector. For example, the computer program 52 may be divided into an environmental parameter obtaining unit, an alarm threshold determining unit and a calibrating unit, and each unit specifically functions as follows:
the environment parameter acquisition unit is used for acquiring environment parameters corresponding to the installation position of the fire detector;
the alarm threshold value determining unit is used for determining an alarm threshold value corresponding to the fire detector according to the corresponding relation between the preset environment parameter and the alarm threshold value of the fire detector;
and the calibration unit is used for calibrating the fire detector according to the alarm threshold value.
The calibration device 5 of the fire detector may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The calibration device of the fire detector may include, but is not limited to, a processor 50 and a memory 51. It will be appreciated by those skilled in the art that fig. 5 is merely an example of the calibration device 5 of the fire detector, and does not constitute a limitation of the calibration device 5 of the fire detector, and may comprise more or less components than those shown, or some components in combination, or different components, for example, the calibration device of the fire detector may also comprise input-output devices, network access devices, buses, etc.
The Processor 50 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 51 may be an internal memory unit of the calibration device 5 of the fire detector, such as a hard disk or a memory of the calibration device 5 of the fire detector. The memory 51 may also be an external storage device of the calibration device 5 of the fire detector, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are equipped on the calibration device 5 of the fire detector. Further, the memory 51 may also comprise both an internal memory unit and an external memory device of the calibration device 5 of the fire detector. The memory 51 is used for storing the computer program and other programs and data required by the calibration device of the fire detector. The memory 51 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention 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 solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (7)
1. A calibration method of a fire detector is characterized by comprising the following steps:
acquiring environmental parameters corresponding to the installation position of the fire detector;
determining an alarm threshold corresponding to the fire detector according to a preset corresponding relation between the environmental parameter and the alarm threshold of the fire detector, specifically: when the environment parameters are multiple, determining the alarm threshold value according to the abnormal environment parameters;
calibrating the fire detector according to the alarm threshold value;
counting to obtain a periodic variation curve of an alarm threshold corresponding to the installation position of the fire detector;
according to the counted periodic variation curve of the alarm threshold value, carrying out fire monitoring on the site environment;
the step of acquiring the environmental parameters corresponding to the installation position of the fire detector comprises the following steps:
acquiring the installation position of the fire detector;
and determining one or more of a gas temperature value, a gas pressure value, a dryness value, a vibration intensity value or a magnetic field intensity value corresponding to the installation position of the fire detector according to the installation position.
2. The method for calibrating a fire detector according to claim 1, wherein before the step of determining the alarm threshold corresponding to the fire detector according to the preset correspondence between the environmental parameter and the alarm threshold of the fire detector, the method further comprises:
acquiring statistical data of alarm thresholds corresponding to various environmental parameters under preset smoke concentration when the environmental parameters are different in value;
and training to obtain a neural network model comprising the corresponding relation between the environmental parameters and the alarm threshold value by taking the various environmental parameters and the alarm threshold value as neural network nodes according to the statistical data.
3. The method for calibrating a fire detector according to claim 1, wherein the alarm threshold is a particle concentration threshold, the fire detector comprises a darkroom, and a camera and a light source arranged in the darkroom, the camera acquires an image of a light beam emitted by the light source, identifies the type and concentration of scattered particles in the image, and determines whether an abnormality occurs according to the comparison between the particle concentration and the particle concentration threshold.
4. A calibration device for a fire detector is characterized in that the calibration device for the fire detector comprises:
the environment parameter acquisition unit is used for acquiring environment parameters corresponding to the installation position of the fire detector;
an alarm threshold determining unit, configured to determine, according to a preset correspondence between the environmental parameter and an alarm threshold of a fire detector, an alarm threshold corresponding to the fire detector, where the alarm threshold determining unit is specifically: when the environment parameters are multiple, determining the alarm threshold value according to the abnormal environment parameters;
the calibration unit is used for calibrating the fire detector according to the alarm threshold value;
the statistical unit is used for obtaining a periodic variation curve of an alarm threshold value corresponding to the installation position of the fire detector through statistics;
the fire monitoring unit is used for carrying out fire monitoring on the site environment according to the counted periodic variation curve of the alarm threshold value;
the environment parameter acquiring unit includes:
an installation position acquisition subunit for acquiring an installation position of the fire detector;
and the parameter determining subunit is used for determining one or more of a gas temperature value, a gas pressure value, a dryness value, a vibration strength value or a magnetic field strength value corresponding to the installation position of the fire detector according to the installation position.
5. A calibration arrangement for a fire detector according to claim 4, characterised in that the arrangement further comprises:
the device comprises a statistical data acquisition unit, a data processing unit and a data processing unit, wherein the statistical data acquisition unit is used for acquiring statistical data of alarm thresholds corresponding to various environmental parameters under preset smoke concentration when the environmental parameters are different in value;
and the training unit is used for training to obtain a neural network model comprising the corresponding relation between the environmental parameters and the alarm threshold value by taking the various environmental parameters and the alarm threshold value as neural network nodes according to the statistical data.
6. Calibration arrangement for a fire detector, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the steps of a calibration method for a fire detector according to any of claims 1 to 3.
7. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a method for calibrating a fire detector according to any one of claims 1 to 3.
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| JP7093175B2 (en) * | 2017-11-27 | 2022-06-29 | ホーチキ株式会社 | Fire alarm |
| CN108389359B (en) * | 2018-04-10 | 2020-03-24 | 中国矿业大学 | Deep learning-based urban fire alarm method |
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