CN115206047A - Photovoltaic module area fire prevention alarm method and system - Google Patents
Photovoltaic module area fire prevention alarm method and system Download PDFInfo
- Publication number
- CN115206047A CN115206047A CN202210565973.4A CN202210565973A CN115206047A CN 115206047 A CN115206047 A CN 115206047A CN 202210565973 A CN202210565973 A CN 202210565973A CN 115206047 A CN115206047 A CN 115206047A
- Authority
- CN
- China
- Prior art keywords
- fire
- processed
- region
- image information
- determining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 32
- 230000002265 prevention Effects 0.000 title claims abstract description 18
- 238000011161 development Methods 0.000 claims abstract description 59
- 230000008859 change Effects 0.000 claims abstract description 47
- 230000007480 spreading Effects 0.000 claims abstract description 36
- 238000013507 mapping Methods 0.000 claims abstract description 25
- 230000009471 action Effects 0.000 claims abstract description 11
- 239000013618 particulate matter Substances 0.000 claims description 48
- 239000000779 smoke Substances 0.000 claims description 48
- 238000012549 training Methods 0.000 claims description 12
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000010801 machine learning Methods 0.000 claims description 6
- 230000006399 behavior Effects 0.000 description 4
- 230000000007 visual effect Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 239000000463 material Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 229910052710 silicon Inorganic materials 0.000 description 1
- 239000010703 silicon Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 244000007214 tumbleweed Species 0.000 description 1
- 235000006422 tumbleweed Nutrition 0.000 description 1
Images
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
Abstract
The invention discloses a photovoltaic module area fire prevention alarm method, which comprises the following steps: the method comprises the steps of obtaining the concentration of particulate matters in the air of a photovoltaic module region, determining a region to be processed based on the concentration of the particulate matters, collecting defogging image information in the region to be processed, obtaining a first temperature signal and a second temperature signal in the region to be processed, obtaining the temperature change rate in the region to be processed according to the first temperature signal and the second temperature signal, building a fire development model based on the defogging image information and the temperature change rate, determining fire spreading trend information in the region to be processed based on the fire development model, obtaining the fire spreading trend information, and taking an alarm action. According to the method and the device, the fire spreading trend information is determined according to the mapping relation between the constructed fire development model and the preset fire model, the hazards caused by fire outburst and randomness can be effectively dealt with, the economic loss is greatly reduced, and meanwhile, the specific fire fighting measures can be made by fire fighting personnel.
Description
Technical Field
The invention relates to the technical field of fireproof alarm, in particular to a method and a system for fireproof alarm of a photovoltaic module area.
Background
With the development and progress of science and technology in China, new energy power generation becomes a future development trend, wherein a photovoltaic module is a power generation device which can generate direct current after being exposed to the sun, is composed of a thin solid photovoltaic cell which is almost made of semiconductor materials (such as silicon), and has the characteristics of no pollution and high power generation efficiency. However, the tumbleweed is easy to gather near the purse seine, the fire disaster is very easy to happen in hot summer, the equipment in the photovoltaic module area is damaged, the fence is easy to crush, and the sending efficiency of the photovoltaic module is seriously influenced.
At present, many areas are provided with fire alarm devices, and when smoke sensors are arranged and the smoke concentration in the air is greater than the standard concentration, the alarm is controlled to give an alarm to remind workers to extinguish a fire. In the prior art, the fire condition cannot be analyzed according to factors such as the burning condition of the fire, the spreading speed of the fire and the like, so that the unexpected consequences can be caused by the outburst and randomness brought by the fire.
Therefore, how to provide a fire prevention alarm method capable of predicting fire conditions and preventing sudden and random fire from bringing great harm to photovoltaic module areas is a technical problem to be solved at present.
Disclosure of Invention
The embodiment of the invention provides a photovoltaic module regional fire prevention alarm method and system, which are used for predicting fire conditions by removing smoke image information and a fire temperature change rate so as to solve the technical problem that the prior art cannot prevent the outburst and randomness of fire according to the real-time fire conditions to cause great harm.
In some embodiments of the application, a region to be treated is determined based on particulate matter concentration by acquiring the particulate matter concentration in the air of a photovoltaic module region, and if the particulate matter concentration is greater than or equal to the particulate matter concentration threshold, position coordinates where a corresponding smoke sensor is located are acquired, and the region to be treated is determined according to the position coordinates. In this application, acquire the particulate matter concentration in photovoltaic module area through smoke transducer, when detecting particulate matter concentration and being higher than the threshold value, corresponding smoke transducer is arrived to accurate location this moment, and the grasp that can be accurate catches fire the place, has saved fire prevention alarm time in the very big degree, can in time control the intensity of a fire.
In some embodiments of the application, defogging image information in an area to be processed is collected in real time, and initial image information in the area to be processed is obtained, wherein the initial image information is image information containing smoke; acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information; and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information. In this application, when fixing a position the place of catching fire, open image acquisition device this moment, can gather the fire behavior image information of the place of catching fire in real time, because can produce dense smog when catching fire, the image information who acquires this moment is unclear, remove the smog step in this application, can clearly obtain the image information of catching fire after getting rid of smog, can provide the clear image of the place of catching fire for staff or fire fighter, the fire fighter has made things convenient for relevant fire fighting measures in the very big degree, the proruption nature of the fire has been avoided effectively and the unexpected harm that brings, economic loss has been avoided in the very big degree.
In some embodiments of the application, a fire development model is constructed based on the defogged image information and the temperature change rate, and fire spread trend information in the region to be processed is determined based on the fire development model; and acquiring fire spreading trend information in real time, and taking an alarm action. Receiving the constructed fire development model and calling a preset fire model prestored in a database; and determining fire spread trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model. In this application, through the condition of a fire development model that will found in real time, confirm the information that stretchs of the intensity of a fire with the mapping relation between the pre-stored preliminary condition of a fire model, can in time carry out visual control to the point of catching a fire through observing the information that stretchs of the intensity of a fire, prevent the too big equipment in the damage area of intensity of a fire, through predicting the condition of a fire of the environment of locating at present, when predicting the condition of a fire and taking place the change, in time carry out the condition of a fire and remind, so that the fire fighter can in time make the counter measure.
In order to achieve the purpose, the invention provides a photovoltaic module regional fire prevention alarm method, which comprises the following steps:
the method comprises the steps of obtaining the concentration of particulate matters in the air of a photovoltaic module area, determining an area to be processed based on the concentration of the particulate matters, and collecting defogging image information in the area to be processed in real time;
acquiring a first temperature signal in the region to be processed, and acquiring a second temperature signal in the region to be processed within a preset time;
acquiring the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal;
constructing a fire development model based on the defogging image information and the temperature change rate, and determining fire spreading trend information in the region to be processed based on the fire development model;
and acquiring fire spreading trend information in real time, and taking an alarm action.
In some embodiments of the present application, when determining the region to be treated based on the particulate matter concentration, in particular:
judging and comparing the particulate matter concentration acquired in real time with a particulate matter concentration threshold value, and determining whether to determine a region to be processed according to a judgment result:
if the concentration of the particulate matters is greater than or equal to the threshold value of the concentration of the particulate matters, acquiring position coordinates of a corresponding smoke sensor, and determining a region to be processed according to the position coordinates;
and if the concentration of the particulate matters is less than the threshold value of the concentration of the particulate matters, determining the area to be treated.
In some embodiments of the present application, when acquiring the defogged image information in the to-be-processed area in real time, the specific steps are:
acquiring initial image information in the region to be processed, wherein the initial image information is image information containing smoke;
acquiring a plurality of appearance characteristic information of the initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information;
and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information.
In some embodiments of the present application, the calculation formula for obtaining the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal is:
wherein T is the temperature change rate, T 2 Is the second temperature signal, T 1 Is a first temperature signal.
In some embodiments of the present application, when determining the fire spreading tendency information in the to-be-processed area based on the fire development model, specifically, the determining step includes:
receiving the constructed fire development model and calling a preset fire model prestored in a database;
determining fire spreading trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model;
the preset fire model is obtained by training through image features of an image training set by using a machine learning algorithm.
In order to achieve the above object, the present invention further provides a photovoltaic module area fire alarm system, including:
the collection module is used for obtaining the concentration of particulate matters in the air of a photovoltaic module area, determining an area to be processed based on the concentration of the particulate matters, and collecting defogged image information in the area to be processed in real time;
the determining module is used for acquiring a first temperature signal in the area to be processed and acquiring a second temperature signal in the area to be processed within preset time;
acquiring the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal;
the generating module is used for constructing a fire development model based on the defogging image information and the temperature change rate and determining fire spread trend information in the region to be processed based on the fire development model;
and the alarm module is used for acquiring the fire spreading trend information in real time and taking an alarm action.
In some embodiments of the present application, in the acquisition module, when determining the region to be treated based on the particulate matter concentration, specifically:
judging and comparing the particulate matter concentration acquired in real time with a particulate matter concentration threshold, and determining whether to determine a region to be processed according to a judgment result:
if the concentration of the particulate matters is greater than or equal to the threshold value of the concentration of the particulate matters, acquiring position coordinates of a corresponding smoke sensor, and determining a region to be processed according to the position coordinates;
and if the particulate matter concentration is smaller than the particulate matter concentration threshold value, determining the region to be treated.
In some embodiments of the present application, in the acquisition module, when acquiring the defogged image information in the to-be-processed region in real time, the acquiring specifically includes:
acquiring initial image information in the region to be processed, wherein the initial image information is image information containing smoke;
acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information;
and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information.
In some embodiments of the present application, in the determining module, a calculation formula for obtaining the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal is as follows:
wherein T is the temperature change rate, T 2 Is the second temperature signal, T 1 Is a first temperature signal.
In some embodiments of the present application, in the generating module, when determining the fire spreading trend information in the to-be-processed area based on the fire development model, specifically:
receiving the constructed fire development model and calling a preset fire model prestored in a database;
determining fire spreading trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model;
the preset fire model is obtained by training through image features of an image training set by using a machine learning algorithm.
The invention provides a photovoltaic module area fire prevention alarm method and system, which have the following beneficial effects compared with the prior art:
the invention discloses a photovoltaic module area fire prevention alarm method, which comprises the following steps: the method comprises the steps of obtaining the concentration of particulate matters in the air of a photovoltaic module region, determining a region to be processed based on the concentration of the particulate matters, collecting defogging image information in the region to be processed, obtaining a first temperature signal and a second temperature signal in the region to be processed, obtaining the temperature change rate in the region to be processed according to the first temperature signal and the second temperature signal, building a fire development model based on the defogging image information and the temperature change rate, determining fire spreading trend information in the region to be processed based on the fire development model, obtaining the fire spreading trend information, and taking an alarm action. In the application, the fire place can be accurately mastered through the method, the fireproof alarm time is saved to a great extent, and the fire behavior can be mastered in time. The fire spreading trend information is determined according to the mapping relation between the constructed fire development model and the preset fire model, so that the damage caused by the outburst and randomness of the fire can be effectively dealt with, the economic loss is greatly reduced, and meanwhile, the specific fire fighting measures can be taken by fire fighting personnel.
Drawings
FIG. 1 is a schematic flow chart illustrating a method for alarming fire in a photovoltaic module area according to an embodiment of the present invention;
fig. 2 shows a schematic structural diagram of a photovoltaic module area fire alarm system in an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
In the description of the present application, it is to be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like indicate orientations or positional relationships based on those shown in the drawings, merely for convenience of description and simplicity of description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present application.
The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless otherwise specified.
In the description of the present application, it should be noted that unless otherwise explicitly stated or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in this application will be understood to be a specific case for those of ordinary skill in the art.
The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.
As shown in fig. 1, an embodiment of the invention discloses a photovoltaic module regional fire alarm method, which includes:
step S101, obtaining the concentration of particulate matters in the air of a photovoltaic module area, determining an area to be processed based on the concentration of the particulate matters, and collecting defogged image information in the area to be processed in real time;
step S102, acquiring a first temperature signal in the region to be processed, and acquiring a second temperature signal in the region to be processed within a preset time;
step S103, acquiring the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal;
step S104, constructing a fire development model based on the defogged image information and the temperature change rate, and determining fire spreading trend information in the region to be processed based on the fire development model;
and step S105, acquiring the fire spreading trend information in real time, and taking an alarm action.
In some embodiments of the present application, when determining the region to be treated based on the particulate matter concentration, in particular:
judging and comparing the particulate matter concentration acquired in real time with a particulate matter concentration threshold, and determining whether to determine a region to be processed according to a judgment result:
if the concentration of the particulate matters is greater than or equal to the threshold value of the concentration of the particulate matters, acquiring position coordinates of a corresponding smoke sensor, and determining a region to be processed according to the position coordinates;
and if the particulate matter concentration is smaller than the particulate matter concentration threshold value, determining the region to be treated.
It should be noted that, in order to pinpoint the photovoltaic module area fire spot, practice thrift the time of fighting a fire. In this application, be provided with a plurality of smoke transducer in the photovoltaic module area, every smoke transducer evenly distributed is in the photovoltaic module area, when smoke transducer acquires particulate matter concentration in real time, judge the relation between the particulate matter concentration and the threshold value that acquire, when particulate matter concentration is greater than the threshold value, this moment explain that there is the conflagration emergence, then corresponding smoke transducer is located to the automation, acquire the position coordinate of this smog sensing, and then confirm the place of catching fire, just be exactly the pending area, when particulate matter concentration is less than the threshold value, this moment explains that there is not the conflagration emergence, do not carry out any processing. In this application, acquire the particulate matter concentration in photovoltaic module area through smoke transducer, when detecting particulate matter concentration and be higher than the threshold value, corresponding smoke transducer is arrived to accurate location this moment, and the grasp that can be accurate catches fire the place, has saved fire prevention alarm time in the very big degree, can in time control the intensity of a fire.
In some embodiments of the present application, when acquiring the defogged image information in the to-be-processed region in real time, the specific steps are:
acquiring initial image information in the area to be processed, wherein the initial image information is image information containing smoke;
acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information;
and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information.
Note that, in order to obtain clear image information of the misfire point. In the application, when the fire point is determined, the initial image information of the fire point, namely the image information containing smoke, is acquired, when a fire actually breaks out, a large amount of smoke is generated, the smoke can cover the fire point, the fire can not be clearly seen through the image acquisition device in time, the image information containing the smoke needs to be subjected to defogging treatment, the appearance characteristic information of the initial image is acquired according to a preset defogging network, the generated characteristic image is mapped to an image grid, and clear image information is acquired. In the application, the fire catching image information after smoke is removed can be clearly obtained, clear images of fire catching places can be provided for working personnel or fire fighters, relevant fire fighting measures can be conveniently made for the fire fighters to the greatest extent, unpredictable harm caused by the outburst of fire is effectively avoided, and economic loss is avoided for the greatest extent.
In some embodiments of the present application, the calculation formula for obtaining the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal is:
wherein T is a temperature change rate, T 2 Is the second temperature signal, T 1 Is a first temperature signal.
It should be noted that, in order to accurately obtain the temperature change signal of the fire, the spread height of the fire is preliminarily predicted. And calculating the temperature change rate of the fire when the first temperature signal and the second temperature signal are obtained. If T2=120 and T1=100, the temperature change rate T is 120-100/100=0.2, and it should be understood that the temperature change rate T is only illustrated by way of example and is not particularly limited.
In some embodiments of the present application, when determining the fire spreading tendency information in the to-be-processed area based on the fire development model, specifically:
receiving the constructed fire development model and calling a preset fire model prestored in a database;
determining fire spreading trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model;
the preset fire model is obtained by training through image features of an image training set by using a machine learning algorithm.
It should be noted that, in order to better grasp the trend of fire behavior development, so that the firefighter can take countermeasures in time. In the application, a fire development model is constructed through the temperature change rate and the defogged image information acquired in real time, and the spreading condition of the fire is predicted through the mapping relation between the fire development model and a preset fire model, including but not limited to the spreading direction of the fire, the burning speed of the fire and the like, and is not limited herein. In this application, through the condition of a fire development model that will establish in real time, confirm the information that stretchs of the intensity of a fire with the mapping relation between the pre-stored preset condition of a fire model, can in time carry out visual control to the point of catching a fire through observing the information that stretchs of the intensity of a fire, prevent that the intensity of a fire from excessively destroying the equipment in the region, through predicting the condition of a fire of the environment of locating at present, when predicting the condition of a fire and taking place and change, in time carry out the condition of a fire and remind to the fire fighter can in time make the counter measure.
As shown in fig. 2, an embodiment of the present invention discloses a photovoltaic module regional fire alarm system, which includes:
the collection module is used for obtaining the concentration of particulate matters in the air of a photovoltaic module area, determining an area to be processed based on the concentration of the particulate matters, and collecting defogged image information in the area to be processed in real time;
the determining module is used for acquiring a first temperature signal in the area to be processed and acquiring a second temperature signal in the area to be processed within preset time;
acquiring the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal;
the generating module is used for constructing a fire development model based on the defogging image information and the temperature change rate and determining fire spreading trend information in the region to be processed based on the fire development model;
and the alarm module is used for acquiring the fire spreading trend information in real time and taking an alarm action.
In some embodiments of the present application, in the acquisition module, when determining the region to be treated based on the particulate matter concentration, specifically:
judging and comparing the particulate matter concentration acquired in real time with a particulate matter concentration threshold value, and determining whether to determine a region to be processed according to a judgment result:
if the concentration of the particulate matter is greater than or equal to the threshold value of the concentration of the particulate matter, acquiring position coordinates of the corresponding smoke sensor, and determining a region to be processed according to the position coordinates;
and if the particulate matter concentration is smaller than the particulate matter concentration threshold value, determining the region to be treated.
It should be noted that, in order to pinpoint the photovoltaic module area fire spot, practice thrift the time of fighting a fire. In the application, a plurality of smoke sensors are arranged in the photovoltaic module area, each smoke sensor is uniformly distributed in the photovoltaic module area, when the smoke sensors acquire the concentration of particulate matters in real time, the relation between the acquired concentration of the particulate matters and a threshold value is judged, when the concentration of the particulate matters is greater than the threshold value, a fire disaster happens, the smoke sensors are automatically positioned to the corresponding smoke sensors, the position coordinates of the smoke sensors are acquired, the fire disaster place is further determined, namely, the area to be processed is also determined, when the concentration of the particulate matters is less than the threshold value, no fire disaster happens to the smoke sensors, and no processing is carried out. In this application, acquire the particulate matter concentration in photovoltaic module area through smoke transducer, when detecting particulate matter concentration and being higher than the threshold value, corresponding smoke transducer is arrived to accurate location this moment, and the grasp that can be accurate catches fire the place, has saved fire prevention alarm time in the very big degree, can in time control the intensity of a fire.
In some embodiments of the present application, in the acquisition module, when acquiring the defogged image information in the to-be-processed area in real time, specifically:
acquiring initial image information in the region to be processed, wherein the initial image information is image information containing smoke;
acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information;
and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information.
Note that, in order to obtain clear image information of the misfire point. In the application, when the fire point is determined, the initial image information of the fire point, namely the image information containing smoke, is acquired, when a fire actually breaks out, a large amount of smoke is generated, the smoke can cover the fire point, the fire can not be clearly seen through the image acquisition device in time, the image information containing the smoke needs to be subjected to defogging treatment, the appearance characteristic information of the initial image is acquired according to a preset defogging network, the generated characteristic image is mapped to an image grid, and clear image information is acquired. In the application, the fire catching image information after smoke is removed can be clearly obtained, clear images of fire catching places can be provided for working personnel or fire fighters, relevant fire fighting measures can be conveniently made for the fire fighters to the greatest extent, unpredictable harm caused by the outburst of fire is effectively avoided, and economic loss is avoided for the greatest extent.
In some embodiments of the present application, in the determining module, the calculation formula for obtaining the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal is:
wherein T is the temperature change rate, T 2 Is the second temperature signal, T 1 Is a first temperature signal.
It should be noted that, in order to accurately obtain a temperature change signal of a fire, the spread height of the fire is preliminarily predicted. And calculating the temperature change rate of the fire when the first temperature signal and the second temperature signal are obtained. If T2=120 and T1=100, the temperature change rate T is 120-100/100=0.2, and it should be understood that the temperature change rate T is only illustrated by way of example and is not particularly limited.
In some embodiments of the present application, in the generating module, when determining the fire spreading tendency information in the to-be-processed area based on the fire development model, specifically:
receiving the constructed fire development model and calling a preset fire model prestored in a database;
determining fire spreading trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model;
the preset fire model is obtained by training through image features of an image training set by using a machine learning algorithm.
It should be noted that in order to better grasp the trend of fire development, so that the firefighters can take countermeasures in time. In the application, a fire development model is constructed through the temperature change rate and the defogged image information acquired in real time, and the spreading condition of the fire is predicted through the mapping relation between the fire development model and a preset fire model, including but not limited to the spreading direction of the fire, the burning speed of the fire and the like, and is not limited herein. In this application, through the condition of a fire development model that will establish in real time, confirm the information that stretchs of the intensity of a fire with the mapping relation between the pre-stored preset condition of a fire model, can in time carry out visual control to the point of catching a fire through observing the information that stretchs of the intensity of a fire, prevent that the intensity of a fire from excessively destroying the equipment in the region, through predicting the condition of a fire of the environment of locating at present, when predicting the condition of a fire to take place and change, in time carry out the condition of a fire and remind, so that the fire fighter can in time make the counter measure.
To sum up, the embodiment of the invention provides a photovoltaic module area fire prevention alarm method, which comprises the following steps: the method comprises the steps of obtaining the concentration of particulate matters in the air of a photovoltaic module region, determining a region to be processed based on the concentration of the particulate matters, collecting defogging image information in the region to be processed, obtaining a first temperature signal and a second temperature signal in the region to be processed, obtaining the temperature change rate in the region to be processed according to the first temperature signal and the second temperature signal, building a fire development model based on the defogging image information and the temperature change rate, determining fire spreading trend information in the region to be processed based on the fire development model, obtaining the fire spreading trend information, and taking an alarm action. In this application, the method in this application can be accurate grasp the place of catching fire, has saved fire prevention alarm time to a great extent, can in time control the intensity of a fire. The fire spreading trend information is determined according to the mapping relation between the constructed fire development model and the preset fire model, so that the hazards caused by the outburst and randomness of the fire can be effectively dealt with, the economic loss is greatly reduced, and meanwhile, the fire fighting personnel can be used for making targeted fire fighting measures.
According to the first concept of the application, the area to be processed is determined based on the concentration of the particulate matters by acquiring the concentration of the particulate matters in the air of the photovoltaic module area, and if the concentration of the particulate matters is greater than or equal to the threshold value of the concentration of the particulate matters, the position coordinates of the corresponding smoke sensor are acquired, and the area to be processed is determined according to the position coordinates. In this application, acquire the particulate matter concentration in photovoltaic module area through smoke transducer, when detecting particulate matter concentration and being higher than the threshold value, corresponding smoke transducer is arrived to accurate location this moment, and the grasp that can be accurate catches fire the place, has saved fire prevention alarm time in the very big degree, can in time control the intensity of a fire.
According to a second concept of the application, defogging image information in an area to be processed is collected in real time, and initial image information in the area to be processed is obtained, wherein the initial image information is image information containing smoke; acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information; and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information. In this application, when fixing a position the place of catching fire, open image acquisition device this moment, can gather the fire behavior image information of the place of catching fire in real time, because can produce dense smog when catching fire, the image information who acquires this moment is unclear, remove the smog step in this application, can clearly obtain the image information of catching fire after getting rid of smog, can provide the clear image of the place of catching fire for staff or fire fighter, the fire fighter has made things convenient for relevant fire fighting measures in the very big degree, the proruption nature of the fire has been avoided effectively and the unexpected harm that brings, economic loss has been avoided in the very big degree.
According to a third concept of the present application, a fire development model is constructed based on the defogged image information and the temperature change rate, and fire spread trend information in the region to be processed is determined based on the fire development model; and acquiring fire spreading trend information in real time, and taking an alarm action. Receiving the constructed fire development model and calling a preset fire model prestored in a database; and determining fire spread trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model. In this application, through the condition of a fire development model that will establish in real time, confirm the information that stretchs of the intensity of a fire with the mapping relation between the pre-stored preset condition of a fire model, can in time carry out visual control to the point of catching a fire through observing the information that stretchs of the intensity of a fire, prevent that the intensity of a fire from excessively destroying the equipment in the region, through predicting the condition of a fire of the environment of locating at present, when predicting the condition of a fire to take place and change, in time carry out the condition of a fire and remind, so that the fire fighter can in time make the counter measure.
In the foregoing description of embodiments, the particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.
While the invention has been described above with reference to an embodiment, various modifications may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In particular, the various features of the disclosed embodiments of the invention can be used in any combination with one another as long as no structural conflict exists, and all combinations that do not exist are described in this specification solely for the sake of brevity and resource savings. Therefore, it is intended that the invention not be limited to the particular embodiments disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Those of ordinary skill in the art will understand that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described above, or equivalents may be substituted for elements thereof. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A photovoltaic module area fire prevention alarm method is characterized by comprising the following steps:
the method comprises the steps of obtaining the concentration of particulate matters in the air of a photovoltaic module region, determining a region to be processed based on the concentration of the particulate matters, and collecting defogging image information in the region to be processed in real time;
acquiring a first temperature signal in the region to be processed, and acquiring a second temperature signal in the region to be processed within a preset time;
acquiring the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal;
constructing a fire development model based on the defogging image information and the temperature change rate, and determining fire spreading trend information in the region to be processed based on the fire development model;
and acquiring fire spreading trend information in real time, and taking an alarm action.
2. The photovoltaic module area fire alarm method according to claim 1, wherein when determining the area to be treated based on the concentration of the particulate matter, specifically:
judging and comparing the particulate matter concentration acquired in real time with a particulate matter concentration threshold, and determining whether to determine a region to be processed according to a judgment result:
if the concentration of the particulate matter is greater than or equal to the threshold value of the concentration of the particulate matter, acquiring position coordinates of the corresponding smoke sensor, and determining a region to be processed according to the position coordinates;
and if the concentration of the particulate matters is less than the threshold value of the concentration of the particulate matters, determining the area to be treated.
3. The photovoltaic module area fire prevention alarm method according to claim 1, wherein when defogged image information in the area to be processed is collected in real time, the method specifically comprises the following steps:
acquiring initial image information in the area to be processed, wherein the initial image information is image information containing smoke;
acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information;
and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information.
4. The photovoltaic module regional fire alarm method of claim 1, wherein the calculation formula for obtaining the temperature change rate in the area to be processed in real time according to the first temperature signal and the second temperature signal is as follows:
wherein T is a temperature change rate, T 2 Is the second temperature signal, T 1 Is a first temperature signal.
5. The photovoltaic module regional fire protection alarm method according to claim 1, wherein when determining the fire spread trend information in the region to be processed based on a fire development model, the method specifically comprises:
receiving the constructed fire development model and calling a preset fire model prestored in a database;
determining fire spread trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model;
the preset fire model is obtained by training through image features of an image training set by using a machine learning algorithm.
6. A photovoltaic module fire alarm system for a region, the system comprising:
the collection module is used for obtaining the concentration of particulate matters in the air of a photovoltaic module area, determining an area to be processed based on the concentration of the particulate matters, and collecting defogged image information in the area to be processed in real time;
the determining module is used for acquiring a first temperature signal in the area to be processed and acquiring a second temperature signal in the area to be processed within preset time;
acquiring the temperature change rate in the region to be processed in real time according to the first temperature signal and the second temperature signal;
the generating module is used for constructing a fire development model based on the defogging image information and the temperature change rate and determining fire spreading trend information in the region to be processed based on the fire development model;
and the alarm module is used for acquiring the fire spreading trend information in real time and taking an alarm action.
7. The photovoltaic module regional fire alarm method of claim 6, wherein in the collection module, when determining the area to be treated based on the concentration of the particulate matter, specifically:
judging and comparing the particulate matter concentration acquired in real time with a particulate matter concentration threshold value, and determining whether to determine a region to be processed according to a judgment result:
if the concentration of the particulate matter is greater than or equal to the threshold value of the concentration of the particulate matter, acquiring position coordinates of the corresponding smoke sensor, and determining a region to be processed according to the position coordinates;
and if the particulate matter concentration is smaller than the particulate matter concentration threshold value, determining the region to be treated.
8. The photovoltaic module area fire prevention alarm method according to claim 6, wherein in the acquisition module, when acquiring the defogged image information in the region to be processed in real time, the method specifically comprises the following steps:
acquiring initial image information in the region to be processed, wherein the initial image information is image information containing smoke;
acquiring a plurality of appearance characteristic information of initial image information according to a preset defogging network, and determining a characteristic image based on the plurality of appearance characteristic information;
and mapping the characteristic image to an image grid to obtain clear image information, wherein the clear image information is defogged image information.
9. The photovoltaic module area fire prevention alarm method according to claim 6, wherein in the determination module, a calculation formula for obtaining the temperature change rate in the area to be processed in real time according to the first temperature signal and the second temperature signal is as follows:
wherein T is a temperature change rate, T 2 Is the second temperature signal, T 1 Is a first temperature signal.
10. The photovoltaic module regional fire alarm method of claim 6, wherein in the generation module, when determining the fire spread trend information in the area to be processed based on the fire development model, specifically:
receiving the constructed fire development model and calling a preset fire model prestored in a database;
determining fire spreading trend information in the area to be processed according to the mapping relation between the fire development model and the preset fire model;
the preset fire model is obtained by training through image features of an image training set by using a machine learning algorithm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210565973.4A CN115206047A (en) | 2022-05-24 | 2022-05-24 | Photovoltaic module area fire prevention alarm method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210565973.4A CN115206047A (en) | 2022-05-24 | 2022-05-24 | Photovoltaic module area fire prevention alarm method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115206047A true CN115206047A (en) | 2022-10-18 |
Family
ID=83574999
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210565973.4A Pending CN115206047A (en) | 2022-05-24 | 2022-05-24 | Photovoltaic module area fire prevention alarm method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115206047A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116363825A (en) * | 2023-06-02 | 2023-06-30 | 北京利达华信电子股份有限公司 | Method and device for displaying fire spreading trend, electronic equipment and medium |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1049773A (en) * | 1996-07-31 | 1998-02-20 | Matsushita Electric Works Ltd | Heat sensor |
| US5920492A (en) * | 1996-04-26 | 1999-07-06 | Southwest Research Institute | Display list generator for fire simulation system |
| KR101093076B1 (en) * | 2011-06-13 | 2011-12-13 | 로지시스템(주) | Building automation management system and method for detecting fire |
| CN104715556A (en) * | 2015-04-02 | 2015-06-17 | 无锡桑尼安科技有限公司 | Fire alarm method based on aerial photography |
| JP2015138477A (en) * | 2014-01-24 | 2015-07-30 | ホーチキ株式会社 | Fire detection system and method |
| CN106228140A (en) * | 2016-07-28 | 2016-12-14 | 国网湖南省电力公司 | The transmission line forest fire smog of a kind of combination weather environment sentences knowledge method |
| US20170082498A1 (en) * | 2008-11-21 | 2017-03-23 | Schechter Tech, Llc | Remote monitoring system |
| CN107147872A (en) * | 2017-05-10 | 2017-09-08 | 合肥慧图软件有限公司 | A kind of pyrotechnics warning system being combined based on video monitoring with image procossing |
| CN207817921U (en) * | 2018-01-15 | 2018-09-04 | 南京信息工程大学 | A kind of fire of high-rise building search and rescue inspection system based on FPGA and ARM |
| CN108492506A (en) * | 2018-04-20 | 2018-09-04 | 杨春明 | A kind of inside fire early warning method and system of multisource data fusion |
| CN109741565A (en) * | 2019-01-28 | 2019-05-10 | 北京工业职业技术学院 | Coal-mine fire identifying system and method |
| KR20200065281A (en) * | 2018-11-30 | 2020-06-09 | (주)아르게스마린 | Video fire detection system |
| CN111627181A (en) * | 2020-06-28 | 2020-09-04 | 四川旷谷信息工程有限公司 | Comprehensive pipe rack fire early warning method fusing multi-source parameters and gradient information thereof |
| CN111882811A (en) * | 2020-07-27 | 2020-11-03 | 安徽九洲农业科技有限公司 | Fire-fighting unmanned aerial vehicle for identifying fire point |
| CN112365671A (en) * | 2021-01-13 | 2021-02-12 | 南京澳晟科技有限公司 | Alarm method for identifying smoke flame |
| CN112687092A (en) * | 2019-11-15 | 2021-04-20 | 华中科技大学 | Lithium cell energy storage system's fire control early warning system |
| 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 |
-
2022
- 2022-05-24 CN CN202210565973.4A patent/CN115206047A/en active Pending
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5920492A (en) * | 1996-04-26 | 1999-07-06 | Southwest Research Institute | Display list generator for fire simulation system |
| JPH1049773A (en) * | 1996-07-31 | 1998-02-20 | Matsushita Electric Works Ltd | Heat sensor |
| US20170082498A1 (en) * | 2008-11-21 | 2017-03-23 | Schechter Tech, Llc | Remote monitoring system |
| KR101093076B1 (en) * | 2011-06-13 | 2011-12-13 | 로지시스템(주) | Building automation management system and method for detecting fire |
| JP2015138477A (en) * | 2014-01-24 | 2015-07-30 | ホーチキ株式会社 | Fire detection system and method |
| CN104715556A (en) * | 2015-04-02 | 2015-06-17 | 无锡桑尼安科技有限公司 | Fire alarm method based on aerial photography |
| CN106228140A (en) * | 2016-07-28 | 2016-12-14 | 国网湖南省电力公司 | The transmission line forest fire smog of a kind of combination weather environment sentences knowledge method |
| CN107147872A (en) * | 2017-05-10 | 2017-09-08 | 合肥慧图软件有限公司 | A kind of pyrotechnics warning system being combined based on video monitoring with image procossing |
| CN207817921U (en) * | 2018-01-15 | 2018-09-04 | 南京信息工程大学 | A kind of fire of high-rise building search and rescue inspection system based on FPGA and ARM |
| CN108492506A (en) * | 2018-04-20 | 2018-09-04 | 杨春明 | A kind of inside fire early warning method and system of multisource data fusion |
| KR20200065281A (en) * | 2018-11-30 | 2020-06-09 | (주)아르게스마린 | Video fire detection system |
| CN109741565A (en) * | 2019-01-28 | 2019-05-10 | 北京工业职业技术学院 | Coal-mine fire identifying system and method |
| CN112687092A (en) * | 2019-11-15 | 2021-04-20 | 华中科技大学 | Lithium cell energy storage system's fire control early warning system |
| CN111627181A (en) * | 2020-06-28 | 2020-09-04 | 四川旷谷信息工程有限公司 | Comprehensive pipe rack fire early warning method fusing multi-source parameters and gradient information thereof |
| CN111882811A (en) * | 2020-07-27 | 2020-11-03 | 安徽九洲农业科技有限公司 | Fire-fighting unmanned aerial vehicle for identifying fire point |
| CN112365671A (en) * | 2021-01-13 | 2021-02-12 | 南京澳晟科技有限公司 | Alarm method for identifying smoke flame |
| 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 |
Non-Patent Citations (1)
| Title |
|---|
| 黄翰鹏: "《融合模糊神经网络与时序模型的火灾预警算法》", 《计算机工程与设计》, vol. 41, no. 6, pages 1639 - 1644 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116363825A (en) * | 2023-06-02 | 2023-06-30 | 北京利达华信电子股份有限公司 | Method and device for displaying fire spreading trend, electronic equipment and medium |
| CN116363825B (en) * | 2023-06-02 | 2023-08-29 | 北京利达华信电子股份有限公司 | Method and device for displaying fire spreading trend, electronic equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111111074B (en) | Fire extinguishing scheduling method and system for power tunnel fire-fighting robot | |
| CN103513637B (en) | Laboratory environment safety control system | |
| CN104361714B (en) | The anti-cheating personal security's protector of work high above the ground based on computer vision | |
| CN115206047A (en) | Photovoltaic module area fire prevention alarm method and system | |
| CN114272548B (en) | Intelligent fire extinguishing equipment for buildings and fire extinguishing method thereof | |
| CN106952441A (en) | Intelligent building firefighting monitoring system and monitoring method | |
| CN107393252A (en) | Computer room smog warning system based on Internet of Things | |
| CN109471398A (en) | Electric power tests operation field secure machine people and supervises exchange method | |
| CN110415478A (en) | Fire alarm grading forewarning system system based on Internet of Things | |
| CN107572322A (en) | A kind of lift facility management platform and lift facility management method | |
| CN110488777A (en) | A kind of chemical plant accident early warning and state of affairs tracking system | |
| CN112071007A (en) | Museum safety prevention and control management system | |
| CN107393251A (en) | Computer room smog alarm method, apparatus and storage medium based on Internet of Things | |
| CN105225398B (en) | A kind of forest fire protection monitor supervision platform | |
| CN114792465B (en) | Fire safety monitoring system based on regional alarm model | |
| CN116667783A (en) | Distributed photovoltaic power station maintenance system | |
| CN113763664B (en) | Intelligent building fire control system | |
| CN217548826U (en) | Integrated oil mist purification system | |
| CN110954165A (en) | Cable interlayer polling method and device and computer-storable medium | |
| CN115331383A (en) | Construction site safety risk identification method and system | |
| CN212484526U (en) | Museum safety prevention and control management system | |
| CN103326267A (en) | Routine inspection method and system of transformer substation | |
| CN111626555A (en) | Fire-fighting equipment operation warning and state evaluation system and device | |
| CN113240877A (en) | Intelligent fire monitoring and escaping method | |
| CN110164095A (en) | A kind of solid intelligent air monitor and alarm system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |