CN114764093A - Method and device for monitoring carbon monoxide content in flue gas of gas-fired boiler - Google Patents
Method and device for monitoring carbon monoxide content in flue gas of gas-fired boiler Download PDFInfo
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- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 title claims abstract description 253
- 239000003546 flue gas Substances 0.000 title claims abstract description 128
- 229910002091 carbon monoxide Inorganic materials 0.000 title claims abstract description 126
- 238000012544 monitoring process Methods 0.000 title claims abstract description 57
- 238000000034 method Methods 0.000 title claims abstract description 54
- 239000007789 gas Substances 0.000 claims abstract description 125
- 238000004590 computer program Methods 0.000 claims description 20
- 238000012806 monitoring device Methods 0.000 claims description 20
- 238000012549 training Methods 0.000 claims description 12
- 230000004044 response Effects 0.000 claims description 11
- 230000006870 function Effects 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 8
- 238000005259 measurement Methods 0.000 abstract description 15
- 238000012423 maintenance Methods 0.000 abstract description 8
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- 239000003795 chemical substances by application Substances 0.000 description 4
- 238000002485 combustion reaction Methods 0.000 description 4
- 239000000446 fuel Substances 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- MCMNRKCIXSYSNV-UHFFFAOYSA-N Zirconium dioxide Chemical compound O=[Zr]=O MCMNRKCIXSYSNV-UHFFFAOYSA-N 0.000 description 2
- 238000013145 classification model Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013499 data model Methods 0.000 description 1
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- 229910052760 oxygen Inorganic materials 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display
- G01N33/0068—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display using a computer specifically programmed
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Abstract
The invention is suitable for the field of gas distributed energy, and provides a method and a device for monitoring the content of carbon monoxide in flue gas of a gas boiler, wherein the method comprises the following steps: acquiring operation data of a target gas boiler; responding to a demand application for detecting the content of the carbon monoxide in the flue gas of the target gas-fired boiler, and determining whether a monitoring model matched with the demand application exists; and responding to the determination of existence, and generating the flue gas carbon monoxide content of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data. This embodiment has realized need not to use the sensor to measure flue gas carbon monoxide content, can real-time supervision flue gas carbon monoxide content, and the maintenance of being convenient for reduces measuring error, and the joint flue gas carbon monoxide content measurement model relies on true data simultaneously, is difficult to receive external environment's influence, can comparatively accurately determine flue gas carbon monoxide content.
Description
Technical Field
The invention belongs to the field of gas distributed energy, and particularly relates to a method and a device for monitoring the content of carbon monoxide in flue gas of a gas-fired boiler.
Background
The content of carbon monoxide in the flue gas refers to the content of the flue gas discharged after the fuel is combusted, and the content is an important index of the combustion of the gas-fired boiler, and the value of the content is related to factors such as the structure of the gas-fired boiler, the type and the property of the fuel, the size of load, the operating air distribution working condition, the sealing condition of equipment and the like. In order to sufficiently burn the fuel during actual operation of the gas boiler, the amount of air actually supplied is much larger than the theoretical amount of air supplied. This is the amount of air supplied, which we generally call the excess amount of air. The excess air ratio is the ratio of the actual supplied air amount to the theoretical supplied air amount. The content of carbon monoxide in the flue gas is too low, namely the coefficient of excess air is smaller, so that the quantity of oxygen supplied to the gas-fired boiler for combustion is insufficient, the fuel cannot be sufficiently combusted, and the heat loss is increased; the content of carbon monoxide in flue gas is too high, namely the larger the excess air coefficient is, the heat efficiency of the gas-fired boiler is reduced, combustion is influenced, the emission of environmental pollutants is easy to exceed the standard, and the power consumption of flue gas emission is increased. Therefore, the content of the carbon monoxide in the flue gas of the gas-fired boiler is controlled in a reasonable range, and the method has important significance for saving energy, maintaining economic combustion of the gas-fired boiler, realizing safe, efficient and low-pollution emission, in other words, the content of the carbon monoxide in the flue gas of the gas-fired boiler is one of important signs for measuring whether the gas-fired boiler is operated safely, economically and environmentally.
Currently, zirconia oxide sensors are commonly used in the industry to measure the carbon monoxide content of flue gases.
However, the sensor has many defects of high cost, large measurement lag, difficult maintenance, large measurement error, short service life and the like, and is not suitable for long-term use in a scene that distributed energy sources mainly comprise small and medium-sized gas boilers.
Disclosure of Invention
In view of this, the embodiment of the present invention provides a method and an apparatus for monitoring the carbon monoxide content in flue gas of a gas boiler, which only need a small amount of tag data, can overcome the defect of complete actual measurement of a sensor, and do not need to rely on a large number of physical parameters like physical modeling.
The first aspect of the embodiment of the invention provides a method for monitoring the content of carbon monoxide in flue gas of a gas-fired boiler, which comprises the following steps:
acquiring operation data of a target gas boiler;
responding to a demand application for detecting the content of the carbon monoxide in the flue gas of the target gas-fired boiler, and determining whether a monitoring model matched with the demand application exists or not;
and responding to the determination of existence, and generating the flue gas carbon monoxide content of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data.
A second aspect of an embodiment of the present invention provides a gas boiler flue gas carbon monoxide content monitoring device, including:
an acquisition module configured to acquire operational data of a target gas boiler;
a determination module configured to determine whether a flue gas carbon monoxide content monitoring model matching the demand application exists in response to the demand application detecting the flue gas carbon monoxide content of the target gas boiler;
a generating module configured to generate a flue gas carbon monoxide content of the target gas-fired boiler in response to determining that the target gas-fired boiler exists, according to the matched flue gas carbon monoxide content monitoring model and the operation data.
A third aspect of embodiments of the present invention provides a terminal device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium having a computer program stored thereon, where the computer program is adapted to perform the steps of the method according to any of the claims 1 to 7 when executed by a processor.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: firstly, acquiring operation data of a target gas boiler; then, responding to a demand application for detecting the content of the carbon monoxide in the flue gas of the target gas-fired boiler, and determining whether a monitoring model matched with the demand application exists or not; and finally, responding to the determined existence, and generating the content of the carbon monoxide in the flue gas of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data. In conclusion, according to the technical scheme of the invention, the content of the carbon monoxide in the flue gas can be monitored in real time without using a sensor to measure the content of the carbon monoxide in the flue gas, the maintenance is convenient, the measurement error is reduced, meanwhile, the combined flue gas carbon monoxide content measurement model depends on real data, is not easily influenced by the external environment, and can accurately determine the content of the carbon monoxide in the flue gas.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for 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 without creative efforts.
FIG. 1 is a schematic flow chart of a method for monitoring carbon monoxide content in flue gas of a gas-fired boiler according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of another method for monitoring the carbon monoxide content in flue gas of a gas-fired boiler according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a device for monitoring carbon monoxide content in flue gas of a gas-fired boiler according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
fig. 5 is a diagram of a scene application 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 shows a method according to an embodiment of the present invention. The method provided by the embodiment of the invention can be applied to electronic equipment, and particularly can be applied to a server or a general computer. The embodiment of the invention provides a method for monitoring the content of carbon monoxide in flue gas of a gas-fired boiler, which comprises the following steps:
In some embodiments, the execution body may acquire the operation data of the target gas boiler through a wired or wireless manner. The target gas boiler has a gas boiler identifier, the gas boiler identifier includes description information of energy stations to be monitored to which the gas boiler belongs, the number of the gas boilers, signals of the gas boilers, working environment, rated power, rated efficiency, manufacturers and the like, and the gas boiler identifier is specifically determined according to actual requirements. Here, the number of gas boilers in the energy station to be monitored is of the same type or the number of gas boilers is similar.
In some embodiments, the executing body may determine whether a flue gas carbon monoxide content monitoring model matching the demand application exists or not in the case of detecting the demand application of the flue gas carbon monoxide content of the target gas boiler.
In practical application, a joint learning internet of things platform can be developed, and the joint learning internet of things platform is used for performing joint learning with a joint learning client (a client performing joint learning), so that a joint learning model is obtained, and the joint learning model is stored. The client side corresponding to the energy station to be monitored sends the demand application of the content of the carbon monoxide in the flue gas through the API, and the demand application of the content of the carbon monoxide in the flue gas is obtained by the platform of the combined learning Internet of things.
In particular, the energy station is generally configured to provide energy to a designated area, such as an area adjacent to the energy station, and the energy system may include and provide energy to a plurality of areas via a plurality of energy stations, with the plurality of gas boilers in the energy station being similar or of the same type. In the embodiment of the application, each energy station is used as a node in the internet of things and is provided with a client, and if the data of the energy station is used for joint learning, the client corresponding to the energy station is called as a joint learning client. The joint learning ensures that the private data of the user is protected to the maximum extent through a distributed training and encryption technology so as to improve the trust of the user on the artificial intelligence technology. In the embodiment of the application, under a joint learning mechanism, each participant (a joint learning client corresponding to each target joint energy station) contributes the encrypted data model to a alliance (a joint learning internet of things platform), and jointly trains a joint learning model.
The method comprises the steps of obtaining description information of the gas boilers in the energy station to be monitored, carried by gas boiler identification, of the candidate gas boilers in the multiple candidate combined energy stations capable of participating in combined learning, calculating similarity between the description information of the gas boilers and the description information of the candidate gas boilers to determine the similarity between the candidate combined energy stations and the energy station to be monitored, and determining a target combined energy station according to the similarity between the candidate combined energy stations and the energy station to be monitored. Wherein the description information comprises a plurality of parameters and a parameter value of each parameter. The parameters include, but are not limited to, rated capacity, rated efficiency, operation mode, model (indicating the performance, specification and size of the gas boiler), brand and operation place, and the specific needs are determined by combining actual conditions. It can be understood that the higher the similarity between the description information of the gas boiler and the description information of the candidate gas boiler, the higher the reference value of the candidate gas boiler, so as to ensure the accuracy of the target combined energy station predicted subsequently. Preferably, the gas boiler and the candidate gas boiler should be of the same model.
As a possible case, when the similarity between the candidate combined energy station and the energy station to be monitored is not less than a preset threshold, the candidate combined energy station is determined as the target combined energy station. The similarity between the candidate combined energy source station and the energy source station to be monitored can be determined by comparing the similarity of the description information between the gas boiler and the candidate gas boiler. In one example, the similarity of each parameter in the description information of the gas boiler and the candidate gas boiler is determined based on the parameter value of each parameter in the description information of the gas boiler and the candidate gas boiler, the similarity of each parameter is weighted and averaged, and the result is determined as the similarity between the candidate combined energy station and the energy station to be monitored. In practical application, the description information of the gas boiler can be used as model input, the target combined energy station is used as model output, a classification model is trained, and the description information of the candidate gas boiler is input into the trained classification model, so that whether the candidate combined energy station corresponding to the candidate gas boiler is the target combined energy station or not is determined.
In some optional implementation manners of some embodiments, based on a target interface, the target terminal sends the requirement application to a joint learning platform. Specifically, the client of the target gas boiler sends a demand application for the content of carbon monoxide in the flue gas through an API (application programming interface).
In some optional implementations of some embodiments, the demand application includes: and the type information of the gas boiler of the energy station corresponding to the target terminal.
In some optional implementation manners of some embodiments, in response to determining that the model exists, sending the matched flue gas carbon monoxide content monitoring model and the relevant model information to the target terminal; and the target terminal selects and downloads the matched flue gas carbon monoxide content monitoring model based on the matched flue gas carbon monoxide content monitoring model and the relevant information of the model.
And 103, responding to the determined existence, and generating the content of the carbon monoxide in the flue gas of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data.
In some embodiments, the executing entity may generate the flue gas carbon monoxide content of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data when the determining is present.
In practical application, the operation data of the target gas-fired boiler is uploaded to a corresponding client, the client substitutes the operation data into the downloaded matched flue gas carbon monoxide content monitoring model, and the flue gas carbon monoxide content of the target gas-fired boiler is predicted through the downloaded matched flue gas carbon monoxide content monitoring model.
In some optional implementation manners of some embodiments, in response to that the content of carbon monoxide in the flue gas is greater than a preset threshold, sending alarm information to a terminal device with a display function corresponding to the target gas-fired boiler, and displaying the alarm information.
Some embodiments of the present disclosure disclose a method for monitoring carbon monoxide content in flue gas of a gas boiler, first, obtaining operation data of a target gas boiler; then, responding to a demand application for detecting the content of the carbon monoxide in the flue gas of the target gas-fired boiler, and determining whether a monitoring model matched with the demand application exists or not; and finally, responding to the determined existence, and generating the content of the carbon monoxide in the flue gas of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data. In conclusion, according to the technical scheme of the invention, the content of the carbon monoxide in the flue gas can be monitored in real time without using a sensor to measure the content of the carbon monoxide in the flue gas, the maintenance is convenient, the measurement error is reduced, meanwhile, the combined flue gas carbon monoxide content measurement model depends on real data, is not easily influenced by the external environment, and can accurately determine the content of the carbon monoxide in the flue gas.
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. 1 shows only a basic embodiment of the method of the present invention, and based on this, certain optimization and expansion can be performed, and other preferred embodiments of the method can also be obtained.
Fig. 2 shows another embodiment of the method for measuring the carbon monoxide content in the flue gas of the gas boiler according to the present invention. On the basis of the foregoing embodiments, the present embodiment is described in more detail with reference to application scenarios. It should be understood that the method described in this embodiment is also applicable in other relevant scenarios.
The specific scenario combined in this embodiment is as follows: as shown in fig. 5, it is assumed that there are 3 energy stations (a plurality of gas boilers in the energy stations are similar) and a joint learning internet-of-things platform T, where the 3 energy stations are a joint energy station a, a joint energy station B, and an energy station C to be monitored, and the joint learning internet-of-things platform T interacts with a joint learning client Ac, a joint learning client Bc, and a monitoring client Cc, where the joint energy stations a and B have abundant data, and a local flue gas carbon monoxide content measurement model, that is, a contributor of the joint learning model, can be trained by using operating data of their gas boilers; a gas boiler in the energy station C to be monitored has no measuring point for the content of carbon monoxide in flue gas; the combined learning client Ac stores the operation data of the gas boilers A1, A2 and A3 in the combined energy station A, the combined learning client Bc stores the operation data of the gas boilers B1, B2 and B3 in the combined energy station B, and the monitoring client Cs stores the operation data of the gas boilers C1, C2 and C3 in the energy station C to be monitored; the joint learning client Ac, the joint learning client Bc and the monitoring client Cc are respectively deployed on local operation and maintenance servers As, Bs and Cs, wherein the local operation and maintenance servers refer to servers for operation and maintenance of the gas-fired boiler. The method aims to establish a combined flue gas carbon monoxide content measurement model for monitoring the flue gas carbon monoxide content of the gas-fired boiler of the energy station to be monitored by combining the gas-fired boiler operation data in the combined learning client.
The method in this embodiment includes the following steps:
In some embodiments, the performing agent may determine a first target gas boiler (e.g., a1 in fig. 5) and a second target gas boiler (e.g., B1 in fig. 5) from the energy stations associated with the joint learning platform based on the gas boiler type information when determining that the gas boiler is not present.
And the energy station C to be monitored initiates a demand application of a gas boiler flue gas carbon monoxide content monitoring model to the joint learning Internet of things platform T through a monitoring client Cc and an API (application programming interface) deployed on the local operation and maintenance server Cs. The joint learning internet of things platform T is based on the type information of a gas boiler C1, wherein the type information of the gas boilers C1, C2 and C3 is the same, the type information of the gas boiler A1 in the joint energy station A is acquired, the type information of the gas boilers A1, A2 and A3 is the same, the type information of the gas boiler B1 in the joint energy station B is the same, and the type information of the gas boilers B1, B2 and B3 is the same.
The model of the gas boiler A1 in the combined energy station A is the same as that of the gas boiler C1, the similarity between the energy station C to be monitored and the combined energy station A is 1, the model of the gas boiler B1 in the combined energy station B is the same as that of the gas boiler C1, and the similarity between the energy station C to be monitored and the combined energy station B is 1.
In some embodiments, the executing agent may send the joint training request to the terminals of the energy stations corresponding to the first target gas boiler and the second target gas boiler, respectively. And the joint learning Internet of things platform T sends a joint training request to the joint learning client Ac and the joint learning client Bc.
In some embodiments, the executing agent may obtain the first target model and the second target model respectively at the terminals of the energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler, when the terminals of the energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler receive and agree to the joint training request. The joint learning client Ac and the joint learning client Bc return agreement,
And 204, based on the target interface, respectively sending the first target model and the second target model to the joint learning platform by the terminals of the energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler.
In some embodiments, the executing agent may send the first target model and the second target model to the joint learning platform based on the target interface and the terminals of the energy stations corresponding to the first target gas boiler and the second target gas boiler, respectively.
The combined learning client Ac performs model training on the model to be trained based on the operation data of the gas boilers A1, A2 and A3, uploads model parameters to the combined learning Internet of things platform T through an API (application programming interface), and the combined learning client Bc performs model training on the model to be trained based on the operation data of the gas boilers B1, B2 and B3, and uploads the model parameters to the combined learning Internet of things platform T.
And 205, processing the first target model and the second target model by the joint learning platform to obtain a joint learning intelligent model and model related information.
In some embodiments, the joint learning platform processes the first target model and the second target model to obtain a joint learning intelligent model and model-related information.
The joint learning Internet of things platform T issues the aggregated model parameters to a joint learning client Ac and a joint learning client Bc to perform model iteration, the joint learning client Ac and the joint learning client Bc respectively obtain local flue gas carbon monoxide content measurement models, and the joint learning Internet of things platform T fuses the local flue gas carbon monoxide content measurement models obtained by the joint learning client Ac and the joint learning client Bc to obtain a joint learning intelligent model.
And step 206, the joint learning platform stores the joint learning intelligent model and the relevant information of the model in a model information base.
In some embodiments, the joint learning platform stores the joint learning intelligent model and the model-related information in a model information base.
In some optional implementations of some embodiments, the target terminal generates the flue gas carbon monoxide content of the target gas boiler based on the joint learning intelligent model and the operation data. According to the method for monitoring the content of carbon monoxide in flue gas of the gas-fired boiler, disclosed by some embodiments of the disclosure, through a demand application, joint learning is initiated, a target joint energy source station similar to the gas-fired boiler is determined, joint learning is performed based on gas-fired boiler data corresponding to the target joint energy source station, a local flue gas carbon monoxide content measurement model is fused to obtain a joint flue gas carbon monoxide content measurement model, the joint flue gas carbon monoxide content measurement model integrates real gas-fired boiler operation data in the target joint energy source station, the influence of an external environment is not easily caused, and the content of carbon monoxide in flue gas can be more accurately determined.
FIG. 3 is a schematic diagram of a gas boiler flue gas carbon monoxide content monitoring device provided by an embodiment of the invention; above-mentioned gas boiler flue gas carbon monoxide content monitoring devices 300 includes: an obtaining module 301, a determining module 302 and a generating module 303. Wherein the obtaining module 301 is configured to obtain the operation data of the target gas boiler; a determining module 302 configured to determine whether a flue gas carbon monoxide content monitoring model matching the demand application exists in response to the demand application for detecting the flue gas carbon monoxide content of the target gas boiler; and the generating module 303 is configured to generate the flue gas carbon monoxide content of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data in response to the determination of existence.
In some optional implementations of some embodiments, the gas boiler flue gas carbon monoxide content monitoring device 300 is further configured to: responding to the determination of existence, and sending the matched flue gas carbon monoxide content monitoring model and the relevant model information to the target terminal; and the target terminal selects and downloads the matched model based on the matched model and the relevant information of the model.
In some optional implementations of some embodiments, the gas boiler flue gas carbon monoxide content monitoring device 300 is further configured to: and responding to the fact that the content of the carbon monoxide in the flue gas is larger than a preset threshold value, sending alarm information to terminal equipment with a display function corresponding to the target gas-fired boiler, and displaying the alarm information.
In some optional implementations of some embodiments, the gas boiler flue gas carbon monoxide content monitoring device 300 is further configured to: and based on a target interface, the target terminal sends the demand application to a joint learning platform.
In some optional implementations of some embodiments, the demand application includes: and the type information of the gas boiler of the energy station corresponding to the target terminal.
In some optional implementations of some embodiments, the gas boiler flue gas carbon monoxide content monitoring device 300 is further configured to: in response to determining not to exist, determining a first target gas boiler and a second target gas boiler from the energy stations associated with the joint learning platform based on the gas boiler type information; respectively sending joint training requests to terminals of energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler; responding to the fact that the terminals of the energy source stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler receive the joint training request and agree, and respectively obtaining a first target model and a second target model by the terminals of the energy source stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler; based on the target interface, terminals of energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler respectively send the first target model and the second target model to the joint learning platform; the joint learning platform processes the first target model and the second target model to obtain a joint learning intelligent model and model related information; and the joint learning platform stores the joint learning intelligent model and the relevant information of the model in a model information base.
In some optional implementations of some embodiments, the generation module 303 in the gas boiler flue gas carbon monoxide content monitoring apparatus 300 is further configured to: and the target terminal generates the content of the carbon monoxide in the flue gas of the target gas-fired boiler based on the combined learning intelligent model and the operation data.
It will be appreciated that the units described in the apparatus 300 correspond to the various steps in the method described with reference to fig. 1. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 300 and the units included therein, and are not described herein again.
Fig. 4 is a schematic diagram of a gas boiler flue gas carbon monoxide content monitoring device/terminal device according to an embodiment of the present invention. As shown in fig. 4, the gas boiler flue gas carbon monoxide content monitoring apparatus/terminal device 4 of this embodiment includes: a processor 40, a memory 41 and a computer program 42 stored in said memory 41 and executable on said processor 40. The processor 40, when executing the computer program 42, implements the steps in each of the above-described gas boiler flue gas carbon monoxide content monitoring method embodiments, such as the steps 101 to 103 shown in fig. 1. Alternatively, the processor 40, when executing the computer program 42, implements the functions of each module/unit in each device embodiment described above, for example, the functions of the modules 401 to 404 shown in fig. 4.
Illustratively, the computer program 42 may be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40 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 for describing the execution process of the computer program 42 in the gas boiler flue gas carbon monoxide content monitoring device/terminal equipment 4. For example, the computer program 42 may be divided into a synchronization module, a summary module, an acquisition module, and a return module (a module in a virtual device), and the specific functions of the modules are as follows:
the gas boiler flue gas carbon monoxide content monitoring device/terminal equipment 4 can be computing equipment such as a desktop computer, a notebook computer, a palm computer and a cloud server. The gas boiler flue gas carbon monoxide content monitoring device/terminal equipment can include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will appreciate that fig. 4 is merely an example of a gas boiler flue gas carbon monoxide content monitoring device/terminal 4, and does not constitute a limitation of the gas boiler flue gas carbon monoxide content monitoring device/terminal 4, and may include more or less components than those shown, or combine certain components, or different components, for example, the gas boiler flue gas carbon monoxide content monitoring device/terminal may also include input and output devices, network access devices, buses, and the like.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field 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 41 may be an internal storage unit of the gas boiler flue gas carbon monoxide content monitoring device/terminal device 4, such as a hard disk or a memory of the gas boiler flue gas carbon monoxide content monitoring device/terminal device 4. The memory 41 may also be an external storage device of the gas boiler flue gas carbon monoxide content monitoring device/terminal device 4, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card), or the like, which is equipped on the gas boiler flue gas carbon monoxide content monitoring device/terminal device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the gas boiler flue gas carbon monoxide content monitoring apparatus/terminal device 4. The memory 41 is used for storing the computer program and other programs and data required by the gas boiler flue gas carbon monoxide content monitoring device/terminal equipment. The memory 41 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 may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated module/unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, 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 content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by 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 (10)
1. A method for monitoring the content of carbon monoxide in flue gas of a gas-fired boiler is characterized by comprising the following steps:
acquiring operation data of a target gas boiler;
responding to a demand application for detecting the content of the carbon monoxide in the flue gas of the target gas-fired boiler, and determining whether a monitoring model matched with the demand application exists or not;
and responding to the determination of existence, and generating the flue gas carbon monoxide content of the target gas-fired boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data.
2. The gas boiler flue gas carbon monoxide content monitoring method of claim 1, characterized in that the method further comprises:
Responding to the determination of existence, and sending the matched flue gas carbon monoxide content monitoring model and the relevant model information to the target terminal;
and the target terminal selects and downloads the matched model based on the matched model and the relevant information of the model.
3. The gas boiler flue gas carbon monoxide content monitoring method of claim 1, characterized in that the method further comprises:
and responding to the fact that the content of the carbon monoxide in the flue gas is larger than a preset threshold value, sending alarm information to terminal equipment with a display function corresponding to the target gas-fired boiler, and displaying the alarm information.
4. The gas boiler flue gas carbon monoxide content monitoring method of claim 1, characterized in that the method further comprises:
and based on a target interface, the target terminal sends the demand application to a joint learning platform.
5. The gas boiler flue gas carbon monoxide content monitoring method of claim 1, wherein the demand application comprises: and the type information of the gas boiler of the energy station corresponding to the target terminal.
6. The gas boiler flue gas carbon monoxide content monitoring method of claim 1, characterized in that the method further comprises:
In response to determining not to exist, determining a first target gas boiler and a second target gas boiler from the energy stations associated with the joint learning platform based on the gas boiler type information;
respectively sending a joint training request to terminals of energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler;
responding to the fact that the terminals of the energy source stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler receive the joint training request and agree, and respectively obtaining a first target model and a second target model by the terminals of the energy source stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler;
based on the target interface, terminals of energy stations corresponding to the first target gas-fired boiler and the second target gas-fired boiler respectively send the first target model and the second target model to the joint learning platform;
the joint learning platform processes the first target model and the second target model to obtain a joint learning intelligent model and model related information;
and the joint learning platform stores the joint learning intelligent model and the relevant information of the model in a model information base.
7. The gas boiler flue gas carbon monoxide content monitoring method according to claim 6, wherein the generating the flue gas carbon monoxide content of the target gas boiler according to the matched flue gas carbon monoxide content monitoring model and the operation data comprises:
and the target terminal generates the content of the carbon monoxide in the flue gas of the target gas-fired boiler based on the combined learning intelligent model and the operation data.
8. The utility model provides a gas boiler flue gas carbon monoxide content monitoring devices which characterized in that includes:
an acquisition module configured to acquire operational data of a target gas boiler;
a determination module configured to determine whether a flue gas carbon monoxide content monitoring model matching the demand application exists in response to detecting the demand application for the flue gas carbon monoxide content of the target gas boiler;
a generating module configured to generate a flue gas carbon monoxide content of the target gas-fired boiler in response to determining that there is, based on the matched flue gas carbon monoxide content monitoring model and the operational data.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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