CN113008588A - Coal fired power plant boiler monitoring visualization system - Google Patents
Coal fired power plant boiler monitoring visualization system Download PDFInfo
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Abstract
The application discloses coal fired power plant boiler monitoring visual system, acquire the user request on front end layer and the real-time supervision data of SIS system in real time through the interface layer, and carry out the on-line calculation to real-time supervision data through the service layer with the feedback data of front end layer propelling movement response user request, and store real-time supervision data and feedback data, thereby can real-time supervision power plant running state and data storage and visualization, need not to adopt historical data to calculate, monitoring accuracy and ageing have been improved, simultaneously, still monitor with data transmission's mode, system performance stability has been improved.
Description
Technical Field
The application relates to the technical field of electric power monitoring, in particular to a coal-fired power plant boiler monitoring visualization system.
Background
The power industry is an important component of the energy industry and is an important foundation for promoting human civilization and supporting the development of socioeconomic industry. According to the energy statistical data of the united nations, the thermal power accounts for about 65% of the total power generation in the world at present. Coal-fired power generation in China is still the main energy consumption, and in 2005, the capacity of power generation equipment in China reaches about 5 hundred million kilowatts. The energy structure relying on coal-fired power generation for a long time causes serious environmental pollution, and pollutants generated by a coal-fired power plant mainly comprise smoke dust, SOx, NOx and the like, which respectively account for 70%, 90% and 70% of the total emission of similar substances. Therefore, the clean and efficient utilization of coal in the power industry of China, the power increase and environment coordinated development are the most important subjects for ensuring the sustainable development of national economy and protecting the environment.
Compared with other power generation modes, thermal power generation is the main power production mode in China, coal consumption is the main mode, and the total amount of pollutant emission of a coal-fired power plant is large and concentrated. Therefore, the pollution and damage to the environment are quite serious, mainly: (1) air pollution: including SO2, NOx, soot, and the like; (2) water body pollution: including ash flushing water, industrial sewage and domestic sewage; (3) solid waste: comprises fly ash, desulfurization waste residue and the like; (4) noise: (5) electromagnetic radiation, and the like. These pollutions not only harm people's health, but also have an impact on the sustainable development of the power industry economy and the industrial upgrading.
At present, in order to respond to national environmental protection policies, reduce pollution Emission and reduce environmental hazards, domestic coal-fired power plants start to perform online Monitoring or prediction on pollutant Emission, an online Monitoring instrument for pollutants of the coal-fired power plants is mainly CEMS (Continuous Emission Monitoring System) which monitors pollutants such as S02, NOx, smoke dust and the like in the air, and most domestic coal-fired power plants are not installed yet. A set of safe, reliable, continuous and accurate online monitoring system is developed, so that whether the pollutants of the power plant exceed standards can be reflected in time, and the problem can be solved as soon as possible. Therefore, an online monitoring system for environmental pollutants of a power plant is very important.
For the online monitoring system of the environmental pollutants of the power plant, although research on online monitoring of the pollutants at home and abroad has been advanced to a certain extent, most of the monitoring of the pollutants is prone to be carried out in an offline state, such as offline calculation and analysis after data transmission, and real-time visual online monitoring is difficult to realize.
The current thermal power flue gas on-line monitoring system samples and detects parameters such as main components SO2, NOx, O2, smoke dust, dry flue gas amount and temperature in flue gas discharged by coal and flue gas after desulfurization. The concentrations of SO2 and O2 in the original flue gas and the clean flue gas are measured by an online monitoring system, SO that operators can conveniently master the relevant conditions of the desulfurization system in time. Meanwhile, the desulfurization efficiency can be analyzed, so that a coal-fired system can be better optimized, and the adjustment of the operating parameters of the desulfurization device can be guided. However, the continuous monitoring capability of the system is poor, the performance stability is deficient, the problem of pipeline water inflow of the device is easy to occur, the function failure of the system device is caused, the detection result is influenced, and even the system is damaged.
In summary, the existing coal-fired power plant on-line monitoring system still has the following disadvantages: (1) the numerical simulation prediction result is greatly different from the field, so that the monitoring accuracy is low; (2) historical data is adopted for analysis, so that timeliness is poor; 3) the stability of the properties is insufficient.
Disclosure of Invention
The application provides a coal fired power plant boiler monitoring visual system for solve coal fired power plant on-line monitoring system monitoring accuracy low, the timeliness is poor and the poor technical problem of performance stability.
In view of this, the present application provides a coal fired power plant boiler monitoring visualization system, and its architecture level includes: the system comprises a front-end layer, an interface layer, a service layer and a storage layer;
the front-end layer is used for providing a human-computer interaction interface so as to obtain a user request and obtain feedback data responding to the user request;
the interface layer is used for receiving the user request of the front end layer and real-time monitoring data in an SIS (service information system) of an external power plant based on API (application program interface) gateway service, sending the user request and the real-time monitoring data to the service layer in a message queue manner, and sending the feedback data to the front end layer after receiving the feedback data which is sent by the service layer and responds to the user request;
the service layer is used for executing a preset application micro server according to the real-time monitoring data so as to obtain the feedback data responding to the user request, and is also used for respectively sending the feedback data to the interface layer and the storage layer, wherein the preset application micro server comprises a denitration efficiency prediction micro server, a coal quality real-time measurement micro server, a consumption difference analysis micro server and a boiler thermal efficiency analysis micro server;
and the storage layer is used for storing data after receiving the real-time monitoring data and the feedback data sent by the interface layer and the service layer respectively.
Preferably, the architecture layer further includes a container layer, which is configured to create a container based on a docker engine, arrange a relationship between the container and the preset application micro server, and perform resource scheduling on the preset application micro server.
Preferably, the front-end layer comprises a web application server and a client;
the web application server interacts with the interface layer and the service layer respectively, and the client is used for sending a user request to the web application server and obtaining the feedback data responding to the user request through the web application server.
Preferably, the client comprises a computer and a mobile phone.
Preferably, the interface layer comprises an API gateway service cluster, a message access microservice cluster, and a Kafka message server cluster;
the API gateway service cluster is used for providing a user access entrance and establishing a data interaction relation with the client and an SIS (service information system) of the external power plant respectively so as to obtain the user request and the real-time monitoring data;
the message access micro-service cluster is used for receiving the real-time monitoring data sent by the SIS system of the external power plant through a transmission protocol;
the Kafka message server cluster is configured to receive the user request and the real-time monitoring data sent by the API gateway service cluster and the real-time monitoring data sent by the message access micro service cluster, and is further configured to perform category division on the real-time monitoring data according to a preset topic category, and is further configured to perform data caching on the user request and the real-time monitoring data in a message queue manner to implement peak clipping and splitting, and is further configured to receive the feedback data pushed by the service layer and send the feedback data to the web application server.
Preferably, the transmission protocol is a tcp transmission protocol, a udp transmission protocol or a ws transmission protocol.
Preferably, the service layer comprises a service registration and discovery cluster, a protocol resolution micro-service cluster and a micro-service cluster;
the service registration and discovery cluster is respectively interacted with the API gateway service cluster and the micro-service cluster in data, is used for respectively carrying out server registration and service discovery on the API gateway service cluster and the micro-service cluster, and is also used for carrying out corresponding micro-service gray-scale release processing on micro-service applications in the micro-service cluster;
the protocol analysis micro-service cluster is respectively in data interaction with the Kafka message server cluster and the micro-service cluster, and is used for carrying out protocol body analysis on the real-time monitoring data and respectively pushing the real-time monitoring data after the protocol body analysis to the micro-service cluster and the storage layer;
the micro-server cluster and the Kafka message server cluster perform data interaction, and the data interaction comprises a denitration efficiency prediction micro-server cluster, a coal quality real-time measurement micro-server cluster, a consumption difference analysis micro-server cluster, a boiler thermal efficiency analysis micro-server cluster, a threshold value alarm analysis micro-server cluster, a change rate analysis micro-server cluster and a data result pushing cluster;
the denitration efficiency prediction micro-server cluster is used for obtaining denitration efficiency prediction data through a preset denitration efficiency prediction model according to the real-time monitoring data;
the coal quality real-time measurement micro-server cluster is used for obtaining coal quality measurement data through a preset coal quality real-time measurement model according to the real-time monitoring data;
the consumption difference analysis micro server cluster is used for obtaining consumption difference data through a preset consumption difference analysis model according to the real-time monitoring data;
the boiler thermal efficiency analysis micro-server cluster is used for obtaining boiler thermal efficiency data through a preset boiler thermal efficiency analysis model according to the real-time monitoring data;
the threshold alarm analysis micro-server cluster is used for obtaining threshold alarm data through a preset threshold alarm analysis model according to the real-time monitoring data;
the change rate analysis micro server cluster is used for obtaining change rate data through a preset change rate analysis model according to the real-time monitoring data;
and the data result pushing cluster is used for pushing the data result obtained by the calculation of the micro service cluster to the Kafka message server cluster.
Preferably, the service layer further includes a service monitoring module, configured to monitor an application process of the micro-service application in the micro-service cluster, and further configured to send a maintenance signal to the client when it is monitored that the application process of the micro-service application has a fault.
Preferably, the service layer further includes an authentication service cluster for performing unified authentication on the users accessing the API gateway service cluster, so as to determine the access rights of the accessing users.
Preferably, the storage tier comprises a Mysql database cluster and a big data storage module.
According to the technical scheme, the embodiment of the application has the following advantages:
the utility model provides a pair of coal fired power plant boiler monitoring visual system, acquire the user request on front end layer and the real-time supervision data of SIS system in real time through the interface layer, and carry out the on-line calculation to real-time supervision data through the service layer with the feedback data of front end layer propelling movement response user request, and store real-time supervision data and feedback data, thereby can real-time supervision power plant running state and data storage and visual, need not to adopt historical data to calculate, monitoring accuracy and ageing have been improved, simultaneously, still monitor with data transmission's mode, system performance stability has been improved.
Drawings
Fig. 1 is a schematic architecture level diagram of a coal-fired power plant boiler monitoring visualization system according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a coal-fired power plant boiler monitoring visualization system provided in an embodiment of the present application;
FIG. 3 is a schematic structural diagram of a service layer in a coal-fired power plant boiler monitoring visualization system according to an embodiment of the present application;
fig. 4 is a flowchart of a coal-fired power plant boiler monitoring visualization system according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
For easy understanding, please refer to fig. 1, the present application provides a coal-fired power plant boiler monitoring visualization system, which includes: a front end layer 100, an interface layer 200, a service layer 300, and a storage layer 400;
the front-end layer 100 is used for providing a human-computer interaction interface so as to obtain a user request and obtain feedback data responding to the user request;
it is understood that the front-end layer 100 is primarily for human-computer interaction of users with the background microservices.
The interface layer 200 is configured to receive a user request of the front end layer 100 and real-time monitoring data in an SIS system of an external power plant based on an API gateway service, send the user request and the real-time monitoring data to the service layer 300 in a message queue, and send feedback data to the front end layer 100 after receiving feedback data, which is sent by the service layer 300 and responds to the user request;
it should be noted that the interface layer 200 provides an external API gateway service, which can simultaneously collect real-time monitoring data in a plurality of SIS systems of an external power plant, so as to improve monitoring efficiency and performance.
The service layer 300 is configured to execute a preset application micro-server according to the real-time monitoring data to obtain feedback data responding to the user request, and further configured to send the feedback data to the interface layer 200 and the storage layer 400, respectively, where the preset application micro-server includes a denitration efficiency prediction micro-server, a coal quality real-time measurement micro-server, a consumption difference analysis micro-server, and a boiler thermal efficiency analysis micro-server;
it is understood that the service layer 300 may respond to a user request through the denitration efficiency prediction micro-server, the coal quality real-time measurement micro-server, the consumption difference analysis micro-server, and the boiler thermal efficiency analysis micro-server according to the real-time monitoring data to provide an on-line calculation function.
In this embodiment, the real-time monitoring data in the SIS system includes boiler design data, environmental data, flue gas data, preheater data, and boiler monitoring data.
The storage layer 400 is used for storing data after receiving the real-time monitoring data and the feedback data sent by the interface layer 200 and the service layer 300, respectively.
In this embodiment, the storage layer 400 includes a Mysql database cluster and a big data storage module, and the big data storage database includes a mysq relational database to implement business data storage; the HDFS distributed file database realizes reliable storage of unstructured data; and the fastDFS distributed file database realizes storage of picture data.
Further, the architecture layer further includes a container layer 500, which is used for creating a container based on the docker engine, arranging a relationship between the container and the preset application micro server, and scheduling resources for the preset application micro server. Thereby simplifying system deployment and optimizing operation and maintenance processes.
It can be understood that the user request of the front end layer 100 and the real-time monitoring data of the SIS system are obtained in real time through the interface layer 200, the real-time monitoring data are calculated on line through the service layer 300 so as to push the feedback data responding to the user request to the front end layer 100, and the real-time monitoring data and the feedback data are stored, so that the operation state of the power plant can be monitored in real time, the data storage and visualization can be realized, the calculation by adopting historical data is not needed, the monitoring accuracy and timeliness are improved, meanwhile, the monitoring is also carried out in a data transmission mode, and the performance stability of the system is improved.
For ease of understanding, reference is made to FIG. 2, which provides a detailed description of an embodiment of the invention.
In the present embodiment, the front-end layer 100 includes a web application server 102 and a client 101;
the web application server 102 interacts with the interface layer 200 and the service layer 300, respectively, and the client 101 is configured to send a user request to the web application server 102 and obtain feedback data responding to the user request through the web application server 102.
It should be noted that the client 101 includes a computer and a mobile phone, and the web application server 102 performs data transmission to the client 101 through the ethernet.
In this embodiment, the interface layer 200 includes an API gateway service cluster 201, a message access micro service cluster 202, and a Kafka message server cluster 203;
the API gateway service cluster 201 is used for providing a user access entrance and establishing a data interaction relationship with the client 101 and the SIS system 600 of the external power plant respectively, so as to obtain a user request and real-time monitoring data;
the message access micro-service cluster 202 is used for receiving real-time monitoring data sent by the SIS system 600 of the external power plant through a transmission protocol;
in this embodiment, the transmission protocol is tcp transmission protocol, udp transmission protocol, or ws transmission protocol.
It should be noted that, in this embodiment, the API gateway service cluster 201 and the message access microservice cluster 202 perform horizontal expansion, which is beneficial to enhancing service capability, increasing concurrent processing amount, and implementing the extension of the whole system.
The Kafka message server cluster 203 is configured to receive a user request and real-time monitoring data sent by the API gateway service cluster 201 and real-time monitoring data sent by the message access micro service cluster 202, further configured to perform category division on the real-time monitoring data according to a preset subject topic category, further configured to perform data caching on the user request and the real-time monitoring data in a message queue manner to implement peak clipping and splitting, and further configured to receive feedback data pushed by the service layer 300 and send the feedback data to the web application server 102.
It should be noted that, because the real-time monitoring data in the SIS system 600 of the power plant corresponds to different devices, such as boiler devices, coal mill devices, and SCR flue gas devices, the number of the monitoring data at the same time is as many as ten thousand, and because the concurrency is large, after the real-time monitoring data is acquired, the real-time monitoring data is cached in the Kafka message server cluster 203 first, and the real-time monitoring data in the SIS system 600 is classified according to the topic category, so that the mapping relationship between the real-time monitoring data and the topic category is constructed, and the data type classification of the Kafka message server cluster 203 is realized, so that the data is prepared for subsequent storage and process processing. Meanwhile, data caching is carried out on the user request and the real-time monitoring data in a message queue mode to achieve peak clipping and shunting, and a receiving and sending concurrent function can be provided, so that timeliness of data processing and system performance stability are improved.
Meanwhile, feedback data pushed by the service layer 300 is received and sent to the web application server 102 in a websocket manner, so that the feedback data is displayed on the client 101, and data visualization is realized.
In the present embodiment, as shown in fig. 3, the service layer 300 includes a service registration and discovery cluster 301, a protocol resolution microservice cluster 303, and a microservice cluster 302;
the service registration and discovery cluster 301 is respectively in data interaction with the API gateway service cluster 201 and the micro service cluster 302, and is used for respectively performing server registration and service discovery on the API gateway service cluster 201 and the micro service cluster 302, and also performing corresponding micro service gray release processing on micro service applications in the micro service cluster 302;
the protocol analysis micro service cluster 303 is respectively in data interaction with the Kafka message server cluster 203 and the micro service cluster 302, and the protocol analysis micro service cluster 303 is used for carrying out protocol body analysis on real-time monitoring data and respectively pushing the real-time monitoring data after the protocol body analysis to the micro service cluster 302 and the storage layer 400;
it should be noted that the protocol parsing microservice cluster 303 and the microservice cluster 302 implement data interaction, and the data interaction is performed by using http to access the rest api.
The data interaction between the micro-service cluster 302 and the Kafka message server cluster 203 comprises a denitration efficiency prediction micro-server cluster 3021, a coal quality real-time measurement micro-server cluster 3022, a consumption difference analysis micro-server cluster 3023, a boiler thermal efficiency analysis micro-server cluster 3024, a threshold alarm analysis micro-server cluster 3025, a change rate analysis micro-server cluster 3026, and a data result push cluster 3027;
it should be noted that the data interaction between the microservice cluster 302 and the Kafka message server cluster 203 is performed by using the publish-subscribe mode of the Kafka message server cluster 203.
The denitration efficiency prediction micro-server cluster 3021 is configured to obtain denitration efficiency prediction data according to the real-time monitoring data through a preset denitration efficiency prediction model;
the coal quality real-time measurement micro-server cluster 3022 is configured to obtain coal quality measurement data through a preset coal quality real-time measurement model according to the real-time monitoring data;
the consumption difference analysis micro server cluster 3023 is configured to obtain consumption difference data through a preset consumption difference analysis model according to the real-time monitoring data;
the boiler thermal efficiency analysis micro-server cluster 3024 is configured to obtain boiler thermal efficiency data according to the real-time monitoring data through a preset boiler thermal efficiency analysis model;
the threshold alarm analysis micro server cluster 3025 is configured to obtain threshold alarm data through a preset threshold alarm analysis model according to the real-time monitoring data;
the change rate analysis micro server cluster 3026 is configured to obtain change rate data through a preset change rate analysis model according to the real-time monitoring data;
the data result pushing cluster 3027 is configured to push the data result calculated by the microservice cluster 302 to the Kafka message server cluster 203.
In this embodiment, the service layer 300 further includes a service monitoring module, configured to monitor an application process of the micro-service application in the micro-service cluster 302, and further configured to send a maintenance signal to the client 101 after monitoring that the application process of the micro-service application has a failure.
It can be understood that the service monitoring module provides application service monitoring and support system monitoring, and improves the operation and maintenance performance and reliability of the whole system.
In this embodiment, the service layer 300 further includes an authentication service cluster, configured to perform unified authentication on users accessing the API gateway service cluster 201, so as to determine access rights of the accessing users.
It can be understood that, when the user accesses the API gateway to send an access request, the authentication service cluster obtains a login ticket carried by the user access, and verifies the login ticket carried by the user access according to the locally cached preset login ticket, thereby responding to the access request.
Meanwhile, in order to improve data stability, a firewall is further provided between the SIS system 600 and the system. The data interaction mode of the embodiment adopts a local area network in the power plant to transmit data so as to improve the reliability and the safety of the data.
It should be noted that, for convenience of understanding, please refer to fig. 4, and a specific working flow of the present embodiment is as follows.
101. A user sends a user request to an API gateway service cluster through a client, wherein the user request comprises a denitration efficiency prediction request, a coal quality real-time measurement request, a consumption difference analysis request, a boiler thermal efficiency analysis request, a threshold alarm analysis request and a change rate analysis request;
102. after receiving a user request, the API gateway service cluster acquires real-time monitoring data in an SIS (SIS) system of an external power plant through the message access micro service cluster and the API gateway service cluster, and the real-time monitoring data is transmitted to the message access micro service cluster and the API gateway service cluster in a real-time streaming mode;
103. pushing the real-time monitoring data to a Kafka message server cluster for caching;
104. after the real-time monitoring data is cached by a Kafka message server cluster, pushing the real-time monitoring data to a protocol analysis micro-service cluster for protocol body analysis;
105. real-time monitoring data analyzed by the protocol body are respectively sent to the micro-service cluster and the storage layer 400, so that online calculation and storage are performed;
106. in the micro-service cluster, calculating real-time monitoring data through micro-service application to obtain feedback data responding to a user request;
107. and pushing the feedback data to a Kafka message server cluster for caching, and then sending the feedback data to a web application server so as to display the feedback data at a client.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, 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 application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated 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, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for executing all or part of the steps of the method described in the embodiments of the present application through a computer device (which may be a personal computer, a server, or a network device). And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should 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; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (10)
1. A coal fired power plant boiler monitoring visualization system is characterized in that the architecture level comprises: the system comprises a front-end layer, an interface layer, a service layer and a storage layer;
the front-end layer is used for providing a human-computer interaction interface so as to obtain a user request and obtain feedback data responding to the user request;
the interface layer is used for receiving the user request of the front end layer and real-time monitoring data in an SIS (service information system) of an external power plant based on API (application program interface) gateway service, sending the user request and the real-time monitoring data to the service layer in a message queue manner, and sending the feedback data to the front end layer after receiving the feedback data which is sent by the service layer and responds to the user request;
the service layer is used for executing a preset application micro server according to the real-time monitoring data so as to obtain the feedback data responding to the user request, and is also used for respectively sending the feedback data to the interface layer and the storage layer, wherein the preset application micro server comprises a denitration efficiency prediction micro server, a coal quality real-time measurement micro server, a consumption difference analysis micro server and a boiler thermal efficiency analysis micro server;
and the storage layer is used for storing data after receiving the real-time monitoring data and the feedback data sent by the interface layer and the service layer respectively.
2. The coal-fired power plant boiler monitoring visualization system of claim 1, wherein the architecture level further comprises a container level for creating a container based on a docker engine, for orchestrating a relationship between the container and the preset application micro server, and for resource scheduling of the preset application micro server.
3. The coal fired power plant boiler monitoring visualization system of claim 1, wherein the front end tier includes a web application server and a client;
the web application server interacts with the interface layer and the service layer respectively, and the client is used for sending a user request to the web application server and obtaining the feedback data responding to the user request through the web application server.
4. The coal fired power plant boiler monitoring visualization system of claim 3, characterized in that the client comprises a computer, a mobile phone.
5. The coal fired power plant boiler monitoring visualization system of claim 3, wherein the interface layer comprises an API gateway service cluster, a message access microservice cluster and a Kafka message server cluster;
the API gateway service cluster is used for providing a user access entrance and establishing a data interaction relation with the client and an SIS (service information system) of the external power plant respectively so as to obtain the user request and the real-time monitoring data;
the message access micro-service cluster is used for receiving the real-time monitoring data sent by the SIS system of the external power plant through a transmission protocol;
the Kafka message server cluster is configured to receive the user request and the real-time monitoring data sent by the API gateway service cluster and the real-time monitoring data sent by the message access micro service cluster, and is further configured to perform category division on the real-time monitoring data according to a preset topic category, and is further configured to perform data caching on the user request and the real-time monitoring data in a message queue manner to implement peak clipping and splitting, and is further configured to receive the feedback data pushed by the service layer and send the feedback data to the web application server.
6. The coal fired power plant boiler monitoring visualization system of claim 5, wherein the transmission protocol is a tcp transmission protocol, a udp transmission protocol or a ws transmission protocol.
7. The coal fired power plant boiler monitoring visualization system of claim 5, wherein the service layer comprises a service registration and discovery cluster, a protocol resolution microservice cluster and a microservice cluster;
the service registration and discovery cluster is respectively interacted with the API gateway service cluster and the micro-service cluster in data, is used for respectively carrying out server registration and service discovery on the API gateway service cluster and the micro-service cluster, and is also used for carrying out corresponding micro-service gray-scale release processing on micro-service applications in the micro-service cluster;
the protocol analysis micro-service cluster is respectively in data interaction with the Kafka message server cluster and the micro-service cluster, and is used for carrying out protocol body analysis on the real-time monitoring data and respectively pushing the real-time monitoring data after the protocol body analysis to the micro-service cluster and the storage layer;
the micro-server cluster and the Kafka message server cluster perform data interaction, and the data interaction comprises a denitration efficiency prediction micro-server cluster, a coal quality real-time measurement micro-server cluster, a consumption difference analysis micro-server cluster, a boiler thermal efficiency analysis micro-server cluster, a threshold value alarm analysis micro-server cluster, a change rate analysis micro-server cluster and a data result pushing cluster;
the denitration efficiency prediction micro-server cluster is used for obtaining denitration efficiency prediction data through a preset denitration efficiency prediction model according to the real-time monitoring data;
the coal quality real-time measurement micro-server cluster is used for obtaining coal quality measurement data through a preset coal quality real-time measurement model according to the real-time monitoring data;
the consumption difference analysis micro server cluster is used for obtaining consumption difference data through a preset consumption difference analysis model according to the real-time monitoring data;
the boiler thermal efficiency analysis micro-server cluster is used for obtaining boiler thermal efficiency data through a preset boiler thermal efficiency analysis model according to the real-time monitoring data;
the threshold alarm analysis micro-server cluster is used for obtaining threshold alarm data through a preset threshold alarm analysis model according to the real-time monitoring data;
the change rate analysis micro server cluster is used for obtaining change rate data through a preset change rate analysis model according to the real-time monitoring data;
and the data result pushing cluster is used for pushing the data result obtained by the calculation of the micro service cluster to the Kafka message server cluster.
8. The coal-fired power plant boiler monitoring visualization system of claim 7, wherein the service layer further comprises a service monitoring module, configured to monitor an application process of the micro-service application in the micro-service cluster, and further configured to send a maintenance signal to the client when it is monitored that the application process of the micro-service application has a failure.
9. The coal fired power plant boiler monitoring visualization system of claim 7, wherein the service layer further comprises an authentication service cluster for performing unified authentication on users accessing the API gateway service cluster, thereby determining access rights of the users.
10. The coal fired power plant boiler monitoring visualization system of claim 1 or 7, characterized in that the storage tier comprises a Mysql database cluster and a big data storage module.
Priority Applications (1)
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