CN114440205A - Safety diagnosis system and method for heating surface of boiler system - Google Patents
Safety diagnosis system and method for heating surface of boiler system Download PDFInfo
- Publication number
- CN114440205A CN114440205A CN202210238250.3A CN202210238250A CN114440205A CN 114440205 A CN114440205 A CN 114440205A CN 202210238250 A CN202210238250 A CN 202210238250A CN 114440205 A CN114440205 A CN 114440205A
- Authority
- CN
- China
- Prior art keywords
- heating surface
- boiler
- server
- sis
- safety
- 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
- 238000010438 heat treatment Methods 0.000 title claims abstract description 57
- 238000003745 diagnosis Methods 0.000 title claims abstract description 18
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000012544 monitoring process Methods 0.000 claims abstract description 21
- 238000004458 analytical method Methods 0.000 claims abstract description 11
- 238000004891 communication Methods 0.000 claims abstract description 6
- 230000003993 interaction Effects 0.000 claims abstract description 5
- 238000004364 calculation method Methods 0.000 claims description 18
- 238000004939 coking Methods 0.000 claims description 16
- 230000008021 deposition Effects 0.000 claims description 16
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 11
- 239000003546 flue gas Substances 0.000 claims description 11
- 230000006870 function Effects 0.000 claims description 5
- 239000003245 coal Substances 0.000 abstract description 14
- 239000002893 slag Substances 0.000 abstract description 6
- 238000012546 transfer Methods 0.000 abstract description 5
- 238000009825 accumulation Methods 0.000 abstract description 3
- 238000007405 data analysis Methods 0.000 abstract description 2
- 230000015572 biosynthetic process Effects 0.000 abstract 2
- 238000005516 engineering process Methods 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 239000007789 gas Substances 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 238000012216 screening Methods 0.000 description 3
- 239000004071 soot Substances 0.000 description 3
- 238000003708 edge detection Methods 0.000 description 2
- 238000010191 image analysis Methods 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 238000012731 temporal analysis Methods 0.000 description 2
- 238000000700 time series analysis Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 239000000779 smoke Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F22—STEAM GENERATION
- F22B—METHODS OF STEAM GENERATION; STEAM BOILERS
- F22B37/00—Component parts or details of steam boilers
- F22B37/02—Component parts or details of steam boilers applicable to more than one kind or type of steam boiler
- F22B37/38—Determining or indicating operating conditions in steam boilers, e.g. monitoring direction or rate of water flow through water tubes
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F22—STEAM GENERATION
- F22B—METHODS OF STEAM GENERATION; STEAM BOILERS
- F22B35/00—Control systems for steam boilers
- F22B35/18—Applications of computers to steam boiler control
Abstract
The invention relates to the technical field of safety monitoring, in particular to a boiler system heating surface safety diagnosis system and a method, which comprises an integrated server, a data acquisition module and a data analysis module, wherein the integrated server is used for receiving real-time monitoring data acquired from a power plant SIS or PI system and carrying out operation analysis; the interface machine is used for communication bridging and transmitting real-time monitoring data acquired from the power plant SIS or PI system to the comprehensive server in an OPC interface form; and the browser client realizes interaction with the system function module through the Web server. The invention solves the problems that the heat transfer coefficient is reduced, the heat exchange is deteriorated, the exhaust gas temperature is increased, the boiler efficiency is reduced, and the ash accumulation and slag formation problems of the boiler become serious because the operating coal type of a power plant often has great deviation with the designed coal type after ash accumulation and slag formation on the surface of the heating surface of the coal-fired boiler.
Description
Technical Field
The invention relates to the technical field of safety monitoring, in particular to a system and a method for safely diagnosing a heating surface of a boiler system.
Background
In order to realize the safety diagnosis of the heating surface of the boiler, the safety management system of the heating surface of the boiler is constructed by matching different subsystems, and mainly comprises a four-pipe management and overtemperature early warning system, a heating surface coking monitoring system and an ash recognition early warning system.
One-pipe and four-pipe management and overtemperature early warning system
The system firstly adds 65 wall temperature measuring points according to a technical specification, automatically tracks the wall temperature trend by collecting the history and real-time data (and other operation data related to wall temperature management) of mass wall temperature monitoring of the boiler and combining big data analysis and a machine learning algorithm, provides early warning of over-temperature parts, amplitude and grading, displays the visual and quantitative data, and is convenient for operators to check and track daily.
Heating surface coking monitoring system
The coking and slagging phenomena of the heating surface seriously threaten the safety of the heating surface of the pulverized coal boiler. To solve the problem, the system carries out direct monitoring on the ash deposition dynamics through optical means. By means of an optical method, advanced image analysis technology and intelligent algorithm are combined, and the ash deposition and slagging states of all heating surfaces in the furnace can be intuitively acquired.
Ash and slag identifying and early warning system
Observing the coking state of part of the heating surface of the boiler by adopting a high-temperature resistant boiler coking detection system, and outputting a real-time monitoring image; and analyzing the shot ash image by adopting an image analysis technology to obtain visual representation of the ash accumulation and slagging state of the heating surface in the furnace.
The research on the management of the wall temperature of the four pipes and the overtemperature early warning mechanism is to combine a data mining technology and a mathematical statistical method and determine a reference value of the unit under multiple working conditions by learning historical data; analyzing the distribution of the four-tube wall temperature based on the nuclear density estimation, and determining the early warning level; and according to the deviation degree of the actual wall temperature operating parameters and the reference value, the average value in the window time is counted by combining a sliding window detection technology, so that the overtemperature early warning of four pipes is realized.
The research content of the part mainly comprises: steady state screening and working condition division, reference value under wall temperature multi-working condition and overtemperature early warning research.
(1) Steady state screening and working condition division: and collecting and sorting historical operating data, design data and thermal performance experimental data of the unit to establish a historical database. Considering the objective condition that the operation condition of the coal-electric unit is always in a dynamic change process to meet the peak regulation requirement of a power grid, steady-state screening is carried out on historical data so as to remove a large amount of unsteady-state operation data mixed in the historical data and determine a steady-state condition library. On the basis, the working conditions are divided according to boundary conditions such as load, ambient temperature and the like.
(2) Determining a reference value under multiple working conditions of wall temperature: clustering wall temperature historical data based on an FCM clustering algorithm, determining the optimal classification number by combining with a Silhouette clustering effective evaluation function, and selecting a clustering center as a reference value.
(3) Wall temperature overtemperature warning: based on the sliding window detection technology, the influence of uncertain factors, random interference (such as measurement errors of a sensor) and the like on the wall temperature during the operation of the unit is solved. The overtemperature grade is determined by counting the average value of the wall temperature in the window time, the uncertain interference is eliminated, and the early warning accuracy and reliability are improved. As shown in fig. 1.
The method comprises the following steps of detecting the outline of a coking area by using an edge detection method in image processing in the coking diagnosis of the heating surface of the power station boiler. Image edges are a reflection of discontinuities in the local characteristics of an image that mark the end of one region and the beginning of another region. Edge detection first detects discontinuities in the local characteristics of the image and then connects the discrete edge pixels together to form an edge. In combination with other image processing methods, the coking region is separated from the background region. The shape of the coking zone is often an irregular geometric shape, and quantitative parameters are selected to describe these irregular areas. The shape of the coking zone changes over time. The pixel gray scale distribution (probability distribution) inside the coking area also changes with time.
The characteristic parameters (parameters for describing coking areas) are quantitatively described on the basis of a time series analysis technology, and commonly used time series analysis models comprise an autoregressive model, a moving average model, an autoregressive differential moving average model, a generalized autoregressive conditional variance model and the like.
Disclosure of Invention
Aiming at the defects of the prior art, the invention discloses a system and a method for safely diagnosing a heating surface of a boiler system, which are used for solving the problems that the heat transfer coefficient is reduced and the heat exchange is deteriorated after ash and slag are deposited on the surface of the heating surface of a coal-fired boiler, so that the exhaust gas temperature is increased and the boiler efficiency is reduced. In addition, the operating coal type of the power plant often has great deviation from the designed coal type, so that the problem of boiler ash deposition and slag bonding becomes serious.
The invention is realized by the following technical scheme:
in a first aspect, the present invention provides a safety diagnostic system for a heating surface of a boiler system, comprising
The comprehensive server is used for receiving the real-time monitoring data acquired from the power plant SIS or PI system and carrying out operation analysis;
the interface machine is used for communication bridging and transmitting real-time monitoring data acquired from the power plant SIS or PI system to the comprehensive server in an OPC interface form;
and the browser client realizes interaction with the system function module through the Web server.
Furthermore, the comprehensive server comprises a four-pipe overtemperature early warning model, a coking recognition model and an ash recognition model.
Furthermore, after the comprehensive server performs operation analysis on the real-time data, the calculation result is stored in the relational database.
Further, the integrated Server is a Windows Server 2010.
Furthermore, the front end of the integrated server is written by adopting Java language.
Further, the relational database employs Mysql.
Furthermore, when the relational database adopts a field self-prepared SIS or PI database, the front end adopts a language compatible with the SIS to write.
Furthermore, when the relational database adopts a field self-prepared SIS or PI database, the comprehensive server stores the calculation result into an SIS database server.
Furthermore, the System is developed in the Browse/System architecture model.
In a second aspect, the invention provides a safety diagnosis method for a heating surface of a boiler system, which uses the safety diagnosis system for the heating surface of the boiler system in the first aspect, and establishes an online calculation model for the ash deposition thickness of an ash layer on a pipe wall of a convection heating surface by monitoring parameters such as flue gas flow resistance, flue gas temperature and flue gas flow rate of each convection heating surface in a stable state and combining the structure of each convection heating surface, so as to perform safety diagnosis on the heating surface of the boiler system.
The invention has the beneficial effects that:
according to the invention, by measuring the front-back pressure difference and the temperature of each convection heating surface of the boiler, combining the structural parameters of each convection heating surface of the boiler, according to the element analysis of coal types combusted by a unit, the air leakage coefficient of the unit and the like, a calculation model of ash deposition thickness is planned to be developed by programming, and a real-time calculation result is issued to a WEB display interface, so that a client can access the calculation model based on a browser mode, and the problems that the heat transfer coefficient is reduced, the heat exchange is deteriorated, the exhaust gas temperature is increased, the boiler efficiency is reduced, and the operating coal types of a power plant often deviate from the designed coal types, so that the problem of ash deposition and slag bonding of the boiler becomes serious are solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a wall temperature warning diagram based on sliding window technology;
FIG. 2 is a diagram of an on-line monitoring system for the thickness of soot on the convection heating surface;
FIG. 3 is a block diagram of a safety diagnostic system for heating surfaces of a boiler system according to embodiment 1;
FIG. 4 is a scheme 1 system data flow process diagram;
FIG. 5 is a block diagram of a safety diagnostic system for a heated surface of a boiler system according to scheme 2;
fig. 6 is a diagram of a scheme 2 system data flow process.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
The embodiment provides a safety diagnosis method for a heating surface of a boiler system, which is used for establishing a model for directly calculating the ash deposition thickness of the convection heating surface of the boiler by using the pressure drop of flue gas according to the essential relationship between the ash deposition thickness of the surface of a pipe wall and the flow resistance of the flue gas.
Referring to fig. 2, in the embodiment, an online calculation model of the soot deposition thickness of the soot layer on the pipe wall of the convection heating surface is established by monitoring parameters such as the flue gas flow resistance, the flue gas temperature and the flue gas flow rate of each convection heating surface in a stable state and combining the structure of each convection heating surface.
The embodiment forms an online ash deposition calculation process pack for each convection heating surface of a tail flue of a boiler.
According to the method, by measuring the front-back pressure difference and the temperature of each convection heating surface of the boiler, combining the structural parameters of each convection heating surface of the boiler, according to the element analysis of the coal burned by the unit, the air leakage coefficient of the unit and the like, a calculation model of the accumulated ash thickness is planned to be developed by programming, the real-time calculation result is issued to a WEB display interface, and a client can access the calculation mode based on a browser.
Example 2
The embodiment provides a safety diagnosis system for a heating surface of a boiler system, which comprises
The comprehensive server is used for receiving the real-time monitoring data acquired from the power plant SIS or PI system and carrying out operation analysis;
the interface machine is used for communication bridging and transmitting real-time monitoring data acquired from the power plant SIS or PI system to the comprehensive server in an OPC interface form;
and the browser client realizes interaction with the system function module through the Web server.
The embodiment solves the problems that the surface of the heating surface of the coal-fired boiler can cause the heat transfer coefficient to become small and the heat exchange to deteriorate after ash deposition and slagging so as to cause the exhaust gas temperature to rise and the boiler efficiency to reduce, and the operating coal type of a power plant often has great deviation with the designed coal type so as to cause the ash deposition and slagging problem of the boiler to become serious.
Example 3
In a specific implementation level, the embodiment provides a boiler system heating surface safety diagnosis system framework in scheme 1.
The safety diagnosis System for the heating surface of the boiler System is developed based on a Browse/System (B/S) architecture mode, a relational database adopts Mysql, a Server System is a Windows Server 2010, and the front end is written in Java language.
The system of the embodiment includes three parts, namely an interface machine, an integrated server and a browser client, and the overall architecture of the system is as shown in fig. 3 and 4.
In the embodiment, real-time monitoring data are acquired from the power plant SIS or PI system through an OPC interface form and are sent to the comprehensive server.
The comprehensive server comprises a four-pipe overtemperature early warning model, a coking recognition model and an ash recognition model, real-time data obtained by communication of the interface machine is subjected to operation analysis through the comprehensive server, and a calculation result is stored in a Mysql database server.
The client accesses the Web server by using the browser to realize the interaction with the system function module.
Example 4
In a specific implementation level, the embodiment provides a boiler system heating surface safety diagnosis system framework in scheme 2.
The safety diagnosis System for the heating surface of the boiler System is developed based on a Browse/System (B/S) architecture mode, a relational database adopts a field self-prepared SIS or PI database, and the front end is written by adopting a language compatible with the SIS.
The system of the embodiment includes two parts, i.e., an integrated server and a browser client, and the overall architecture of the system is as shown in fig. 5 and 6.
The embodiment acquires real-time monitoring data from the power plant SIS or PI system and sends the data to the integrated server.
The comprehensive server comprises a four-pipe overtemperature early warning model, a coking identification model and an ash identification model, real-time data obtained by communication of an interface machine is subjected to operation analysis through the comprehensive server, and a calculation result is stored in an SIS database server; the client is accessed using a browser.
In conclusion, by measuring the front-back pressure difference and the temperature of each convection heating surface of the boiler, combining the structural parameters of each convection heating surface of the boiler, according to the element analysis of the coal types burned by the units, the air leakage coefficient of the units and the like, the invention plans to adopt a programming development ash deposition thickness calculation model, and issues the real-time calculation result to a WEB display interface, and a client can access the model based on a browser, thereby solving the problems that the heat transfer coefficient is reduced, the heat exchange is deteriorated after the ash deposition and slagging of the surface of the heating surface of the coal-fired boiler, the smoke temperature is increased, the boiler efficiency is reduced, and the ash deposition and slagging problem of the boiler becomes serious due to the fact that the operating coal types of a power plant often have large deviation from the designed coal types.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; 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; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A safety diagnosis system for the heating surface of boiler system is composed of
The comprehensive server is used for receiving the real-time monitoring data acquired from the power plant SIS or PI system and carrying out operation analysis;
the interface machine is used for communication bridging and transmitting real-time monitoring data acquired from the power plant SIS or PI system to the comprehensive server in an OPC interface form;
and the browser client realizes interaction with the system function module through the Web server.
2. The boiler system heating surface safety diagnostic system according to claim 1, wherein the integrated server comprises a four-pipe overtemperature early warning model, a coking identification model and an ash identification model.
3. The system of claim 2, wherein the integrated server stores the calculation results in the relational database after performing operation analysis on the real-time data.
4. The boiler system heating surface safety diagnostic system according to claim 2, wherein the integrated Server is a Windows Server 2010.
5. The boiler system heating surface safety diagnostic system according to claim 2, wherein the integrated server front end is written in Java language.
6. The system of claim 1, wherein the relational database is Mysql.
7. The boiler system heating surface safety diagnostic system according to claim 1, wherein the relational database is written in an SIS compatible language when a site-owned SIS or PI database is used as the front end.
8. The boiler system heating surface safety diagnostic system according to claim 7, wherein when the relational database is a site-owned SIS or PI database, the integrated server stores the calculation result to an SIS database server.
9. The System of claim 1, wherein the System is developed in a Browse/System architecture model.
10. A safety diagnosis method for a heating surface of a boiler system, which uses the safety diagnosis system for the heating surface of the boiler system as claimed in any one of claims 1 to 9, and is characterized in that the method establishes an online calculation model for the ash deposition thickness of an ash layer on a pipe wall of a convection heating surface by monitoring parameters such as flue gas flow resistance, flue gas temperature and flue gas flow rate of each convection heating surface in a stable state and combining the structure of each convection heating surface, and thereby carries out safety diagnosis on the heating surface of the boiler system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210238250.3A CN114440205A (en) | 2022-03-11 | 2022-03-11 | Safety diagnosis system and method for heating surface of boiler system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210238250.3A CN114440205A (en) | 2022-03-11 | 2022-03-11 | Safety diagnosis system and method for heating surface of boiler system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114440205A true CN114440205A (en) | 2022-05-06 |
Family
ID=81359699
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210238250.3A Pending CN114440205A (en) | 2022-03-11 | 2022-03-11 | Safety diagnosis system and method for heating surface of boiler system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114440205A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116399400A (en) * | 2023-04-13 | 2023-07-07 | 大唐绥化热电有限公司 | Method and system for detecting operation faults of boiler unit |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010025747A (en) * | 2008-07-18 | 2010-02-04 | Chugoku Electric Power Co Inc:The | Remaining life measuring system |
| CN202118880U (en) * | 2011-06-10 | 2012-01-18 | 张慧 | Early warning system of intelligent soot blowing optimization and online coking of boiler |
| CN202582601U (en) * | 2012-04-25 | 2012-12-05 | 青岛斌正仪表技术有限公司 | Cogeneration boiler heating surface state detection, analysis and management system |
| CN104808634A (en) * | 2015-04-24 | 2015-07-29 | 中国神华能源股份有限公司 | Thermal power plant visual management system based on virtual reality |
| CN106642059A (en) * | 2016-12-08 | 2017-05-10 | 国电龙源电力技术工程有限责任公司 | Safety online monitoring method for high-temperature heated faces of utility boiler |
| CN109140474A (en) * | 2018-09-11 | 2019-01-04 | 北京巴布科克·威尔科克斯有限公司 | A kind of coal-fired power station boiler manually intelligent sootblowing |
| CN109458610A (en) * | 2018-11-09 | 2019-03-12 | 华为三立(北京)能源科技有限公司 | Thermal power station's boiler diagnoses early warning system and device |
| CN111550763A (en) * | 2020-01-20 | 2020-08-18 | 张铭源 | Method for monitoring ash pollution on heating surface of boiler |
| CN112283689A (en) * | 2020-10-29 | 2021-01-29 | 西安工业大学 | On-line monitoring system and detection method for accumulated ash on heating surface of coal-fired power station boiler |
| CN112283731A (en) * | 2020-10-27 | 2021-01-29 | 广东电科院能源技术有限责任公司 | Soot blowing method and system for heating surface of coal-fired power station boiler |
| CN113361192A (en) * | 2021-05-31 | 2021-09-07 | 浙江大学 | Boiler internal heating surface wall temperature safety monitoring and evaluating system |
| CN217423214U (en) * | 2022-03-11 | 2022-09-13 | 国家能源集团山西电力有限公司 | Safety diagnosis system for heating surface of boiler system |
-
2022
- 2022-03-11 CN CN202210238250.3A patent/CN114440205A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010025747A (en) * | 2008-07-18 | 2010-02-04 | Chugoku Electric Power Co Inc:The | Remaining life measuring system |
| CN202118880U (en) * | 2011-06-10 | 2012-01-18 | 张慧 | Early warning system of intelligent soot blowing optimization and online coking of boiler |
| CN202582601U (en) * | 2012-04-25 | 2012-12-05 | 青岛斌正仪表技术有限公司 | Cogeneration boiler heating surface state detection, analysis and management system |
| CN104808634A (en) * | 2015-04-24 | 2015-07-29 | 中国神华能源股份有限公司 | Thermal power plant visual management system based on virtual reality |
| CN106642059A (en) * | 2016-12-08 | 2017-05-10 | 国电龙源电力技术工程有限责任公司 | Safety online monitoring method for high-temperature heated faces of utility boiler |
| CN109140474A (en) * | 2018-09-11 | 2019-01-04 | 北京巴布科克·威尔科克斯有限公司 | A kind of coal-fired power station boiler manually intelligent sootblowing |
| CN109458610A (en) * | 2018-11-09 | 2019-03-12 | 华为三立(北京)能源科技有限公司 | Thermal power station's boiler diagnoses early warning system and device |
| CN111550763A (en) * | 2020-01-20 | 2020-08-18 | 张铭源 | Method for monitoring ash pollution on heating surface of boiler |
| CN112283731A (en) * | 2020-10-27 | 2021-01-29 | 广东电科院能源技术有限责任公司 | Soot blowing method and system for heating surface of coal-fired power station boiler |
| CN112283689A (en) * | 2020-10-29 | 2021-01-29 | 西安工业大学 | On-line monitoring system and detection method for accumulated ash on heating surface of coal-fired power station boiler |
| CN113361192A (en) * | 2021-05-31 | 2021-09-07 | 浙江大学 | Boiler internal heating surface wall temperature safety monitoring and evaluating system |
| CN217423214U (en) * | 2022-03-11 | 2022-09-13 | 国家能源集团山西电力有限公司 | Safety diagnosis system for heating surface of boiler system |
Non-Patent Citations (1)
| Title |
|---|
| 王仲: "基于历史数据聚类的火电机组工况划分", 《仪器仪表学报》, vol. 40, no. 2, 28 February 2019 (2019-02-28), pages 90 - 95 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116399400A (en) * | 2023-04-13 | 2023-07-07 | 大唐绥化热电有限公司 | Method and system for detecting operation faults of boiler unit |
| CN116399400B (en) * | 2023-04-13 | 2023-12-15 | 大唐绥化热电有限公司 | Method and system for detecting operation faults of boiler unit |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN217423214U (en) | Safety diagnosis system for heating surface of boiler system | |
| US20130297374A1 (en) | Targeted Equipment Monitoring System and Method for Optimizing Equipment Reliability | |
| CN112285287B (en) | Flue gas online monitoring data preprocessing method | |
| CN112906787A (en) | Industrial boiler fault identification method and system | |
| CN104808634A (en) | Thermal power plant visual management system based on virtual reality | |
| CN111651933B (en) | Industrial boiler fault early warning method and system based on statistical inference | |
| CN110750872A (en) | Boiler metal wall temperature data analysis system and method | |
| CN106649919A (en) | Method and system for predicting carbon content of fly ash in coal-fired power plant boiler | |
| CN116681187B (en) | Enterprise carbon quota prediction method based on enterprise operation data | |
| CN111550763A (en) | Method for monitoring ash pollution on heating surface of boiler | |
| CN114440205A (en) | Safety diagnosis system and method for heating surface of boiler system | |
| CN107450428A (en) | A kind of main transformer oil level method for real-time monitoring equivalent based on translation | |
| CN108168659A (en) | A kind of vortex-shedding meter intelligent diagnosing method | |
| CN114519923A (en) | Intelligent diagnosis and early warning method and system for power plant | |
| CN117196159A (en) | Intelligent water service partition metering system based on Internet big data analysis | |
| CN112989694B (en) | Segmented monitoring system and method for ash on heating surface | |
| CN112489194A (en) | Method and system for displaying account information and boiler four-tube information in three-dimensional scene | |
| CN109469919A (en) | A kind of stifled grey monitoring method of power station air preheater based on weight cluster | |
| CN105302476B (en) | A kind of reliability data online acquisition for nuclear power plant equipment analyzes storage system and its storage method | |
| CN116805065A (en) | Intelligent management method for monitoring data of coal powder heating furnace burner | |
| CN115469585B (en) | Hydropower unit state monitoring method and system based on big data | |
| CN116429269A (en) | Infrared intelligent analysis system for ethylene cracking furnace tube | |
| CN116384732A (en) | Intelligent assessment method, system, storage medium and computing device for station pipeline risk | |
| CN207112772U (en) | Boiler hearth temperature on-line prediction system based on core offset minimum binary | |
| CN114881470A (en) | Data-based waste incineration power generation pollutant emission risk diagnosis and early warning method |
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 |