CN105758661B - Boiler heating surface service life evaluation system and method - Google Patents
Boiler heating surface service life evaluation system and method Download PDFInfo
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- CN105758661B CN105758661B CN201610289777.3A CN201610289777A CN105758661B CN 105758661 B CN105758661 B CN 105758661B CN 201610289777 A CN201610289777 A CN 201610289777A CN 105758661 B CN105758661 B CN 105758661B
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Abstract
The application relates to a boiler heating surface service life assessment system and method, which comprises a detection device, a data processing device, an analysis device and a monitoring system, wherein the detection device is sequentially connected with the data processing device and the analysis device, and the analysis device analyzes data and transmits the data to the monitoring system; the method is characterized in that: the service life prediction and analysis device comprises a trend prediction and analysis device and a service life calculation device, wherein the trend prediction and analysis device performs future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method, the service life calculation device determines the residual service life, reversely verifies whether the trend analysis of the trend prediction and analysis device is correct, and makes a suggested operation strategy for prolonging the service life. This application can carry out the life-span prediction, carries out reverse verification simultaneously, and the life face of more effectual extension boiler improves the security performance.
Description
Technical Field
The present disclosure relates to systems and methods for estimating a lifetime of a heating surface of a boiler, and more particularly, to a system and method for estimating a lifetime of a heating surface of a boiler, which can predict and verify the lifetime of the heating surface of the boiler.
Background
The equipment running state detection and diagnosis is a very important research object in actual production and application, such as the running working condition of a boiler, and not only relates to the production efficiency, but also relates to the production safety, for example, Chinese invention application CN200810200502.3 discloses a thermal power plant superheated steam temperature abnormity self-diagnosis method, which faces the diagnosis information to on-site centralized control operators and provides a quick and simple method for the safe running and the maintenance of industrial equipment of a thermal power plant, but the application can only provide estimation diagnosis and can not predict the residual service life of the equipment; for example, a discussion on the evaluation of the service life of a heated surface pipe of a boiler (linlizhen, proceedings of the institute of electrical and occupational technology, jiang xi, vol. No. 18, No. 4) discloses that the service life of the heated surface of the boiler is evaluated, the service life loss is evaluated mainly by a service life loss score method and a parameter method, the evaluation result cannot be verified, a corresponding control strategy for prolonging the service life is not specified, and the problem of the service life of equipment cannot be well solved. Then, for the detection of the operation of the boiler and the life of the boiler which is related to the economical efficiency and safety of the actual operation, it is urgently needed to provide a system which can accurately carry out the comprehensive life evaluation on the boiler, so as to provide the safety protection and improve the economical operation for the operation equipment of enterprises or power plants.
Disclosure of Invention
In order to solve the technical problems: the application provides a boiler heating surface service life evaluation system which comprises a detection device, a data processing device, an analysis device and a monitoring system, wherein the detection device is sequentially connected with the data processing device and the analysis device, and the analysis device analyzes data and conveys the data to the monitoring system; the service life prediction and analysis device comprises a trend prediction and analysis device and a service life calculation device, wherein the trend prediction and analysis device performs future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method, the service life calculation device determines the residual service life, reversely verifies whether the trend analysis of the trend prediction and analysis device is correct, and makes a suggested operation strategy for prolonging the service life.
In any of the above embodiments, the detection device is preferably configured to detect data of at least one of thickness, creep, metallographic phase and mechanical properties.
In any of the above embodiments, preferably, the detection means detects the temperature of the access wall by a thermocouple.
In any of the above embodiments, the data processing device is preferably configured to perform AD conversion, screening, or screening of data and to eliminate unnecessary data.
In any of the above embodiments, the analysis device is preferably configured to analyze the screened or screened data and form a data perspective for transmission to a monitoring system.
In any of the above embodiments, preferably, the monitoring system includes a central processing unit, a signal transceiver, and a display, and the monitoring system can draw a wall temperature line graph in the thickness direction of the furnace, and has functions of data storage, query statistics, and data display.
In any of the above embodiments, preferably, the signal transceiver includes at least one of WIFI, bluetooth, ZIGBEE, GPRS, 3G, and 4G, or a combination thereof.
Any of the above embodiments preferably wherein the signal transceiver comprises a web server that evaluates data transmissions from static documents, dynamic documents without database access, dynamic documents with database access, or a combination of the three.
In any of the above embodiments, preferably, the monitoring system includes a data export or display device for exporting or displaying the data in a columnar or cake or excel manner.
In any of the above embodiments, preferably, the trend prediction analysis device classifies at least one of the thickness, creep, metallographic phase, and mechanical properties of the collected data and the historical data stored in the system according to the data output by the data processing device and the historical data, performs fitting processing, generates an equipment overhaul project trend analysis graph, and gives warning in different colors when significant upward abnormal protruding points occur in combination with the overhaul period and the wall temperature line graph.
In any of the above embodiments, preferably, the life calculating means calculates the remaining service life of the boiler according to the result of the trend predictive analysis by the trend predictive analyzing means and the input future operating condition, and makes an operation control strategy for prolonging the service life.
Any of the above embodiments preferably provides that the life calculating means is capable of sending the operation control policy to the monitoring system to provide a technician to adjust the operation mode of the boiler, or to an authorized mobile terminal specified by the technician according to the authority.
In any of the above embodiments, preferably, the monitoring system includes two redundant industrial personal computers.
A method for evaluating the service life of a heating surface of a boiler comprises the following steps:
1) detecting real-time data of a heating surface of the boiler;
2) performing AD conversion processing on the data, setting a data threshold value and screening useless data;
3) respectively inputting the collected and processed heating surface data into an analysis device and a trend prediction analysis device, analyzing the data through the analysis device, forming a data perspective and transmitting the data perspective to a monitoring system; the trend prediction analysis device carries out future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method; accumulating the over-temperature records by accessing wall temperature measuring point data, and calculating the creep loss service life caused by over-temperature;
4) and determining the residual service life through a service life calculating device, reversely verifying whether the trend analysis of the trend prediction analysis device is correct, and making a recommended operation strategy for prolonging the service life.
In any one of the above embodiments, the trend prediction analysis device may perform the operation trend analysis, including: 1a) acquiring online data, extracting offline historical data, selecting comprehensive data of the online data and the offline historical data, and determining characteristic parameters of the neural network; 2a) establishing a 4-layer neural network model consisting of an input layer, 2 hidden layers and an output layer; 3a) establishing a sample library and training the sample library, wherein the training is to take 2 input and output orders and determine the only output; 4a) and the output is used as the result of the operation trend analysis of the heating surface of the boiler, and whether the output is output to the service life calculating device is determined according to the result.
In any of the above embodiments, preferably, the step 4a) includes: the trend prediction analysis device determines the specific states of the heating surface of the boiler according to the analysis result, wherein the states comprise a high-risk state, a sub-health state and a normal operation state; when the system is in the high-risk state and the sub-health state, directly outputting the result to a monitoring system; immediately diagnosing faults and immediately determining a maintenance plan in the high-risk state; judging the defect trend of the sub-health state; and when in the normal operation state, outputting the result to the service life calculating device for carrying out reverse verification of service life prediction.
In any of the above embodiments, preferably, the performing of the reverse verification by the lifetime calculation means includes: 1b) data preprocessing, namely, the data input by the trend prediction analysis device are subjected to abnormal point verification, standardization or normalization processing; 2b) selecting a modeling direction, namely selecting one direction from the existing directions, setting the direction as i, and setting i as i +1 once every time i is selected, wherein i is greater than or equal to 1; 3b) selecting a modeling method; 4b) establishing a model; 5b) judging whether the modeling purpose is met or not, if yes, entering a step 6b), and if not, entering a step 2 b); 6b) an application model; 7b) and outputting a verification result, setting an operation strategy for prolonging the service life according to the verification result, and providing the operation strategy for technical personnel to select.
Preferably, in any of the above embodiments, the providing for selection by the operator includes sending the operation control policy to the monitoring system to provide for the technician to adjust the boiler operation mode, or to an authorized mobile terminal specified by the technician according to the authority.
In any of the above embodiments, preferably, the designated authorized mobile terminal includes authorization according to at least one of the authority, the level, and the title.
The method and the device can perform real-time monitoring and early warning according to the detected data of the heating surface of the boiler, perform centralized control processing on the detected data through wireless transmission, export the processed data in a shallow and understandable data format to technicians to visually detect the condition of the heating surface of the boiler, analyze the running condition of the heating surface of the boiler, formulate different running strategies according to different running conditions, protect the boiler in a safe running environment in real time, predict future trends according to the data, perform reverse verification according to the result of the future trend prediction, ensure the correctness of the trend prediction result, and formulate a corresponding service life prolonging running strategy to be selected by the technicians.
Drawings
Fig. 1 is a schematic diagram of a preferred life evaluation system of the present application.
Fig. 2 is a schematic structural diagram of a neural network model according to the present application.
Detailed Description
The present application will now be described in further detail with reference to the drawings, it being noted that the following detailed description is given for illustrative purposes only and is not to be construed as limiting the scope of the present application, as those skilled in the art will be able to make numerous insubstantial modifications and adaptations to the present application.
As shown in fig. 1, the present application provides a boiler heating surface life evaluation system, which includes a detection device, a data processing device, an analysis device, and a monitoring system, wherein the detection device is sequentially connected to the data processing device and the analysis device, and the analysis device analyzes data and transmits the data to the monitoring system; the service life prediction and analysis device comprises a trend prediction and analysis device and a service life calculation device, wherein the trend prediction and analysis device performs future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method, the service life calculation device determines the residual service life, reversely verifies whether the trend analysis of the trend prediction and analysis device is correct, and makes a suggested operation strategy for prolonging the service life.
In any of the above embodiments, the detection device is preferably configured to detect data of at least one of thickness, creep, metallographic phase and mechanical properties.
In any of the above embodiments, preferably, the detection means detects the temperature of the access wall by a thermocouple.
In any of the above embodiments, the data processing device is preferably configured to perform AD conversion, screening, or screening of data and to eliminate unnecessary data.
In any of the above embodiments, the analysis device is preferably configured to analyze the screened or screened data and form a data perspective for transmission to a monitoring system.
In any of the above embodiments, preferably, the monitoring system includes a central processing unit, a signal transceiver, and a display, and the monitoring system can draw a wall temperature line graph in the thickness direction of the furnace, and has functions of data storage, query statistics, and data display.
In any of the above embodiments, preferably, the signal transceiver includes at least one of WIFI, bluetooth, ZIGBEE, GPRS, 3G, and 4G, or a combination thereof.
Any of the above embodiments preferably wherein the signal transceiver comprises a web server that evaluates data transmissions from static documents, dynamic documents without database access, dynamic documents with database access, or a combination of the three.
In any of the above embodiments, preferably, the monitoring system includes a data export or display device for exporting or displaying the data in a columnar or cake or excel manner.
In any of the above embodiments, preferably, the trend prediction analysis device classifies at least one of the thickness, creep, metallographic phase, and mechanical properties of the collected data and the historical data stored in the system according to the data output by the data processing device and the historical data, performs fitting processing, generates an equipment overhaul project trend analysis graph, and gives warning in different colors when significant upward abnormal protruding points occur in combination with the overhaul period and the wall temperature line graph.
In any of the above embodiments, preferably, the life calculating means calculates the remaining service life of the boiler according to the result of the trend predictive analysis by the trend predictive analyzing means and the input future operating condition, and makes an operation control strategy for prolonging the service life.
Any of the above embodiments preferably provides that the life calculating means is capable of sending the operation control policy to the monitoring system to provide a technician to adjust the operation mode of the boiler, or to an authorized mobile terminal specified by the technician according to the authority.
The preferred of any above-mentioned embodiment is that monitored control system includes that two are each other redundant industrial computer, and redundant monitored control system can reduce the industrial computer and go on the problem monitored to equipment when going wrong, realizes hot reserve, guarantees that the control of boiler can be in time accurate going on.
A method for evaluating the service life of a heating surface of a boiler comprises the following steps:
1) detecting real-time data of a heating surface of the boiler; when temperature detection is carried out, a thermocouple can be adopted for detection;
2) performing AD conversion processing on the data, setting a data threshold value and screening useless data;
3) respectively inputting the collected and processed heating surface data into an analysis device and a trend prediction analysis device, analyzing the data through the analysis device, forming a data perspective and transmitting the data perspective to a monitoring system; the trend prediction analysis device carries out future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method; accumulating the over-temperature records by accessing wall temperature measuring point data, and calculating the creep loss service life caused by over-temperature; the data of the heating surface is input into the analysis device and the trend prediction analysis device, a wireless communication mode can be adopted, such as a communication mode of at least one of WIFI, Bluetooth, ZIGBEE, GPRS, 3G and 4G, and the monitoring system can issue the arranged data to the outside or facilitate remote checking of technicians through a web server.
4) Determining the residual service life through a service life calculating device, reversely verifying whether the trend analysis of the trend prediction analysis device is correct, and making a recommended operation strategy for prolonging the service life, wherein the recommended operation strategy can comprise one or more than one, technicians can compare and select the recommended operation strategy from the plurality of recommended operation strategies, determine an optimal choice, set a later operation mode for the boiler and the like.
In any one of the above embodiments, the trend prediction analysis device may perform the operation trend analysis, including: 1a) acquiring online data, extracting offline historical data, selecting comprehensive data of the online data and the offline historical data, and determining characteristic parameters of the neural network; 2a) as shown in fig. 2, a 4-layer neural network model composed of an input layer, 2 hidden layers and an output layer is established, the model is a multi-input single-output network structure, an input signal is transmitted to the hidden layers and is transmitted to the output layer through hidden layer node function, and finally a result is output, the network is fully connected, namely, the connection between network units is the connection between adjacent layers, and the nodes of the layer are not connected with each other; 3a) establishing a sample library and training the sample library, wherein the training is carried out for 2 times, the input order and the output order are taken, the unique output is determined, and the training process of the neural network is to obtain the nonlinear mapping relation of the system through the learning of the sample; 4a) and the output is used as the result of the operation trend analysis of the heating surface of the boiler, and whether the output is output to the service life calculating device is determined according to the result.
In any of the above embodiments, preferably, the step 4a) includes: the trend prediction analysis device determines the specific states of the heating surface of the boiler according to the analysis result, wherein the states comprise a high-risk state, a sub-health state and a normal operation state; when the boiler is in the high-risk state and the sub-health state, directly outputting the result to a monitoring system, and determining whether to continue boiler operation or not by the monitoring system according to different states, or adjusting the boiler to a normal state and then continuing life prediction analysis by adopting modes of reducing operation load, adjusting operation output value and the like; immediately diagnosing faults and immediately determining a maintenance plan in the high-risk state; judging the defect trend of the sub-health state; and when in the normal operation state, outputting the result to the service life calculating device for carrying out reverse verification of service life prediction. The operation conditions of the equipment are judged in all directions, and different strategies are adopted to carry out corresponding operation according to different conditions.
In any of the above embodiments, preferably, the performing of the reverse verification by the lifetime calculation means includes: 1b) data preprocessing, namely, the data input by the trend prediction analysis device are subjected to abnormal point verification, standardization or normalization processing; 2b) selecting a modeling direction, namely selecting one direction from the existing directions, setting the direction as i, and setting i as i +1 once every time i is selected, wherein i is greater than or equal to 1; 3b) selecting a modeling method; 4b) establishing a model; 5b) judging whether the modeling purpose is met or not, if yes, entering a step 6b), and if not, entering a step 2 b); 6b) an application model; 7b) and outputting a verification result, setting an operation strategy for prolonging the service life according to the verification result, and providing the operation strategy for technical personnel to select.
Preferably, in any of the above embodiments, the providing for selection by the operator includes sending the operation control policy to the monitoring system to provide for the technician to adjust the boiler operation mode, or to an authorized mobile terminal specified by the technician according to the authority.
In any of the above embodiments, preferably, the designated authorized mobile terminal includes authorization according to at least one authority set by the working age, the level, and the title, for example, a higher level vacation may designate a corresponding lower level mobile terminal without authority for viewing.
The method and the device can perform real-time monitoring and early warning according to the detected data of the heating surface of the boiler, perform centralized control processing on the detected data through wireless transmission, export the processed data in a shallow and understandable data format to technicians to visually detect the condition of the heating surface of the boiler, analyze the running condition of the heating surface of the boiler, formulate different running strategies according to different running conditions, protect the boiler in a safe running environment in real time, predict future trends according to the data, perform reverse verification according to the result of the future trend prediction, ensure the correctness of the trend prediction result, and formulate a corresponding service life prolonging running strategy to be selected by the technicians.
Claims (10)
1. The boiler heating surface service life evaluation system is characterized by comprising a detection device, a data processing device, an analysis device and a monitoring system, wherein the detection device, the data processing device and the analysis device are sequentially connected, and the analysis device analyzes data and transmits the data to the monitoring system; the method is characterized in that: the monitoring system comprises two industrial personal computers which are mutually redundant, a trend prediction analysis device and a service life calculation device, wherein the trend prediction analysis device performs future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method, the service life calculation device determines the residual service life and reversely verifies whether the trend analysis of the trend prediction analysis device is correct or not, the detection device detects the temperature of the boiler wall through a thermocouple;
the life calculating device performing reverse verification comprises: 1b) data preprocessing, namely, the data input by the trend prediction analysis device are subjected to abnormal point verification, standardization or normalization processing; 2b) selecting a modeling direction, namely selecting one direction from the existing directions, setting the direction as i, and setting i = i +1 once the direction is selected, wherein i is greater than or equal to 1; 3b) selecting a modeling method; 4b) establishing a model; 5b) judging whether the modeling purpose is met or not, if yes, entering a step 6b), and if not, entering a step 2 b); 6b) an application model; 7b) outputting a verification result, setting an operation strategy for prolonging the service life according to the verification result, and providing the operation strategy for technicians to select;
and the service life calculating device calculates the residual service life of the boiler according to the trend prediction analysis result of the trend prediction analysis device and the input future operation working condition, and works out an operation control strategy for prolonging the service life.
2. The boiler heating surface life evaluation system of claim 1, wherein: the detection device is also used for detecting data of at least one of thickness, creep, metallographic phase and mechanical property.
3. The boiler heating surface life evaluation system of claim 1, wherein: the data processing device is used for performing AD conversion on data, screening or screening the data and eliminating useless data.
4. The boiler heating surface life evaluation system of claim 3, wherein: the analysis device is used for analyzing the screened or screened data, forming a data perspective view and transmitting the data perspective view to the monitoring system.
5. The boiler heating surface life evaluation system of claim 4, wherein: the monitoring system comprises a central processing unit, a signal transceiver and a display, can draw a wall temperature line graph in the thickness direction of the hearth, and has the functions of data storage, inquiry statistics and data display.
6. The boiler heating surface life evaluation system of claim 5, wherein: the signal transceiver comprises at least one of WIFI, Bluetooth, ZIGBEE, GPRS and 3G and 4G communication modes or a combined communication mode.
7. The boiler heating surface life evaluation system of claim 5, wherein: the signal transceiver includes a web server that evaluates data transmissions from static documents, dynamic documents without database access, dynamic documents with database access, or a combination of the three.
8. The boiler heating surface life evaluation system of claim 5, wherein: the monitoring system comprises a step of exporting or displaying data in a columnar or cake or excel mode.
9. The boiler heating surface life evaluation system of claim 1, wherein: the trend prediction analysis device classifies at least one of the collected data and the thickness, creep, metallographic phase and mechanical property in the historical data for fitting according to the data output by the data processing device and the historical data stored in the system to generate an equipment overhaul project trend analysis graph, and gives warnings in different colors when obvious upward abnormal prominent points occur in combination with an overhaul period and a wall temperature line graph; the service life calculating device can send the operation control strategy to the monitoring system to provide a technician for adjusting the operation mode of the boiler or to an authorized mobile terminal specified by the technician according to the authority.
10. A method for evaluating the service life of a heating surface of a boiler is characterized by comprising the following steps:
1) detecting real-time data of a heating surface of the boiler;
2) performing AD conversion processing on the data, setting a data threshold value and screening useless data;
3) respectively inputting the collected and processed heating surface data into an analysis device and a trend prediction analysis device, analyzing the data through the analysis device, forming a data perspective and transmitting the data perspective to a monitoring system; the trend prediction analysis device carries out future operation trend analysis according to off-line and on-line data by using a fuzzy neural network method; accumulating the over-temperature records by accessing wall temperature measuring point data, and calculating the creep loss service life caused by over-temperature;
4) determining the residual service life through a service life calculating device, reversely verifying whether the trend analysis of the trend prediction analysis device is correct or not, and making a suggested operation strategy for prolonging the service life;
the life calculating device performing reverse verification comprises: 1b) data preprocessing, namely, the data input by the trend prediction analysis device are subjected to abnormal point verification, standardization or normalization processing; 2b) selecting a modeling direction, namely selecting one direction from the existing directions, setting the direction as i, and setting i = i +1 once the direction is selected, wherein i is greater than or equal to 1; 3b) selecting a modeling method; 4b) establishing a model; 5b) judging whether the modeling purpose is met or not, if yes, entering a step 6b), and if not, entering a step 2 b); 6b) an application model; 7b) outputting a verification result, setting an operation strategy for prolonging the service life according to the verification result, and providing the operation strategy for technicians to select;
and the service life calculating device calculates the residual service life of the boiler according to the trend prediction analysis result of the trend prediction analysis device and the input future operation working condition, and works out an operation control strategy for prolonging the service life.
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| CN106289376A (en) * | 2016-07-30 | 2017-01-04 | 董超超 | A kind of Industrial Boiler intelligent detection device |
| CN106524118B (en) * | 2016-09-30 | 2018-11-13 | 河北云酷科技有限公司 | The method for building up of boiler wear resistant explosion-proof temperature field model |
| CN108229042A (en) * | 2018-01-12 | 2018-06-29 | 中国大唐集团科学技术研究院有限公司华东分公司 | A kind of generator tube remaining life early warning system and method for early warning |
| CN108644753B (en) * | 2018-05-15 | 2019-10-08 | 中国石油化工股份有限公司 | A kind of digitized representation method of coal-burning boiler operating status |
| CN109101460B (en) * | 2018-06-21 | 2022-09-20 | 国网山东省电力公司电力科学研究院 | Thermal generator set operation safety performance evaluation method based on safety margin |
| CN109253870B (en) * | 2018-08-21 | 2019-09-06 | 嘉兴新嘉爱斯热电有限公司 | The assessment device and method in biomass fuel boiler heat-exchange tube service life |
| CN110378052B (en) * | 2019-07-25 | 2020-11-06 | 北京航空航天大学 | Equipment residual life prediction method considering future working conditions based on cyclic neural network |
| CN113377839A (en) * | 2021-06-18 | 2021-09-10 | 北京德风新征程科技有限公司 | Industrial internet-based big data analysis and extraction method |
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