A method and device for evaluating the cleaning degree of a boiler heating surface
By acquiring temperature and DCS data from the boiler heating surface, calculating fouling thermal resistance and evaluation index, and combining cluster analysis, the problem of low accuracy in assessing the cleanliness of boiler heating surfaces in existing technologies is solved, achieving accurate multi-dimensional assessment and adapting to dynamically changing boiler operating environments.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ZHEJIANG UNIV
- Filing Date
- 2026-03-20
- Publication Date
- 2026-06-12
AI Technical Summary
Existing methods for assessing the cleanliness of boiler heating surfaces rely on a single parameter, resulting in low accuracy of assessment results. This makes it difficult to accurately assess the cleanliness level under dynamically changing control scenarios. Furthermore, existing probe devices cannot flexibly adjust the position of the measuring points, leading to measurement errors.
By acquiring temperature data from the surface of the boiler heating surface fouling probe and DCS operation data, fouling thermal resistance and assessment index are calculated. Combined with cluster analysis, a multi-dimensional quantitative index of cleanliness is constructed, and the weights of assessment parameters are dynamically adjusted to achieve multi-level accurate assessment.
It improves the accuracy of boiler heating surface cleanliness assessment, adapts to cleanliness assessment in different locations, avoids the uncertainty and uniformity of the quantification process, and meets the adaptability and targeted needs of boiler operation.
Smart Images
Figure CN122193296A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of boiler heating surface cleanliness assessment technology, and in particular to a method and apparatus for assessing the cleanliness of boiler heating surfaces. Background Technology
[0002] As the core component for heat transfer after fuel combustion, the cleanliness of boiler heating surfaces is crucial to the healthy and stable operation of the boiler. Especially with the large-scale development of current generator unit capacity, the synergistic combustion of multiple fuels, and the dynamic peak-shaving and valley-filling of generator units, these variable control scenarios can lead to increased fouling of heating surfaces. This can result in a deterioration of heat exchange effect and a reduction in operating efficiency, or even an increased risk of tube rupture and boiler shutdown due to uneven heat transfer. Therefore, real-time monitoring and evaluation of the cleanliness of boiler heating surfaces is of great guiding significance for timely removal of slag and ash buildup.
[0003] Currently, the main method for assessing the cleanliness of boiler heating surfaces is to rely on the operating parameters in the Distributed Control System (DCS) to make manual judgments and corresponding operational adjustments. For example, boiler operators mainly judge the cleanliness of the heating surfaces by selecting parameters such as the pressure drop and temperature drop of the flue gas flowing through the heating surfaces, the temperature rise of the working fluid, and the heat transfer coefficient to evaluate the overall cleanliness of the heating surfaces. However, this method is prone to over-reliance on changes in a single parameter, resulting in a one-sided assessment and thus low accuracy in determining the cleanliness of the heating surfaces. Summary of the Invention
[0004] Therefore, it is necessary to provide a method and apparatus for assessing the cleanliness of boiler heating surfaces, addressing the aforementioned technical problems. This method improves the accuracy of assessing the cleanliness of boiler heating surfaces.
[0005] The following technical solution is adopted in this specification: This manual provides a method for assessing the cleanliness of boiler heating surfaces, including: Acquire the temperature data of the surface of the fouling probe on the boiler's heating surface at the current moment, as well as the DCS operation data of the distributed control system; the placement direction of the fouling probe is perpendicular to the flow direction of the boiler flue gas. Calculate the contamination thermal resistance deposited on the surface of the contaminated probe head based on the temperature data of the contaminated probe head surface; Using the fouling thermal resistance and DCS operation data as evaluation parameters, the fouling degree index and fouling trend index corresponding to each evaluation parameter are calculated respectively, and the fouling evaluation index of each evaluation parameter is determined based on the fouling degree index and fouling trend index. The comprehensive contamination assessment index is determined based on the contamination assessment index of each assessment parameter and the weight coefficient of each assessment parameter. Multiple cleanliness indices are calculated based on the comprehensive contamination assessment index and different cleanliness factors. The weight coefficient of each assessment parameter is determined by dynamic weight assignment. Cluster analysis was performed on all cleanliness indices to obtain the cleanliness level of the heated surface.
[0006] Optionally, the temperature data includes the surface temperature of the ash layer outside the contaminated probe head, the outer surface temperature of the contaminated probe head, and the inner surface temperature of the contaminated probe head; the formula for calculating the contamination thermal resistance is: ; in, The contamination thermal resistance of the ash and slag deposit layer on the surface of the contaminated probe tip. Thermal conductivity of the material used for the contaminated probe tip. The surface temperature of the ash layer is measured by a thermocouple positioned outside the contaminated probe tip. The temperature of the outer surface of the contaminated probe tip is measured by a thermocouple positioned on the outer layer of the contaminated probe tip. The temperature of the inner surface of the contaminated probe head is measured by a thermocouple arranged inside the contaminated probe head. The radius of the contaminated probe tip. The distance between the thermocouple positioned on the outer layer of the contaminated probe tip and the center of the contaminated probe tip. This is the distance between the thermocouple arranged in the inner layer of the contaminated probe head and the center of the contaminated probe head.
[0007] Optionally, the method further includes: Acquire historical ash images captured at the previous moment and historical ash images captured at the current moment by an optical camera positioned directly in front of the contaminated probe head; Image processing is performed on historical ash and slag images taken at the previous moment and historical ash and slag images taken at the current moment to determine the ash and slag deposition thickness in the vertical direction on the surface of the contaminated probe head between the previous moment and the current moment. Based on the thickness of the ash deposit, the thermocouple outside the contaminated probe head is moved vertically to the surface of the deposited ash so that the thermocouple outside the contaminated probe head can measure the surface temperature of the deposited ash.
[0008] Optionally, the contamination degree index and contamination trend index corresponding to each assessment parameter are calculated, and the contamination assessment index of each assessment parameter is determined based on the contamination degree index and contamination trend index, specifically including: For each assessment parameter, calculate the corresponding contamination level index and contamination trend index; The contamination degree index and the contamination trend index are added together to obtain the contamination assessment index corresponding to the assessment parameters.
[0009] Optionally, for each assessment parameter, a corresponding contamination degree index and contamination trend index are calculated, specifically including: When the assessment parameter is a positive assessment parameter, the contamination degree index is calculated using the first contamination degree index formula, and the contamination trend index is calculated using the first contamination trend index formula; the first contamination degree index formula is: ; in, The contamination index is a positive evaluation parameter. The feature function within the moving window after data normalization and smoothing. The duration of the window selected using the moving window method, The time value at which the cleanliness assessment of the heated surface needs to be performed; The formula for the first contamination trend index is: ; in, The pollution trend index is a positive evaluation parameter. It is the tilt angle obtained by linear fitting after obtaining the feature sequences at each time step using the moving window method. It is the coefficient of determination for linear fitting of the feature sequence; When the assessment parameter is a reverse assessment parameter, the contamination degree index is calculated using the second contamination degree index formula, and the contamination trend index is calculated using the second contamination trend index formula; the second contamination degree index formula is: ; in, A contamination index used for reverse evaluation parameters; The formula for the second contamination trend index is: ; in, The pollution trend index is used to evaluate parameters in reverse.
[0010] Optionally, the formula for calculating the cleanliness index is: ; in, This is an index representing the cleanliness of the heated surface. The cleanliness factor of the heated surface This is the comprehensive fouling assessment index for the heated surface.
[0011] Optionally, cluster analysis is performed on all cleanliness indices to obtain the cleanliness level of the heated surface, specifically including: The number of clusters was set to 4, and all cleanliness indices were clustered based on the number of clusters to obtain 4 cluster centers; The four cluster centers are sorted in ascending order of their numerical values. Using the four sorted cluster centers as the dividing points, five consecutive numerical intervals are divided along the numerical axis. The five consecutive numerical intervals correspond to the optimal cleanliness range, the relatively good cleanliness range, the medium cleanliness range, the relatively poor cleanliness range, and the worst cleanliness range, respectively. The cleanliness level corresponding to the interval with the highest cleanliness index distribution among the five consecutive numerical intervals is determined as the cleanliness level of the heated surface at the current moment.
[0012] This manual provides a device for evaluating the cleanliness of a heated surface, including: a protective outer tube (1), a cooling inner tube (2), a contamination probe head (3), a temperature acquisition unit, a field operation data control center (18), a temperature measurement mobile unit, and a data processor (16). The cooling inner tube (2) is coaxially fixed inside the protective outer tube (1) by welding; the data processor (16) is connected to the field operation data control center (18) and the temperature acquisition unit respectively; the contaminated probe head (3) is placed outside the protective outer tube (1) extending to one end of the flue gas, and the placement direction is perpendicular to the flow direction of the flue gas. The contaminated probe head (3) is used for ash and slag deposition in the exposed flue. Temperature acquisition unit, used to acquire temperature data of the surface of the contaminated probe head (3) in real time; The field operation data control center (18) is used to acquire the operation data of the distributed control system (DCS). The data processor (16) is used to acquire the temperature data of the surface of the boiler's heating surface and the DCS operation data of the distributed control system at the current moment; the placement direction of the fouling probe head is perpendicular to the flow direction of the boiler flue gas; the fouling thermal resistance deposited on the surface of the fouling probe head is calculated based on the temperature data of the surface of the fouling probe head; the fouling thermal resistance and the DCS operation data are used as evaluation parameters to calculate the fouling degree index and fouling trend index corresponding to each evaluation parameter, and the fouling evaluation index of each evaluation parameter is determined based on the fouling degree index and the fouling trend index; the comprehensive fouling evaluation index is determined based on the fouling evaluation index of each evaluation parameter and the weight coefficient of each evaluation parameter, and multiple cleanliness indices are calculated based on the comprehensive fouling evaluation index and different cleanliness factors; the weight coefficient of each evaluation parameter is determined by dynamic weight assignment; cluster analysis is performed on all cleanliness indices to obtain the cleanliness level of the heating surface.
[0013] Optionally, the temperature acquisition unit includes a first thermocouple (9), a second thermocouple (8), and a third thermocouple (7) arranged in the direction of flue gas flow; the temperature probes of the first thermocouple (9), the second thermocouple (8), and the third thermocouple (7) are all kept in the same radial plane and parallel to each other; the temperature probe of the first thermocouple (9) is located in the inner layer of the contaminated probe head to obtain the inner surface temperature of the contaminated probe head, the temperature probe of the second thermocouple (8) is located in the outer layer of the contaminated probe head to obtain the outer surface temperature of the contaminated probe head, and the temperature probe of the third thermocouple (7) is located in the outer side of the contaminated probe head (3) to obtain the surface temperature of the ash layer; The temperature measurement moving unit includes a telescopic component (6) fixed inside the protective outer tube (1); A temperature measurement moving unit is used to move the contaminated probe head (3); The bottom of the telescopic assembly (6) is connected to a movable baffle, and the telescopic assembly (6) moves the movable baffle up and down by extending and retracting in the vertical direction. The movable baffle (10) has a fixing hole on the inner side for inserting a third thermocouple protective bushing. The end of the protective outer tube (1) that extends into the flue gas has a rectangular protrusion hole and two circular protrusion holes. The inner side of the rectangular protrusion hole is close to the movable baffle (10). The two circular protrusion holes are used to arrange the protrusion and fixing of the first thermocouple (9) and the second thermocouple (8), and all protrusion holes are matched with the temperature probe size of the thermocouple. The air inlet of the cooling inner tube (2) is connected to the cooling air supply device (17); Cooling gas supply device (17) is used to supply cooling gas to the cooling inner tube (2). The cooling gas flows into the contaminated probe head (3) through the cooling inner tube (2) to cool the contaminated probe head (3) before entering the protective outer tube (1) and flowing out of the exhaust port of the protective outer tube (1) in the opposite direction to the air inlet.
[0014] Optionally, the contamination image monitoring unit includes an optical camera (11) and a lens cooling conduit (12) arranged directly in front of the contamination probe head (3). The lens cooling duct (12) has a cooling air inlet near the end of the optical camera (11) for supplying the required cooling air source to the cooling air supplier (17); An airflow guide plate is arranged near the end of the lens cooling duct (12) close to the contaminated probe head (3) so that the cooling air flows out in a downward direction; An optical camera (11) is connected to a data processor (16); The data processor (16) is connected to the PID control box (15) and is used to calculate the contamination thickness of the ash image through the data processor (16), and then feed back the distance that the third thermocouple (7) needs to move in real time to the PID control box (15), thereby outputting the control command for the telescopic component (6) to perform closed-loop control of the movement of the third thermocouple (7).
[0015] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for evaluating the cleanliness of boiler heating surfaces.
[0016] This specification provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method for evaluating the cleanliness of boiler heating surfaces.
[0017] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects: The boiler heating surface cleanliness assessment method provided in this specification utilizes fouling thermal resistance data and DCS operating data as raw assessment parameters to calculate corresponding fouling assessment indices. It then introduces a cleanliness index and uses a clustering algorithm to obtain the cleanliness level of the boiler heating surface. This method comprehensively extracts the overall operating parameters of the heating surface and the measured fouling thermal resistance to achieve a multi-dimensional and accurate analysis and evaluation of the heating surface cleanliness. It fully considers the influence of the overall fouling distribution and local fouling growth characteristics of the heating surface, enriching the evaluation system for heating surface cleanliness and avoiding the uncertainty and uniformity of the quantification process, thereby improving the accuracy of boiler heating surface cleanliness assessment. By extracting the fouling degree index and fouling trend index of each assessment parameter, the development degree and trend of fouling on the heating surface are quantified, further obtaining the cleanliness index under different cleanliness factors. The cleanliness level of the heating surface is then determined based on the results of the clustering algorithm, satisfying the adaptability and specificity of the cleanliness assessment process for heating surfaces in different locations within the boiler. This method improves the accuracy of boiler heating surface cleanliness assessment. Attached Figure Description
[0018] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:
[0019] Figure 1 This document provides a flowchart illustrating a method for assessing the cleanliness of boiler heating surfaces. Figure 2 A schematic diagram of the boiler heating surface cleanliness assessment method provided by the present invention; Figure 3 A schematic diagram of the clustering results of the heat-receiving surface cleanliness index calculated from four different cleanliness factors provided by the present invention; Figure 4 This manual provides a schematic diagram of a device for assessing the cleanliness of boiler heating surfaces. Figure 5 This is a schematic diagram of the temperature measurement moving unit provided in this manual; Figure 6 This is a schematic diagram of a computer device for implementing a method to assess the cleanliness of boiler heating surfaces, as provided in this specification.
[0020] Figure label: 1. Protective outer tube; 2. Cooling inner tube; 3. Contaminated probe head; 4. Probe head cooling air inlet; 5. Probe head cooling air outlet; 6. Telescopic assembly; 7. Third thermocouple; 8. Second thermocouple; 9. First thermocouple; 10. Movable baffle; 11. Optical camera; 12. Lens cooling duct; 13. Lens cooling duct air inlet; 14. Linear motion assembly; 15. PID control box; 16. Data processor; 17. Cooling air supplier; 18. Field operation data control center. Detailed Implementation
[0021] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.
[0022] Existing probe devices for measuring contamination parameters mainly analyze and evaluate the cleanliness of local heated surfaces by measuring relevant ash growth parameters (such as heat flux density, thickness, mass, etc.). However, they still lack comprehensive diagnostic analysis by combining DCS data. In addition, considering that the thickness of ash is a dynamic growth process, existing probe devices often neglect the need for timely dynamic adjustment of thermocouple positions when measuring ash thermal resistance. As a result, it is difficult to ensure the accuracy and continuity of the evaluation results when obtaining contamination thermal resistance.
[0023] This invention addresses the problem that current methods for assessing the cleanliness of boiler heating surfaces mostly rely on operating parameters such as the boiler heating surface heat transfer coefficient and flue gas pressure drop, or simply on local parameters after ash and slag deposition on the probe to quantify the cleanliness of the heating surface in a one-sided manner. This makes it difficult to guarantee the accuracy and reliability of dynamic assessment results. At the same time, current methods for measuring the thermal resistance of the probe surface contamination also suffer from measurement errors due to the inability to flexibly adjust the position of the measuring point according to the ash and slag growth.
[0024] This invention provides a method and apparatus for assessing the cleanliness of boiler heating surfaces. It constructs multiple quantitative indicators of cleanliness by integrating operating data parameters of the heating surfaces and the fouling thermal resistance measured on the surface of a fouling probe. It effectively extracts the fouling degree index and fouling trend index of each indicator parameter. Based on this, it introduces the cleanliness index of the heating surfaces to quantify the cleanliness of the heating surfaces at different times. Then, based on the clustering results, it selects the optimal cleanliness factor and classifies the corresponding cleanliness levels, thereby determining the cleanliness assessment results of the heating surfaces at different times. This provides reasonable, efficient, accurate, and reliable judgment results for on-site operators to monitor the operation of the heating surfaces online and to promptly address fouling issues.
[0025] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.
[0026] Figure 1 This is a flowchart illustrating a method for assessing the cleanliness of boiler heating surfaces as described in this specification, which specifically includes the following steps: S101: Acquire the temperature data of the surface of the fouling probe on the boiler's heating surface at the current moment, as well as the DCS operation data of the distributed control system; the placement direction of the fouling probe is perpendicular to the flow direction of the boiler flue gas.
[0027] The system continuously acquires DCS operating data, which are highly correlated with the cleanliness of the heated surface, as well as ash and slag images of the contaminated probe head and temperature data of the contaminated probe head surface. DCS operating data highly correlated with the cleanliness of the heated surface includes the outlet temperature of the flue gas flowing through the heated surface, the pressure drop of the flue gas after passing through the heated surface, the temperature rise of the working fluid after passing through the heated surface, and the heat transfer coefficient of the heated surface.
[0028] The historical data of multiple continuous operating parameters selected are mainly historical DCS operating parameters that are highly correlated with the cleanliness of the heat transfer surface to be evaluated. In the process of evaluating the cleanliness of the air preheater, the main operating parameter data selected include flue gas inlet and outlet pressure drop, flue gas outlet temperature, primary air temperature rise, secondary air temperature rise, and comprehensive heat transfer coefficient.
[0029] The contamination device extends the contamination probe and contamination image acquisition equipment into the flue by opening a hole in the manhole door of the air preheater on site, thereby avoiding the relocation and modification of the original heating surface pipes. The acquisition interval of the air preheater's operating parameter data and probe temperature data is set to 1 minute. Furthermore, all evaluation parameters are preprocessed through data cleaning methods and time delay analysis to obtain an evaluation parameter database at the same time after eliminating outliers and time delays.
[0030] In an exemplary embodiment, historical ash images captured by an optical camera positioned directly in front of the contaminated probe head at the previous moment and at the current moment are acquired; image processing is performed on the historical ash images captured at the previous moment and at the current moment to determine the ash deposition thickness in the vertical direction on the surface of the contaminated probe head between the previous moment and the current moment; based on the ash deposition thickness, a thermocouple outside the contaminated probe head is moved vertically to the surface of the deposited ash so that the thermocouple outside the contaminated probe head measures the surface temperature of the deposited ash.
[0031] Specifically, the ash images acquired at the current and previous moments are processed using a contour edge detection algorithm to obtain the ash deposition thickness in the vertical direction on the surface of the contaminated probe head between the current and previous moments. Based on the ash deposition thickness, the thermocouple above the contaminated probe head is moved to the surface of the deposited ash.
[0032] S102: Calculate the contamination thermal resistance deposited on the surface of the contaminated probe head based on the temperature data of the contaminated probe head surface.
[0033] The temperature data collected by the three thermocouples were calculated, and the heat conduction process inside the contaminated probe head was treated according to the cylindrical heat conduction model, while the heat conduction process of the ash layer formed on the surface of the contaminated probe head was treated according to the flat plate heat conduction model. It was assumed that the heat flux density of the heat conduction process remained stable.
[0034] In an exemplary embodiment, the temperature data includes the surface temperature of the ash layer outside the contaminated probe head, the outer surface temperature of the contaminated probe head, and the inner surface temperature of the contaminated probe head; the formula for calculating the contamination thermal resistance is formula (1): (1); in, The contamination thermal resistance of the ash and slag deposit layer on the surface of the contaminated probe tip. Thermal conductivity of the material used for the contaminated probe tip. The surface temperature of the ash layer is measured by a thermocouple positioned outside the contaminated probe tip. The temperature measured by the thermocouple placed on the outer layer of the contaminated probe tip. The temperature measured by the thermocouple arranged inside the contaminated probe tip. The radius of the contaminated probe tip. The distance between the thermocouple positioned on the outer layer of the contaminated probe tip and the center of the contaminated probe tip. This is the distance between the thermocouple arranged in the inner layer of the contaminated probe head and the center of the contaminated probe head.
[0035] S103: Using the fouling thermal resistance and DCS operation data as evaluation parameters, calculate the fouling degree index and fouling trend index corresponding to each evaluation parameter, and determine the fouling evaluation index of each evaluation parameter based on the fouling degree index and fouling trend index.
[0036] The formula for calculating the contamination degree index is obtained by normalizing historical contamination thermal resistance data and historical DCS operation data; the formula for calculating the contamination trend index is obtained by fitting historical contamination thermal resistance data and historical DCS operation data.
[0037] In an exemplary embodiment, the contamination degree index and contamination trend index corresponding to each evaluation parameter are calculated, and the contamination evaluation index of each evaluation parameter is determined based on the contamination degree index and contamination trend index. Specifically, this includes: calculating the corresponding contamination degree index and contamination trend index for each evaluation parameter; and adding the contamination degree index and contamination trend index to obtain the contamination evaluation index corresponding to the evaluation parameter.
[0038] Specifically, the obtained fouling thermal resistance and DCS operation data that are highly correlated with the cleanliness of the heated surface are used as evaluation parameters. For any characteristic parameter, the respective fouling degree index and fouling trend index are calculated, and the fouling evaluation index corresponding to each evaluation parameter is determined.
[0039] For any evaluation parameter, the moving window method is used to obtain the feature sequence of each evaluation parameter at each time point from the established database. The window duration of the moving window method is set to 30 minutes, that is, for each evaluation parameter at each time point, the moving window method can obtain the 30 data points before that time point as the feature sequence. The degree of contamination is introduced for quantification based on the degree to which the air preheater is biased towards the most severe contamination in the historical data over a period of time. At the same time, the rate at which the contamination of the air preheater deteriorates over a period of time is introduced for quantification. Based on the constructed feature sequence, the contamination degree index and the contamination trend index of each evaluation parameter at each time point are calculated respectively.
[0040] In an exemplary embodiment, for each evaluation parameter, the corresponding contamination degree index and contamination trend index are calculated, specifically including: when the evaluation parameter is a positive evaluation parameter, the contamination degree index is calculated using a first contamination degree index formula, and the contamination trend index is calculated using a first contamination trend index formula; when the evaluation parameter is a negative evaluation parameter, the contamination degree index is calculated using a second contamination degree index formula, and the contamination trend index is calculated using a second contamination trend index formula.
[0041] Specifically, a moving window method is used to construct a feature sequence for any evaluation parameter at any given time. The degree of contamination is quantified by introducing a contamination index based on the extent to which the heated surface tends to be as contaminated as the most severe situation in historical data over a period of time. At the same time, a contamination trend index is quantified based on the rate of deterioration of the contamination of the heated surface over a period of time. Based on the constructed feature sequence, the contamination degree index and contamination trend index for each evaluation parameter at each time are calculated.
[0042] The higher the primary air temperature rise, secondary air temperature rise, and overall heat transfer coefficient, the cleaner the air preheater is considered to be. The first contamination index formula is used to calculate the contamination index. The first contamination index formula is formula (2):
[0043] (2); in, The contamination index is a positive evaluation parameter. To normalize and smooth the data under different boiler heat loads, the characteristic function within the moving window is used. The duration of the window selected using the moving window method, The time value at which the cleanliness assessment of the heated surface needs to be performed.
[0044] The three inverse evaluation characteristic parameters—flue gas inlet and outlet pressure drop, flue gas outlet temperature, and fouling thermal resistance—indicate a cleaner air preheater. The fouling index is calculated using the second fouling index formula. The second fouling index formula is formula (3):
[0045] (3); in, This is a contamination index used for reverse evaluation parameters.
[0046] The three positive evaluation parameters—primary air temperature rise, secondary air temperature rise, and overall heat transfer coefficient—indicate a cleaner air preheater. The first fouling tendency index is calculated using the first fouling tendency index formula. The first fouling tendency index formula is formula (4):
[0047] (4); in, The pollution trend index is a positive evaluation parameter. It is the tilt angle obtained by linear fitting after obtaining the feature sequences at each time step using the moving window method. It is the coefficient of determination for linear fitting of the feature sequence; The three inverse evaluation characteristic parameters—flue gas inlet and outlet pressure drop, flue gas outlet temperature, and fouling thermal resistance—indicate a cleaner air preheater. The fouling tendency index is calculated using the second fouling tendency index formula. The second fouling tendency index formula is formula (5):
[0048] (5); in, The pollution trend index is used to evaluate parameters in reverse.
[0049] The pollution degree index and pollution trend index at each time point are calculated for the positive and negative evaluation parameters respectively. Based on the pollution degree index and pollution trend index at each time point for each evaluation parameter, the pollution degree index and pollution trend index are added together to determine the pollution degree index at each time point for each evaluation parameter.
[0050] Based on the feature sequence constructed by the moving window method, the dynamic weight coefficients corresponding to each evaluation parameter at each time point are determined by the relevant weight assignment method. The dynamic weight coefficients of each evaluation parameter are multiplied by the contamination index. Then, the results of multiplying the dynamic weight coefficients of all evaluation parameters by the contamination index at the same time point are summed. The summed result is determined as the comprehensive contamination evaluation index of the air preheater at each time point.
[0051] The entropy weight method is chosen to extract the weight coefficients of each evaluation parameter based on the dispersion of the feature sequence of each evaluation parameter. In order to avoid the situation where the weight coefficients of some evaluation parameters are too large or too small, the calculation formula of the weight coefficients of each evaluation parameter is formula (6): (6); in, This represents the weighting coefficient of each evaluation parameter. This represents the information entropy of each evaluation parameter. This represents the correction coefficient for the entropy weight method. .
[0052] Based on the contamination assessment index of all assessment parameters, the weight coefficients of each assessment parameter of the heated surface are determined using the relevant dynamic weight assignment method, and the comprehensive contamination assessment index of the heated surface is determined. Multiple sets of heated surface cleanliness indices are calculated based on different cleanliness factors.
[0053] The cleanliness of the air preheater is quantified by back-calculating the comprehensive contamination assessment index of the air preheater at various times. The cleanliness index is introduced to evaluate the cleanliness of the air preheater and mapped to a range of 0-1. Different cleanliness factor values are substituted to calculate multiple cleanliness index results for the air preheater. The larger the cleanliness index, the cleaner the air preheater is. Generally, the value range of the cleanliness factor is 2-8, and the larger the cleanliness factor, the greater the change in the cleanliness index.
[0054] In one exemplary embodiment, the formula for calculating the cleanliness index is formula (7): (7); in, This is an index representing the cleanliness of the heated surface. The cleanliness factor of the heated surface This is the comprehensive fouling assessment index for heated surfaces.
[0055] S105: Perform cluster analysis on all cleanliness indices to obtain the cleanliness level of the heated surface.
[0056] In an exemplary embodiment, cluster analysis is performed on all cleanliness indices to obtain the cleanliness level of the heated surface. Specifically, this includes: setting the number of clusters to 4, and clustering all cleanliness indices based on the number of clusters to obtain 4 cluster centers; sorting the 4 cluster centers in ascending order of value, and using the 4 sorted cluster centers as the dividing points, dividing the data into 5 consecutive numerical intervals along the numerical axis; the 5 consecutive numerical intervals correspond to the optimal cleanliness range, the better cleanliness range, the medium cleanliness range, the poor cleanliness range, and the worst cleanliness range, respectively; and determining the cleanliness level of the numerical interval with the highest distribution of cleanliness indices among the 5 consecutive numerical intervals as the cleanliness level of the heated surface at the current moment.
[0057] Specifically, clustering algorithms are used to perform cluster analysis on the heat transfer surface cleanliness data at all times under different cleanliness factors. The optimal heat transfer surface cleanliness factor is selected based on the silhouette coefficient of each clustering result, and the heat transfer surface cleanliness result at each time is finally determined. Based on the cluster analysis results of the selected optimal heat transfer surface cleanliness factor, the level corresponding to different cleanliness of the heat transfer surface is obtained. Based on the interval range corresponding to the cleanliness calculated at each time, the cleanliness assessment result of the heat transfer surface at each time is determined.
[0058] The cleanliness index of the air preheater at each time point is calculated by selecting different cleanliness factors. Then, cluster analysis is performed on the cleanliness index results of the air preheater at all time points to obtain the cluster analysis results corresponding to different cleanliness factors. By comparing multiple cluster analysis results, the optimal cleanliness factor value is determined, and the cluster center value under the optimal cleanliness factor is calculated. The cleanliness level is divided according to the cluster center value, and the cleanliness result of the air preheater at each time point is evaluated based on the cleanliness level.
[0059] In one exemplary embodiment, the present invention provides as follows Figure 2 The method for assessing the cleanliness of boiler heating surfaces is shown below. Figure 2 As shown, historical data of multiple continuous operating parameters and corresponding contamination probe temperature data were collected. The contamination thermal resistance at different times was calculated using the continuously acquired contamination probe temperature data. Operating parameters and contamination thermal resistance were used as evaluation parameters to calculate the contamination degree index and contamination trend index, respectively, determining the contamination evaluation index for each evaluation parameter at each time. Based on the dynamic weighting method and the contamination evaluation index of each evaluation parameter, the comprehensive contamination evaluation index of the heated surface at each time was determined. Based on the method for calculating the cleanliness index of the heated surface, the cleanliness index corresponding to different cleanliness factors was obtained. Cluster analysis was performed on multiple cleanliness indices to select the optimal cleanliness factor, and cleanliness levels were divided according to cluster centers to determine the cleanliness evaluation result of the heated surface at each time.
[0060] The formula for calculating the contamination level index is obtained by normalizing historical DCS operating data; the formula for calculating the contamination trend index is obtained by fitting historical DCS operating data.
[0061] Figure 3 This is a schematic diagram illustrating the clustering results of the heat-receiving surface cleanliness index calculated from four different cleanliness factors provided by the present invention, as shown in the figure. Figure 3 As shown, a K-means clustering algorithm with 4 clusters was used to perform cluster analysis on the air preheater cleanliness index results at all time points. The clustering results calculated when the cleanliness factor values were 3, 4, 5, and 6 can be further compared with the silhouette coefficients of the clustering results for each cleanliness factor to obtain the optimal cleanliness factor. In finding the optimal cleanliness factor, intelligent optimization algorithms such as genetic algorithms, particle swarm optimization algorithms, and Bayesian optimization algorithms can be combined for selection. The selection process used here is existing technology and will not be elaborated further. Based on the cluster centers corresponding to the optimal cleanliness factor, five cleanliness levels can be obtained for evaluating the cleanliness of the air preheater. Figure 4Taking the clustering results with a cleanliness factor of 3 as an example, the worst cleanliness range can be set to [0, 0.2862], the poor cleanliness range can be set to (0.2862, 0.3847], the medium cleanliness range can be set to (0.3847, 0.4809], the good cleanliness range can be set to (0.4809, 0.6171], and the best cleanliness range can be set to (0.6171, 1]. When the cleanliness index is between [0, 0.2862], it indicates that the air preheater is the worst clean, the ash and slag deposition on the surface of the air preheater is very serious, and the air preheater needs to be blown clean every hour; when the cleanliness index is between (0.2862, 0.2862], it indicates that the air preheater is the worst clean, the ash and slag deposition on the surface of the air preheater is very serious, and the air preheater needs to be blown clean every hour; when the cleanliness index is between (0.2862, 0.2862, 0.3847], it indicates that the air preheater is the worst clean, the ash and slag deposition on the surface of the air preheater is very serious, and the air preheater needs to be blown clean every hour; when the cleanliness index is between ( .... A cleanliness index between [0.3847] indicates poor cleanliness of the air preheater, requiring soot blowing every 4 hours; a cleanliness index between [0.3847, 0.4809] indicates moderate cleanliness, requiring soot blowing every 8 hours; a cleanliness index between [0.4809, 0.6171] indicates good cleanliness, requiring soot blowing every 16 hours; and a cleanliness index between [0.6171, 1] indicates optimal cleanliness, with very slight ash deposition on the air preheater surface, requiring soot blowing every 24 hours.
[0062] When applying the boiler heating surface cleanliness assessment method provided in this manual, it is not necessary to consider... Figure 1 The steps shown are executed in sequence. The specific execution order of each step can be determined as needed, and this manual does not impose any restrictions on it.
[0063] The above are one or more embodiments of the boiler heating surface cleanliness assessment method provided in this specification. Based on the same idea, this specification also provides a corresponding heating surface cleanliness assessment device, such as... Figure 4 As shown.
[0064] A device for assessing the cleanliness of a heated surface includes: a protective outer tube (1), a cooling inner tube (2), a contamination probe head (3), a temperature acquisition unit, a field operation data control center (18), a temperature measurement mobile unit, and a data processor (16).
[0065] The cooling inner tube (2) is coaxially fixed inside the protective outer tube (1) by welding; the data processor (16) is connected to the field operation data control center (18) and the temperature acquisition unit respectively; the contaminated probe head (3) is placed outside the protective outer tube (1) at one end extending to the flue gas, and its placement direction is perpendicular to the flue gas flow direction.
[0066] The contaminated probe head (3) is used for ash and slag deposition in the exposed flue.
[0067] Temperature acquisition unit is used to acquire temperature data of the surface of the contaminated probe head (3) in real time.
[0068] The field operation data control center (18) is used to acquire the operation data of the distributed control system (DCS).
[0069] The data processor (16) is used to acquire the temperature data of the surface of the boiler's heating surface and the DCS operation data of the distributed control system at the current moment; the placement direction of the fouling probe head is perpendicular to the flow direction of the boiler flue gas; the fouling thermal resistance deposited on the surface of the fouling probe head is calculated based on the temperature data of the surface of the fouling probe head; the fouling thermal resistance and the DCS operation data are used as evaluation parameters to calculate the fouling degree index and fouling trend index corresponding to each evaluation parameter, and the fouling evaluation index of each evaluation parameter is determined based on the fouling degree index and the fouling trend index; the comprehensive fouling evaluation index is determined based on the fouling evaluation index of each evaluation parameter and the weight coefficient of each evaluation parameter, and multiple cleanliness indices are calculated based on the comprehensive fouling evaluation index and different cleanliness factors; the weight coefficient of each evaluation parameter is determined by dynamic weight assignment; cluster analysis is performed on all cleanliness indices to obtain the cleanliness level of the heating surface.
[0070] Optionally, the temperature acquisition unit includes a first thermocouple (9), a second thermocouple (8), and a third thermocouple (7) arranged in the direction of flue gas flow; the temperature probes of the first thermocouple (9), the second thermocouple (8), and the third thermocouple (7) are all kept in the same radial plane and are parallel to each other; the temperature probe of the first thermocouple (9) is located in the inner layer of the contaminated probe head to obtain the inner surface temperature of the contaminated probe head, the temperature probe of the second thermocouple (8) is located in the outer layer of the contaminated probe head to obtain the outer surface temperature of the contaminated probe head, and the temperature probe of the third thermocouple (7) is located in the outer side of the contaminated probe head (3) to obtain the surface temperature of the ash layer.
[0071] The temperature measurement moving unit includes a telescopic component (6) fixed inside the protective outer tube (1).
[0072] Temperature measurement moving unit is used to move the contaminated probe head (3).
[0073] The bottom of the telescopic assembly (6) is connected to a movable baffle, and the telescopic assembly (6) moves the movable baffle up and down by extending and retracting in the vertical direction. The movable baffle (10) has a fixing hole on the inner side for inserting the third thermocouple protective bushing. The end of the protective outer tube (1) that extends into the flue gas has a rectangular protrusion hole and two circular protrusion holes. The inner side of the rectangular protrusion hole is close to the movable baffle (10). The two circular protrusion holes are used to arrange the protrusion and fixing of the first thermocouple (9) and the second thermocouple (8), and all protrusion holes are matched with the size of the thermocouple temperature probe.
[0074] The air inlet of the cooling inner tube (2) is connected to the cooling air supply device (17).
[0075] Cooling gas supply device (17) is used to supply cooling gas to the cooling inner tube (2). The cooling gas flows into the contaminated probe head (3) through the cooling inner tube (2) to cool the contaminated probe head (3) before entering the protective outer tube (1) and flowing out of the exhaust port of the protective outer tube (1) in the opposite direction to the air inlet.
[0076] The contamination image monitoring unit includes an optical camera (11) and a lens cooling conduit (12) arranged directly in front of the contamination probe head (3).
[0077] The lens cooling duct (12) has a cooling air inlet near the end of the optical camera (11) for supplying the required cooling air source to the cooling air supplier (17).
[0078] An airflow guide plate is arranged near the end of the lens cooling duct (12) close to the contaminated probe head (3) so that the cooling air flows out in a downward direction.
[0079] An optical camera (11) is connected to a data processor (16).
[0080] The data processor (16) is connected to the PID control box (15) and is used to calculate the contamination thickness of the ash image through the data processor (16), and then feed back the distance that the third thermocouple (7) needs to move in real time to the PID control box (15), thereby outputting the control command for the telescopic component (6) to perform closed-loop control of the movement of the third thermocouple (7).
[0081] Figure 5 A schematic diagram of the temperature measurement moving unit structure provided by the present invention is shown below. Figure 5 As shown, two screws are installed on the top inner wall of the rectangular cross-section protective outer tube to fix the telescopic assembly. One end of the cross-shaped telescopic bracket built into the telescopic assembly is connected to the left and right sides of the movable baffle. The movement of the movable baffle is controlled by controlling the distance between multiple brackets. A circular fixing hole with the same diameter as the third thermocouple probe is opened in the center of the movable baffle. A rectangular extension hole with the same diameter as the third thermocouple probe is also opened at one end of the protective outer tube. The third thermocouple probe passes through the circular fixing hole and the rectangular extension hole in sequence. One end of the movable baffle is close to the inner wall of the protective outer tube, and the size of the movable baffle is larger than the size of the rectangular extension hole, ensuring that the movable baffle always covers the rectangular extension hole, thereby preventing the cooling gas in the protective outer tube from leaking out of the rectangular extension hole. In addition, two circular extension holes are opened directly below the rectangular extension hole. Their diameters are the same as the probe diameters of the second and third thermocouples, respectively, and they are directly opposite the outer and inner circular insertion holes of the contaminated probe head.
[0082] The contamination image monitoring unit includes an optical camera and a lens cooling duct arranged directly in front of the contamination probe head; the lens cooling duct has an air inlet for cooling air near the optical camera end, which is used to provide the required cooling air source with the cooling air supplier; an airflow guide plate is arranged near the contamination probe head end of the lens cooling duct to allow the cooling air to flow out in a downward direction; the optical camera is connected to a data processor; the data processor is connected to a PID control box, which calculates the contamination thickness from the ash image and feeds back the distance the third thermocouple needs to move in real time to the PID control box, thereby outputting control commands to the telescopic device to perform closed-loop control of the movement of the third thermocouple.
[0083] The boiler heating surface cleanliness assessment method provided by this invention acquires the temperature data of the surface of the boiler heating surface at the current moment and the DCS operation data of the distributed control system. It comprehensively extracts the DCS operation data and the temperature data of the contamination probe related to the cleanliness of the heating surface at the current moment as raw data to evaluate the cleanliness of the heating surface. Based on the temperature data of the surface of the contamination probe, it calculates the contamination thermal resistance deposited on the surface of the contamination probe. Using the contamination thermal resistance and the DCS operation data as evaluation parameters, it calculates the contamination degree index and contamination trend index corresponding to each evaluation parameter, and determines the contamination evaluation index of each evaluation parameter based on the contamination degree index and the contamination trend index. Based on the contamination evaluation index and the weight coefficient of each evaluation parameter, it determines the comprehensive contamination evaluation index, and calculates multiple cleanliness indices based on the comprehensive contamination evaluation index and different cleanliness factors. The weight coefficient of each evaluation parameter is determined through dynamic weight assignment. It performs cluster analysis on all cleanliness indices to obtain the cleanliness level of the heating surface, and monitors the cleanliness of the boiler heating surface in real time and accurately based on the cleanliness index calculated at the current moment. This method uses fouling thermal resistance data and DCS operation data as raw evaluation parameters to calculate the corresponding fouling assessment index. It further introduces a cleanliness index and obtains the cleanliness level of the boiler heating surface based on a clustering algorithm. It fully considers the influence of the overall fouling distribution of the heating surface and the local fouling growth characteristics, avoids the uncertainty and uniformity of the heating surface degree quantification process, overcomes the limitation that thermocouples cannot be moved in real time when measuring the surface temperature of deposited ash slag, and meets the adaptability and pertinence of the cleanliness assessment process of heating surfaces in different locations inside the boiler.
[0084] A method and apparatus for online assessment of the degree of contamination on heated surfaces. The technical advantages of this invention are as follows: 1. By comprehensively extracting the overall operating parameters of the heated surface and the fouling thermal resistance measured by the fouling device, the cleanliness of the heated surface can be accurately analyzed and evaluated in a multi-dimensional and hierarchical manner. This fully considers the influence of the overall fouling distribution on the heated surface and the local fouling growth characteristics, enriching the evaluation system for the cleanliness of the heated surface and avoiding the uncertainty and uniformity of the quantitative process of the heated surface cleanliness.
[0085] 2. The contamination device overcomes the limitation of the thermocouple not being able to move in real time when measuring the surface temperature of deposited ash and slag. Furthermore, it combines the image of deposited ash and slag to achieve dynamic adjustment, ensuring the accuracy and flexibility of the contamination thermal resistance measurement.
[0086] 3. By extracting the fouling degree index and fouling trend index of each fouling indicator, the development degree and trend of fouling on the heating surface are quantified. Furthermore, the cleanliness index under different cleaning factors is obtained. Based on the results of the clustering algorithm, the optimal cleaning factor and cluster center are selected as the division threshold, thereby satisfying the adaptability and pertinence of the cleanliness assessment process of heating surfaces in different locations inside the boiler.
[0087] Specific limitations regarding the heating surface cleanliness assessment device can be found in the limitations of the boiler heating surface cleanliness assessment method described above, and will not be repeated here. Each module in the aforementioned heating surface cleanliness assessment device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.
[0088] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 The provided method for assessing the cleanliness of boiler heating surfaces.
[0089] This instruction manual also provides Figure 6 The schematic diagram of the computer device shown is as follows: Figure 6 At the hardware level, the computer device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above-mentioned functions. Figure 1 The provided method for assessing the cleanliness of boiler heating surfaces.
[0090] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.
[0091] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
Claims
1. A method for evaluating the cleanliness of boiler heating surfaces, characterized in that, include: Acquire the temperature data of the surface of the boiler's heating surface at the current moment of the contaminated probe head, as well as the DCS operation data of the distributed control system; The contamination probe head should be placed perpendicular to the direction of boiler flue gas flow. Calculate the contamination thermal resistance deposited on the surface of the contaminated probe head based on the temperature data of the contaminated probe head surface; Using the aforementioned contamination thermal resistance and DCS operating data as evaluation parameters, the contamination degree index and contamination trend index corresponding to each evaluation parameter are calculated respectively, and the contamination evaluation index of each evaluation parameter is determined based on the contamination degree index and contamination trend index. The comprehensive contamination assessment index is determined based on the contamination assessment index of each assessment parameter and the weighting coefficient of each assessment parameter. Multiple cleanliness indices are then calculated based on the comprehensive contamination assessment index and different cleanliness factors. The weighting coefficients of each evaluation parameter are determined through a dynamic weighting method; Cluster analysis was performed on all cleanliness indices to obtain the cleanliness level of the heated surface.
2. The method for evaluating the cleanliness of boiler heating surfaces as described in claim 1, characterized in that, The temperature data includes the surface temperature of the ash layer outside the contaminated probe head, the outer surface temperature of the contaminated probe head, and the inner surface temperature of the contaminated probe head; the formula for calculating the contamination thermal resistance is: ; in, The contamination thermal resistance of the ash and slag deposit layer on the surface of the contaminated probe tip. Thermal conductivity of the material used for the contaminated probe tip. The surface temperature of the ash layer is measured by a thermocouple positioned outside the contaminated probe tip. The temperature of the outer surface of the contaminated probe tip is measured by a thermocouple positioned on the outer layer of the contaminated probe tip. The temperature of the inner surface of the contaminated probe head is measured by a thermocouple arranged inside the contaminated probe head. The radius of the contaminated probe tip. The distance between the thermocouple positioned on the outer layer of the contaminated probe tip and the center of the contaminated probe tip. This is the distance between the thermocouple arranged in the inner layer of the contaminated probe head and the center of the contaminated probe head.
3. The method for evaluating the cleanliness of boiler heating surfaces as described in claim 2, characterized in that, The method further includes: Acquire historical ash images captured at the previous moment and historical ash images captured at the current moment by an optical camera positioned directly in front of the contaminated probe head; Image processing is performed on historical ash and slag images taken at the previous moment and historical ash and slag images taken at the current moment to determine the ash and slag deposition thickness in the vertical direction on the surface of the contaminated probe head between the previous moment and the current moment. Based on the thickness of the ash deposit, the thermocouple outside the contaminated probe head is moved vertically to the surface of the deposited ash so that the thermocouple outside the contaminated probe head can measure the surface temperature of the deposited ash.
4. The method for evaluating the cleanliness of boiler heating surfaces as described in claim 1, characterized in that, The calculation of the contamination degree index and contamination trend index corresponding to each assessment parameter, and the determination of the contamination assessment index for each assessment parameter based on the contamination degree index and contamination trend index, specifically includes: For each assessment parameter, calculate the corresponding contamination level index and contamination trend index; The contamination degree index and the contamination trend index are added together to obtain the contamination assessment index corresponding to the assessment parameters.
5. The method for evaluating the cleanliness of boiler heating surfaces as described in claim 4, characterized in that, For each evaluation parameter, the corresponding contamination degree index and contamination trend index are calculated, specifically including: When the evaluation parameter is a positive evaluation parameter, the pollution degree index is calculated using the first pollution degree index formula, and the pollution trend index is calculated using the first pollution trend index formula; the first pollution degree index formula is: ； in, The contamination index is a positive evaluation parameter. The feature function within the moving window after data normalization and smoothing. The duration of the window selected using the moving window method, The time value at which the cleanliness assessment of the heated surface needs to be performed; The formula for the first contamination trend index is: ； in, The pollution trend index is a positive evaluation parameter. It is the tilt angle obtained by linear fitting after obtaining the feature sequences at each time step using the moving window method. It is the coefficient of determination for linear fitting of the feature sequence; When the assessment parameter is a reverse assessment parameter, the contamination degree index is calculated using the second contamination degree index formula, and the contamination trend index is calculated using the second contamination trend index formula; the second contamination degree index formula is: ； in, A contamination index used for reverse evaluation of parameters; The formula for the second contamination trend index is: ； in, The pollution trend index is used to evaluate parameters in reverse.
6. The method for evaluating the cleanliness of boiler heating surfaces as described in claim 1, characterized in that, The formula for calculating the cleanliness index is as follows: ； in, This is an index representing the cleanliness of the heated surface. The cleanliness factor of the heated surface This is the comprehensive fouling assessment index for the heated surface.
7. The method for evaluating the cleanliness of boiler heating surfaces as described in claim 1, characterized in that, The cluster analysis of all cleanliness indices yields the cleanliness level of the heated surface, specifically including: The number of clusters was set to 4, and based on the number of clusters, all cleanliness indices were clustered to obtain 4 cluster centers; The four cluster centers are sorted in ascending order of their numerical values. Using the four sorted cluster centers as the dividing points, five consecutive numerical intervals are divided along the numerical axis. The five consecutive numerical intervals correspond to the optimal cleanliness range, the relatively good cleanliness range, the medium cleanliness range, the relatively poor cleanliness range, and the worst cleanliness range, respectively. The cleanliness level corresponding to the interval with the highest cleanliness index distribution among the five consecutive numerical intervals is determined as the cleanliness level of the heated surface at the current moment.
8. A device for evaluating the cleanliness of boiler heating surfaces, characterized in that, include: Protective outer tube (1), cooling inner tube (2), contaminated probe head (3), temperature acquisition unit, field operation data control center (18), temperature measurement mobile unit and data processor (16). The cooling inner tube (2) is coaxially fixed inside the protective outer tube (1) by welding; the data processor (16) is connected to the field operation data control center (18) and the temperature acquisition unit respectively; the contaminated probe (3) is placed outside the protective outer tube (1) at one end extending to the flue gas, and its placement direction is perpendicular to the flue gas flow direction; The contaminated probe (3) is used to deposit ash and slag in the flue. The temperature acquisition unit is used to acquire the temperature data of the surface of the contaminated probe head (3) in real time; The field operation data control center (18) is used to acquire the operation data of the distributed control system (DCS). The data processor (16) is used to acquire the temperature data of the surface of the boiler's heating surface and the DCS operation data of the distributed control system at the current moment; the placement direction of the contamination probe is perpendicular to the flow direction of the boiler flue gas; the contamination thermal resistance deposited on the surface of the contamination probe is calculated based on the temperature data of the surface of the contamination probe; the contamination thermal resistance and the DCS operation data are used as evaluation parameters to calculate the contamination degree index and contamination trend index corresponding to each evaluation parameter, and the contamination evaluation index of each evaluation parameter is determined based on the contamination degree index and the contamination trend index; the comprehensive contamination evaluation index is determined based on the contamination evaluation index of each evaluation parameter and the weight coefficient of each evaluation parameter, and multiple cleanliness indices are calculated based on the comprehensive contamination evaluation index and different cleanliness factors. The weighting coefficients of each evaluation parameter are determined by dynamic weighting; cluster analysis is performed on all cleanliness indices to obtain the cleanliness level of the heated surface.
9. The heating surface cleanliness assessment device as described in claim 8, characterized in that, The temperature acquisition unit includes a first thermocouple (9), a second thermocouple (8), and a third thermocouple (7) arranged in the direction of flue gas flow; the temperature probes of the first thermocouple (9), the second thermocouple (8), and the third thermocouple (7) are all kept in the same radial plane and are parallel to each other; the temperature probe of the first thermocouple (9) is located in the inner layer of the contaminated probe head to obtain the inner surface temperature of the contaminated probe head, the temperature probe of the second thermocouple (8) is located in the outer layer of the contaminated probe head to obtain the outer surface temperature of the contaminated probe head, and the temperature probe of the third thermocouple (7) is located in the outer side of the contaminated probe head (3) to obtain the surface temperature of the ash layer; The temperature measurement moving unit includes a telescopic component (6) fixed inside the protective outer tube (1). The temperature measurement moving unit is used to move the contaminated probe head (3); The bottom of the telescopic component (6) is connected to a movable baffle, and the telescopic component (6) moves the movable baffle up and down by extending and retracting in the vertical direction; the movable baffle (10) has a fixing hole on the inner side for inserting a third thermocouple protective bushing, and the end of the protective outer tube (1) that extends into the flue gas has a rectangular protrusion hole and two circular protrusion holes respectively; the inner side of the rectangular protrusion hole is close to the movable baffle (10); the two circular protrusion holes are used to arrange the protrusion and fixing of the first thermocouple (9) and the second thermocouple (8) respectively, and all protrusion holes are matched with the temperature probe size of the thermocouple; The air inlet of the cooling inner tube (2) is connected to the cooling air supply device (17); The cooling gas supply device (17) is used to supply cooling gas to the inner cooling tube (2). The cooling gas flows into the contaminated probe head (3) through the inner cooling tube (2) to cool the contaminated probe head (3) before entering the outer protective tube (1) and flowing out of the exhaust port of the outer protective tube (1) in the opposite direction to the air inlet.
10. The heating surface cleanliness assessment device as described in claim 8, characterized in that, The contamination image monitoring unit includes an optical camera (11) and a lens cooling conduit (12) arranged directly in front of the contamination probe head (3). The lens cooling conduit (12) has a cooling air inlet at the end near the optical camera (11) for supplying the required cooling air source to the cooling air supplier (17); An airflow guide plate is arranged near the end of the lens cooling duct (12) close to the contaminated probe head (3) so that the cooling air flows out in a downward direction; The optical camera (11) is connected to the data processor (16). The data processor (16) is connected to the PID control box (15) and is used to calculate the contamination thickness of the ash image through the data processor (16), and then feed back the distance that the third thermocouple (7) needs to move in real time to the PID control box (15), thereby outputting the control command of the telescopic component (6) to perform closed-loop control of the movement of the third thermocouple (7).