A coking monitoring and early warning device system and method for coal-fired power station boilers

Abstract

The present invention provides a coking monitoring and early warning system and method for coal-fired power plant boilers. By adding flue gas temperature monitoring devices and wall temperature monitoring devices to the partition screen, final superheater, and final reheater of a coal-fired power plant boiler, calculations are performed based on massive amounts of flue gas and wall temperature data to determine the contamination coefficient of the boiler's heating surfaces. Based on this data, indirect monitoring and digital visualization of boiler coking conditions, ash accumulation levels, and coking locations are performed. This coking monitoring and early warning method is more accurate and proactive than manual assessment of boiler coking conditions, guiding operators in optimizing operations and ensuring the safe and stable operation of coal-fired power plant boilers.

Description

Technical Field

[0001] The present invention relates to the technical field of boiler operation optimization, and in particular to a coking monitoring and early warning device system and method for coal-fired power station boilers. Background Art

[0002] To reduce power generation costs and improve competitiveness, some coal-fired units have begun blending other types of coal beyond their designated coal type, primarily with low-quality coals such as lignite. However, blending with low-quality coals can lead to a series of problems, including coking and fouling. Furthermore, improper combustion conditions can also cause uneven combustion within the furnace, a deflected flame center, and flame brushing. In severe cases, this can lead to coking on the furnace's heating surfaces.

[0003] Dust and coke buildup on boiler heating surfaces affects heat transfer, reducing boiler efficiency and increasing coal consumption. Due to the unique operating environment of boiler heating surfaces, operators have long lacked effective monitoring methods. Instead, they rely primarily on on-site inspections, checking fire holes, and reviewing historical data for empirical analysis and judgment, which is both timely and inaccurate. Therefore, solving the problem of online, real-time monitoring and early warning of coke buildup on boiler heating surfaces has become a pressing issue.

[0004] CN202118880U discloses a boiler intelligent sootblowing optimization and online coking warning system, including a controller, a monitoring system, and a gas sootblowing system. The monitoring point of the monitoring system is set on the local heating surface of the boiler, and the controller determines and transmits instructions to the gas sootblowing system based on the signal analysis transmitted by the monitoring system, and the gas sootblowing system performs sootblowing according to the instructions. The preferred scheme also includes a coking warning system and an ultra-high temperature warning system. On the basis of online monitoring of pollution on each heating surface of the boiler, an intelligent sootblowing operation mode combining open-loop operation guidance of the system with closed-loop feedback monitoring and control is realized, which reduces the exhaust gas temperature and improves the boiler efficiency. At the same time, a coking warning and over-temperature warning system are established, so that the safe and economical operation of the boiler is further guaranteed.

[0005] CN110738328A discloses a preventative maintenance system for boiler heating surface wear and explosion prevention, comprising: a 3D model module for establishing a 3D model for visual management of boiler equipment; a ledger management module for establishing equipment ledger information for electronic equipment ledger management; the ledger information includes heating surface tube banks, headers, and weld information; the equipment ledger information is associated with the 3D model; a SIS data acquisition module for collecting SIS data; the SIS data is associated with the 3D model; a high-temperature warning module for issuing high-temperature alarms based on furnace temperature distribution and wall temperature; and a metal thinning rate analysis module for analyzing metal thinning rates based on operating condition data, furnace wall thickness, and sootblower purge locations. The system enables visual management of boiler equipment data, electronic equipment ledger management, heating surface high-temperature warnings, and four-pipe leakage warnings, providing a powerful analysis platform for boiler leakage analysis, combustion uniformity analysis, coking warnings, and maintenance planning.

[0006] CN109934417A discloses a boiler coking early warning method based on a convolutional neural network, comprising the following steps: 1) collecting data information on whether the boiler is coked or not; 2) selecting the temperature data of several measuring points of coking or not in the same time period from the data information of step 1); 3) constructing a convolutional neural network model of coking or not, which includes: an input layer, a convolutional layer, a downsampling layer, a fully connected layer, and an output layer; 4) randomly selecting the temperature data of several measuring points of the same time period from the boiler data source collected in real time, inputting the convolutional neural network model of coking or not in step 3), obtaining the image features of the temperature data of the measuring points, and judging whether it is coked or not. The boiler coking early warning method provides an early warning scheme for boiler coking, can accurately predict the coking situation of the boiler heating surface, and provides a scientific guiding basis for judging the coking of the boiler heating surface.

[0007] However, the above-mentioned monitoring and data analysis methods for coking on the heating surface of the boiler are relatively complex, and the early warning signals issued are not accurate enough to guide the operating personnel to carry out timely processing and maintenance.

[0008] Therefore, considering the overall safety, economy and environmental protection of the boiler, it is of great significance to develop a coking monitoring and early warning device system and method for coal-fired power plant boilers to achieve operation optimization of coal-fired power plant boilers. Summary of the Invention

[0009] In view of the problems existing in the prior art, the present invention provides a coking monitoring and early warning device system and method for coal-fired power station boilers. By adding flue gas temperature monitoring devices and wall temperature monitoring devices at the partition screen, final superheater and final reheater of the coal-fired power station boiler, mining is carried out based on massive flue gas temperature data and wall temperature data, and the intrinsic correlation between the wall temperature change of the heating surface and the contamination and coking events is analyzed. The pollution coefficient of the furnace and the heating surface is calculated and determined, and on this basis, indirect monitoring and digital visualization of boiler coking conditions, ash accumulation degree, coking location and other information are carried out. Compared with the original manual judgment of coking conditions, it is more accurate and advanced, and can guide operating personnel to perform relevant optimization operations to ensure the safe and stable operation of coal-fired power station boilers.

[0010] To achieve this object, the present invention adopts the following technical solutions:

[0011] In a first aspect, the present invention provides a coking monitoring and early warning device system for a coal-fired power plant boiler, the coking monitoring and early warning device system comprising a temperature monitoring device, a data acquisition device, a DCS control system, an algorithm server, and a monitoring result screen display device connected in sequence;

[0012] The temperature monitoring device includes a smoke temperature monitoring device and a wall temperature monitoring device;

[0013] The smoke temperature monitoring device includes a first smoke temperature monitoring device arranged at the inlet of the partition screen, a second smoke temperature monitoring device arranged at the inlet of the final superheater, a third smoke temperature monitoring device arranged at the inlet of the final reheater, and a fourth smoke temperature monitoring device arranged at the outlet of the final reheater;

[0014] The wall temperature monitoring device includes a first wall temperature monitoring device arranged on the partition panel tube bundle, a second wall temperature monitoring device arranged on the last stage superheater panel tube bundle, and a third wall temperature monitoring device arranged on the last stage reheater panel tube bundle.

[0015] The coking monitoring and early warning device system for coal-fired power plant boilers of the present invention installs flue gas temperature monitoring devices and wall temperature monitoring devices at the three main heating surfaces of the boiler: the partition screen, the final superheater and the final reheater to monitor the flue gas temperature and the wall temperature of the boiler heating surface in real time. The massive flue gas temperature data and the wall temperature data are sent to the algorithm server for calculation along with the steam-water parameters of the unit to obtain the contamination coefficient C of each heating surface of the boiler. f By setting different threshold color changes to intuitively reflect the coking condition of the heating surface, the coking and contamination condition of the heating surface is digitized and visualized for reference by operating personnel to determine the coking condition of the boiler heating surface, and then guide operating personnel to perform relevant optimization operations to ensure the safe and stable operation of the boiler.

[0016] Preferably, the number of the first smoke temperature monitoring device, the second smoke temperature monitoring device, the third smoke temperature monitoring device and the fourth smoke temperature monitoring device are all 2.

[0017] Preferably, the number of the first wall temperature monitoring devices is 40 to 60, for example, it can be 40, 41, 43, 45, 48, 50, 55, 57 or 60, etc., but is not limited to the listed values, and other unlisted values within this numerical range are also applicable.

[0018] Preferably, the number of the second wall temperature monitoring devices is 62 to 124, for example, it can be 62, 64, 68, 70, 80, 90, 100, 110, 120 or 124, etc., but is not limited to the listed values, and other unlisted values within the numerical range are also applicable.

[0019] Preferably, the number of the third wall temperature monitoring devices is 182 to 273, for example, it can be 182, 185, 190, 200, 220, 250, 260, 270 or 273, etc., but is not limited to the listed values, and other unlisted values within this numerical range are also applicable.

[0020] The second invention, the present invention also provides a coking monitoring and early warning method for coal-fired power station boilers, the coking monitoring and early warning method is performed using the coking monitoring and early warning device system for coal-fired power station boilers described in the first aspect.

[0021] Preferably, the coking monitoring and early warning method comprises the following steps:

[0022] (1) The smoke temperature monitoring device and the wall temperature monitoring device respectively monitor the smoke temperature data and the wall temperature data and transmit them to the DCS control system through the data acquisition device;

[0023] (2) The DCS control system combines the flue gas temperature data and the wall temperature data with the steam-water parameters of the unit and sends them to the algorithm server for calculation to obtain the contamination coefficient C of the boiler heating surface. f ;

[0024] (3) The contamination coefficient C f Displayed in the monitoring result screen display device.

[0025] The coking monitoring and early warning method for coal-fired power plant boilers of the present invention sends a large amount of flue gas temperature data, wall temperature data and unit operation steam-water parameters to the algorithm server for calculation to obtain the contamination coefficient C of the boiler heating surface. f, providing auxiliary decision-making for operating personnel to determine the temperature level, coking degree, coking location and other information of the specific heating surface; intuitive, digital and visual feedback of the pollution situation of the heating surface, generating corresponding early warnings and operational guidance suggestions to ensure the safe and stable operation of coal-fired power plant boilers.

[0026] Preferably, the steam-water parameters in step (2) include the temperature of the working fluid, the pressure of the working fluid and the flow rate of the working fluid.

[0027] The working medium described in the present invention includes any one of water, steam or flue gas, or a combination of at least two of them.

[0028] Preferably, the contamination coefficient C in step (2) f The calculation process includes:

[0029] (I) Based on the pressure and temperature of the working fluid, the enthalpy values of the steam and water at the inlet and outlet of each heating surface and the flue gas at that state point are obtained;

[0030] (II) Using the convection heat transfer equation, the heat balance equation on the flue gas side, and the heat balance equation on the working fluid side, calculate the heat absorption and heat release of each heating surface, and then calculate the convection heat transfer coefficient K under different working conditions;

[0031] (III) According to the formula K = 1 / (1 / α + ε + 1 / β),

[0032] Among them, α is the convection heat transfer coefficient of the flue gas side of the outer wall of each heating surface tube, β is the convection heat transfer coefficient of the steam-water side of the inner wall of each heating surface tube, and ε is the ash contamination coefficient. The ash contamination coefficient ε of each heating surface is calculated and normalized to obtain the contamination coefficient C of each heating surface. f .

[0033] Preferably, the contamination coefficient C in step (2) f Including the overall contamination coefficient C f and local contamination coefficient C f .

[0034] Preferably, the overall contamination coefficient C f Including the overall contamination coefficient C of the partition screen f , the overall contamination coefficient C of the final superheater f and the overall contamination coefficient C of the final reheater f .

[0035] Preferably, the local contamination coefficient C f Including the contamination coefficient C of different areas of the partition screen f , the contamination coefficient C of different areas of the final superheater f The contamination coefficient C of different areas of the final reheater f .

[0036] The local contamination coefficient C of the present invention f It means that according to the physical structure of the partition screen, the final superheater and the final reheater, the three are divided into different areas according to the actual situation. The contamination coefficient C of the heating surface of each different small area of the partition screen, the final superheater and the final reheater is obtained by calculating the flue gas temperature and wall temperature data monitored by the temperature monitoring device in each small area after division and combining the steam-water parameters of the unit. f .

[0037] Preferably, according to step (2), the contamination coefficient C f Classify the coking degree of the heating surface;

[0038] When 0<C f <4, indicating that the current heating surface screen tubes are normal and no obvious coking occurs;

[0039] When 4≤C f <6, indicating that the heating surface screen tubes are slightly coked and require attention from the operator;

[0040] When 6≤C f <8, indicating that the heating surface screen tubes are currently heavily coked, and the operator needs to take relevant measures to prevent the deterioration of boiler coking;

[0041] When 8≤C f , indicating that the heating surface screen tubes are currently severely coked and the operator needs to take immediate measures.

[0042] Preferably, the display screen of the monitoring result display device in step (3) is provided with different colors to reflect the coking and contamination of the heated surface; among them, green represents normal, blue represents light coking, yellow represents heavy coking, and red represents severe coking.

[0043] The present invention reflects the coking and contamination conditions of the heating surface through different colors, so that the coking and contamination conditions of the heating surface can be intuitively visualized.

[0044] As a preferred technical solution of the present invention, the coking monitoring and early warning method includes the following steps:

[0045] (1) The smoke temperature monitoring device and the wall temperature monitoring device respectively monitor the smoke temperature data and the wall temperature data and transmit them to the DCS control system through the data acquisition device;

[0046] (2) The DCS control system combines the flue gas temperature data and the wall temperature data with the working fluid temperature, working fluid pressure and working fluid flow, and sends them to the algorithm server for calculation to obtain the contamination coefficient C of the boiler heating surface. f ; The contamination coefficient C f The calculation process includes:

[0047] (I) Based on the pressure and temperature of the working fluid, the enthalpy values of the steam and water at the inlet and outlet of each heating surface and the flue gas at that state point are obtained;

[0048] (II) Using the convection heat transfer equation, the heat balance equation on the flue gas side, and the heat balance equation on the working fluid side, calculate the heat absorption and heat release of each heating surface, and then calculate the convection heat transfer coefficient K under different working conditions;

[0049] (III) According to the formula K = 1 / (1 / α + ε + 1 / β),

[0050] Among them, α is the convection heat transfer coefficient of the flue gas side of the outer wall of each heating surface tube, β is the convection heat transfer coefficient of the steam-water side of the inner wall of each heating surface tube, and ε is the ash contamination coefficient. The ash contamination coefficient ε of each heating surface is calculated and normalized to obtain the contamination coefficient C of each heating surface. f .

[0051] The contamination coefficient C f Including the overall contamination coefficient C f and local contamination coefficient C f The overall contamination coefficient C f Including the overall contamination coefficient C of the partition screen f , the overall contamination coefficient C of the final superheater f and the overall contamination coefficient C of the final reheater f The local contamination coefficient C f Including the contamination coefficient C of different areas of the partition screen f , the contamination coefficient C of different areas of the final superheater f The contamination coefficient C of different areas of the final reheater f ;

[0052] According to the contamination coefficient C f Classify the coking degree of the heating surface;

[0053] When 0<C f <4, indicating that the current heating surface screen tubes are normal and no obvious coking occurs;

[0054] When 4≤C f <6, indicating that the current heating surface screen tubes are slightly coked;

[0055] When 6≤C f <8, indicating that the current heating surface screen tubes are heavily coked;

[0056] When 8≤C f , indicating that the current heating surface screen tubes are seriously coked;

[0057] (3) The contamination coefficient C fThe monitoring result is displayed on the screen display device, and different colors are set in the display screen to reflect the coking and contamination conditions of the heated surface; among them, green represents normal, blue represents light coking, yellow represents heavy coking, and red represents severe coking.

[0058] Compared with the prior art, the present invention has at least the following beneficial effects:

[0059] (1) The coking monitoring and early warning device system for coal-fired power station boilers provided by the present invention integrates the heat transfer model of the furnace, adds a flue gas temperature and wall temperature monitoring device, and calculates the contamination coefficient C of the boiler heating surface through the flue gas temperature data and wall temperature data. f And the coking situation of the heated surface can be displayed intuitively through the picture;

[0060] (2) The coking monitoring and early warning method for coal-fired power plant boilers provided by the present invention not only takes the boiler as a whole as the object, but also calculates the overall contamination coefficient C of the partition screen, the final superheater and the final reheater. f ; Moreover, the partition screen, final superheater and final reheater are divided into several small areas, and the contamination coefficient C of each area is obtained by calculation. f , and finally obtain the overall and local heat transfer characteristics of each heating surface, so that the overall and local coking and contamination conditions of the heating surface can be digitized;

[0061] (3) The coking monitoring and early warning method for coal-fired power station boilers provided by the present invention intuitively reflects the coking situation of the heating surface by setting different threshold color changes, providing auxiliary decision-making for operating personnel to determine the temperature level, coking degree, coking location and other information of the specific heating surface, intuitive, digital and visual feedback of the pollution situation of the heating surface, and early warning, providing reliable operation guidance for operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a schematic diagram of the coking monitoring and early warning device system for coal-fired power station boilers in the present invention.

[0063] Figure 2 It is a schematic diagram of the working process of the coking monitoring and early warning method for coal-fired power station boilers in the present invention.

[0064] Figure 3 This is a display screen effect diagram of the coking monitoring and early warning device system for coal-fired power station boilers in the present invention.

[0065] In the figure: 1-coal-fired power plant boiler; 2-partition screen; 21-first flue gas temperature monitoring device; 22-first wall temperature monitoring device; 3-final superheater; 31-second flue gas temperature monitoring device; 32-second wall temperature monitoring device; 4-final reheater; 41-third flue gas temperature monitoring device; 42-third wall temperature monitoring device; 43-fourth flue gas temperature monitoring device; 5-data acquisition device; 6-DCS control system; 7-algorithm server; 8-monitoring result screen display device. DETAILED DESCRIPTION

[0066] The technical solution of the present invention will be further described below with reference to the accompanying drawings and through specific implementation methods.

[0067] The present invention is further described in detail below. However, the following examples are merely simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims.

[0068] It should be understood that, in the description of the present invention, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0069] As a specific embodiment of the present invention, a coking monitoring and early warning device system for a coal-fired power station boiler is provided, as shown in FIG. Figure 1 The coking monitoring and early warning system is used to monitor the coking situation of a 660MW ultra-supercritical tangentially heated boiler produced by Harbin Boiler Plant and issue an early warning. In the figure, 1 is a coal-fired power station boiler.

[0070] The coking monitoring and early warning device system includes a temperature monitoring device, a data acquisition device 5, a DCS control system 6, an algorithm server 7 and a monitoring result screen display device 8 which are connected in sequence.

[0071] The algorithm server 7 is arranged in the control cabinet of the electronic equipment room, and the monitoring result screen display device 8 is arranged in the control room.

[0072] The temperature monitoring device includes a smoke temperature monitoring device and a wall temperature monitoring device.

[0073] The smoke temperature monitoring device includes a first smoke temperature monitoring device 21 provided at the inlet of the partition screen 2, a second smoke temperature monitoring device 31 provided at the inlet of the final superheater 3, a third smoke temperature monitoring device 41 provided at the inlet of the final reheater 4, and a fourth smoke temperature monitoring device 43 provided at the outlet of the final reheater 4;

[0074] The wall temperature monitoring device includes a first wall temperature monitoring device 22 arranged on the panel tube bundle of the separator 2, a second wall temperature monitoring device 32 arranged on the panel tube bundle of the last stage superheater 3, and a third wall temperature monitoring device 42 arranged on the panel tube bundle of the last stage reheater 4.

[0075] The number of the first smoke temperature monitoring device 21 , the second smoke temperature monitoring device 31 , the third smoke temperature monitoring device 41 and the fourth smoke temperature monitoring device 43 are all two.

[0076] The number of the first wall temperature monitoring devices 22 is 40; the number of the second wall temperature monitoring devices 32 is 100; and the number of the third wall temperature monitoring devices 42 is 240. Combined with the existing flue gas temperature monitoring devices and wall temperature monitoring devices on a 660MW ultra-supercritical tangentially connected boiler manufactured by Harbin Boiler Plant, there are a total of 62 wall temperature monitoring devices at the partition 2, 214 wall temperature monitoring devices at the final superheater 3, and 465 wall temperature monitoring devices at the final reheater 4.

[0077] As a specific embodiment of the present invention, a coking monitoring and early warning method for a coal-fired power station boiler is also provided, and its workflow diagram is as follows: Figure 2 As shown, the coking monitoring and early warning method is performed using the above-mentioned coking monitoring and early warning device system for coal-fired power station boilers.

[0078] The coking monitoring and early warning method comprises the following steps:

[0079] (1) The smoke temperature monitoring device and the wall temperature monitoring device respectively monitor the smoke temperature data and the wall temperature data and transmit them to the DCS control system through the data acquisition device;

[0080] (2) The DCS control system combines the flue gas temperature data and the wall temperature data with the working fluid temperature, working fluid pressure and working fluid flow, and sends them to the algorithm server for calculation to obtain the contamination coefficient C of the boiler heating surface. f ; The contamination coefficient C f The calculation process includes:

[0081] (I) Based on the pressure and temperature of the working fluid, the enthalpy values of the steam and water at the inlet and outlet of each heating surface and the flue gas at that state point are obtained;

[0082] (II) Using the convection heat transfer equation, the heat balance equation on the flue gas side, and the heat balance equation on the working medium side, calculate the heat absorption and heat release of the partition screen, the final superheater, and the final reheater, and then calculate the convection heat transfer coefficient K under different operating conditions;

[0083] (III) According to the formula K = 1 / (1 / α + ε + 1 / β),

[0084] Among them, α is the convection heat transfer coefficient of the flue gas side of the outer wall of each heating surface tube, β is the convection heat transfer coefficient of the steam-water side of the inner wall of each heating surface tube, ε is the ash contamination coefficient, the ash contamination coefficient ε of the partition screen, the final superheater and the final reheater is calculated, and the overall contamination coefficient C of the partition screen is obtained after normalization. f The overall contamination coefficient C of the final superheater is 4.6. f is 6.2, and the overall contamination coefficient C of the final reheater is f is 6.8;

[0085] According to the contamination coefficient C f Classify the coking degree of the separator, final superheater and final reheater;

[0086] The overall contamination coefficient of the partition screen is 4≤C f <6, indicating that the partition screen tube is slightly coked; the overall contamination coefficient of the final superheater is 6≤C f <8, indicating that the last stage superheater screen tube is heavily coked; the overall contamination coefficient of the last stage reheater is 6≤C f <8, indicating that the last stage reheater screen tubes are severely coked;

[0087] (3) The overall contamination coefficient C of the partition screen f , the overall contamination coefficient C of the final superheater f and the overall contamination coefficient C of the final reheater f The monitoring result is displayed in the display device, and the display effect diagram is as follows Figure 3 Different colors are set in the display screen to reflect the coking and contamination of the heated surface; among them, green represents normal, blue represents light coking, yellow represents heavy coking, and red represents severe coking;

[0088] The separator screen is displayed in blue, the last stage superheater is displayed in yellow, and the last stage reheater is displayed in yellow.

[0089] According to the results shown in the display, operators need to pay attention to the partition screen, carry out soot blowing on the final superheater and final reheater, increase the soot blowing frequency in the coking area, reduce the boiler load when necessary, and change the coke stress through load disturbance to achieve the purpose of coke removal and ensure the safe operation of coal-fired power plant boilers.

[0090] In summary, the coking monitoring and early warning device system and method for coal-fired power station boilers provided by the present invention intuitively, digitally, and visually reflect the contamination status of the heating surface of the coal-fired power station boiler, provide auxiliary decision-making for operating personnel to determine the temperature level, coking degree, coking location and other information of the specific heating surface, and provide early warning, providing reliable operational guidance for the safe operation of coal-fired power station boilers.

[0091] The applicant declares that the above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention fall within the scope of protection and disclosure of the present invention.

Claims

1. A coking monitoring and early warning method for coal-fired power station boilers, characterized in that: The coking monitoring and early warning method is carried out using the following coking monitoring and early warning device system for coal-fired power station boilers; The coking monitoring and early warning device system includes a temperature monitoring device, a data acquisition device, a DCS control system, an algorithm server and a monitoring result screen display device connected in sequence; The temperature monitoring device includes a smoke temperature monitoring device and a wall temperature monitoring device; The smoke temperature monitoring device includes a first smoke temperature monitoring device arranged at the inlet of the partition screen, a second smoke temperature monitoring device arranged at the inlet of the final superheater, a third smoke temperature monitoring device arranged at the inlet of the final reheater, and a fourth smoke temperature monitoring device arranged at the outlet of the final reheater; The wall temperature monitoring device includes a first wall temperature monitoring device provided on the separator panel tube bundle, a second wall temperature monitoring device provided on the final stage superheater panel tube bundle, and a third wall temperature monitoring device provided on the final stage reheater panel tube bundle; The coking monitoring and early warning method comprises the following steps: (1) The smoke temperature monitoring device and the wall temperature monitoring device respectively monitor the smoke temperature data and the wall temperature data and transmit them to the DCS control system through the data acquisition device; (2) The DCS control system combines the flue gas temperature data and the wall temperature data with the steam-water parameters of the unit and sends them to the algorithm server for calculation to obtain the contamination coefficient C of the boiler heating surface. f ; The steam-water parameters include the temperature of the working fluid, the pressure of the working fluid and the flow rate of the working fluid; The contamination coefficient C f The calculation process includes: (I) According to the pressure and temperature of the working fluid, the enthalpy values of the steam and water at the inlet and outlet of each heating surface and the flue gas at the pressure and temperature are obtained; (II) Using the convection heat transfer equation, the heat balance equation on the flue gas side, and the heat balance equation on the working fluid side, calculate the heat absorption and heat release of each heating surface, and then calculate the convection heat transfer coefficient K under different working conditions; (III) According to the formula K = 1 / (1 / α + ε + 1 / β), Among them, α is the convection heat transfer coefficient of the flue gas side of the outer wall of each heating surface tube, β is the convection heat transfer coefficient of the steam-water side of the inner wall of each heating surface tube, and ε is the ash contamination coefficient. The ash contamination coefficient ε of each heating surface is calculated and normalized to obtain the contamination coefficient C of each heating surface. f ; (3) The contamination coefficient C f Displayed in the monitoring result screen display device.

2. The coking monitoring and early warning method according to claim 1, characterized in that: The number of the first smoke temperature monitoring device, the second smoke temperature monitoring device, the third smoke temperature monitoring device and the fourth smoke temperature monitoring device are all 2.

3. The coking monitoring and early warning method according to claim 1, characterized in that: The number of the first wall temperature monitoring devices is 40 to 60.

4. The coking monitoring and early warning method according to claim 1, characterized in that: The number of the second wall temperature monitoring devices is 62 to 124.

5. The coking monitoring and early warning method according to claim 1, characterized in that: The number of the third wall temperature monitoring devices is 182 to 273.

6. The coking monitoring and early warning method according to claim 1, characterized in that: The contamination coefficient C in step (2) f Including the overall contamination coefficient C f and local contamination coefficient C f .

7. The coking monitoring and early warning method according to claim 6, characterized in that: The overall contamination coefficient C f Including the overall contamination coefficient C of the partition screen f , the overall contamination coefficient C of the final superheater f and the overall contamination coefficient C of the final reheater f .

8. The coking monitoring and early warning method according to claim 6, characterized in that: The local contamination coefficient C f Including the contamination coefficient C of different areas of the partition screen f , the contamination coefficient C of different areas of the final superheater f The contamination coefficient C of different areas of the final reheater f .

9. The coking monitoring and early warning method according to claim 1, characterized in that: According to the contamination coefficient C in step (2) f Classify the coking degree of the heating surface; When 0<C f <4, indicating that the current heating surface screen tubes are normal and no obvious coking occurs; When 4≤C f <6, indicating that the current heating surface screen tubes are slightly coked; When 6≤C f <8, indicating that the current heating surface screen tubes are heavily coked; When 8≤C f , indicating that the current heating surface screen tubes are severely coked.

10. The coking monitoring and early warning method according to claim 1, characterized in that: In step (3), the display screen of the monitoring result display device is provided with different colors to reflect the coking and contamination of the heated surface; among them, green represents normal, blue represents light coking, yellow represents heavy coking, and red represents severe coking.

11. The coking monitoring and early warning method according to claim 1, characterized in that: The coking monitoring and early warning method comprises the following steps: (1) The smoke temperature monitoring device and the wall temperature monitoring device respectively monitor the smoke temperature data and the wall temperature data and transmit them to the DCS control system through the data acquisition device; (2) The DCS control system combines the flue gas temperature data and the wall temperature data with the working fluid temperature, working fluid pressure and working fluid flow, and sends them to the algorithm server for calculation to obtain the contamination coefficient C of the boiler heating surface. f ; The contamination coefficient C f The calculation process includes: (I) According to the pressure and temperature of the working fluid, the enthalpy values of the steam and water at the inlet and outlet of each heating surface and the flue gas at the pressure and temperature are obtained; (II) Using the convection heat transfer equation, the heat balance equation on the flue gas side, and the heat balance equation on the working fluid side, calculate the heat absorption and heat release of each heating surface, and then calculate the convection heat transfer coefficient K under different working conditions; (III) According to the formula K = 1 / (1 / α + ε + 1 / β), Among them, α is the convection heat transfer coefficient of the flue gas side of the outer wall of each heating surface tube, β is the convection heat transfer coefficient of the steam-water side of the inner wall of each heating surface tube, and ε is the ash contamination coefficient. The ash contamination coefficient ε of each heating surface is calculated and normalized to obtain the contamination coefficient C of each heating surface. f ; The contamination coefficient C f Including the overall contamination coefficient C f and local contamination coefficient C f The overall contamination coefficient C f Including the overall contamination coefficient C of the partition screen f , the overall contamination coefficient C of the final superheater f and the overall contamination coefficient C of the final reheater f The local contamination coefficient C f Including the contamination coefficient C of different areas of the partition screen f , the contamination coefficient C of different areas of the final superheater f The contamination coefficient C of different areas of the final reheater f ; According to the contamination coefficient C f Classify the coking degree of the heating surface; When 0<C f <4, indicating that the current heating surface screen tubes are normal and no obvious coking occurs; When 4≤C f <6, indicating that the current heating surface screen tubes are slightly coked; When 6≤C f <8, indicating that the current heating surface screen tubes are heavily coked; When 8≤C f , indicating that the current heating surface screen tubes are seriously coked; (3) The contamination coefficient C f The monitoring result is displayed on the screen display device, and different colors are set in the display screen to reflect the coking and contamination conditions of the heated surface; among them, green represents normal, blue represents light coking, yellow represents heavy coking, and red represents severe coking.

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