A rotary air preheater radial gap control system and gap adjustment method

Abstract

The application provides a rotary air preheater radial sealing gap control method, comprising the following steps: collecting target unit historical operation data set; training rotor thermal deformation prediction model based on the training sample set, and establishing gap-pressure mapping relationship library corresponding to different sealing wear stages through cold-state pressure calibration test; synchronously collecting multi-source parameters under current operation condition in real time; inputting real-time multi-source parameters into the trained rotor thermal deformation prediction model to output rotor gap prediction value under current condition; calling mapping relationship corresponding to wear stage from the gap-pressure mapping relationship library according to actual sealing operation time length, and converting the gap prediction value into pressure prediction value; setting contact pressure threshold value, combining with adjustment dead zone, overpressure / underpressure protection constraint condition, and calculating target adjustment amount of the sector plate; and controlling sector plate actuator to complete adjustment according to the target adjustment amount.

Description

Technical Field

[0001] This application relates to the field of rotary air preheaters, and more particularly to a radial clearance control system and clearance adjustment method for rotary air preheaters. Background Technology

[0002] During operation, a rotary air preheater relies on a radial sealing device to achieve radial sealing between the sector plate and the rotor. Radial sealing devices are divided into contact and non-contact types. Contact sealing devices generally use an elastic sealing plate, utilizing resilience to maintain a seal between the sealing plate and the sector plate. Many contact sealing devices have been fabricated based on this principle. For example, Chinese utility model patent number 202420152018.2, entitled "Flexible Sealing Device for Rotary Air Preheater and Rotary Air Preheater," discloses a solution including: a mounting component; a rotating shaft component rotatably connected to the mounting component; a flexible sealing component rotatably connected to the mounting component via the rotating shaft component; a rotating component rotatably disposed on the mounting component; and an elastic component having a first end and a second end, the first end connected to the rotating component and the second end connected to the flexible sealing component; under compression or extension, the elastic component drives the rotating component to rotate.

[0003] In actual use, due to factors such as coal quality, the calorific value of flue gas can vary significantly, resulting in large differences in flue gas temperature. Consequently, the gap between the sector plate and the rotor will also change considerably. The pressure on the sealing components will also change accordingly. When the sealing components are subjected to high pressure, they are prone to wear, warping, deformation, and accelerated aging of the springs, leading to poor sealing performance, increased air leakage, and, in severe cases, jamming, ultimately causing damage to the sealing components. Summary of the Invention

[0004] In view of this, this application proposes a radial sealing control method for a rotary air preheater, which improves the pressure between the sector plate and the sealing component by adjusting the gap between the sector plate and the rotor, thereby extending the service life of the sealing component and reducing the air leakage rate.

[0005] This application also proposes a radial sealing gap control system for a rotary air preheater.

[0006] A method for controlling the radial sealing gap of a rotary air preheater includes the following steps: Collect historical operating datasets of the target unit, including at least the unit load, flue gas temperature, rotor temperature, measured clearance value, and air leakage rate data under full load range, start-up and shutdown conditions, and different coal quality conditions, and construct a training sample set; A rotor thermal deformation prediction model is trained based on the training sample set, and a clearance-pressure mapping relationship library corresponding to different sealing wear stages is established through cold pressure calibration tests. Real-time synchronous acquisition of multi-source parameters under the current operating conditions, including at least the unit's real-time load, flue gas inlet and outlet temperature, rotor multi-position temperature, current position of the sector plate, air preheater drive current, ambient temperature, and calorific value of the coal fed into the furnace. The real-time multi-source parameters are input into the trained rotor thermal deformation prediction model, and the predicted value of rotor clearance under the current working condition is output. Based on the actual operating time of the seal, the corresponding wear stage mapping relationship is called from the gap-pressure mapping relationship library, and the gap prediction value is converted into the current seal contact pressure value. By setting the full radial contact pressure threshold and combining it with the adjustment dead zone and overpressure / underpressure protection constraints, the target adjustment amount of the sector plate is calculated. The control sector plate actuator completes the adjustment according to the target adjustment amount. After the adjustment is completed, the adjustment effect is verified by the change of air preheater drive current and flue gas oxygen content. If the control target is not achieved, fine-tuning correction is automatically triggered.

[0007] Preferably, the radial sealing gap control method for the rotary air preheater further includes incorporating the actual operating data of the day into the training sample set, incrementally updating the rotor thermal deformation prediction model parameters, and setting a period to combine the results of artificial air leakage rate tests to complete the model accuracy verification, so as to iteratively optimize the rotor thermal deformation prediction model.

[0008] Based on the radial sealing gap control method of rotary air preheater, this application also proposes a radial sealing gap control system for rotary air preheater to achieve radial sealing gap control.

[0009] A radial sealing clearance control system for a rotary air preheater, configured in a rotary air preheater with an adjustable sector plate and an elastic contact seal, comprising: The data acquisition unit is used to collect two types of data: Offline modeling dataset: Includes at least the target unit's full load range, start-up and shutdown, unit load under different coal quality conditions, flue gas temperature, rotor temperature, measured clearance, and air leakage rate data; Real-time operating parameters: These should include at least the unit's real-time load, flue gas inlet and outlet temperatures, rotor multi-position temperatures, current position of the sector plate, air preheater drive current, ambient temperature, and calorific value of the coal fed into the furnace. The model storage unit stores: The pre-trained rotor thermal deformation prediction model is used to output the rotor clearance prediction value based on real-time operating parameters; A clearance-pressure mapping library, including clearance values ​​and wear correction coefficients for different stages of seal wear; The control unit is configured to execute the following logic: The rotor thermal deformation prediction model is invoked based on real-time operating parameters to obtain the predicted clearance value; Based on the actual operating time of the seal, the mapping relationship of the corresponding wear stage is invoked to convert the gap prediction value into the pressure prediction value. By setting a contact pressure threshold and combining it with the adjustment dead zone and overpressure / underpressure protection constraints, the target adjustment amount of the sector plate is calculated. The execution feedback unit includes: The sector plate drive mechanism receives the target adjustment amount and completes the sector plate position adjustment; The feedback verification module verifies the adjustment effect by measuring the changes in air preheater drive current and flue gas oxygen content after adjustment. If the target is not met, it automatically triggers fine-tuning correction.

[0010] Preferably, the rotary air preheater radial sealing gap control system further includes an iterative calibration unit, which incorporates the actual operating data of the day into the modeling dataset, incrementally updates the rotor thermal deformation prediction model parameters, and completes the model accuracy verification by combining the results of artificial air leakage rate test within a set period.

[0011] The technical advantages of this application are as follows: By optimizing the radial pressure distribution, the sealing contact pressure deviation is significantly reduced, effectively preventing overpressure wear and deformation of the sealing components, improving the average lifespan of the sealing device, and reducing the maintenance cost of the sealing device. Simultaneously, due to the improved sealing contact pressure, the sealing performance of the sealing components is effectively maintained, reducing the air leakage rate of the rotary preheater. Detailed Implementation

[0012] The embodiments of the technical solution of this application will be described in detail below. The following embodiments are only used to illustrate the technical solution of this application more clearly, and are therefore only examples, and should not be used to limit the scope of protection of this application.

[0013] A method for controlling the radial sealing gap of a rotary air preheater includes the following steps: Collect historical operating datasets of the target unit, including full load range operating conditions, start-up and shutdown operating conditions, unit load, flue gas temperature, rotor temperature, measured clearance value, and air leakage rate data under different coal quality conditions, and construct a training sample set; A rotor thermal deformation prediction model is trained based on the training sample set, and a clearance-pressure mapping relationship library corresponding to different sealing wear stages is established through cold pressure calibration tests. The rotor thermal deformation prediction model is trained based on historical unit load, flue gas temperature, rotor temperature, corresponding measured gap values, and air leakage rate data. This enables the rotor thermal deformation prediction model to predict the gap and air leakage at a future time by real-time detection data. Furthermore, by adjusting the lifting and lowering of the sector plate, the pressure between the sector plate and the sealing device is stabilized, ensuring that the wear of the sealing devices at each location is consistent.

[0014] The gap-pressure mapping relationship library is a set of correspondences between the gap values ​​of the sector plate and the sealing sheet and the sealing contact pressure values ​​under different wear stages. It is used to quickly convert the gap values ​​predicted by the model into the contact pressure values ​​required for control. It is stored in the control system in two forms: piecewise linear interpolation table and fitting formula, and can be directly called without complex calculations.

[0015] In a preferred embodiment, the wear of the sealing device is divided into five stages based on its operating time. The first stage is within one year of operation, with a cumulative wear thickness of 0 to 0.5 mm, and the gap-pressure mapping relationship is the reference mapping curve calibrated in the cold state. The second stage is 1 to 3 years of operation, with a cumulative wear thickness of 0.5 to 1.5 mm, and the reference curve shifts to the right by 0.5 mm. The third stage is 3 to 5 years, with a cumulative wear thickness of 1.5 to 2.5 mm, and the reference curve shifts to the right by 1.5 mm. The fourth stage is 5 to 7 years, with a cumulative wear thickness of 2.5 to 3.5 mm, and the reference curve shifts to the right by 2.5 mm. The fifth stage is 7 to 10 years, with a cumulative wear thickness of 3.5 to 4.5 mm, and the reference curve shifts to the right by 3.5 mm. For example, if the current sealing device has been in operation for four years and is in the third wear stage, with a predicted gap of 3.5mm: if the mapping table for a new seal is used, 3.5mm corresponds to a pressure of 0.11MPa. The control logic will judge the pressure as too low, thus incorrectly pressing down the sector plate. Therefore, it is necessary to call the corrected mapping table for the third stage. The 3.5mm gap corresponds to an actual compression of 2mm, corresponding to a pressure of 0.2MPa. The pressure is within the set range, and no adjustment of the sector plate is needed. Through staged correction, even if the seal wears to the end of its lifespan, the pressure calculation error remains controllable.

[0016] The expression for the reference mapping curve is: The reference mapping curve conforms to a quadratic polynomial law, and its general expression is: in: P: Sealing contact pressure, in MPa; h: The gap between the sector plate and the top surface of the rotor radial partition, in mm; a, b, c: Coefficients obtained through cold calibration tests, which are related to the sealing structure, spring stiffness, and material.

[0017] The mapping curves for different wear stages only require gap shift correction to the baseline function; there is no need to refit the coefficients. in Dh This represents the cumulative wear amount corresponding to the wear stage.

[0018] Real-time synchronous acquisition of multi-source parameters under the current operating conditions, including real-time unit load, flue gas inlet and outlet temperature, rotor multi-position temperature, current position of sector plate, air preheater drive current, ambient temperature and calorific value of coal fed into the furnace; The real-time multi-source parameters are input into the trained rotor thermal deformation prediction model, and the predicted value of the rotor clearance under the current working condition is output. Based on the actual operating time of the seal, the corresponding wear stage mapping relationship is called from the clearance-pressure mapping relationship library to convert the clearance prediction value into the pressure prediction value; By setting a contact pressure threshold and combining it with the adjustment dead zone and overpressure / underpressure protection constraints, the target adjustment amount of the sector plate is calculated. The control sector plate actuator completes the adjustment according to the target adjustment amount. After the adjustment is completed, the adjustment effect is verified by the change of air preheater drive current and flue gas oxygen content. If the control target is not achieved, fine-tuning correction is automatically triggered.

[0019] In a preferred embodiment, this application employs the XGBoost regression algorithm, combined with the physical properties of air preheater thermal deformation, to train the rotor thermal deformation prediction model. Specifically, during the training process, a loss function is constructed using the physical formula of thermal expansion as a hard constraint: in: For data fitting terms; For physical constraints; For regularization terms; N represents the total number of training samples; Indicates the first i The model predicts the gap value for each sample; Indicates the first i The manually measured gap value corresponding to each sample; λ: Physical constraint weighting coefficient, ranging from 0.3 to 0.5, balancing the data fit and physical consistency; This represents the basic deformation calculated using physical formulas; Indicates the first i The temperature difference between the rotor end face of each sample and the cold reference; α represents the coefficient of linear expansion of the rotor material; H Indicates the axial height of the rotor; K(r) This represents the radial position correction factor, which increases linearly from 0.1 to 1.0 from the center to the outer edge. γ represents the leaf node splitting penalty coefficient, which controls the complexity of the decision tree; T This represents the total number of decision trees; l reg This represents the regularization coefficient, which prevents the model from overfitting. w j Indicates the first j The weight values ​​of each leaf node.

[0020] The training of a rotor thermal deformation prediction model has three elements: initial input features, label features, and loss function.

[0021] In a preferred embodiment, the weights of four features in the input features—unit load, flue gas inlet / outlet temperature, rotor center cylinder temperature, and rotor outer edge temperature—account for more than 70% of the total weight, in order to conform to the physical laws of thermal deformation and avoid the model learning spurious correlations.

[0022] In a preferred embodiment, the label features include: manually measured radial clearance values ​​under different operating conditions and leakage rate test data at corresponding time points. Due to the hysteresis of rotor thermal deformation, the feature data corresponding to the label clearance value is shifted forward by 10-15 minutes to ensure that the features correspond to the time sequence of the label.

[0023] The initial input features are historical operating condition parameters; the label features are the measured gap values ​​under the corresponding operating conditions; the loss function is used to calculate the deviation between the predicted value and the label, while ensuring that the result conforms to the physical laws of thermal deformation. The rotor thermal deformation prediction model adopts the XGBoost regression algorithm, aiming to minimize the loss function. The decision tree parameters inside the model are iteratively adjusted repeatedly until the loss function converges and the deviation no longer decreases. After training, a fixed prediction model is obtained. The trained XGBoost regression model is essentially a set of optimized decision tree rules.

[0024] During runtime, the current working condition features are directly input into the training model, and the prediction results are output as follows: Collect current operating data and input features: unit load, flue gas inlet / outlet temperature, rotor center cylinder temperature, rotor outer edge temperature, primary / secondary air pressure, ambient temperature, calorific value of coal fed into the furnace, and air preheater operating time; Based on the fixed XGBoost model, the interval prediction value is output within the current or future set time period through the rule judgment of multiple decision trees.

[0025] The final output is the full radial clearance distribution curve, which is used for subsequent pressure mapping and sector plate adjustment.

[0026] It should be noted that XGBoost is an algorithm framework. The rotor thermal deformation prediction model in this application is a proprietary prediction model adapted to the rotary air preheater after training based on this framework, rather than a general algorithm.

[0027] In a preferred embodiment, the radial sealing gap control method for the rotary air preheater further includes incorporating the actual operating data of the day into the training sample set, incrementally updating the rotor thermal deformation prediction model parameters, and setting a period to combine the results of artificial air leakage rate tests to complete the model accuracy verification, so as to iteratively optimize the rotor thermal deformation prediction model.

[0028] Based on the radial sealing gap control method of rotary air preheater, this application also proposes a radial sealing gap control system for rotary air preheater to achieve radial sealing gap control.

[0029] A radial sealing clearance control system for a rotary air preheater, configured in a rotary air preheater with an adjustable sector plate and an elastic contact seal, comprising: The data acquisition unit is used to collect two types of data: Offline modeling dataset: Includes at least the target unit's full load range, start-up and shutdown, unit load under different coal quality conditions, flue gas temperature, rotor temperature, measured clearance, and air leakage rate data; Real-time operating parameters: These should include at least the unit's real-time load, flue gas inlet and outlet temperatures, rotor multi-position temperatures, current position of the sector plate, air preheater drive current, ambient temperature, and calorific value of the coal fed into the furnace. The model storage unit stores: The pre-trained rotor thermal deformation prediction model is used to output the rotor clearance prediction value based on real-time operating parameters; A clearance-pressure mapping library, including clearance values ​​and wear correction coefficients for different stages of seal wear; The control unit is configured to execute the following logic: The rotor thermal deformation prediction model is invoked based on real-time operating parameters to obtain the predicted clearance value; Based on the actual operating time of the seal, the mapping relationship of the corresponding wear stage is invoked to convert the gap prediction value into the pressure prediction value. By setting a contact pressure threshold and combining it with the adjustment dead zone and overpressure / underpressure protection constraints, the target adjustment amount of the sector plate is calculated. The execution feedback unit includes: The sector plate drive mechanism receives the target adjustment amount and completes the sector plate position adjustment; The feedback verification module verifies the adjustment effect by measuring the changes in air preheater drive current and flue gas oxygen content after adjustment. If the target is not met, it automatically triggers fine-tuning correction.

[0030] In a preferred embodiment, the rotary air preheater radial sealing gap control system further includes an iterative calibration unit, which incorporates the actual operating data of the day into the modeling dataset, incrementally updates the rotor thermal deformation prediction model parameters, and completes model accuracy verification by combining the results of artificial air leakage rate tests within a set period.

[0031] In a preferred embodiment, the sector plate is an integral hinged sector plate, a segmented flexible sector plate, or a semi-segmented floating sealing plate, and the control calculation unit can adapt to different structures to output corresponding adjustment amounts.

[0032] In a preferred embodiment, the single adjustment step of the sector plate actuator is ≤2mm, the adjustment speed is 0.5mm / s, and the adjustment dead zone is 0.5mm.

[0033] The effectiveness of the proposed solution will be verified below with reference to the embodiments.

[0034] This embodiment is based on the retrofit project of a rotary air preheater for a 300MW coal-fired unit in a domestic power plant. No changes were made to the original mechanical structure, such as the sector plates and sealing plates; performance improvements were achieved solely through software algorithm upgrades. The gateway directly connects to the power plant's existing DCS system, collecting data from 12 existing operational measurement points without requiring any additional field sensors. The collected parameters include: real-time unit load, primary / secondary air pressure, flue gas inlet and outlet temperatures, rotor center / outer edge temperature, current position of the sector plates, air preheater drive current, ambient temperature, and calorific value of the coal fed into the furnace.

[0035] Training dataset: Export the unit's historical operating data for the past year, totaling 100,000 valid samples, including 48 sets of manually measured gap label data, covering the full load range of 0% to 100%; Cold pressure calibration: Adjust the sector plate in 0.5mm increments while the machine is stopped, record 10 sets of gap-current corresponding values, fit the gap-pressure mapping curve of the new sealing stage, and calculate the mapping library of 5 wear stages based on an annual wear of 0.5mm. Model training: The XGBoost algorithm is used for training, with a loss function that incorporates the physical constraint of thermal expansion.

[0036] Daily air leakage rate checks were conducted on the rotary preheater. After six months of operation, the average air leakage rate was 6.8%. Before the modification, the average air leakage rate was 10.1%. Compared to the original model, this application significantly reduced the air leakage rate of the rotary preheater. The air leakage rate indicates that this application significantly improves the sealing performance of the radial sealing device, providing excellent protection for it. Furthermore, during maintenance, 10 radial sealing devices on this rotary preheater were replaced, compared to 15 devices on the same rotary preheater during the same six months prior to the modification. This demonstrates that this application significantly extends the service life of the radial sealing device.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for controlling the radial sealing gap of a rotary air preheater, applied to a rotary air preheater equipped with an adjustable sector plate and an elastic contact seal, characterized in that, Includes the following steps: Collect historical operating datasets of the target unit, including full load range operating conditions, start-up and shutdown operating conditions, unit load, flue gas temperature, rotor temperature, measured clearance value, and air leakage rate data under different coal quality conditions, and construct a training sample set; A rotor thermal deformation prediction model is trained based on the training sample set, and a clearance-pressure mapping relationship library corresponding to different sealing wear stages is established through cold pressure calibration tests. Real-time synchronous acquisition of multi-source parameters under the current operating conditions, including real-time unit load, flue gas inlet and outlet temperature, rotor multi-position temperature, current position of sector plate, air preheater drive current, ambient temperature and calorific value of coal fed into the furnace; The real-time multi-source parameters are input into the trained rotor thermal deformation prediction model, and the predicted value of rotor clearance under the current working condition is output. Based on the actual operating time of the seal, the corresponding wear stage mapping relationship is called from the gap-pressure mapping relationship library, and the gap prediction value is converted into the current seal contact pressure value. By setting a contact pressure threshold and combining it with the adjustment dead zone and overpressure / underpressure protection constraints, the target adjustment amount of the sector plate is calculated. The control sector plate actuator completes the adjustment according to the target adjustment amount. After the adjustment is completed, the adjustment effect is verified by the change of air preheater drive current and flue gas oxygen content. If the control target is not achieved, fine-tuning correction is automatically triggered.

2. The radial sealing gap control method for a rotary air preheater as described in claim 1, characterized in that, The rotor thermal deformation prediction model is trained using the XGBoost regression algorithm combined with a loss function that incorporates thermal expansion physical constraints.

3. The radial sealing gap control method for a rotary air preheater as described in claim 2, characterized in that, The loss function is: in: N represents the total number of training samples; Indicates the first i The model predicts the gap value for each sample; Indicates the first i The manually measured gap value corresponding to each sample; λ: Physical constraint weighting coefficient, ranging from 0.3 to 0.5, balancing the data fit and physical consistency; This represents the basic deformation calculated using physical formulas; Indicates the first i The temperature difference between the rotor end face of each sample and the cold reference; α represents the coefficient of linear expansion of the rotor material; H Indicates the axial height of the rotor; K(r) This represents the radial position correction factor, which increases linearly from 0.1 to 1.0 from the center to the outer edge. γ represents the leaf node splitting penalty coefficient, which controls the complexity of the decision tree; T This represents the total number of decision trees; λ reg This represents the regularization coefficient, which prevents the model from overfitting. w j Indicates the first j The weight values ​​of each leaf node.

4. The radial sealing gap control method for a rotary air preheater as described in claim 2, characterized in that, When training with the XGBoost regression algorithm, the weights of the four features—unit load, flue gas inlet / outlet temperature, rotor center cylinder temperature, and rotor outer edge temperature—account for more than 70% of the total weight.

5. The radial sealing gap control method for a rotary air preheater as described in claim 2, characterized in that, When training with the XGBoost regression algorithm, the label features include: manually measured gap values ​​under different operating conditions and air leakage rates at corresponding time points.

6. The radial sealing gap control method for a rotary air preheater as described in claim 1, characterized in that, The process also includes the following steps: incorporating the actual operating data of the day into the training sample set, incrementally updating the parameters of the rotor thermal deformation prediction model, setting a period to combine the results of artificial air leakage rate tests to complete the model accuracy verification, so as to iteratively optimize the rotor thermal deformation prediction model.

7. A radial sealing clearance control system for a rotary air preheater, configured in a rotary air preheater with an adjustable sector plate and an elastic contact seal, characterized in that, include: The data acquisition unit is used to collect two types of data: Offline modeling dataset: Includes at least the target unit's full load range, start-up and shutdown, unit load under different coal quality conditions, flue gas temperature, rotor temperature, measured clearance, and air leakage rate data; Real-time operating parameters: These should include at least the unit's real-time load, flue gas inlet and outlet temperatures, rotor multi-position temperatures, current position of the sector plate, air preheater drive current, ambient temperature, and calorific value of the coal fed into the furnace. The model storage unit stores: The pre-trained rotor thermal deformation prediction model is used to output the rotor full radial clearance distribution curve based on real-time operating parameters; A clearance-pressure mapping library, including clearance-pressure mapping curves and wear correction coefficients corresponding to different stages of seal wear; The control unit is configured to execute the following logic: The rotor thermal deformation prediction model is invoked based on real-time operating parameters to obtain the predicted clearance value; Based on the actual operating time of the seal, the mapping relationship of the corresponding wear stage is invoked to convert the gap prediction value into the pressure prediction value; By setting a contact pressure threshold and combining it with the adjustment dead zone and overpressure / underpressure protection constraints, the target adjustment amount of the sector plate is calculated. The execution feedback unit includes: The sector plate drive mechanism receives the target adjustment amount and completes the sector plate position adjustment; The feedback verification module verifies the adjustment effect by measuring the changes in air preheater drive current and flue gas oxygen content after adjustment. If the target is not met, it automatically triggers fine-tuning correction.

8. The rotary air preheater radial sealing gap control system as described in claim 7, characterized in that, The rotary air preheater radial sealing gap control system also includes an iterative calibration unit, which incorporates the actual operating data of the day into the modeling dataset, incrementally updates the rotor thermal deformation prediction model parameters, and completes the model accuracy verification by combining the results of artificial air leakage rate tests within a set period.

9. The rotary air preheater radial sealing gap control system as described in claim 7, characterized in that, The sector plate can be an integral hinged sector plate, a segmented flexible sector plate, or a semi-segmented floating sealing plate. The control calculation unit can be adapted to different structures to output corresponding adjustment amounts.

10. The rotary air preheater radial sealing gap control system as described in claim 7, characterized in that, The single adjustment step of the sector plate actuator is ≤2mm, the adjustment speed is 0.5mm / s, and the adjustment dead zone is 0.5mm.

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