Heating furnace energy efficiency optimization method and system

Abstract

The invention discloses a heating furnace energy efficiency optimization method and system, and particularly relates to the technical field of operation control. The method comprises the following steps: acquiring boiling state parameters and structural deformation parameters of a water jacket heater in an operation process, identifying a critical point position of conversion from nuclear boiling to membrane boiling and membrane boiling duration, and calculating a thermal expansion displacement rate and an oscillation phase angle of a furnace shell; a heat transfer coefficient fluctuation compensation factor is generated by analyzing the phase lag relation between boiling phase change circulation and thermal expansion deformation; calculating a heat flow distribution adjustment amount according to the heat transfer coefficient fluctuation compensation factor; calculating a dynamic compensation correction coefficient by combining the flow velocity variable quantity of the cooling water and the flow-thermal expansion transfer function; based on the heat flow distribution adjustment amount and the dynamic compensation correction coefficient, the power output and the cooling water flow of the water jacket heating furnace are regulated and controlled, dynamic optimization adjustment of the heat transfer behavior of the heating furnace is achieved, and the energy efficiency stability and the heat transfer control precision of the water jacket heating furnace under complex working conditions are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of operation control, and more specifically, to a method and system for optimizing the energy efficiency of a heating furnace. Background Art

[0002] In the existing operation control of water jacket heating furnaces, it is generally assumed that the heat transfer process occurs under stable structural conditions, ignoring the dynamic coupling relationship between the boiling state inside the furnace body and the structural thermal response under variable load conditions. Especially during the phase change cycle where nucleate boiling and film boiling states frequently alternate, a two-way feedback mechanism is formed between the heat flux density on the furnace wall and the thermal expansion and contraction of the structure, resulting in the heat transfer coefficient showing phase lag and periodic fluctuations. Summary of the Invention

[0003] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a method and system for optimizing the energy efficiency of a heating furnace to solve the problems raised in the above background art.

[0004] To achieve the above object, the present invention provides the following technical solutions: A method for optimizing the energy efficiency of a heating furnace, comprising the following steps: S1: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace; S2: Based on the boiling state parameters of the furnace body, identify the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling; S3: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell; S4: Combine the critical point position of the transition from nucleate boiling to film boiling, the duration of film boiling, the thermal expansion displacement rate and oscillation phase angle of the furnace body, analyze the phase lag relationship between the boiling phase change cycle and thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor; S5: According to the heat transfer coefficient fluctuation compensation factor, calculate the adjustment amount of the heat flux distribution to suppress the boiling-thermal expansion co-instability; S6: Collect the change amount of the flow rate of cooling water, and calculate the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function; S7: According to the adjustment amount of the heat flux distribution and the dynamic compensation correction coefficient, regulate the power output and the cooling water flow rate of the water jacket heating furnace.

[0005] In a preferred embodiment, S1 is specifically: Collect the temperature gradient data on the inner wall of the furnace body and the bubble detachment frequency data on the inner wall of the furnace body during the operation of the water jacket heating furnace; Collect the displacement data and thermal stress distribution data of the furnace shell at different monitoring positions during the operation of the water jacket heating furnace; Align and synchronize the temperature gradient data, bubble detachment frequency data, furnace shell displacement data, and thermal stress distribution data in time series to obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell.

[0006] In a preferred embodiment, S2 is specifically as follows: Perform multi-scale analysis on the temperature gradient data to determine the critical point position corresponding to the transition from nucleate boiling to film boiling; Based on the fluctuation characteristics of the bubble detachment frequency data, determine the start time and end time of film boiling, and calculate the duration of film boiling on the inner wall of the furnace body.

[0007] In a preferred embodiment, S3 is specifically as follows: Based on the displacement data at different monitoring positions of the furnace shell, calculate the thermal expansion displacement change rate at different monitoring positions of the furnace shell; Based on the thermal stress distribution data at different monitoring positions of the furnace shell, calculate the oscillation phase angle when the displacement changes at different monitoring positions of the furnace shell.

[0008] In a preferred embodiment, S4 is specifically as follows: Based on the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, determine the temperature fluctuation period and phase change law of the inner wall of the furnace body during the boiling phase change cycle; Based on the thermal expansion displacement change rate and oscillation phase angle at different monitoring positions of the furnace shell, determine the displacement oscillation period and phase change law of the furnace shell structure during the thermal expansion deformation process; Through the temperature fluctuation period and phase change law, and the displacement oscillation period and phase change law, determine the phase lag relationship between the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure; According to the phase lag relationship, calculate the heat transfer coefficient fluctuation compensation factor for correcting the heat transfer coefficient fluctuation.

[0009] In a preferred embodiment, S5 is specifically as follows: Based on the heat transfer coefficient fluctuation compensation factor, calculate the local temperature fluctuation amplitude at different monitoring positions of the inner wall of the furnace body during the boiling phase change cycle; Based on the heat transfer coefficient fluctuation compensation factor, calculate the displacement oscillation amplitude at different monitoring positions of the furnace shell during the thermal expansion deformation process; According to the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude, identify the boiling-thermal expansion co-instability region under the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure; For the boiling-thermal expansion co-instability region, calculate the heat flux distribution adjustment amount.

[0010] In a preferred embodiment, S6 is specifically as follows: Collect the change amount of the cooling water flow rate during the operation of the water jacket heating furnace; Substitute the change amount of the cooling water flow rate into the pre-established flow rate-thermal expansion transfer function, and calculate the dynamic compensation correction coefficient for correcting the change amount of the cooling water flow rate.

[0011] In a preferred embodiment, S7 is specifically: Based on the adjustment amount of the heat flow distribution, determine the target adjustment value of the heating power of the water jacket heating furnace; Adjust the power output of the heating unit of the water jacket heating furnace according to the target adjustment value; Based on the dynamic compensation correction coefficient, determine the target adjustment value of the cooling water flow rate; According to the target adjustment value, adjust the opening amplitude of the cooling water flow rate regulating valve in real time.

[0012] On the other hand, the present invention provides a heating furnace energy efficiency optimization system, including: Data acquisition module: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace; Boiling identification module: Based on the boiling state parameters of the furnace body, identify the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling; Deformation analysis module: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell; Phase analysis module: Combine the critical point position of the transition from nucleate boiling to film boiling, the duration of film boiling, the thermal expansion displacement rate and oscillation phase angle of the furnace body, analyze the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor; Heat flow adjustment module: According to the heat transfer coefficient fluctuation compensation factor, calculate the heat flow distribution adjustment amount for suppressing the boiling-thermal expansion co-instability; Flow rate compensation module: Collect the change amount of the cooling water flow rate, and calculate the dynamic compensation correction coefficient based on the flow rate-thermal expansion transfer function; Regulation execution module: According to the heat flow distribution adjustment amount and the dynamic compensation correction coefficient, regulate the power output and the cooling water flow rate of the water jacket heating furnace.

[0013] The technical effects and advantages of the heating furnace energy efficiency optimization method and system of the present invention: By obtaining the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace, the phase change behavior and the characteristics of thermal stress response during the heating process can be comprehensively perceived, and the critical behavior of the transition from nucleate boiling to film boiling and its continuous influence can be effectively captured; by identifying the position and duration of the transition critical point from nucleate boiling to film boiling and calculating the thermal expansion displacement rate and oscillation phase angle, the accurate quantification of the phase change periodicity and structural dynamic response can be achieved; by analyzing the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation, a heat transfer coefficient fluctuation compensation factor is generated to effectively predict and correct the unstable trend of the heat flux response; according to the heat transfer coefficient fluctuation compensation factor, the heat flux distribution adjustment amount is calculated; the flow rate change of the cooling water is collected, and the dynamic compensation correction coefficient is calculated; according to the heat flux distribution adjustment amount and the dynamic compensation correction coefficient, the power output and the cooling water flow rate of the water jacket heating furnace are regulated, and the efficiency of heat energy transfer and the operation stability are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 Schematic diagram of an energy efficiency optimization method for a heating furnace according to the present invention; Figure 2 Schematic structural diagram of an energy efficiency optimization system for a heating furnace according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0015] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0016] Embodiment 1

[0017] Figure 1 An energy efficiency optimization method for a heating furnace according to the present invention is provided, which includes the following steps: S1: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace; S2: Based on the boiling state parameters of the furnace body, identify the position of the transition critical point from nucleate boiling to film boiling and the duration of film boiling; S3: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell; S4: Combine the position of the transition critical point from nucleate boiling to film boiling and the duration of film boiling, the thermal expansion displacement rate and oscillation phase angle of the furnace body, analyze the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor; S5: According to the heat transfer coefficient fluctuation compensation factor, calculate the heat flux distribution adjustment amount for suppressing the boiling-thermal expansion co-instability; S6: Collect the flow rate change of cooling water and calculate the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function; S7: According to the heat flux distribution adjustment amount and the dynamic compensation correction coefficient, the power output and cooling water flow of the water jacket heating furnace are regulated.

[0018] S1: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace, including: Collect the temperature gradient data of the inner wall of the water jacket heating furnace and the frequency data of the bubbles separating from the inner wall of the furnace during operation; The method for collecting temperature gradient data is as follows: multiple temperature sensors are set at different positions on the inner wall of the water-jacketed heating furnace, with equal spacing between the temperature sensors, and high-precision thermocouple temperature sensors are used; the measurement accuracy of the high-precision thermocouple temperature sensor is plus or minus 0.1 degree Celsius, and during installation, ensure that the temperature sensing end of each sensor is directly fixed on the inner side of the inner wall of the furnace body to ensure that the measured data is true and accurate; during measurement, the temperature value measured by each sensor is recorded in real time in seconds, and the temperature value recorded by each sensor is spatially marked and timestamped; the collected original temperature data is calculated after the temperature difference of adjacent spatial positions to generate the temperature gradient distribution data of the inner wall of the furnace body; the temperature gradient is calculated as follows: the measured temperature difference of any two adjacent temperature sensors on the inner wall of the furnace body is divided by the spatial distance between the two temperature sensors, thereby obtaining the temperature gradient value between any adjacent positions on the inner wall of the furnace body, and after the above calculation, the complete temperature gradient data of the inner wall of the furnace body is generated.

[0019] Recording the formation and detachment of bubbles on the furnace's inner wall: Cameras are placed on the furnace's inner wall, each with a capture rate of no less than one thousand frames per second. The camera lenses are oriented perpendicular to the furnace's inner wall, and the camera focus is aligned with the area where bubbles frequently form. The image data recorded by the cameras is processed using a bubble edge recognition algorithm and a bubble separation detection algorithm. The bubble edge recognition algorithm uses an edge detection operator to extract the bubble image contour frame by frame. The bubble separation detection algorithm determines whether a bubble has detached from the inner wall based on the positional changes of the bubble contours between adjacent frames. The frequency of bubble detachment from the furnace's inner wall is determined by dividing the number of detached bubbles per unit time by the unit time length. After the above processing, the frequency of bubble detachment from the furnace's inner wall is obtained.

[0020] Collect the displacement data and thermal stress distribution data of the furnace shell at different monitoring positions during the operation of the water jacket heating furnace; A plurality of displacement sensors are arranged at different positions of the furnace shell, and the type of displacement sensor is a non-contact laser displacement sensor; when the non-contact laser displacement sensor is installed at each monitoring position of the furnace shell, a fixed installation bracket is used to ensure that the laser beam is vertically incident on the surface of the furnace shell, and the position change of the furnace shell surface relative to the initial state is monitored in real time; the real-time displacement amount of each monitoring position is recorded at a frequency of not less than ten times per second, and the corresponding time stamps are marked; the furnace shell displacement amount data changing with the running time of each monitoring position is generated.

[0021] Strain gauge type stress sensors are used. A plurality of strain gauge type stress sensors are fixedly installed at different monitoring positions of the furnace shell, and the measurement accuracy of each strain gauge type stress sensor reaches the megapascal level; each strain gauge type stress sensor is pasted at a specific position on the outer surface of the furnace shell to ensure that the thermal stress data measured by each strain gauge type stress sensor truly reflects the thermal stress change caused by the real-time heating of the furnace shell during operation; the recording frequency is not less than ten times per second, the thermal stress value measured in real time by each strain gauge type stress sensor is recorded, and a time stamp is marked, generating a set of thermal stress distribution data of the furnace shell.

[0022] The temperature gradient data, the bubble detachment frequency data, the furnace shell displacement amount data and the thermal stress distribution data are aligned and synchronized in time series to obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell. The time series alignment and synchronization method is as follows: based on the time stamps of the data collected by the above various sensors, and taking the minimum sampling time interval as the reference time unit, interpolation is performed to synchronize all types of data at the same time reference point; specifically, for the sensor data with a large interval, the linear interpolation method is used, and interpolation is performed according to the data of the two adjacent measurement points to calculate the data of the interpolation point, so that all types of data in the complete data are completely synchronized in the time domain; after the above processing, all the temperature gradient data of the inner wall of the furnace body, the bubble detachment frequency data, the furnace shell displacement amount data and the thermal stress distribution data are unified in time scale, thereby obtaining the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell with a time series alignment relationship.

[0023] S2: Based on the boiling state parameters of the furnace body, identify the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, including: Perform multi-scale analysis on the temperature gradient data to determine the critical point position corresponding to the transition from nucleate boiling to film boiling. The multi-scale analysis method of temperature gradient data is as follows: pre-processing the temperature gradient data of the inner wall of the furnace body by removing outliers, that is, by setting upper and lower thresholds to eliminate abnormal temperature gradient data that exceeds the normal range; processing the pre-processed temperature gradient data by multi-scale wavelet analysis method, specifically using continuous wavelet transform analysis method, which can identify hidden change characteristics in temperature gradient data at multiple time scales; in the multi-scale wavelet analysis process, continuous wavelet transform is performed on the temperature gradient data at larger scales, medium scales and smaller scales respectively to obtain the time-frequency characteristics of temperature gradient changes at different scales; identifying the time positions of rapid rise and fall of temperature gradient in the continuous wavelet transform results at multiple scales. The time position of rapid rise and fall indicates the critical point position where the nucleate boiling state transforms into the film boiling state; for example, when the temperature gradient at a local position on the inner wall of the furnace body rises on a large scale and then fluctuates violently on a smaller scale, it is regarded as the critical point position where the nucleate boiling transforms into the film boiling state; the above process is repeatedly applied to the temperature gradient data of all monitoring positions, thereby determining the critical point positions corresponding to the transformation from the nucleate boiling state to the film boiling state on all the inner walls of the furnace body.

[0024] Based on the fluctuation characteristics of the bubble detachment frequency data, the start and end times of film boiling are determined, and the duration of film boiling on the inner wall of the furnace is calculated. The bubble detachment frequency data is subjected to frequency domain analysis. The frequency domain analysis method is the fast Fourier transform spectrum analysis method. The fast Fourier transform spectrum analysis method can accurately identify the periodic characteristics of the bubble detachment frequency data changing with time. The stable segment and the fluctuating segment of the bubble detachment frequency data on the time axis are determined according to the frequency domain analysis results. The stable segment of the bubble detachment frequency corresponds to the nucleate boiling state, and the fluctuating segment of the bubble detachment frequency corresponds to the beginning and end of the film boiling state. For example, when the bubble detachment frequency data rapidly decreases from a high and stable state within a time period and is accompanied by obvious fluctuations, this time period is determined to be the film boiling state. start time; when the bubble detachment frequency data returns to a higher and stable state, this time period is determined as the end time of the film boiling state; the above method is used to identify the start and end times of the corresponding film boiling states in all bubble detachment frequency data one by one; the method for calculating the duration of the film boiling state is: subtract the start time of the corresponding film boiling state from the end time of the film boiling state, so as to obtain the duration of a single film boiling state; the above time length calculation is performed on all identified start and end times of the film boiling state, so as to obtain the complete duration data of the film boiling state on the inner wall of the furnace body.

[0025] S3: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell, including: Based on the displacement data at different monitoring positions of the furnace shell, calculate the thermal expansion displacement change rate of the furnace shell at different monitoring positions; Process the displacement data of the furnace shell according to the monitoring positions respectively. Specifically: Based on the data of the displacement varying with time at each monitoring position, use the finite difference numerical calculation method to calculate the change value of the displacement between consecutive adjacent time points at each monitoring position; Obtain the instantaneous change rate of the thermal expansion displacement of the furnace shell varying with time at the monitoring position by dividing the displacement difference obtained by subtracting the structural displacement at the previous moment from the structural displacement at the next moment by the time interval between two adjacent time points; Process the displacement data of each monitoring position of the furnace shell one by one to obtain the thermal expansion displacement change rates of all monitoring positions of the furnace shell.

[0026] Based on the thermal stress distribution data at different monitoring positions of the furnace shell, calculate the oscillation phase angle when the displacement changes at different monitoring positions of the furnace shell; Utilize the timestamp alignment relationship between the thermal stress data and the displacement data to perform per-position data synchronization processing on the thermal stress data and the displacement data at different monitoring positions of the furnace shell. Specifically: Use the same timestamps between the thermal stress data and the displacement data of the furnace shell to synchronize the thermal stress data at each monitoring position and the displacement data at the corresponding monitoring position to a unified time reference point; Subsequently, through the synchronized data, use the cross-correlation analysis method to determine the phase difference between the structural displacement change and the thermal stress change. The cross-correlation analysis method is: Perform data normalization processing on the thermal stress data and the structural displacement data at each monitoring position of the furnace shell in the time domain respectively; Calculate the cross-correlation function between the normalized thermal stress data and the structural displacement data through numerical methods. The numerical calculation method of the cross-correlation function is to make continuous sliding comparisons of the two normalized data on the time axis respectively, and judge the time offset at which the maximum correlation of the numerical fluctuations between the two data appears; Divide the time offset obtained by the numerical calculation of the cross-correlation function by the oscillation period length common to the two data, and convert it to the oscillation phase difference expressed in degrees, that is, the structural oscillation phase angle.

[0027] S4: Combine the critical point position of the transition from nucleate boiling to film boiling, the duration of film boiling, the thermal expansion displacement rate and the oscillation phase angle of the furnace body to analyze the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor, including: Based on the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, determine the temperature fluctuation period and phase change law of the inner wall of the furnace body during the boiling phase change cycle; Based on the critical point position of the transition from nucleate boiling to film boiling on the inner wall of the furnace and the duration of film boiling, using the temperature gradient data of the inner wall of the furnace, the periodic variation law of the temperature data is analyzed by the periodic analysis method. The periodic analysis method selects the autocorrelation function analysis method, and the autocorrelation function analysis method can accurately judge the periodic length of the temperature gradient data. Specifically, the temperature gradient data at each monitoring position on the inner wall of the furnace is standardized. The standardization is to divide the value of each data point minus the average value by the standard deviation. Subsequently, the autocorrelation function values of the standardized temperature gradient data at different time offsets are calculated. The time length corresponding to the position where the autocorrelation function value first reaches the maximum value is determined as the temperature fluctuation period. For example, after the temperature gradient data at a certain monitoring position on the inner wall of the furnace is standardized, it is found through autocorrelation function analysis that the autocorrelation function value reaches the maximum value after a certain determined time offset, which means that the determined time offset length is the temperature fluctuation period length. The calculation method of the phase change law is: taking the critical point position as the reference point, calculating the time intervals between the critical point position and the time points of the wave peaks and troughs, then dividing the time intervals by the temperature fluctuation period length, and multiplying by the circumferential angle of the complete cycle, finally obtaining the phase change angle at the corresponding position. It is applied one by one to the temperature gradient data at each monitoring position on the inner wall of the furnace to completely determine the temperature fluctuation period and the phase change law of all monitoring positions on the inner wall of the furnace.

[0028] Based on the thermal expansion displacement change rate and the oscillation phase angle at different monitoring positions of the furnace shell, determine the displacement oscillation period and the phase change law of the furnace shell structure during the thermal expansion deformation process; Use the spectrum analysis method to analyze the thermal expansion displacement change rate at each monitoring position of the furnace shell to determine the period length of the displacement oscillation. The spectrum analysis method uses the fast Fourier transform. By analyzing the frequency characteristics of the thermal expansion displacement change rate data through the fast Fourier transform, find the period time length corresponding to the frequency with the maximum amplitude. The period time length corresponding to the frequency with the maximum amplitude is the displacement oscillation period of the monitoring position of the furnace shell. For example, after the thermal expansion displacement change rate at a certain monitoring position of the furnace shell is analyzed by the fast Fourier transform spectrum, it is found that the maximum amplitude frequency appears at a specific frequency position, that is, the displacement oscillation period data of the monitoring position is calculated according to the specific frequency position. Determine the displacement oscillation phase change law of each monitoring position of the furnace shell according to the oscillation phase angle. Specifically: taking the starting phase angle in the oscillation phase angle as the reference, calculate the difference between the subsequent oscillation phase angles and the starting phase angle, and determine the phase change law of the thermal expansion displacement oscillation of the furnace shell structure for each monitoring position one by one.

[0029] Through the temperature fluctuation period and the phase change law, the displacement oscillation period and the phase change law, determine the phase lag relationship between the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure; Cross - compare and analyze the temperature fluctuation period data of the inner wall of the furnace body and the displacement oscillation period of the furnace shell structure respectively. Calculate the time offset corresponding to the maximum correlation between the temperature fluctuation period data and the displacement oscillation period data through the cross - correlation analysis method. The time offset is the phase - lag time length between the temperature fluctuation period of the furnace body and the displacement oscillation period of the structure. For example, when the temperature fluctuation period data at a certain monitoring position on the inner wall of the furnace body and the displacement oscillation period data at a certain monitoring position on the furnace shell show the maximum correlation at a certain time offset after cross - correlation analysis, it is determined that the time offset length represents the phase - lag relationship between the boiling phase - change cycle of the furnace body and the thermal expansion deformation of the furnace shell structure.

[0030] According to the phase - lag relationship, calculate the heat - transfer coefficient fluctuation compensation factor used to correct the heat - transfer coefficient fluctuation; The calculation method of the heat - transfer coefficient fluctuation compensation factor is as follows: based on the ratio of the time offset corresponding to the phase - lag relationship to the temperature fluctuation period length of the inner wall of the furnace body, and then multiplied by the proportional relationship between the corresponding temperature fluctuation amplitude and the displacement oscillation amplitude, and converted into the compensation factor value used to correct the heat - transfer coefficient fluctuation. For example, if the time offset corresponding to the phase - lag relationship at a certain position is determined to be a certain ratio and the ratio of the temperature fluctuation to the displacement oscillation amplitude is known, the heat - transfer coefficient fluctuation compensation factor at this position can be calculated through the above method. Through the above method, the heat - transfer coefficient fluctuation compensation factors at all positions are determined one by one.

[0031] S5: According to the heat - transfer coefficient fluctuation compensation factor, calculate the adjustment amount of the heat - flux distribution to suppress the boiling - thermal expansion co - instability, including: Based on the heat - transfer coefficient fluctuation compensation factor, calculate the local temperature fluctuation amplitude at different monitoring positions on the inner wall of the furnace body during the boiling phase - change cycle; The calculation method of the local temperature fluctuation amplitude is as follows: for the temperature gradient data at each monitoring position on the inner wall of the furnace body after being standardized, calculate the wave peaks and wave valleys respectively, and determine the difference between each pair of wave peaks and wave valleys. The difference between the wave peak and the wave valley represents the single - time amplitude of the temperature fluctuation; use the heat - transfer coefficient fluctuation compensation factor to numerically correct the temperature fluctuation amplitude: multiply the single - time amplitude of the temperature fluctuation by the heat - transfer coefficient fluctuation compensation factor at the corresponding monitoring position to determine the corrected local temperature fluctuation amplitude.

[0032] Based on the heat - transfer coefficient fluctuation compensation factor, calculate the displacement oscillation amplitude at different monitoring positions on the furnace shell during the thermal expansion deformation; The calculation method of the displacement oscillation amplitude is as follows: Using the structural displacement data at different monitoring positions of the furnace shell, by calculating the displacement difference between the displacement peak and the adjacent valley at each monitoring position, the displacement difference is the initial amplitude of the displacement oscillation; Numerically correct the initial displacement oscillation amplitude using the heat transfer coefficient fluctuation compensation factor: Multiply the initial displacement oscillation amplitude by the heat transfer coefficient fluctuation compensation factor corresponding to the monitoring position to obtain the corrected displacement oscillation amplitude.

[0033] According to the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude, identify the boiling-thermal expansion collaborative instability region under the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure; Using the corrected local temperature fluctuation amplitude at each monitoring position on the inner wall of the furnace body, compare it with the corrected displacement oscillation amplitude at each monitoring position of the furnace shell structure, and use the two-dimensional space mapping method to identify the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude. The two-dimensional space mapping method is as follows: Define the temperature fluctuation amplitude and the displacement oscillation amplitude at each monitoring position as the horizontal axis and the vertical axis in the two-dimensional space respectively, and then perform point-to-point mapping of the temperature fluctuation amplitude and the displacement oscillation amplitude at each monitoring position of the furnace body and the furnace shell in the two-dimensional coordinate space; After the mapping process, perform density clustering analysis on all the mapped points in the two-dimensional coordinate space. The density clustering analysis method uses the density-based spatial clustering algorithm. By the spatial clustering algorithm, identify the region where the data points are densely aggregated in the two-dimensional space, which represents the region where both the temperature fluctuation amplitude and the displacement oscillation amplitude are relatively large, that is, the boiling-thermal expansion collaborative instability region.

[0034] For the boiling-thermal expansion collaborative instability region, calculate the adjustment amount of the heat flux distribution; The calculation method of the adjustment amount of the heat flux distribution is as follows: Calculate the product of the temperature fluctuation amplitude and the displacement oscillation amplitude at each monitoring position within the collaborative instability region, and sort the products of all monitoring positions; According to the sorting results, divide the monitoring positions within the collaborative instability region into high-risk level, medium-risk level, and low-risk level; The monitoring positions with the high-risk level require the largest adjustment amount of the heat flux distribution, the monitoring positions with the medium-risk level require the second largest adjustment amount of the heat flux distribution, and the monitoring positions with the low-risk level require the smallest adjustment amount of the heat flux distribution; The adjustment amount of the heat flux distribution is obtained by multiplying the product of the temperature fluctuation amplitude and the displacement oscillation amplitude by a preset adjustment coefficient.

[0035] S6: Collect the flow rate change of the cooling water, and calculate the dynamic compensation correction coefficient based on the flow-heat expansion transfer function, including: Collect the flow rate change of the cooling water during the operation of the water jacket heating furnace; Install ultrasonic flow sensors on the inlet and outlet pipes of the cooling water of the water jacket heating furnace respectively; when installing the ultrasonic flow sensors, ensure that the sensor probes are perpendicular to the pipe axis respectively to ensure the accuracy of measurement. The acquisition process is as follows: under the normal operation state of the water jacket heating furnace, continuous acquisition is carried out at a fixed time interval, and the fixed time interval is set to once per second, and the flow velocity data of the cooling water flowing through the inlet and outlet pipes of the water jacket heating furnace is recorded in real time. Record the instantaneous flow velocity of the cooling water in real time, and mark the time stamp for the data obtained by each acquisition to ensure the real-time and consistency of the data. The calculation method of the change amount of the cooling water flow velocity is: subtract the flow velocity data collected at the previous time point from the flow velocity data collected at the later time point to obtain the change amount of the cooling water flow velocity between adjacent acquisition times, and record the change amount of the cooling water flow velocity successively. Through the above acquisition and calculation methods, the complete change amount of the flow velocity of the cooling water during the operation of the water jacket heating furnace is obtained.

[0036] Substitute the change amount of the cooling water flow velocity into the pre-established flow-thermal expansion transfer function to calculate the dynamic compensation correction coefficient for correcting the change amount of the cooling water flow velocity. The flow-thermal expansion transfer function is a numerical relationship function describing the influence of the change of the cooling water flow velocity on the thermal expansion response of the furnace shell. Specifically: establish the flow-thermal expansion transfer function based on the furnace shell displacement data and the corresponding change amount of the cooling water flow velocity. The establishment method of the flow-thermal expansion transfer function adopts the system identification method, specifically the recursive least squares identification method. The recursive least squares identification method can effectively identify the dynamic relationship of the system. Specifically, take the change amount of the cooling water flow velocity as the input data and the furnace shell displacement data as the output data, and perform parameter identification on the input and output data through the recursive least squares identification method to determine the functional relationship between the input data and the output data. Specifically, construct the input data and the output data into the form of an input-output matrix, and gradually perform identification operations on the input-output matrix to obtain the model parameters in the transfer function.

[0037] The dynamic compensation correction coefficient is defined as the correction value used to correct the dynamic influence of the change of the cooling water flow velocity on the thermal expansion of the furnace shell. The calculation method of the dynamic compensation correction coefficient is: substitute the change amount of the cooling water flow velocity at each sampling moment into the flow-thermal expansion transfer function one by one, and through function operations, obtain the predicted value of the thermal expansion response corresponding to each sampling moment; then compare the predicted value of the thermal expansion response with the furnace shell displacement data, calculate the difference between the furnace shell displacement data and the predicted value of the thermal expansion response, and then use the difference to calculate the dynamic compensation correction coefficient. The calculation process of the dynamic compensation correction coefficient is: subtract the predicted value of the thermal expansion response from the furnace shell displacement data, and then divide it by the absolute value of the predicted value of the thermal expansion response to obtain the dynamic compensation correction coefficient. Calculate the dynamic compensation correction coefficient at all sampling moments one by one to obtain the complete dynamic compensation correction coefficient.

[0038] S7: Adjust the power output and cooling water flow rate of the water jacket heating furnace according to the heat flux distribution adjustment amount and the dynamic compensation correction coefficient, including: Determine the target adjustment value of the heating power of the water jacket heating furnace based on the heat flux distribution adjustment amount; The method for determining the target adjustment value of the heating power of the water jacket heating furnace is as follows: Perform spatial mapping on the heat flux distribution adjustment amounts at each monitoring position within the co-instability region. The spatial mapping method is: Corresponding the heat flux distribution adjustment amounts at each monitoring position within the co-instability region to specific heating units; The heat flux distribution adjustment amount corresponding to each heating unit is the result of the spatial superposition of the heat flux distribution adjustment amounts corresponding to the monitoring positions. Determine the target adjustment value of the heating power based on the heat flux distribution adjustment amount corresponding to each heating unit. Specifically: Based on the relative magnitudes of the heat flux distribution adjustment amounts of each heating unit, formulate the target power output adjustment amplitude for each heating unit: Divide the heat flux distribution adjustment amount of each heating unit by the sum of the heat flux distribution adjustment amounts of all heating units to obtain the relative proportionality coefficient for each heating unit; Then multiply the relative proportionality coefficient by the maximum adjustable power of the heating units designed for the water jacket heating furnace to obtain the target adjustment value. Implement the above method for all heating units one by one to completely determine the target adjustment value of the heating power of the water jacket heating furnace.

[0039] Adjust the power output of the heating units of the water jacket heating furnace according to the target adjustment value; The heating units of the water jacket heating furnace are electric heating tubes, and the power output adjustment method is the pulse width modulation control method. The pulse width modulation control method is: Using the controller in the heating control system of the water jacket heating furnace, convert the target adjustment value into a pulse duty cycle value. The pulse duty cycle value is: The proportional relationship between the target adjustment value and the designed maximum power output of the heating units of the water jacket heating furnace. The calculation method is: Divide the target adjustment value by the designed maximum power output of the heating unit (the maximum power output is less than or equal to the maximum adjustable power) to obtain the pulse duty cycle value. The controller sends corresponding control signals to each heating unit according to the pulse duty cycle value to achieve the adjustment of the power output of each heating unit. For example, if the target adjustment value of a certain heating unit is large, the proportion of the high-level duration in the control signal sent by the controller is relatively high, so that the power value output by the heating unit is large; otherwise, the output power value is small. Apply to all heating units to completely achieve precise adjustment of the power output of the water jacket heating furnace.

[0040] Determine the target adjustment value of the cooling water flow rate based on the dynamic compensation correction coefficient; The method for determining the target adjustment value of the cooling water flow rate is as follows: The initial adjustment value of the cooling water flow rate is corrected using the dynamic compensation correction factor. The initial adjustment value of the flow rate is: taking the designed standard cooling water flow rate required under the normal operating state of the water jacket heating furnace as the reference flow rate. Specifically: multiplying the reference flow rate by the dynamic compensation correction factor and then adding the reference flow rate to obtain the target adjustment value of the cooling water flow rate. For example, if the dynamic compensation correction factor is positive at a certain moment, it means that the cooling water flow rate needs to be increased to offset the influence of the increased thermal expansion response. Calculate the target adjustment value of the cooling water flow rate corresponding to each sampling moment one by one to form a complete target adjustment value of the cooling water flow rate.

[0041] Adjust the opening amplitude of the cooling water flow rate regulating valve in real time according to the target adjustment value; The cooling water flow rate regulating valve is an electric proportional regulating valve, and its opening amplitude adjustment method is: converting the target adjustment value of the cooling water flow rate into an opening signal of the flow rate regulating valve; specifically, matching the target adjustment value of the cooling water flow rate with the valve flow - opening characteristic curve to obtain the target value of the valve opening amplitude. The flow - opening characteristic curve is: the numerical relationship between the corresponding cooling water flow rate and the valve opening obtained by pre - calibrating through experiments. Specifically: measuring the corresponding actual flow rate values under different valve opening conditions one by one to calibrate and form the flow - opening characteristic curve. For example, when the target adjustment value of the cooling water flow rate is large, determine the target value of a larger valve opening according to the characteristic curve; conversely, determine the target value of a smaller valve opening. The target value of the valve opening is converted into a driving signal of the electric proportional regulating valve by the control system, and the driving signal acts on the electric proportional regulating valve in real time to accurately realize the adjustment of the opening amplitude of the flow rate regulating valve and achieve precise and real - time flow rate adjustment of the cooling water system.

[0042] Embodiment 2

[0043] The difference between Embodiment 2 and Embodiment 1 of the present invention is that this embodiment introduces an energy efficiency optimization system for a heating furnace.

[0044] Figure 2 The structural schematic diagram of an energy efficiency optimization system for a heating furnace according to the present invention is given. An energy efficiency optimization system for a heating furnace includes: Data acquisition module: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace; Boiling identification module: Based on the boiling state parameters of the furnace body, identify the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling; Deformation analysis module: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell; Phase analysis module: Combining the critical point position of the transition from nucleate boiling to film boiling, the duration of film boiling, the thermal expansion displacement rate of the furnace body, and the oscillation phase angle, analyze the phase lag relationship between the boiling phase change cycle and thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor; Heat flux adjustment module: Calculate the heat flux distribution adjustment amount for suppressing the boiling-thermal expansion co-instability according to the heat transfer coefficient fluctuation compensation factor; Flow rate compensation module: Collect the change in the flow rate of cooling water, and calculate the dynamic compensation correction coefficient based on the flow rate-thermal expansion transfer function; Regulation execution module: Regulate the power output and the cooling water flow rate of the water jacket heating furnace according to the heat flux distribution adjustment amount and the dynamic compensation correction coefficient.

[0045] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to obtain a formula closest to the actual situation. The preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.

[0046] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access, or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0047] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0048] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and modules described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0049] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there can be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or modules can be in electrical, mechanical, or other forms.

[0050] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules. They can be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0051] In addition, the functional modules in each embodiment of this application can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0052] If the above-mentioned functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0053] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0054] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for optimizing the energy efficiency of a heating furnace, characterized in that, It includes the following steps: S1: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace; S2: Based on the boiling state parameters of the furnace body, identify the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling; S3: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell; S4: Combine the critical point position of the transition from nucleate boiling to film boiling, the duration of film boiling, the thermal expansion displacement rate and oscillation phase angle of the furnace body, analyze the phase lag relationship between the boiling phase change cycle and thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor; S5: According to the heat transfer coefficient fluctuation compensation factor, calculate the adjustment amount of the heat flux distribution to suppress the boiling-thermal expansion co-instability; S6: Collect the change amount of the flow rate of cooling water, and calculate the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function; S7: According to the heat flux distribution adjustment amount and the dynamic compensation correction coefficient, regulate the power output and the cooling water flow rate of the water jacket heating furnace.

2. The energy efficiency optimization method of a heating furnace according to claim 1, wherein S1 specifically is: Collect the temperature gradient data on the inner wall of the furnace body and the bubble detachment frequency data on the inner wall of the furnace during the operation of the water jacket heating furnace; Collect the displacement data and thermal stress distribution data of the furnace shell at different monitoring positions during the operation of the water jacket heating furnace; Perform time series alignment and synchronization on the temperature gradient data, bubble detachment frequency data, furnace shell displacement data and thermal stress distribution data to obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell.

3. The energy efficiency optimization method of a heating furnace according to claim 2, wherein, S2 specifically is: Perform multi-scale analysis on the temperature gradient data to determine the critical point position corresponding to the transition from nucleate boiling to film boiling; Based on the fluctuation characteristics of the bubble detachment frequency data, determine the start time and end time of film boiling, and calculate the duration of film boiling on the inner wall of the furnace body.

4. The energy efficiency optimization method of a heating furnace according to claim 3, wherein S3 specifically is: Based on the displacement data of different monitoring positions of the furnace shell, calculate the thermal expansion displacement change rate of different monitoring positions of the furnace shell; Based on the thermal stress distribution data of different monitoring positions of the furnace shell, calculate the oscillation phase angle when the displacement changes at different monitoring positions of the furnace shell.

5. The method for optimizing the energy efficiency of a heating furnace according to claim 4, characterized in that, S4 specifically is: Based on the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, determine the temperature fluctuation period and phase change law of the inner wall of the furnace body during the boiling phase change cycle; Based on the thermal expansion displacement change rate and oscillation phase angle of different monitoring positions of the furnace shell, determine the displacement oscillation period and phase change law of the furnace shell structure during the thermal expansion deformation process; Through the temperature fluctuation period and phase change law, and the displacement oscillation period and phase change law, determine the phase lag relationship between the furnace body boiling phase change cycle and the furnace shell structure thermal expansion deformation; According to the phase lag relationship, calculate the heat transfer coefficient fluctuation compensation factor for correcting the heat transfer coefficient fluctuation.

6. The energy efficiency optimization method of a heating furnace according to claim 5, characterized in that, S5 specifically is: Based on the heat transfer coefficient fluctuation compensation factor, calculate the local temperature fluctuation amplitude at different monitoring positions of the inner wall of the furnace body during the boiling phase change cycle; Based on the heat transfer coefficient fluctuation compensation factor, calculate the displacement oscillation amplitude at different monitoring positions of the furnace shell during the thermal expansion deformation process; Identify the boiling-thermal expansion collaborative instability region under the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure according to the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude; For the boiling-thermal expansion collaborative instability region, calculate the adjustment amount of the heat flux distribution.

7. A method for optimizing the energy efficiency of a heating furnace according to claim 6, characterized in that, S6, specifically: Collect the change in the flow rate of the cooling water during the operation of the water jacket heating furnace; Substitute the change in the flow rate of the cooling water into the pre-established flow rate-thermal expansion transfer function to calculate the dynamic compensation correction coefficient for correcting the change in the flow rate of the cooling water.

8. The energy efficiency optimization method of a heating furnace according to claim 7, characterized in that S7, specifically: Based on the adjustment amount of the heat flux distribution, determine the target adjustment value of the heating power of the water jacket heating furnace; Adjust the power output of the heating unit of the water jacket heating furnace according to the target adjustment value; Based on the dynamic compensation correction coefficient, determine the target adjustment value of the cooling water flow rate; According to the target adjustment value, adjust the opening amplitude of the cooling water flow rate regulating valve in real time.

9. An energy efficiency optimization system for a heating furnace, which is used to implement the energy efficiency optimization method for a heating furnace described in any one of claims 1-8, characterized in that, Including: Data acquisition module: Obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during the operation of the water jacket heating furnace; Boiling identification module: Based on the boiling state parameters of the furnace body, identify the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling; Deformation analysis module: Based on the structural deformation parameters of the furnace shell, calculate the thermal expansion displacement rate and oscillation phase angle of the furnace shell; Phase analysis module: Combine the critical point position of the transition from nucleate boiling to film boiling, the duration of film boiling, the thermal expansion displacement rate and oscillation phase angle of the furnace body to analyze the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor; Heat flux adjustment module: Calculate the adjustment amount of the heat flux distribution to suppress the boiling-thermal expansion collaborative instability according to the heat transfer coefficient fluctuation compensation factor; Flow rate compensation module: Collect the change in the flow rate of the cooling water and calculate the dynamic compensation correction coefficient based on the flow rate-thermal expansion transfer function; Regulation execution module: Regulate the power output and the cooling water flow rate of the water jacket heating furnace according to the adjustment amount of the heat flux distribution and the dynamic compensation correction coefficient.

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