A heating furnace energy efficiency optimization method and system

Abstract

The present invention discloses a method and system for optimizing the energy efficiency of a heating furnace, which specifically relates to the field of operation control technology. The method obtains boiling state parameters and structural deformation parameters of a water-jacketed heating furnace during operation, identifies the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, and calculates the thermal expansion displacement rate and oscillation phase angle of the furnace shell. The method generates a heat transfer coefficient fluctuation compensation factor by analyzing the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation. The method calculates the heat flux distribution adjustment amount based on the heat transfer coefficient fluctuation compensation factor. The method calculates the dynamic compensation correction coefficient by combining the flow rate change of cooling water and the flow-thermal expansion transfer function. The method controls the power output and cooling water flow of the water-jacketed heating furnace based on the heat flux distribution adjustment amount and the dynamic compensation correction coefficient, thereby realizing dynamic optimization and regulation of the heat transfer behavior of the heating furnace and effectively improving the energy efficiency stability and heat transfer control accuracy of the water-jacketed heating furnace under complex working conditions.

Description

Technical Field

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

[0002] Existing water-jacketed furnace operation control systems generally assume that the heat transfer process occurs under structurally stable conditions, ignoring the dynamic coupling between the boiling state within the furnace and the structural thermal response under variable load conditions. In particular, during the phase transition cycle, where nucleate boiling and film boiling frequently alternate, the heat flux density on the furnace wall and the thermal expansion and contraction of the structure form a bidirectional feedback mechanism, resulting in phase lag and periodic fluctuations in the heat transfer coefficient. 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-mentioned background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for optimizing the energy efficiency of a heating furnace comprises the following steps:

[0006] S1: Obtain boiling state parameters of the furnace body and structural deformation parameters of the furnace shell during operation of the water jacket heating furnace;

[0007] S2: Based on the boiling state parameters of the furnace, identify the critical point of the transition from nucleate boiling to film boiling and the duration of film boiling;

[0008] S3: Based on the structural deformation parameters of the furnace shell, the thermal expansion displacement rate and oscillation phase angle of the furnace shell are calculated;

[0009] S4: Combining 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, the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation is analyzed to generate the heat transfer coefficient fluctuation compensation factor;

[0010] S5: Calculate the heat flux distribution adjustment to suppress the boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor;

[0011] S6: Collect the flow rate change of cooling water and calculate the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function;

[0012] 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.

[0013] In a preferred embodiment, S1 is specifically:

[0014] 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;

[0015] 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;

[0016] The temperature gradient data, bubble detachment frequency data, furnace shell displacement data and thermal stress distribution data are time-series aligned and synchronized to obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell.

[0017] In a preferred embodiment, S2 is specifically:

[0018] Perform multi-scale analysis on temperature gradient data to determine the critical point where nucleate boiling transitions to film boiling.

[0019] The start and end times of film boiling are determined based on the fluctuation characteristics of the bubble detachment frequency data, and the duration of film boiling on the inner wall of the furnace is calculated.

[0020] In a preferred embodiment, S3 is specifically:

[0021] Based on the displacement data of different monitoring positions of the furnace shell, the thermal expansion displacement change rate of the furnace shell at different monitoring positions is calculated;

[0022] Based on the thermal stress distribution data at different monitoring positions of the furnace shell, the oscillation phase angle when the furnace shell undergoes displacement changes at different monitoring positions is calculated.

[0023] In a preferred embodiment, S4 is specifically:

[0024] Based on the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, the temperature fluctuation period and phase change law of the inner wall of the furnace during the boiling phase change cycle are determined;

[0025] Based on the thermal expansion displacement change rate and oscillation phase angle of the furnace shell at different monitoring positions, the displacement oscillation period and phase change law of the furnace shell structure during thermal expansion deformation are determined;

[0026] The phase lag relationship between the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure is determined by the temperature fluctuation cycle and phase change law, as well as the displacement oscillation cycle and phase change law.

[0027] According to the phase lag relationship, the heat transfer coefficient fluctuation compensation factor for correcting the heat transfer coefficient fluctuation is calculated.

[0028] In a preferred embodiment, S5 is specifically:

[0029] Based on the heat transfer coefficient fluctuation compensation factor, the local temperature fluctuation amplitude at different monitoring positions on the furnace inner wall during the boiling phase change cycle is calculated.

[0030] Based on the heat transfer coefficient fluctuation compensation factor, the displacement oscillation amplitude of the furnace shell at different monitoring positions during thermal expansion and deformation is calculated;

[0031] Based on the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude, the boiling-thermal expansion synergistic instability region caused by the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure is identified;

[0032] For the boiling-thermal expansion synergistic instability region, the heat flux distribution adjustment is calculated.

[0033] In a preferred embodiment, S6 is specifically:

[0034] Collect the change in cooling water flow rate during the operation of the water jacket heating furnace;

[0035] The flow rate change of the cooling water is substituted into the pre-established flow-thermal expansion transfer function to calculate the dynamic compensation correction coefficient for correcting the flow rate change of the cooling water.

[0036] In a preferred embodiment, S7 is specifically:

[0037] Based on the heat flux distribution adjustment amount, determine the target adjustment value of the water jacket heating furnace heating power;

[0038] Adjusting the power output of the heating unit of the water jacket heating furnace according to the target adjustment value;

[0039] Determine the target adjustment value of the cooling water flow based on the dynamic compensation correction coefficient;

[0040] The opening range of the cooling water flow regulating valve is adjusted in real time according to the target adjustment value.

[0041] In another aspect, the present invention provides a heating furnace energy efficiency optimization system, comprising:

[0042] Data acquisition module: obtains 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;

[0043] Boiling identification module: Based on the boiling state parameters of the furnace body, it identifies the critical point of the transition from nucleate boiling to film boiling and the duration of film boiling;

[0044] Deformation analysis module: Calculates the thermal expansion displacement rate and oscillation phase angle of the furnace shell based on the structural deformation parameters of the furnace shell;

[0045] Phase analysis module: Combines 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 to analyze the phase lag relationship between the boiling phase change cycle and thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor;

[0046] Heat flux adjustment module: Calculates the heat flux distribution adjustment amount to suppress boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor;

[0047] Flow compensation module: collects the change in cooling water flow rate and calculates the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function;

[0048] Control execution module: controls the power output and cooling water flow of the water jacket heating furnace according to the heat flow distribution adjustment amount and dynamic compensation correction coefficient.

[0049] The technical effects and advantages of the heating furnace energy efficiency optimization method and system of the present invention are as follows:

[0050] By obtaining the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell during operation of the water jacket heating furnace, it is possible to fully perceive the phase change behavior and thermal stress response characteristics during the heating process, and effectively capture the critical behavior of the transition from nucleate boiling to film boiling and its continuous impact; by identifying the position and duration of the critical point of the transition from nucleate boiling to film boiling and calculating the thermal expansion displacement rate and oscillation phase angle, accurate quantification of the phase change periodicity and structural dynamic response is 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 instability trend of the thermal flow response; based on the heat transfer coefficient fluctuation compensation factor, the heat flux distribution adjustment amount is calculated; the flow rate change of cooling water is collected and the dynamic compensation correction coefficient is calculated; based on 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, significantly improving the efficiency of heat energy transfer and the stability of operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic diagram of a method for optimizing energy efficiency of a heating furnace according to the present invention;

[0052] Figure 2 This is a structural schematic diagram of a heating furnace energy efficiency optimization system of the present invention. DETAILED DESCRIPTION

[0053] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] Example 1

[0055] Figure 1 The present invention provides a method for optimizing the energy efficiency of a heating furnace, which comprises the following steps:

[0056] S1: Obtain boiling state parameters of the furnace body and structural deformation parameters of the furnace shell during operation of the water jacket heating furnace;

[0057] S2: Based on the boiling state parameters of the furnace, identify the critical point of the transition from nucleate boiling to film boiling and the duration of film boiling;

[0058] S3: Based on the structural deformation parameters of the furnace shell, the thermal expansion displacement rate and oscillation phase angle of the furnace shell are calculated;

[0059] S4: Combining 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, the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation is analyzed to generate the heat transfer coefficient fluctuation compensation factor;

[0060] S5: Calculate the heat flux distribution adjustment to suppress the boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor;

[0061] S6: Collect the flow rate change of cooling water and calculate the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function;

[0062] 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.

[0063] 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:

[0064] 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;

[0065] 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.

[0066] 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.

[0067] 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;

[0068] Multiple displacement sensors are arranged at different positions of the furnace shell, and the displacement sensor type used 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 mounting bracket is used to ensure that the laser beam is incident vertically on the furnace shell surface, and the position change of the furnace shell surface relative to the initial state is monitored in real time. The real-time displacement of each monitoring position is recorded at a frequency of not less than ten times per second, and the corresponding timestamp is marked; the furnace shell displacement data of each monitoring position changing with the operating time is generated.

[0069] Strain gauge stress sensors are used, and multiple strain gauge stress sensors are fixedly installed at different monitoring positions of the furnace shell. The measurement accuracy of each strain gauge stress sensor reaches the MPa level. Each strain gauge 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 stress sensor truly reflects the thermal stress changes caused by real-time heating of the furnace shell during operation. The recording frequency is no less than ten times per second, and the thermal stress value measured in real time by each strain gauge stress sensor is recorded and timestamped to generate a thermal stress distribution data set for the furnace shell.

[0070] The temperature gradient data, bubble detachment frequency data, furnace shell displacement data and thermal stress distribution data are time-series aligned and synchronized to obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell;

[0071] The timing alignment and synchronization method is as follows: using the timestamps of the data collected by the above-mentioned various sensors as the benchmark and the minimum sampling time interval as the benchmark time unit, interpolation is performed to synchronize all types of data at the same time reference point; specifically, linear interpolation is used for sensor data with large intervals, and interpolation is performed based on the data of the two previous and next measurement points to calculate the interpolation point data so that all types of data in the complete data are completely synchronized in the time domain; after the above processing, all furnace body inner wall temperature gradient data, bubble detachment frequency data, furnace shell displacement data and thermal stress distribution data are all unified in time scale, thereby obtaining furnace body boiling state parameters and furnace shell structural deformation parameters with a timing alignment relationship.

[0072] S2: Based on the boiling state parameters of the furnace, identify the critical point where nucleate boiling transitions to film boiling and the duration of film boiling, including:

[0073] Perform multi-scale analysis on temperature gradient data to determine the critical point where nucleate boiling transitions to film boiling.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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:

[0078] Based on the displacement data of different monitoring positions of the furnace shell, the thermal expansion displacement change rate of the furnace shell at different monitoring positions is calculated;

[0079] The displacement data of the furnace shell are processed separately according to the monitoring positions. Specifically, based on the data of the displacement change of each monitoring position over time, the finite difference numerical calculation method is used to calculate the displacement change value of each monitoring position between consecutive adjacent time points; the displacement difference obtained by subtracting the structural displacement of the previous moment from the structural displacement of the latter moment is divided by the time interval between the two adjacent time points to obtain the instantaneous change rate of the thermal expansion displacement of the furnace shell at the monitoring position over time; the displacement data of each monitoring position of the furnace shell are processed one by one to obtain the thermal expansion displacement change rate of all monitoring positions of the furnace shell.

[0080] Based on the thermal stress distribution data at different monitoring positions of the furnace shell, the oscillation phase angle when the furnace shell displacement changes at different monitoring positions is calculated;

[0081] By utilizing the timestamp alignment between the thermal stress data and the displacement data, the thermal stress data and displacement data at different monitoring locations of the furnace shell are synchronized position by position. Specifically, the thermal stress data at each monitoring location are synchronized with the displacement data at the corresponding monitoring location at a unified time reference point using the same timestamp between the thermal stress data and the displacement data. Subsequently, the phase difference between the structural displacement change and the thermal stress change is determined using the synchronized data using a cross-correlation analysis method. The cross-correlation analysis method is as follows: the thermal stress data and the structural displacement data at each monitoring location of the furnace shell are normalized in the time domain; the cross-correlation function of the normalized thermal stress data and the structural displacement data is numerically calculated. The cross-correlation function is numerically calculated by continuously sliding and comparing the two normalized data on the time axis to determine the time offset at which the maximum correlation between the numerical fluctuations of the two data occurs; the time offset calculated by the cross-correlation function is then divided by the common oscillation period length of the two data to obtain the oscillation phase difference expressed in degrees, i.e., the structural oscillation phase angle.

[0082] S4: Combined with 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, the phase lag relationship between the boiling phase change cycle and thermal expansion deformation is analyzed to generate the heat transfer coefficient fluctuation compensation factor, including:

[0083] Based on the critical point position of the transition from nucleate boiling to film boiling and the duration of film boiling, the temperature fluctuation period and phase change law of the inner wall of the furnace during the boiling phase change cycle are determined;

[0084] Based on the critical point location and duration of film boiling transition from nucleate boiling to film boiling on the furnace inner wall, the temperature gradient data on the furnace inner wall are analyzed using a periodic analysis method to analyze the periodic variation of the temperature data. The autocorrelation function analysis method is used as the periodic analysis method, which can accurately determine the period length of the temperature gradient data. Specifically, the temperature gradient data at each monitoring location on the furnace inner wall are normalized. Normalization is performed by subtracting the mean value from each data point and dividing it by the standard deviation. The autocorrelation function values ​​of the normalized temperature gradient data at different time offsets are then calculated. The time length corresponding to the first maximum value of the autocorrelation function is determined as the temperature fluctuation period. For example, after the temperature gradient data at a monitoring location on the furnace inner wall are normalized, the autocorrelation function analysis finds that the temperature gradient data reaches its maximum value after a certain time offset. This indicates that the time offset is the temperature fluctuation period length. The phase variation pattern is calculated by using the critical point location as the reference point and calculating the time interval between the critical point location and the peak and trough time points. The time interval is then divided by the temperature fluctuation period length and multiplied by the circumferential angle of the complete cycle to obtain the phase variation angle at the corresponding location. The temperature gradient data of each monitoring position on the inner wall of the furnace is applied one by one to completely determine the temperature fluctuation period and phase change law of all monitoring positions on the inner wall of the furnace.

[0085] Based on the thermal expansion displacement change rate and oscillation phase angle of the furnace shell at different monitoring positions, the displacement oscillation period and phase change law of the furnace shell structure during thermal expansion deformation are determined;

[0086] The spectrum analysis method is used to analyze the rate of change of thermal expansion displacement at each monitoring position of the furnace shell and determine the period length of the displacement oscillation. The spectrum analysis method uses fast Fourier transform to analyze the frequency characteristics of the thermal expansion displacement change rate data through fast Fourier transform, and find the period time length corresponding to the maximum amplitude frequency. The period time length corresponding to the maximum amplitude frequency is the displacement oscillation period of the furnace shell monitoring position. For example, after fast Fourier transform spectrum analysis of the rate of change of thermal expansion displacement at a monitoring position of the furnace shell, 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 obtained by conversion based on the specific frequency position. The phase change law of the displacement oscillation at each monitoring position of the furnace shell is determined based on the oscillation phase angle. Specifically, the starting phase angle in the oscillation phase angle is used as a reference, and the difference between the subsequent oscillation phase angle and the starting phase angle is calculated. The phase change law of the thermal expansion displacement oscillation of the furnace shell structure is determined at each monitoring position.

[0087] The phase lag relationship between the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure is determined by the temperature fluctuation cycle and phase change law, as well as the displacement oscillation cycle and phase change law.

[0088] Cross-correlation analysis is performed on the furnace wall temperature fluctuation cycle data and the furnace shell structural displacement oscillation cycle. The time offset corresponding to the maximum correlation between the temperature fluctuation cycle data and the displacement oscillation cycle data is calculated using a cross-correlation analysis method. The time offset is the phase lag between the furnace body temperature fluctuation cycle and the structural displacement oscillation cycle. For example, if the cross-correlation analysis of the temperature fluctuation cycle data at a certain monitoring location on the furnace wall and the displacement oscillation cycle data at a certain monitoring location on the furnace shell shows that the maximum correlation occurs at a certain time offset, then the time offset is determined to represent the phase lag relationship between the furnace body boiling phase change cycle and the thermal expansion and deformation of the furnace shell structure.

[0089] According to the phase lag relationship, the heat transfer coefficient fluctuation compensation factor for correcting the heat transfer coefficient fluctuation is calculated;

[0090] The heat transfer coefficient fluctuation compensation factor is calculated by multiplying the ratio of the time offset corresponding to the phase lag relationship to the length of the furnace wall temperature fluctuation period by the proportional relationship between the corresponding temperature fluctuation amplitude and the displacement oscillation amplitude. This factor is then converted into a compensation factor value to correct for heat transfer coefficient fluctuations. For example, if the phase lag relationship at a certain location determines the time offset at 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 that location can be calculated using this method. This method can be used to determine the heat transfer coefficient fluctuation compensation factor for all locations one by one.

[0091] S5: Calculate the heat flux distribution adjustment to suppress the boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor, including:

[0092] Based on the heat transfer coefficient fluctuation compensation factor, the local temperature fluctuation amplitude at different monitoring positions on the furnace inner wall during the boiling phase change cycle is calculated.

[0093] The local temperature fluctuation amplitude is calculated by taking the standardized temperature gradient data from each monitoring location on the furnace wall, calculating the peaks and troughs, and determining the difference between each pair of peaks and troughs. This difference represents the single amplitude of the temperature fluctuation. The temperature fluctuation amplitude is then numerically corrected using the heat transfer coefficient fluctuation compensation factor: the single amplitude of the temperature fluctuation is multiplied by the heat transfer coefficient fluctuation compensation factor at the corresponding monitoring location to determine the corrected local temperature fluctuation amplitude.

[0094] Based on the heat transfer coefficient fluctuation compensation factor, the displacement oscillation amplitude of the furnace shell at different monitoring positions during thermal expansion and deformation is calculated;

[0095] The method for calculating the displacement oscillation amplitude is as follows: using the structural displacement data of different monitoring positions of the furnace shell, by calculating the displacement difference between the displacement peak and the adjacent trough at each monitoring position, the displacement difference is the initial displacement oscillation amplitude; using the heat transfer coefficient fluctuation compensation factor to numerically correct the initial displacement oscillation amplitude: multiplying the initial displacement oscillation amplitude by the heat transfer coefficient fluctuation compensation factor at the corresponding monitoring position to obtain the corrected displacement oscillation amplitude.

[0096] Based on the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude, the boiling-thermal expansion synergistic instability region caused by the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure is identified;

[0097] The corrected local temperature fluctuation amplitudes at each monitoring location on the furnace body's inner wall are compared with the corrected displacement oscillation amplitudes at each monitoring location on the furnace shell structure. A two-dimensional spatial mapping method is then used to identify the corresponding relationship between the local temperature fluctuation amplitudes and the displacement oscillation amplitudes. The two-dimensional spatial mapping method defines the temperature fluctuation amplitudes and displacement oscillation amplitudes at each monitoring location as the horizontal and vertical axes in two-dimensional space, respectively. The temperature fluctuation amplitudes and displacement oscillation amplitudes at each monitoring location on the furnace body and furnace shell are then mapped point-to-point in a two-dimensional coordinate space. After the mapping process, a density clustering analysis is performed on all mapped points in the two-dimensional coordinate space. The density clustering analysis method uses a density-based spatial clustering algorithm to identify areas in the two-dimensional space where data points are densely clustered. This indicates areas with both large temperature fluctuation amplitudes and large displacement oscillation amplitudes, which are areas of boiling-thermal expansion synergistic instability.

[0098] Calculate the heat flux distribution adjustment for the boiling-thermal expansion synergistic instability region;

[0099] The calculation method of the heat flux distribution adjustment amount is as follows: the product of the temperature fluctuation amplitude and the displacement oscillation amplitude at each monitoring position in the coordinated instability area is calculated, and the products of all monitoring positions are sorted; according to the sorting results, the monitoring positions in the coordinated instability area are divided into high-risk level, medium-risk level and low-risk level; the heat flux distribution adjustment amount required for the high-risk level monitoring position is the largest, the heat flux distribution adjustment amount required for the medium-risk level monitoring position is the second largest, and the heat flux distribution adjustment amount required for the low-risk level monitoring position is the smallest; the heat flux distribution adjustment amount is obtained by multiplying the product of the temperature fluctuation amplitude and the displacement oscillation amplitude by a pre-set adjustment coefficient.

[0100] S6: Collect the cooling water flow rate change and calculate the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function, including:

[0101] Collect the change in cooling water flow rate during the operation of the water jacket heating furnace;

[0102] Ultrasonic flow sensors are installed on the inlet and outlet pipes of the cooling water of the water jacket heating furnace. When installing the ultrasonic flow sensors, ensure that the sensor probe is perpendicular to the axis of the pipe to ensure the accuracy of the measurement. The acquisition process is as follows: when the water jacket heating furnace is in normal operation, continuous acquisition is performed at fixed time intervals, and the fixed time interval is set to once per second, and the flow rate data of the cooling water flowing through the inlet and outlet pipes of the water jacket heating furnace is recorded in real time. The instantaneous flow rate of the cooling water is recorded in real time, and the data collected each time is timestamped to ensure the real-time and consistency of the data. The method for calculating the change in cooling water flow rate is: the flow rate data collected at the latter time point is subtracted from the flow rate data collected at the previous time point to obtain the change in cooling water flow rate between adjacent acquisition moments, and the change in cooling water flow rate is recorded one by one. Through the above acquisition and calculation methods, the complete change in cooling water flow rate during the operation of the water jacket heating furnace is obtained.

[0103] Substituting the cooling water flow rate change into a pre-established flow-thermal expansion transfer function, and calculating a dynamic compensation correction coefficient for correcting the cooling water flow rate change;

[0104] The flow-thermal expansion transfer function is a numerical relationship function that describes the effect of cooling water flow rate changes on the thermal expansion response of the furnace shell. Specifically, the flow-thermal expansion transfer function is established based on the furnace shell displacement data and the corresponding cooling water flow rate changes. The method for establishing the flow-thermal expansion transfer function adopts a system identification method, specifically a recursive least squares identification method. The recursive least squares identification method can effectively identify the dynamic relationship of the system. Specifically, the cooling water flow rate change is used as input data and the furnace shell displacement data is used as output data. The input and output data are parameterized by the recursive least squares identification method to determine the functional relationship between the input data and the output data. Specifically, the input data and the output data are constructed into an input-output matrix form, and the input-output matrix is ​​gradually identified to obtain the model parameters in the transfer function.

[0105] The dynamic compensation correction coefficient is defined as a correction value used to correct the dynamic effects of cooling water flow rate changes on furnace shell thermal expansion. The dynamic compensation correction coefficient is calculated by substituting the cooling water flow rate change at each sampling moment into the flow-thermal expansion transfer function. Through functional calculations, the predicted thermal expansion response value corresponding to each sampling moment is obtained. The predicted thermal expansion response value is then compared with the furnace shell displacement data, and the difference between the furnace shell displacement data and the predicted thermal expansion response value is calculated. The dynamic compensation correction coefficient is then calculated using this difference. The dynamic compensation correction coefficient is calculated by subtracting the predicted thermal expansion response value from the furnace shell displacement data, and then dividing it by the absolute value of the predicted thermal expansion response value. The dynamic compensation correction coefficient is calculated for all sampling moments one by one to obtain the complete dynamic compensation correction coefficient.

[0106] S7: Regulate the power output and cooling water flow of the water jacket heating furnace according to the heat flow distribution adjustment amount and dynamic compensation correction coefficient, including:

[0107] Based on the heat flux distribution adjustment amount, determine the target adjustment value of the water jacket heating furnace heating power;

[0108] The method for determining the target adjustment value of the heating power of the water jacket heating furnace is: spatially mapping the heat flux distribution adjustment amount of each monitoring position in the collaborative instability area. The spatial mapping method is: corresponding the heat flux distribution adjustment amount of each monitoring position in the collaborative instability area to a specific heating unit; the heat flux distribution adjustment amount corresponding to each heating unit is the result of spatial superposition of the heat flux distribution adjustment amount corresponding to the monitoring position. The target adjustment value of the heating power is determined based on the heat flux distribution adjustment amount corresponding to each heating unit, specifically: based on the relative size of the heat flux distribution adjustment amount of each heating unit, the target power output adjustment amplitude of each heating unit is formulated: the heat flux distribution adjustment amount of each heating unit is divided by the sum of the heat flux distribution adjustment amounts of all heating units to obtain the relative proportional coefficient of each heating unit; and then the relative proportional coefficient is multiplied by the maximum adjustable power of the heating unit designed for the water jacket heating furnace to obtain the target adjustment value. The above method is implemented one by one on all heating units to completely determine the target adjustment value of the heating power of the water jacket heating furnace.

[0109] Adjusting the power output of the heating unit of the water jacket heating furnace according to the target adjustment value;

[0110] The heating units of a water-jacket heater are electric heating tubes, and the power output is regulated using pulse-width modulation (Pulse-Width Modulation). This Pulse-Width Modulation (PWM) control method uses a controller within the water-jacket heater's heating control system to convert the target regulation value into a pulse duty cycle. The pulse duty cycle is the ratio between the target regulation value and the designed maximum power output of the water-jacket heater's heating units. This value is calculated by dividing the target regulation value by the designed maximum power output of the heating unit (maximum power output is less than or equal to the maximum adjustable power). Based on the pulse duty cycle value, the controller sends a corresponding control signal to each heating unit to adjust the power output of each heating unit. For example, if the target regulation value for a heating unit is high, the control signal sent by the controller will have a higher proportion of high-level duration, resulting in a higher power output for that unit; conversely, the output power will be lower. This control method, applied to all heating units, enables precise power regulation of the water-jacket heater's power output.

[0111] Determine the target adjustment value of the cooling water flow based on the dynamic compensation correction coefficient;

[0112] The target adjustment value for the cooling water flow rate is determined by using the dynamic compensation correction factor to modify the initial adjustment value for the cooling water flow rate. This initial adjustment value is calculated by taking the design standard cooling water flow rate required for normal operation of the water-jacketed heater as the baseline flow rate. Specifically, the baseline flow rate is multiplied by the dynamic compensation correction factor and then added to the baseline flow rate to determine the target adjustment value for the cooling water flow rate. For example, if the dynamic compensation correction factor is positive at a certain moment, it indicates that the cooling water flow rate needs to be increased to offset the effects of the increased thermal expansion response. The target adjustment value for the cooling water flow rate is calculated for each sampling moment to form a complete target adjustment value for the cooling water flow rate.

[0113] Adjust the opening range of the cooling water flow regulating valve in real time according to the target adjustment value;

[0114] The cooling water flow control valve is an electric proportional control valve. Its opening amplitude adjustment method involves converting the target cooling water flow rate into an opening signal for the flow control valve. Specifically, the target cooling water flow rate is matched with the valve's flow-opening characteristic curve to obtain the target valve opening amplitude. The flow-opening characteristic curve is a numerical relationship between the corresponding cooling water flow rate and valve opening, obtained through pre-calibrated experiments. Specifically, the flow-opening characteristic curve is generated by measuring the corresponding actual flow rate under different valve opening conditions. For example, when the target cooling water flow rate is large, the characteristic curve determines a larger target valve opening; conversely, when the target cooling water flow rate is low, a smaller target valve opening is determined. The valve opening target value is converted by the control system into a drive signal for the electric proportional control valve. This drive signal acts on the electric proportional control valve in real time, precisely adjusting the opening amplitude of the flow control valve and achieving accurate and real-time flow regulation in the cooling water system.

[0115] Example 2

[0116] The difference between Example 2 of the present invention and Example 1 is that this example introduces a heating furnace energy efficiency optimization system.

[0117] Figure 2 A schematic structural diagram of a heating furnace energy efficiency optimization system according to the present invention is provided. The heating furnace energy efficiency optimization system comprises:

[0118] Data acquisition module: obtains 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;

[0119] Boiling identification module: Based on the boiling state parameters of the furnace body, it identifies the critical point of the transition from nucleate boiling to film boiling and the duration of film boiling;

[0120] Deformation analysis module: Calculates the thermal expansion displacement rate and oscillation phase angle of the furnace shell based on the structural deformation parameters of the furnace shell;

[0121] Phase analysis module: Combines 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 to analyze the phase lag relationship between the boiling phase change cycle and thermal expansion deformation, and generate a heat transfer coefficient fluctuation compensation factor;

[0122] Heat flux adjustment module: Calculates the heat flux distribution adjustment amount to suppress boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor;

[0123] Flow compensation module: collects the change in cooling water flow rate and calculates the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function;

[0124] Control execution module: controls the power output and cooling water flow of the water jacket heating furnace according to the heat flow distribution adjustment amount and dynamic compensation correction coefficient.

[0125] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0126] The above embodiments can be implemented in whole or in part via 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 comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0127] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0128] Those skilled in the art will 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 aforementioned method embodiments and will not be repeated here.

[0129] In the 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 schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0130] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0131] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0132] If the 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 the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0133] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0134] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for optimizing the energy efficiency of a heating furnace, characterized in that: The steps include: S1: Obtain boiling state parameters of the furnace body and structural deformation parameters of the furnace shell during operation of the water jacket heating furnace; S2: Based on the boiling state parameters of the furnace, identify the critical point 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, the thermal expansion displacement rate and oscillation phase angle of the furnace shell are calculated; S4: Combining 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, the phase lag relationship between the boiling phase change cycle and the thermal expansion deformation is analyzed to generate the heat transfer coefficient fluctuation compensation factor; S5: Calculate the heat flux distribution adjustment to suppress the boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor; Based on the heat transfer coefficient fluctuation compensation factor, the local temperature fluctuation amplitude at different monitoring positions on the furnace inner wall during the boiling phase change cycle is calculated. Based on the heat transfer coefficient fluctuation compensation factor, the displacement oscillation amplitude of the furnace shell at different monitoring positions during thermal expansion and deformation is calculated; Based on the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude, the boiling-thermal expansion synergistic instability region caused by the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure is identified; Calculate the heat flux distribution adjustment for the boiling-thermal expansion synergistic instability region; 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.

2. A heating furnace energy efficiency optimization method according to claim 1, characterized in that: S1, specifically: 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; 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; The temperature gradient data, bubble detachment frequency data, furnace shell displacement data and thermal stress distribution data are time-series aligned and synchronized to obtain the boiling state parameters of the furnace body and the structural deformation parameters of the furnace shell.

3. A heating furnace energy efficiency optimization method according to claim 2, characterized in that: S2, specifically: Perform multi-scale analysis on temperature gradient data to determine the critical point where nucleate boiling transitions to film boiling. The start and end times of film boiling are determined based on the fluctuation characteristics of the bubble detachment frequency data, and the duration of film boiling on the inner wall of the furnace is calculated.

4. A method for optimizing heating furnace energy efficiency according to claim 3, characterized in that: S3, specifically: Based on the displacement data of different monitoring positions of the furnace shell, the thermal expansion displacement change rate of the furnace shell at different monitoring positions is calculated; Based on the thermal stress distribution data at different monitoring positions of the furnace shell, the oscillation phase angle when the furnace shell undergoes displacement changes at different monitoring positions is calculated.

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

6. A method for optimizing heating furnace energy efficiency according to claim 5, characterized in that: S6, specifically: Collect the change in cooling water flow rate during the operation of the water jacket heating furnace; The flow rate change of the cooling water is substituted into the pre-established flow-thermal expansion transfer function to calculate the dynamic compensation correction coefficient for correcting the flow rate change of the cooling water.

7. A method for optimizing heating furnace energy efficiency according to claim 6, characterized in that: S7, specifically: Based on the heat flux distribution adjustment amount, determine the target adjustment value of the water jacket heating furnace heating power; Adjusting the power output of the heating unit of the water jacket heating furnace according to the target adjustment value; Determine the target adjustment value of the cooling water flow based on the dynamic compensation correction coefficient; The opening range of the cooling water flow regulating valve is adjusted in real time according to the target adjustment value.

8. A heating furnace energy efficiency optimization system, used to implement a heating furnace energy efficiency optimization method according to any one of claims 1 to 7, characterized in that: include: Data acquisition module: obtains 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, it identifies the critical point of the transition from nucleate boiling to film boiling and the duration of film boiling; Deformation analysis module: Calculates the thermal expansion displacement rate and oscillation phase angle of the furnace shell based on the structural deformation parameters of the furnace shell; Phase analysis module: Combines 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 to 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: Calculates the heat flux distribution adjustment amount to suppress boiling-thermal expansion synergistic instability based on the heat transfer coefficient fluctuation compensation factor; Based on the heat transfer coefficient fluctuation compensation factor, the local temperature fluctuation amplitude at different monitoring positions on the furnace inner wall during the boiling phase change cycle is calculated. Based on the heat transfer coefficient fluctuation compensation factor, the displacement oscillation amplitude of the furnace shell at different monitoring positions during thermal expansion and deformation is calculated; Based on the corresponding relationship between the local temperature fluctuation amplitude and the displacement oscillation amplitude, the boiling-thermal expansion synergistic instability region caused by the combined action of the furnace body boiling phase change cycle and the thermal expansion deformation of the furnace shell structure is identified; Calculate the heat flux distribution adjustment for the boiling-thermal expansion synergistic instability region; Flow compensation module: collects the change in cooling water flow rate and calculates the dynamic compensation correction coefficient based on the flow-thermal expansion transfer function; Control execution module: controls the power output and cooling water flow of the water jacket heating furnace according to the heat flow distribution adjustment amount and dynamic compensation correction coefficient.

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