A method for optimizing energy consumption of heat treatment furnace

Abstract

The invention discloses an energy consumption optimization method for a heat treatment furnace, and specifically relates to the field of energy consumption optimization of a heat treatment furnace, comprising: collecting temperature distribution data in a furnace in real time, generating a temperature data sequence combining a continuous time series and a spatial distribution; establishing a thermal field distribution coordinate system of three-dimensional coordinates, identifying an area of ​​uneven heat distribution, estimating gas density, and integrating it with a gas type into the thermal field distribution coordinate system to form a thermal field-gas distribution comprehensive model; constructing an acoustic wave propagation path and setting an initial frequency and amplitude of the acoustic wave, generating an operation instruction set of an acoustic wave excitation device; the acoustic wave excitation device emits an excitation acoustic wave according to the instruction, enhances the kinetic energy of gas molecules in a high-temperature area, and promotes the flow of thermal energy to a low-temperature area; and by real-time monitoring of thermal field changes, analyzing and identifying uneven areas, and dynamically adjusting an acoustic wave excitation strategy, a closed-loop correction of acoustic wave excitation and heat distribution is achieved to optimize the temperature uniformity in the furnace.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption optimization of heat treatment furnaces, and more specifically, to an energy consumption optimization method for heat treatment furnaces. Background Art

[0002] Stainless steel heat treatment furnace is a basic facility for the heat treatment process of stainless steel or other metals (such as annealing, quenching, aging and other heat treatment processes). One of the core problems during its operation is the uneven heat distribution in the furnace, which leads to local overheating or overcooling. This phenomenon will directly affect the performance consistency and processing quality of the product, and also cause a lot of energy waste. Traditional heat distribution methods mainly rely on thermal radiation, thermal convection or thermal conduction, but these methods have inherent limitations. Thermal radiation can only cover a specific area, and it is difficult to achieve global uniform heating; although thermal convection can promote gas circulation, it is easy to form flow field retention and dead corners; the heat conduction efficiency is low, and it cannot adapt to non-contact heating requirements.

[0003] The heat energy redistribution system based on acoustic wave conduction is a new heat distribution optimization technology. Its core principle is to use the propagation characteristics of sound waves in high-temperature gases, induce changes in the kinetic energy of gas molecules through acoustic wave oscillations, and stimulate the flow of heat energy from high-temperature areas to low-temperature areas, thereby balancing the thermal field distribution in the furnace. The acoustic wave system has the characteristics of wide energy transfer coverage and strong dynamic adaptability, and can accurately control the heat distribution path by adjusting the frequency and amplitude. Based on the above technical features, a method for optimizing energy consumption for heat treatment furnaces is proposed, which does not require additional high-power equipment and relies on existing thermal energy to achieve active regulation. It has higher energy efficiency and lower deployment costs. Compared with traditional technologies, the heat energy redistribution system based on acoustic wave conduction has significant advantages in solving the problem of energy waste caused by uneven heat in heat treatment furnaces, and is particularly suitable for the heat treatment requirements of stainless steel processing.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an energy consumption optimization method for a heat treatment furnace to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] S1: A temperature sensor array is set in the furnace of the heat treatment furnace to collect temperature distribution data in the furnace in real time, and establish a temperature data sequence combining continuous time series and spatial distribution;

[0008] S2: Generate a thermal field distribution coordinate system in the furnace in the form of three-dimensional coordinates from the temperature data sequence to identify the area with uneven heat distribution in the set monitoring area;

[0009] S3: Estimate the gas density in the area with uneven heat distribution in the furnace, integrate the gas density and gas type data into the thermal field distribution coordinate system, and establish a comprehensive thermal field-gas distribution model;

[0010] S4: extract the positional relationship of the control target area in the thermal field-gas distribution integrated model, construct several sound wave propagation paths, set the initial frequency and initial amplitude of the sound wave that excites the gas molecular motion, and form a set of operation instructions for the sound wave excitation device in combination with the directional parameters of the sound wave propagation path;

[0011] S5: The acoustic wave excitation device emits an excitation acoustic wave based on the parameters of the acoustic wave propagation direction, amplitude and frequency in the operation instruction set, and enhances the local kinetic energy of the gas molecules in the high-temperature area through the excitation acoustic wave, thereby generating gas molecule vibrations to drive the heat energy to flow to the low-temperature area;

[0012] S6: Real-time monitoring of thermal field changes in the thermal field-gas distribution integrated model after acoustic excitation, and re-analysis to identify areas of uneven heat distribution;

[0013] S7: Dynamically adjust the acoustic wave excitation strategy to establish a closed-loop correction of acoustic wave excitation and heat distribution.

[0014] In a preferred embodiment, in S1, a temperature sensor array is arranged in the furnace of the heat treatment furnace to collect temperature distribution data in the furnace in real time, and establishing a temperature data sequence combining continuous time series and spatial distribution specifically includes:

[0015] In the furnace of the heat treatment furnace, a high-precision temperature sensor array is arranged in a set thermal field monitoring area based on the gas thermal convection characteristics;

[0016] The temperature sensor array continuously collects gas temperature information data corresponding to the thermal field monitoring area within a preset time interval. The gas temperature information data includes the real-time temperature collected by the sensor, the temperature upload timestamp, and the position information of the sensor in the furnace;

[0017] Filter and denoise the collected temperature data to remove abnormal temperature information data points caused by interference;

[0018] The mathematical interpolation method is used to correct the corrected temperature information data, forming a continuous temperature data sequence combining time series and spatial distribution in the heat treatment furnace.

[0019] In a preferred embodiment, in S2, the temperature data sequence is used to generate a thermal field distribution coordinate system in the furnace in the form of three-dimensional coordinates, and the identification of the heat distribution uneven area in the set monitoring area specifically includes:

[0020] Based on the temperature data sequence and the specific location of the thermal field monitoring area set inside the furnace, a thermal field distribution coordinate system inside the furnace is generated in the form of three-dimensional coordinates to describe the temperature values ​​and spatial distribution states at different locations in the furnace;

[0021] Obtain the real-time temperature values ​​of each monitoring area in the thermal field distribution coordinate system, analyze the temperature gradient changes in each monitoring area, identify areas with uneven heat distribution, and mark their specific coordinate positions and coverage areas.

[0022] In a preferred embodiment, in S3, estimating the gas density in the area of ​​uneven heat distribution in the furnace, integrating the gas density and gas type data into the thermal field distribution coordinate system, and establishing a thermal field-gas distribution comprehensive model specifically includes:

[0023] According to the current operation process stage of the heat treatment furnace, the type of gas in the furnace is obtained. Based on the coordinate position and coverage area of ​​the location of the uneven heat distribution area in each monitoring area, the propagation time of the sound wave at the location is measured through the sound wave generating device, and the gas density of the uneven heat distribution area is estimated in combination with the physical properties of the gas type;

[0024] The gas type and gas density data are integrated into the thermal field distribution coordinate system to form a comprehensive thermal field-gas distribution model that represents the temperature values ​​at different locations in the furnace and the spatial distribution of gas density.

[0025] In a preferred embodiment, in S4, the positional relationship of the control target area is extracted in the thermal field-gas distribution integrated model, a plurality of sound wave propagation paths are constructed, the initial frequency and initial amplitude of the sound wave that excites the motion of gas molecules are set, and the operation instruction set for the sound wave excitation device is formed in combination with the directional parameters of the sound wave propagation path, specifically including:

[0026] Extract the spatial coordinates of the high and low temperature positions of the heat distribution imbalance area from the thermal field-gas distribution comprehensive model, and define the positional relationship of the control target area;

[0027] Based on the refraction law of sound waves under gas density conditions, several sound wave propagation paths are constructed according to the principle of shortest transmission time;

[0028] Based on the boundary conditions and obstacle distribution of the heat treatment furnace structure, the paths that may cause sound wave scattering or energy loss in the sound wave propagation path selection are eliminated, and the direction and coverage parameters of the remaining sound wave propagation paths are retained;

[0029] Based on the physical properties of the gas in the target area and the selection of the sound wave propagation path, the initial frequency and initial amplitude of the sound wave are set to stimulate the kinetic energy transfer between the sound wave and the gas molecules;

[0030] The set initial frequency, initial amplitude and directional parameters of the propagation path of the excitation sound wave are integrated to form a set of operating instructions for the sound wave excitation device.

[0031] In a preferred embodiment, in S5, the acoustic wave excitation device emits an excitation acoustic wave based on the parameters of the acoustic wave propagation direction, amplitude and frequency in the operation instruction set, and enhances the local kinetic energy of the gas molecules in the high-temperature area by the excitation acoustic wave, generates gas molecule vibrations to drive the heat energy to flow to the low-temperature area, specifically including:

[0032] According to the instruction set generated by the calculation of the acoustic wave excitation parameters, the acoustic wave emission device is started to emit the acoustic wave according to the set frequency, amplitude and direction;

[0033] The sound waves stimulate and regulate the vibration of gas molecules in the target area. The gas molecules transfer kinetic energy by colliding with each other, accelerating the flow of heat energy to the low-temperature area.

[0034] The input energy density of the sound wave is calculated based on the frequency and amplitude of the sound wave. The nonlinear dynamic model of kinetic energy transfer is established by combining the kinetic energy density of the gas molecular motion and the viscosity characteristic parameters. The model expression is:

[0035]

[0036] In the formula, is the kinetic energy density of the gas molecules, is the kinetic energy flux, is the input energy density of the sound wave, is the energy attenuation coefficient of sound wave propagation in gas, and t is the time subscript of the temperature data series.

[0037] In a preferred embodiment, in S6, real-time monitoring of thermal field changes in the thermal field-gas distribution integrated model after acoustic wave excitation and re-analyzing and identifying areas of uneven heat distribution specifically include:

[0038] The real-time temperature value of the target area under control in the comprehensive model of thermal field and gas distribution is extracted, the temperature gradient change in the target area under control is analyzed, the area of ​​uneven heat distribution is re-identified, the area where the sound waves meet is selected and the excitation parameters are corrected.

[0039] In a preferred embodiment, the selecting of the acoustic wave intersection area and performing excitation parameter correction specifically includes:

[0040] The newly generated high-temperature area in the area of ​​uneven heat distribution is marked as the intersection energy accumulation area, and the phase, frequency synchronization and emission angle parameters of the acoustic wave excitation device are adjusted to correct the energy accumulation in the acoustic wave intersection area.

[0041] In a preferred embodiment, in S7, dynamically adjusting the acoustic wave excitation strategy and establishing a closed-loop correction of acoustic wave excitation and heat distribution specifically includes:

[0042] Based on the re-identified heat distribution uneven area, several sound wave propagation paths are constructed, and the phase, amplitude, frequency and emission direction of the sound wave emission device are dynamically adjusted according to the set adjustment amplitude limit to establish a dynamic new parameter combination that satisfies the nonlinear dynamic model of kinetic energy transfer;

[0043] The dynamic new parameter combination is continuously input into the acoustic wave excitation device to cyclically optimize and correct the uneven quantity distribution of the thermal field.

[0044] Technical effects and advantages of an energy consumption optimization method for a heat treatment furnace of the present invention:

[0045] The heat energy redistribution system based on acoustic wave conduction is a new heat distribution optimization technology. Its core principle is to use the propagation characteristics of sound waves in high-temperature gas to induce changes in the kinetic energy of gas molecules through acoustic wave oscillations, stimulate the flow of heat energy from high-temperature areas to low-temperature areas, and thus balance the thermal field distribution in the furnace. The acoustic wave system has the characteristics of wide energy transfer coverage and strong dynamic adaptability. It can accurately control the heat distribution path by adjusting the frequency and amplitude, and has significant advantages in solving the energy waste problem caused by uneven heat in heat treatment furnaces. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a schematic diagram of an energy consumption optimization method for a heat treatment furnace according to the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Example 1

[0049] Figure 1 The present invention provides an energy consumption optimization method for a heat treatment furnace, which comprises the following steps:

[0050] S1: A temperature sensor array is set in the furnace of the heat treatment furnace to collect temperature distribution data in the furnace in real time, and establish a temperature data sequence combining continuous time series and spatial distribution;

[0051] S2: Generate a thermal field distribution coordinate system in the furnace in the form of three-dimensional coordinates from the temperature data sequence to identify the area with uneven heat distribution in the set monitoring area;

[0052] S3: Estimate the gas density in the area with uneven heat distribution in the furnace, integrate the gas density and gas type data into the thermal field distribution coordinate system, and establish a comprehensive thermal field-gas distribution model;

[0053] S4: extract the positional relationship of the control target area in the thermal field-gas distribution integrated model, construct several sound wave propagation paths, set the initial frequency and initial amplitude of the sound wave that excites the gas molecular motion, and form a set of operation instructions for the sound wave excitation device in combination with the directional parameters of the sound wave propagation path;

[0054] S5: The acoustic wave excitation device emits an excitation acoustic wave based on the parameters of the acoustic wave propagation direction, amplitude and frequency in the operation instruction set, and enhances the local kinetic energy of the gas molecules in the high-temperature area through the excitation acoustic wave, thereby generating gas molecule vibrations to drive the heat energy to flow to the low-temperature area;

[0055] S6: Real-time monitoring of thermal field changes in the thermal field-gas distribution integrated model after acoustic excitation, and re-analysis to identify areas of uneven heat distribution;

[0056] S7: Dynamically adjust the acoustic wave excitation strategy to establish a closed-loop correction of acoustic wave excitation and heat distribution.

[0057] In S1, a temperature sensor array is arranged in the furnace of the heat treatment furnace to collect temperature distribution data in the furnace in real time, and a temperature data sequence combining continuous time series and spatial distribution is established.

[0058] In the heat treatment furnace, a high-precision temperature sensor array is designed and arranged according to the thermal convection characteristics of the gas and the thermal field area to be monitored. The arrangement of the sensor array should cover multiple key positions in the furnace to ensure that the temperature changes of the entire thermal field can be monitored in real time. During the layout process, the spatial distribution of the sensors is optimized according to the thermal flow characteristics in the furnace, such as installing more sensors in areas with strong thermal convection and reducing the installation density in more stable areas. Each sensor has high-precision, low-latency temperature acquisition capabilities and has the durability to adapt to high temperature environments.

[0059] The temperature sensor array starts to collect temperature data of the corresponding thermal field monitoring area at a preset time interval. Each sensor not only collects real-time temperature, but also records the timestamp of each temperature data upload, and the spatial position information of the sensor in the furnace. Position data can be achieved through pre-calibration or position sensors (such as RFID tags) to ensure that each temperature data point can accurately identify its location.

[0060] A low-pass filter is used to smooth the data to eliminate fluctuations caused by high-frequency noise. Based on statistical analysis methods, such as median filtering or outlier detection algorithms (such as IQR algorithm or Z-score algorithm), abnormal data points that are obviously inconsistent with physical laws are identified and eliminated. These abnormal data may be caused by sensor failure, short-term interference or other atypical situations. After processing, a more accurate and reliable set of temperature data is obtained.

[0061] The temperature data after filtering and denoising are corrected by using appropriate spline interpolation methods. The interpolated data will fill the blank areas between the original data points and generate a complete temperature data series that combines time series and spatial distribution.

[0062] In S2, the temperature data sequence is converted into a thermal field distribution coordinate system in the furnace in the form of three-dimensional coordinates to identify the area with uneven heat distribution in the set monitoring area.

[0063] Based on the real-time collected temperature data sequence and the specific location of the thermal field monitoring area set in the furnace, a three-dimensional coordinate system is generated to describe the temperature values ​​and spatial distribution states at different locations in the furnace. Specifically, the furnace is first divided into multiple monitoring areas through a high-precision temperature sensor array. The temperature data in each monitoring area will be mapped to a three-dimensional coordinate system. These coordinates represent the spatial position and corresponding temperature value of each point in the furnace. Through this three-dimensional coordinate system, the temperature distribution of each area of ​​the furnace and the local heat distribution changes can be presented in detail.

[0064] After obtaining the real-time temperature values ​​of each monitoring area in the thermal field distribution coordinate system, the temperature gradient changes in each monitoring area are calculated to identify the areas with uneven heat distribution. The temperature gradient is calculated based on the temperature difference of adjacent points in the three-dimensional coordinate system. The numerical difference method (such as forward difference or central difference) is used to obtain the temperature gradient of the local area. Assume that in three-dimensional space, for the coordinate point (x, y, z), the temperature change of its adjacent points can be calculated by the following formula:

[0065]

[0066] In the formula, is the spatial separation of adjacent points in the x direction, is the actual temperature of the coordinate point (x, y, z). This formula can be applied to the y and z directions to obtain a complete temperature gradient. The acceptable range of the heat distribution gradient deviation of the heat treatment furnace can be set later, and all areas of uneven heat distribution can be marked by the threshold comparison method.

[0067] In S3, the gas density in the area of ​​uneven heat distribution in the furnace is estimated, the gas density and gas type data are integrated into the thermal field distribution coordinate system, and a comprehensive thermal field-gas distribution model is established.

[0068] According to the current operation process stage of the heat treatment furnace, the type of gas in the furnace is obtained. Different operation stages may involve different gases (such as nitrogen, argon, etc.), and the physical properties of these gases (such as specific heat capacity, density, etc.) have a significant impact on the propagation of sound waves and heat distribution. On this basis, combined with the location and coverage area of ​​the area with uneven heat distribution in each monitoring area, the sound wave generator is started to emit sound waves in the area and measure the propagation time of the sound waves in the area. The density of the gas in the area is estimated through the sound wave propagation time, combined with the physical properties of the gas type (such as the density and temperature correlation of the gas). The sound wave propagation speed is directly related to the gas density and compressibility, which can be derived and estimated by the following formula:

[0069] In the formula, is the speed of sound wave propagation, , , ,T, They are gas density, gas molar mass, gas constant (the default setting is 8.314J / (mol·K)), gas temperature and specific heat ratio.

[0070] The gas type and gas density data are integrated into the thermal field distribution coordinate system to form a comprehensive thermal field-gas distribution model that represents the temperature values ​​at different locations in the furnace and the spatial distribution of gas density.

[0071] In S4, the positional relationship of the control target area is extracted in the thermal field-gas distribution comprehensive model, a number of sound wave propagation paths are constructed, the initial frequency and initial amplitude of the sound wave that excites the movement of gas molecules are set, and the directional parameters of the sound wave propagation path are combined to form a set of operating instructions for the sound wave excitation device.

[0072] Extract the spatial coordinates of the high and low temperature positions of the heat distribution imbalance area from the thermal field-gas distribution comprehensive model, and define the positional relationship of the control target area;

[0073] The propagation of sound waves in gas follows the law of refraction (satisfying Snell's law), and areas with different gas densities will produce a refraction effect on the sound waves. In order to efficiently transfer energy and achieve uniform heat distribution, it is necessary to select and optimize the sound wave propagation path based on the law of sound wave refraction. First, considering factors such as gas density changes and temperature gradients, use the following refraction law formula to calculate the path of sound wave propagation:

[0074]

[0075] In the formula, , are the incident angle and refraction angle of the sound wave in the medium, , It is the propagation speed of sound waves in different gas density areas. With the known gas density data and sound speed measurement results, the angle of sound wave refraction can be calculated, and then the optimal path for sound waves to propagate in the furnace can be determined.

[0076] The shortest path algorithm (such as Dijkstra algorithm or A* algorithm) is used to construct the shortest transmission path of the sound wave, while considering the redundancy of multiple paths to avoid energy loss caused by local interference on a single path.

[0077] According to the actual structure of the heat treatment furnace and possible obstacles inside the furnace (such as furnace walls, heating elements, etc.), the sound wave propagation path needs to be further adjusted. Obstacles will cause sound wave scattering, reflection or energy attenuation, affecting the effective transmission of sound waves in the target area.

[0078] According to the physical properties of the gas (such as the specific heat capacity and density of the gas) and the choice of the sound wave propagation path, the initial frequency and amplitude of the sound wave are set. The setting of the frequency and amplitude will affect the efficiency of the sound wave in transferring kinetic energy to the gas molecules. For example, through the calculated propagation path, the propagation distance of the sound wave and the heat demand of the target area are analyzed to select the appropriate sound wave frequency. Lower frequency sound waves can propagate over a longer path, while higher frequency sound waves are suitable for heat concentration in local areas. The set initial frequency, initial amplitude and directional parameters of the propagation path of the excitation sound wave are integrated to form a set of operating instructions for the sound wave excitation device.

[0079] In S5, the acoustic wave excitation device emits excitation sound waves based on the parameter settings of the sound wave propagation direction, amplitude and frequency in the operation instruction set, and enhances the local kinetic energy of the gas molecules in the high-temperature area by the excitation sound waves, generating gas molecule vibrations to drive heat energy to flow to the low-temperature area.

[0080] According to the instruction set generated by the calculation of the acoustic wave excitation parameters, the acoustic wave emission device is started to emit the acoustic wave according to the set frequency, amplitude and direction;

[0081] The sound waves stimulate and regulate the vibration of gas molecules in the target area. The gas molecules transfer kinetic energy by colliding with each other, accelerating the flow of heat energy to the low-temperature area. The kinetic energy of gas molecules is related to their vibration speed and mass. For gas molecules, their kinetic energy density The calculation method is:

[0082]

[0083] In the formula, and are the mass and vibration speed of the gas molecules respectively.

[0084] Viscosity of gas It affects the propagation of sound waves in the gas because viscosity causes energy dissipation. The energy loss caused by viscosity usually leads to the attenuation of the sound wave, which is expressed as the attenuation coefficient of the sound wave. The specific calculation method is:

[0085]

[0086] The input energy density of the sound wave is calculated based on the frequency and amplitude of the sound wave. The nonlinear dynamic model of kinetic energy transfer is established by combining the kinetic energy density of the gas molecular motion and the viscosity characteristic parameters. The model expression is:

[0087]

[0088] In the above formula, is the kinetic energy density of the gas molecules, is the kinetic energy flux, is the input energy density of the sound wave, is the energy attenuation coefficient of sound wave propagation in gas, and t is the time subscript of the temperature data series.

[0089] In S6, the thermal field changes in the thermal field-gas distribution integrated model after acoustic wave excitation are monitored in real time, and the areas of uneven heat distribution are re-analyzed and identified.

[0090] Extract the real-time temperature value of the target area in the thermal field-gas distribution comprehensive model, analyze the temperature gradient changes in the target area, and re-identify the area of ​​uneven heat distribution.

[0091] After re-identifying the area of ​​uneven heat distribution, the newly generated high-temperature area is marked as the intersection energy concentration area. At this time, the sound wave emission device needs to be adjusted according to the new thermal field distribution. First, by analyzing the specific location and energy requirements of the intersection area, the phase, frequency synchronization and emission angle of the sound wave emission device are adjusted to ensure that the sound wave can disperse the energy of the area. Through this process, the sound wave excitation strategy can maximize the optimization of heat distribution, correct the energy concentration in the intersection area of ​​the sound wave, and improve the uniformity of the overall thermal field.

[0092] In S7, the acoustic wave excitation strategy is dynamically adjusted to establish a closed-loop correction of acoustic wave excitation and heat distribution.

[0093] Based on the re-identified uneven heat distribution areas, several sound wave propagation paths are constructed, and the phase, amplitude, frequency and emission direction of the sound wave emitting device are dynamically adjusted according to the set adjustment amplitude limit (the proportional scale adjustment method can be selected, and iterative adjustment is performed according to the set proportional adjustment limit) to establish a new dynamic parameter combination that satisfies the nonlinear dynamic model of kinetic energy transfer.

[0094] The new parameter combination after dynamic adjustment is input into the acoustic excitation device to ensure that these parameters can be continuously executed during the acoustic excitation process. After each adjustment, the system monitors the uniformity of the thermal field in real time through temperature monitoring and gas feedback data, and optimizes and corrects the areas with uneven heat distribution. This process is a continuous cycle. The system will continuously iterate and adjust the acoustic excitation strategy based on real-time data feedback to ensure the gradual homogenization of the thermal field and maximize the energy transfer efficiency. Through this closed-loop control, the heat distribution in the heat treatment furnace can be continuously optimized to meet the precise requirements of the production process.

[0095] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.

[0096] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may 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 process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0097] Those of ordinary skill 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 to be beyond the scope of this application.

[0098] 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 aforementioned method embodiments and will not be repeated here.

[0099] In the several embodiments provided in the present 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 only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, 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.

[0100] 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, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0101] 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.

[0102] 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 can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0103] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0104] 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 protection scope of the present invention.

Claims

1. A method for optimizing energy consumption of a heat treatment furnace, characterized in that: The steps include: S1: A temperature sensor array is set in the furnace of the heat treatment furnace to collect temperature distribution data in the furnace in real time, and establish a temperature data sequence combining continuous time series and spatial distribution; S2: Generate a thermal field distribution coordinate system in the furnace in the form of three-dimensional coordinates from the temperature data sequence to identify the area with uneven heat distribution in the set monitoring area; S3: Estimate the gas density in the area with uneven heat distribution in the furnace, integrate the gas density and gas type data into the thermal field distribution coordinate system, and establish a comprehensive thermal field-gas distribution model; S4: extract the positional relationship of the control target area in the thermal field-gas distribution integrated model, construct several sound wave propagation paths, set the initial frequency and initial amplitude of the sound wave that excites the gas molecular motion, and form a set of operation instructions for the sound wave excitation device in combination with the directional parameters of the sound wave propagation path; S5: The acoustic wave excitation device emits an excitation acoustic wave based on the parameters of the acoustic wave propagation direction, amplitude and frequency in the operation instruction set, and enhances the local kinetic energy of the gas molecules in the high-temperature area through the excitation acoustic wave, thereby generating gas molecule vibrations to drive the heat energy to flow to the low-temperature area; S6: Real-time monitoring of thermal field changes in the thermal field-gas distribution integrated model after acoustic excitation, and re-analysis to identify areas of uneven heat distribution; S7: Dynamically adjust the acoustic wave excitation strategy to establish a closed-loop correction of acoustic wave excitation and heat distribution.

2. The method for optimizing energy consumption of a heat treatment furnace according to claim 1, characterized in that: In S1, a temperature sensor array is set in the furnace of the heat treatment furnace to collect temperature distribution data in the furnace in real time, and a temperature data sequence combining continuous time series and spatial distribution is established, which specifically includes: In the furnace of the heat treatment furnace, a high-precision temperature sensor array is arranged in a set thermal field monitoring area based on the gas thermal convection characteristics; The temperature sensor array continuously collects gas temperature information data corresponding to the thermal field monitoring area within a preset time interval. The gas temperature information data includes the real-time temperature collected by the sensor, the temperature upload timestamp, and the position information of the sensor in the furnace; Filter and denoise the collected temperature data to remove abnormal temperature information data points caused by interference; The mathematical interpolation method is used to correct the corrected temperature information data, forming a continuous temperature data sequence combining time series and spatial distribution in the heat treatment furnace.

3. The method for optimizing energy consumption of a heat treatment furnace according to claim 2, characterized in that: In S2, the temperature data sequence is converted into a three-dimensional coordinate system to generate a thermal field distribution coordinate system in the furnace, and the identification of the heat distribution imbalance area in the set monitoring area specifically includes: Based on the temperature data sequence and the specific location of the thermal field monitoring area set inside the furnace, a thermal field distribution coordinate system inside the furnace is generated in the form of three-dimensional coordinates to describe the temperature values ​​and spatial distribution states at different locations in the furnace; Obtain the real-time temperature values ​​of each monitoring area in the thermal field distribution coordinate system, analyze the temperature gradient changes in each monitoring area, identify areas with uneven heat distribution, and mark their specific coordinate positions and coverage areas.

4. The method for optimizing energy consumption of a heat treatment furnace according to claim 3, characterized in that: In S3, the gas density in the area with uneven heat distribution in the furnace is estimated, and the gas density and gas type data are integrated into the thermal field distribution coordinate system to establish a comprehensive thermal field-gas distribution model, which specifically includes: According to the current operation process stage of the heat treatment furnace, the type of gas in the furnace is obtained. Based on the coordinate position and coverage area of ​​the location of the uneven heat distribution area in each monitoring area, the propagation time of the sound wave at the location is measured through the sound wave generating device, and the gas density of the uneven heat distribution area is estimated in combination with the physical properties of the gas type; The gas type and gas density data are integrated into the thermal field distribution coordinate system to form a comprehensive thermal field-gas distribution model that represents the temperature values ​​at different locations in the furnace and the spatial distribution of gas density.

5. The method for optimizing energy consumption of a heat treatment furnace according to claim 4, characterized in that: In S4, the positional relationship of the control target area is extracted in the thermal field-gas distribution integrated model, a number of sound wave propagation paths are constructed, the initial frequency and initial amplitude of the sound wave that excites the movement of gas molecules are set, and the operation instruction set for the sound wave excitation device is formed in combination with the directional parameters of the sound wave propagation path. Specifically, it includes: Extract the spatial coordinates of the high and low temperature positions of the heat distribution imbalance area from the thermal field-gas distribution comprehensive model, and define the positional relationship of the control target area; Based on the refraction law of sound waves under gas density conditions, several sound wave propagation paths are constructed according to the principle of shortest transmission time; Based on the boundary conditions and obstacle distribution of the heat treatment furnace structure, the paths that may cause sound wave scattering or energy loss in the sound wave propagation path selection are eliminated, and the direction and coverage parameters of the remaining sound wave propagation paths are retained; Based on the physical properties of the gas in the target area and the selection of the sound wave propagation path, the initial frequency and initial amplitude of the sound wave are set to stimulate the kinetic energy transfer between the sound wave and the gas molecules; The set initial frequency, initial amplitude and directional parameters of the propagation path of the excitation sound wave are integrated to form a set of operating instructions for the sound wave excitation device.

6. The method for optimizing energy consumption of a heat treatment furnace according to claim 5, characterized in that: In S5, the acoustic wave excitation device emits an excitation acoustic wave based on the acoustic wave propagation direction, amplitude and frequency parameter settings in the operation instruction set, and enhances the local kinetic energy of the gas molecules in the high-temperature area by the excitation acoustic wave, generates gas molecule vibrations and drives the heat energy to flow to the low-temperature area. Specifically, the steps include: According to the instruction set generated by the calculation of the acoustic wave excitation parameters, the acoustic wave emission device is started to emit the acoustic wave according to the set frequency, amplitude and direction; The sound waves stimulate and regulate the vibration of gas molecules in the target area. The gas molecules transfer kinetic energy by colliding with each other, accelerating the flow of heat energy to the low-temperature area. The input energy density of the sound wave is calculated based on the frequency and amplitude of the sound wave. The nonlinear dynamic model of kinetic energy transfer is established by combining the kinetic energy density of the gas molecular motion and the viscosity characteristic parameters. The model expression is: In the formula, is the kinetic energy density of the gas molecules, is the kinetic energy flux, is the input energy density of the sound wave, is the energy attenuation coefficient of sound wave propagation in gas, and t is the time subscript of the temperature data series.

7. The method for optimizing energy consumption of a heat treatment furnace according to claim 6, characterized in that: In S6, the thermal field changes in the thermal field-gas distribution integrated model after acoustic excitation are monitored in real time, and the areas of uneven heat distribution are re-analyzed and identified, including: The real-time temperature value of the target area under control in the comprehensive model of thermal field and gas distribution is extracted, the temperature gradient change in the target area under control is analyzed, the area of ​​uneven heat distribution is re-identified, the area where the sound waves meet is selected and the excitation parameters are corrected.

8. The method for optimizing energy consumption of a heat treatment furnace according to claim 7, characterized in that: The selecting of the acoustic wave intersection area and performing excitation parameter correction specifically includes: The newly generated high-temperature area in the area of ​​uneven heat distribution is marked as the intersection energy accumulation area, and the phase, frequency synchronization and emission angle parameters of the acoustic wave excitation device are adjusted to correct the energy accumulation in the acoustic wave intersection area.

9. The method for optimizing energy consumption of a heat treatment furnace according to claim 8, characterized in that: In S7, the acoustic excitation strategy is dynamically adjusted to establish a closed-loop correction of acoustic excitation and heat distribution, specifically including: Based on the re-identified heat distribution uneven area, several sound wave propagation paths are constructed, and the phase, amplitude, frequency and emission direction of the sound wave emission device are dynamically adjusted according to the set adjustment amplitude limit to establish a dynamic new parameter combination that satisfies the nonlinear dynamic model of kinetic energy transfer; The dynamic new parameter combination is continuously input into the acoustic wave excitation device to cyclically optimize and correct the uneven quantity distribution of the thermal field.

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