Heat exchanger high-efficiency heat exchange management method and system under low-temperature working condition

Abstract

This invention provides a method and system for efficient heat exchange management of heat exchangers under low-temperature conditions, relating to the field of energy conservation and environmental protection technology. The method includes: real-time monitoring of the operating status parameters and inlet air parameters of the heat exchanger under low-temperature conditions; determining whether the heat exchanger has entered a frosting-sensitive condition using a frosting state identification model; if so, identifying available waste heat sources; otherwise, continuing monitoring; determining the optimal waste heat recovery scheme based on the available waste heat sources; constructing an air preheating loop using a heat pipe heat exchanger based on the optimal waste heat recovery scheme, and transferring the heat from the available waste heat sources to the air inlet side of the heat exchanger through the air preheating loop; using the heat recovered by the heat pipe heat exchanger to preheat the air entering the heat exchanger; dynamically adjusting the flow rate of the available waste heat sources based on the preheating results; and determining whether the frosting sensitivity index of the heat exchanger is greater than the forced defrosting threshold based on the dynamic adjustment results; if so, initiating the defrosting procedure; otherwise, continuing monitoring.

Description

Technical Field

[0001] This invention relates to the field of energy conservation and environmental protection technology, and in particular to a method and system for efficient heat exchange management of heat exchangers under low-temperature conditions. Background Technology

[0002] In industrial refrigeration systems, air-source heat pump systems, low-temperature environment heat exchange systems, and cold chain equipment, the heat exchanger, as the core component for heat exchange, directly affects the overall heat exchange efficiency and energy utilization level of the system. When the system is operating under low-temperature conditions, the ambient air temperature is low and the relative humidity is high, and water vapor in the air is prone to condense on the surface of the heat exchanger and further form frost.

[0003] To address the issue of frost formation on heat exchangers under low-temperature conditions, preheating the air entering the heat exchanger by rationally utilizing industrial waste heat resources in the system can not only increase the intake air temperature, reduce relative humidity and dew point risk, but also effectively improve the effective operating time and overall heat exchange efficiency of the heat exchanger, thereby increasing waste heat utilization efficiency. This is of great significance for improving the energy-saving operation level and operational reliability of low-temperature heat exchange systems.

[0004] However, existing low-temperature heat exchanger anti-frost or defrosting technologies mostly use timed defrosting, temperature threshold control, or differential pressure threshold control to judge and handle the frost situation. These methods usually rely on a single operating parameter for simple judgment, which is difficult to accurately reflect the actual frost state of the heat exchanger. They are prone to problems such as defrosting too early or defrosting too late, which leads to increased system energy consumption or reduced heat exchange efficiency, resulting in low waste heat utilization efficiency. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a high-efficiency heat exchange management method and system for heat exchangers under low-temperature conditions. This method can solve the problem that existing low-temperature heat exchanger anti-frost or defrosting technologies mostly use timed defrosting, temperature threshold control, or differential pressure threshold control to judge and handle the frost situation. Such methods usually rely on a single operating parameter for simple judgment, which is difficult to accurately reflect the actual frost state of the heat exchanger. They are prone to problems such as premature or delayed defrosting, which leads to increased system energy consumption or reduced heat exchange efficiency, resulting in low waste heat utilization efficiency.

[0006] A first aspect of this invention provides a method for efficient heat exchange management of heat exchangers under low-temperature operating conditions, comprising: S1: Real-time monitoring of the heat exchanger's operating status parameters and inlet air parameters under low-temperature conditions; S2: Based on the operating status parameters and inlet air parameters, determine whether the heat exchanger has entered a frosting sensitive condition using the frosting status identification model; if yes, proceed to step S3; otherwise, return to step S1 and continue monitoring. S3: Based on the industrial waste heat recovery algorithm, identify available waste heat sources suitable for air preheating; S4: Determine the optimal waste heat recovery scheme based on the coverage capacity of the available waste heat source during the critical time window of the entire frosting process and the ability to inhibit refreezing after defrosting; S5: Based on the optimal waste heat recovery scheme, an air preheating loop is constructed using a heat pipe heat exchanger, and the heat from the available waste heat source is transferred to the air inlet side of the heat exchanger through the air preheating loop. S6: Use the heat recovered by the heat pipe heat exchanger to preheat the air entering the heat exchanger; S7: Dynamically adjust the flow rate of available waste heat source according to the changes in the operating status parameters of the preheated heat exchanger; S8: Based on the dynamic adjustment results, determine whether the frost sensitivity index of the heat exchanger is greater than the forced defrosting threshold; if so, start the defrosting program and drain the defrosting water through the drainage channel formed by the louvered fins on the air side of the heat exchanger; otherwise, return to step S1 and continue monitoring.

[0007] A second aspect of the present invention provides a high-efficiency heat exchange management system for heat exchangers under low-temperature operating conditions, comprising: a processor and a memory; The memory stores programs or instructions that can run on a processor, and when the programs or instructions are executed by the processor, they implement the steps of the efficient heat exchanger management method under low-temperature conditions as described in the first aspect.

[0008] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following: In this embodiment of the invention, a frosting state recognition model is used to predict whether the heat exchanger has entered a frosting-sensitive condition, enabling early identification and warning of frosting risks. This avoids control lag caused by single threshold judgments. An industrial waste heat recovery algorithm identifies available waste heat sources suitable for air preheating, and the optimal waste heat recovery scheme is determined by combining the critical time window coverage capability throughout the frosting process and the refreezing inhibition capability after defrosting, thereby improving the targeting and effectiveness of waste heat utilization. By using a heat pipe heat exchanger to construct an air preheating loop and transferring heat from available waste heat sources to the air inlet side of the heat exchanger, the air entering the heat exchanger is preheated. This effectively increases the inlet air temperature, delays frost formation, and extends the effective heat exchange time of the heat exchanger. The system's heating capacity can adaptively adjust according to changes in frosting risk, thereby improving system operational stability while ensuring anti-frost effect and enhancing the overall heat exchange efficiency and operational reliability of the heat exchanger under low-temperature conditions. Attached Figure Description

[0009] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0010] Figure 1 This is a flowchart illustrating the efficient heat exchange management method for heat exchangers under low-temperature conditions provided in this embodiment of the invention.

[0011] Figure 2 This is a schematic diagram of the structure of the high-efficiency heat exchange management system for heat exchangers under low-temperature conditions provided in an embodiment of the present invention. Detailed Implementation

[0012] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0013] The following description, in conjunction with the accompanying drawings, details the efficient heat exchange management method for heat exchangers under low-temperature conditions provided by the embodiments of the present invention through specific examples and application scenarios.

[0014] Reference manual attached Figure 1 The diagram shows a flowchart of the high-efficiency heat exchange management method for heat exchangers under low-temperature conditions provided in an embodiment of the present invention.

[0015] This invention provides a method for efficient heat exchange management of heat exchangers under low-temperature conditions, which may include the following steps: S1: Real-time monitoring of the heat exchanger's operating status parameters and inlet air parameters under low-temperature conditions.

[0016] Low-temperature operating conditions refer to the operating state where the ambient temperature of the heat exchanger is low, and water vapor in the air easily condenses on the surface of the heat exchanger, forming a frost layer. This generally occurs in cold regions or winter environments. The operating status parameters of the heat exchanger refer to monitoring data that reflect the current operating condition of the heat exchanger, including parameters such as inlet air temperature, outlet air temperature, air-side pressure difference, air velocity, and air flow rate. These parameters reflect heat exchange efficiency, airflow resistance, and system operational stability. Inlet air parameters refer to the environmental characteristics of the air before it enters the heat exchanger, including inlet air temperature, inlet air relative humidity, and inlet air dew point temperature. These parameters reflect the water vapor content in the air and the likelihood of frost or condensation.

[0017] In one possible implementation, the operating parameters include the heat exchanger inlet air temperature, outlet air temperature, air-side pressure differential, air velocity, and air flow rate.

[0018] The inlet air parameters include inlet air temperature, inlet air relative humidity, and inlet air dew point temperature.

[0019] It should be noted that by monitoring the operating status parameters of the heat exchanger and the inlet air parameters in real time under low-temperature conditions, key operational information affecting the frost formation process and heat exchange efficiency can be comprehensively obtained, thus providing an accurate data foundation for subsequent frost status identification and heat exchange management decisions. Simultaneously, by comprehensively monitoring multiple parameters such as inlet air temperature, air humidity, dew point temperature, and air-side pressure difference, the actual operating status of the heat exchanger in the low-temperature environment can be more fully reflected, helping to promptly detect abnormal changes that may lead to increased frost formation or decreased heat exchange efficiency. Furthermore, real-time monitoring can improve the system's response speed to environmental changes, enabling heat exchange management strategies to be dynamically adjusted according to changes in air conditions and equipment operating status, thereby improving the operational stability of the heat exchanger under low-temperature conditions, extending the effective heat exchange time, and enhancing overall heat exchange efficiency.

[0020] S2: Based on the operating status parameters and inlet air parameters, determine whether the heat exchanger has entered a frosting-sensitive condition using the frosting status identification model. If yes, proceed to step S3. Otherwise, return to step S1 and continue monitoring.

[0021] The frosting condition identification model is a predictive model built based on heat exchanger operating parameters and inlet air parameters to determine whether a heat exchanger has a frosting trend or risk. This model comprehensively analyzes various operating data to output the current frosting sensitivity level or frosting sensitivity index of the heat exchanger. Frosting-sensitive conditions refer to an operating state where, under the combined influence of current ambient temperature, air humidity, and heat exchanger operating conditions, the heat exchanger surface has the conditions for frost formation and the risk of frost formation is significantly increased. If no control measures are taken under this state, the frost layer may grow rapidly and affect the heat exchanger's heat transfer performance.

[0022] It should be noted that by using a frosting state identification model based on operating status parameters and inlet air parameters to determine whether the heat exchanger has entered a frosting-sensitive condition, the traditional passive judgment method relying on a single temperature or pressure difference threshold can be transformed into an active prediction method based on multi-parameter comprehensive analysis. This allows for a more accurate identification of the heat exchanger's frosting trend. Furthermore, this method can identify potential frosting risks before a significant frost layer forms, providing sufficient response time for subsequent anti-frost measures such as air preheating or waste heat utilization. This effectively delays the frosting process and reduces the impact of frequent defrosting on system operation.

[0023] In one possible implementation, S2 specifically includes: S201: Construct the input feature vector of the frost condition recognition model based on the operating status parameters and inlet air parameters.

[0024] The input feature vector refers to a set of data formed by combining heat exchanger operating status parameters and inlet air parameters in a certain order. It is used as the input variable of the frosting state identification model to reflect the multi-dimensional feature information that affects frosting formation under the current operating conditions.

[0025] S202: Objective function for constructing a frosting state recognition model.

[0026] Specifically, firstly, the input feature vectors and corresponding true output values ​​for each sampling time in the training sample set are obtained. The true output value is the frost sensitivity index or frost state label value of the heat exchanger at the corresponding time. Then, a loss function is selected as the objective function of the model to measure the deviation between the model's prediction result and the true output value. Based on this, the loss function values ​​of all samples are summed or averaged to obtain the overall prediction error expression. This overall error is used as the objective function to be minimized during model training. By continuously reducing the value of this objective function in subsequent iterations of training, the predicted output of the frost state recognition model gradually approaches the true output, thereby improving the model's accuracy in recognizing the frost-sensitive conditions of the heat exchanger.

[0027] The objective function is a mathematical function used to measure the degree of error between the model's predicted results and the actual frost conditions. Its role is to guide the optimization of model parameters during model training, so that the prediction error is gradually reduced.

[0028] S203: Set the initial base learner for the frost condition recognition model.

[0029] The initial base learner refers to the initial prediction function established before the model iterative training begins. It is used to provide a uniform initial prediction value for all input samples and serves as the basis for the subsequent model to gradually correct the prediction results.

[0030] Specifically, when setting the initial base learner for the frost state recognition model, the true output values ​​of all samples in the training sample set are first obtained, i.e., the frost sensitivity index or frost state label value corresponding to each sampling time. Then, a constant *c* is set as a candidate initial prediction value, and the loss function value between the true value and the predicted value of each sample is calculated when the prediction result of all samples takes this constant *c*. Then, the loss function values ​​of all samples are summed to obtain the overall prediction error. Next, the value that minimizes this overall error is found among all possible constants *c*, and this optimal constant is used as the initial prediction output of the model. Finally, this constant function is denoted as the initial base learner, which represents the unified initial prediction result given for any input feature vector before the model iterative training begins.

[0031] S204: Input the input feature vector into the frost condition recognition model, and output the negative gradient residual: in, Indicates the first During the nth iteration, the 1st The negative gradient residual value corresponding to each sample Indicates the first The actual output value of each sample Indicates the first The input feature vector of each sample, Represents the loss function. This represents the predicted output value of the frosting condition recognition model. Indicates the first In the next iteration, the predicted output value of the frosting state recognition model is... N Represents the total number of samples. x This represents the input feature vector.

[0032] Here, the negative gradient residual refers to the negative gradient value of the loss function with respect to the model's predicted output. It is used to represent the direction and magnitude of the current model's prediction error and serves as the target for the next round of learner fitting during gradient reinforcement learning.

[0033] S205: Fit the negative gradient residuals using a regression tree and divide the input feature space into multiple non-overlapping leaf node regions.

[0034] The leaf node region refers to the feature space sub-region obtained by the final division of the regression tree, and each region corresponds to a predicted output value.

[0035] Specifically, the negative gradient residual is used as the target value for training the regression tree, and the input feature vector of the corresponding sample is used as the input variable of the regression tree to construct the training dataset. Then, starting from all samples as the root node, the input features are traversed, and the feature that minimizes the residual error within a region and its splitting threshold are selected as the splitting conditions to divide the samples into multiple sub-regions, making the negative gradient residuals of samples within the same region as close as possible. Next, the sub-nodes are recursively divided, and by continuously selecting the optimal splitting feature and threshold, the residual error within the region is gradually reduced until a preset stopping condition is met, such as reaching the maximum tree depth or the number of node samples falling below a set threshold. Finally, several terminating nodes are obtained, each forming a leaf node region, thus achieving the fitting of the negative gradient residual and dividing the input feature space into multiple non-overlapping leaf node regions.

[0036] S206: Based on the fitting results, calculate the regional output value for each leaf node region: in, Indicates the first m During the nth iteration, the 1st j The output value of each leaf node region c This represents the predicted correction value for the candidate. Indicates the first m The partition obtained in the nth iteration j There are leaf node regions, and arg min represents minimizing them.

[0037] The regional output value refers to the optimal prediction correction amount corresponding to a certain leaf node region in the regression tree, which is used to locally correct the current model prediction results.

[0038] Specifically, in the gradient boosting regression tree algorithm, a new regression tree is generated in each training round, dividing the input feature space into multiple regions. For samples falling into the same leaf node region, an optimal prediction correction needs to be determined for that region, minimizing the sum of prediction errors for all samples within that region. The formula obtains the optimal constant by minimizing the loss function of the samples within the region. This value is then used as the output value of that leaf node. Subsequently, these leaf node output values ​​are superimposed on the existing model, thereby gradually correcting the model's prediction error, making the model's prediction results continuously approach the true output, and improving the overall prediction accuracy.

[0039] S207: Update the frosting state recognition model based on the initial base learner and the region output values ​​of each leaf node region until the objective function value is less than the preset objective function value, and determine the frosting sensitivity prediction function: in, express M The predicted output value of the frost condition recognition model after the next iteration. Represents the initial base learner. Indicates the number of iterations. I ( ) indicates an indicator function. J k Indicates the first k The number of leaf nodes in a regression tree.

[0040] Among them, the frost sensitivity prediction function refers to the comprehensive prediction function obtained through multiple rounds of regression tree iterative training, which is used to predict the frost sensitivity index of the current heat exchanger based on the input features.

[0041] It should be noted that those skilled in the art can set the value of the preset objective function according to actual needs, and this invention does not limit this.

[0042] Specifically, this formula describes the overall prediction structure of the gradient-boosting regression tree model, that is, it constructs the final strong learner model by successively stacking the prediction results of multiple regression trees. During training, an initial prediction function is first established. Each subsequent training iteration generates a new regression tree that divides the input feature space into several regions and provides a prediction correction value for each region. When an input sample falls into a certain region, the corresponding correction value for that region is added to the current model's prediction result. By continuously accumulating these region correction values, the model gradually corrects the prediction error, making the final prediction function more sensitive to changes. It can more accurately approximate the true output, thereby improving prediction accuracy and the expressive power of the model.

[0043] S208: Based on the frost sensitivity prediction function, determine whether the heat exchanger has entered a frost-sensitive operating condition. If yes, proceed to step S3. Otherwise, return to step S1 and continue monitoring.

[0044] Specifically, the feature vector of the current operating status parameter is input into the frost sensitivity prediction function, and the predicted value of the frost sensitivity index at the current moment is output. The predicted value of the frost sensitivity index is compared with the frost sensitivity threshold. When the predicted value of the frost sensitivity index is greater than or equal to the frost sensitivity threshold, it is determined that the system has entered the frost sensitivity condition.

[0045] It should be noted that by constructing a frosting state identification model based on gradient-enhanced regression trees, and using operating state parameters and inlet air parameters to construct input feature vectors for model training and prediction, a multi-parameter comprehensive analysis of heat exchanger frosting risk can be achieved. This avoids the inaccuracy problems caused by traditional single temperature or pressure difference threshold judgment methods. Simultaneously, by iteratively fitting negative gradient residuals and using regression trees to correct prediction errors, the model can continuously approximate the actual frosting state, improving the accuracy and stability of the frosting sensitivity index prediction. Furthermore, by establishing a frosting sensitivity prediction function and inputting real-time monitored operating characteristics into the model for judgment, frosting trends can be identified before significant frosting formation. This provides sufficient response time for subsequent waste heat preheating or heat exchange regulation measures, effectively delaying frosting formation, reducing frequent defrosting operations, and improving the overall heat exchange efficiency and operational stability of the heat exchanger under low-temperature conditions.

[0046] S3: Based on the industrial waste heat recovery algorithm, identify available waste heat sources suitable for air preheating.

[0047] Industrial waste heat recovery algorithms refer to computational methods or optimization strategies that determine effectively usable waste heat resources based on parameters such as heat supply capacity, temperature level, and system heat demand through calculation and matching analysis. Air preheating refers to heating air using an external heat source before it enters the heat exchanger, thereby increasing the air temperature and reducing air humidity and the risk of frost formation. Available waste heat sources refer to waste heat sources that, after being screened by waste heat recovery algorithms, meet the air preheating requirements in terms of heat quantity, temperature level, and stability, and are suitable for the air preheating process.

[0048] In one possible implementation, S3 specifically includes: S301: Construct a set of candidate waste heat sources and calculate the heat supply capacity and heat supply capacity of each candidate waste heat source in the set.

[0049] The calculation method for heat supply capacity is as follows: First, obtain the mass flow rate of the candidate waste heat source per unit time and determine the isobaric specific heat capacity of the waste heat medium. Then, measure the inlet temperature of the waste heat medium before entering the heat exchange process and the outlet temperature after heat exchange, and calculate the temperature difference between the inlet and outlet temperatures. Finally, multiply the mass flow rate, isobaric specific heat capacity, and temperature difference of the waste heat medium to obtain the heat supply capacity that the candidate waste heat source can provide under the current operating conditions. This calculation result reflects the amount of heat released by the waste heat medium due to the temperature decrease per unit time. The greater the heat supply capacity, the more capable the waste heat source is of providing heat energy for the subsequent air preheating process.

[0050] The specific calculation method for heat supply capacity is as follows: First, determine the heat supply capacity of the candidate waste heat source, that is, the amount of heat that the waste heat source can release per unit time. Then, obtain the ambient reference temperature and determine the average heat source temperature of the candidate waste heat source. Next, calculate the temperature potential coefficient between the ambient reference temperature and the heat source temperature, that is, first divide the ambient reference temperature by the heat source temperature, and then subtract the ratio from 1 to obtain the proportion of effective work capacity of the waste heat source relative to the environment. Finally, multiply the heat supply capacity by the temperature potential coefficient to obtain the heat supply capacity of the candidate waste heat source. This calculation result not only reflects the amount of heat contained in the waste heat source, but also reflects the quality of that heat relative to the environment that can be effectively utilized. Therefore, the larger the heat supply capacity, the more abundant the heat source is, and the higher the heat energy quality is, making it more suitable as a usable waste heat source for air preheating.

[0051] S302: Construct a model of the air preheating requirements on the inlet side of the heat exchanger.

[0052] Specifically, the mass flow rate, inlet air temperature, and specific heat capacity of the air entering the heat exchanger are first obtained. Combined with the control objective of suppressing frosting or delaying entry into frosting-sensitive conditions under low-temperature operating conditions, a target preheating temperature is set. Then, based on the heat absorbed by the inlet air to rise from its current temperature to the target preheating temperature, an expression for the air preheating heat power demand is established, thus obtaining the preheating load required by the inlet air under the current operating conditions. Furthermore, by combining the ambient reference temperature and the target preheating temperature, a corresponding expression for the air preheating efficiency demand can be established to characterize the thermal energy quality requirements of the air preheating process. The purpose of constructing this model is to transform the originally general "air preheating demand" into calculable and quantifiable heat sink demand parameters. This allows subsequent industrial waste heat recovery algorithms to match the heat and efficiency of each candidate waste heat source with the air preheating demand on the inlet side of the heat exchanger, thereby identifying truly suitable available waste heat sources for air preheating and providing a basis for determining the optimal waste heat recovery scheme and constructing the heat pipe heat exchanger preheating loop.

[0053] S303: Based on the air preheating demand model on the air intake side, calculate the heat demand and heat demand of the air preheating heat sink.

[0054] Specifically, the calculation of heat demand is as follows: First, obtain the mass flow rate of the air entering the heat exchanger's inlet side and determine the air's isobaric specific heat capacity. Then, measure the current inlet temperature of the air and determine the target preheating temperature based on the preheating control objective. Next, calculate the temperature difference between the target preheating temperature and the inlet air temperature, representing the temperature increase required for the air to rise from its current state to the target state. Finally, multiply the air mass flow rate, the air's isobaric specific heat capacity, and the temperature difference to obtain the heat demand required for the inlet air under the current operating conditions. This result reflects the amount of heat required per unit time to heat the inlet air to the target preheating temperature. A higher heat demand indicates a higher external heating capacity required to achieve preheating and prevent frost formation.

[0055] The calculation process for heat demand is as follows: First, determine the heat demand for the air preheating process on the intake side, that is, the amount of heat required to heat the inlet air to the target preheating temperature per unit time. Then, obtain the ambient reference temperature and determine the target temperature after air preheating. Next, calculate the temperature potential coefficient corresponding to the air preheating process, that is, first divide the ambient reference temperature by the target preheating temperature, and then subtract the ratio from 1 to obtain the proportion of preheated heat that can be effectively converted into useful energy. Finally, multiply the air preheating heat demand by the temperature potential coefficient to obtain the heat demand for the air preheating process on the intake side. This result does not simply represent the amount of heat required, but rather the level of effective energy required to achieve the preheating target. Therefore, the larger the heat demand, the more heat the air preheating process requires, and the higher the requirements for heating temperature and thermal energy quality.

[0056] S304: Calculate the recoverable heat of each candidate waste heat source based on the heat overlap relationship between heat supply capacity and heat demand.

[0057] Specifically, the recoverable heat is calculated as follows: after determining the start and end times of the heat recovery process, the instantaneous heat recovery power of the system within the time interval is first obtained, and then the instantaneous heat recovery power is integrated within the time interval to obtain the cumulative heat recovered during that time period.

[0058] Specifically, in efficient heat exchange management methods for heat exchangers under low-temperature conditions, simply knowing that a waste heat source has "high instantaneous heat power" is insufficient. This is because the preheating demand of the air on the inlet side of the heat exchanger constantly changes with ambient temperature, humidity, airflow, and operating conditions, and the temperature and flow rate of the waste heat source itself also fluctuate. Therefore, this formula needs to further transform "whether it can match at a certain moment" into "how much effective heat it can contribute over a period of time." Only in this way can we accurately determine whether a waste heat source is truly suitable as an air preheating heat source, and provide a basis for subsequent selection of the optimal waste heat recovery scheme, design of the heat pipe heat exchanger preheating loop, and dynamic adjustment strategies.

[0059] S305: Calculate the recoverable energy of each candidate waste heat source based on the overlap between energy supply capacity and energy demand.

[0060] Specifically, the start and end times of the waste heat recovery process are first determined. Then, the instantaneous energy output power of each candidate waste heat source within this time interval is obtained. This parameter represents the effective usable energy that the waste heat source can provide per unit time. Subsequently, the instantaneous energy output power is integrated over the time interval to obtain the cumulative recoverable energy that the candidate waste heat source can provide throughout the entire recovery cycle.

[0061] Specifically, in efficient heat exchange management methods for heat exchangers under low-temperature conditions, simply calculating recoverable heat is insufficient, because different waste heat sources, even those with similar heat amounts, can have significantly different thermal quality. Some waste heat sources, while having a large total heat, may have a low temperature level and may not effectively meet the temperature rise requirements for preheating the incoming air. Conversely, some waste heat sources may not have the largest heat output, but due to their higher temperature and stronger efficiency, they are more suitable for air preheating. This formula elevates the assessment of "whether a waste heat source is usable" from a simple heat comparison to an "efficiency matching" level by integrating the overlap function over time. Therefore, it can more accurately identify waste heat sources truly suitable for low-temperature anti-frost preheating.

[0062] S306: Calculate the air preheating compatibility index based on recoverable heat and recoverable volume, combined with the degree of air preheating compatibility. in, Indicates the first h Air preheating compatibility index of candidate waste heat sources express t Calorie requirements at all times express t The need for time, This represents the weighting coefficient for heat matching. This represents the matching weight coefficient. It indicates that heat can be restored. Indicates the start time of the air preheating evaluation cycle. This indicates the end time of the air preheating evaluation cycle. This indicates that the amount of energy can be restored.

[0063] It should be noted that those skilled in the art can set the size of the heat matching weight coefficient and the heat matching weight coefficient according to actual needs, and this invention does not limit them.

[0064] Among them, the air preheating compatibility index is an indicator that comprehensively evaluates the degree of heat matching and heat matching of the waste heat source, and is used to determine whether a certain waste heat source is suitable for the air preheating process.

[0065] Specifically, under low-temperature conditions, the purpose of preheating the inlet air of the heat exchanger is not simply to supplement heat, but to delay the heat exchanger from entering a frosting-sensitive condition, reduce the defrosting frequency, and increase the effective heat exchange time by raising the inlet air temperature and temperature level. Therefore, it is insufficient to merely consider the amount of heat from a waste heat source; it is also necessary to consider whether the thermal quality of the waste heat source is sufficient to support the air preheating target. This formula evaluates "whether the heat is sufficient" in the first term and "whether the quality is sufficient" in the second term, thereby transforming different candidate waste heat sources into a single, directly comparable comprehensive indicator. This facilitates the subsequent determination of the optimal waste heat recovery scheme and the construction of the heat pipe air preheating loop.

[0066] S307: Identify available waste heat sources suitable for air preheating based on the air preheating compatibility index.

[0067] Specifically, when the air preheating compatibility index is greater than or equal to the air preheating compatibility index threshold, the available waste heat source is determined.

[0068] It should be noted that those skilled in the art can set the air preheating adaptation index threshold according to actual needs, and this invention does not limit it.

[0069] It should be noted that by constructing a candidate waste heat source set and simultaneously calculating the heat supply capacity and energy supply capacity of each waste heat source, a comprehensive evaluation of waste heat resources can be conducted from both the aspects of heat scale and thermal energy quality, thereby avoiding selection errors caused by relying solely on heat quantity. Furthermore, by establishing an air preheating demand model on the air intake side and calculating the heat and energy requirements for air preheating, the air preheating demand can be quantitatively expressed, providing a clear matching basis for the waste heat source selection process. In addition, by calculating recoverable heat and recoverable energy and further constructing an air preheating suitability index, a comprehensive comparison of different candidate waste heat sources can be achieved, thereby selecting truly suitable usable waste heat sources for air preheating and improving the accuracy and efficiency of waste heat utilization.

[0070] S4: Determine the optimal waste heat recovery scheme based on the coverage capacity of the available waste heat source during the critical time window of the entire frosting process and the ability to inhibit refreezing after defrosting.

[0071] The entire frosting process refers to the entire operation of a heat exchanger under low-temperature conditions, from an initial frost-free state to the formation, growth, and defrosting of frost. Critical time window coverage capability refers to the ability of a waste heat recovery scheme to provide effective heat and meet air preheating requirements during critical stages of the frosting development process (e.g., preheating warning stage or frost suppression stage). This capability is used to evaluate the actual effectiveness of the waste heat recovery scheme in the critical stages of frost prevention control. Post-defrost refreezing inhibition capability refers to the ability to maintain a relatively high surface temperature of the heat exchanger through air preheating or waste heat supply after defrosting, thereby reducing the re-freezing of residual moisture and the formation of frost. The optimal waste heat recovery scheme refers to the waste heat utilization scheme with the best overall effect and most suitable for air preheating of the heat exchanger, determined by comprehensively comparing critical time window coverage capability and refreezing inhibition capability among multiple candidate waste heat utilization schemes.

[0072] It should be noted that by determining the optimal waste heat recovery scheme based on the coverage capacity of the available waste heat source during the critical time window of the entire frosting process and the ability to inhibit refreezing after defrosting, the waste heat utilization effect can be comprehensively evaluated from the perspective of the entire process of heat exchanger frosting development, rather than simply selecting based on instantaneous heating capacity, thereby improving the scientificity and rationality of the waste heat recovery scheme selection.

[0073] In one possible implementation, S4 specifically includes: S401: Based on the evolution of the frosting state, the key time windows for waste heat recovery are divided to determine the early warning preheating time window, the frost suppression maintenance time window, and the post-frosting drying time window.

[0074] The preheating window refers to the time period when the heat exchanger shows a tendency to frost before obvious frost formation, by preheating the air in advance to reduce the risk of frost formation. The frost suppression and maintenance window refers to the time period when the heat exchanger has entered a frost-sensitive state, by continuously supplying heat to maintain the surface temperature of the heat exchanger to slow down frost growth. The post-defrost drying window refers to the time period after defrosting, by maintaining a certain temperature to accelerate the evaporation of residual moisture and prevent refreezing.

[0075] S402: Construct a set of candidate waste heat recovery schemes.

[0076] Among them, the candidate waste heat recovery scheme set refers to a set of multiple possible waste heat utilization schemes formed based on different waste heat sources, heating methods or recovery paths.

[0077] S403: For each candidate waste heat recovery scheme in the candidate waste heat recovery scheme set, calculate the key time window coverage factor and threshold delay gain.

[0078] Specifically, the threshold delay gain is calculated as follows: First, under the baseline operating condition without a waste heat recovery scheme, the change in the frost sensitivity index during heat exchanger operation is continuously monitored, and the time corresponding to the first occurrence of the forced defrost threshold is recorded. Then, under the condition of employing the g-th waste heat recovery scheme, the frost sensitivity index is monitored again under the same operating conditions, and the time corresponding to the first occurrence of the forced defrost threshold is recorded. Next, the time difference between the two is calculated; this difference represents the time delay in the heat exchanger entering the forced defrost state due to the waste heat preheating effect. Finally, this delay time is divided by a preset standard operating evaluation period to obtain the dimensionless threshold delay gain. This result reflects the degree to which the waste heat recovery scheme improves the ability of the heat exchanger to delay entering the forced defrost state; the larger the value, the more the scheme can extend the effective heat exchange operating time of the heat exchanger.

[0079] Specifically, by comparing the ratio between the effective heat supply of candidate waste heat recovery schemes and the total demand for air preheating within the critical preheating window, the critical time window coverage coefficient is obtained. This quantitatively evaluates the actual contribution of different waste heat recovery schemes in delaying the heat exchanger from entering the frosting-sensitive operating condition, providing a basis for selecting the optimal waste heat recovery scheme in the efficient heat exchange management of heat exchangers under low-temperature conditions.

[0080] S404: Calculate the refreezing inhibition factor based on the drying window after defrost, combined with the residual water state after defrost and the duration of low surface temperature. in, Indicates the first g Refreezing inhibition factors for candidate waste heat recovery schemes express t At all times, the first g When considering candidate waste heat recovery schemes, the residual water mass on the heat exchanger surface or fin surface is important. Indicates an indicator function, express t The mass of residual water on the heat exchanger surface at any given time when no waste heat recovery scheme is employed (baseline operating condition). express t Always adopting the first g When considering multiple candidate waste heat recovery schemes, the surface temperature of the heat exchanger is... express t The surface temperature of the heat exchanger surface at any given time when no waste heat recovery scheme is employed (baseline operating condition). This indicates the drying time after the frost has melted.

[0081] The refreezing inhibition factor refers to the index that reduces the degree of refreezing of residual moisture during the drying stage after defrosting by preheating the air or using waste heat. It is used to measure the inhibitory effect of waste heat recovery schemes on refreezing.

[0082] S405: Determine the optimal waste heat recovery scheme by combining the critical time window coverage factor, threshold delay gain, and refreezing inhibition factor.

[0083] Specifically, after obtaining the key time window coverage coefficient, threshold delay gain, and refreezing inhibition factor for each candidate waste heat recovery scheme, the three indicators are first processed to be dimensionless, making the evaluation parameters of different dimensions comparable. Then, based on the heat exchanger operation and management objectives under low-temperature conditions, corresponding weight coefficients are set for the key time window coverage coefficient, threshold delay gain, and refreezing inhibition factor, and the three indicators are weighted and fused to obtain the comprehensive evaluation value of each candidate waste heat recovery scheme. Subsequently, the comprehensive evaluation values ​​of each candidate scheme are ranked and compared, and the candidate waste heat recovery scheme with the largest comprehensive evaluation value is selected as the optimal waste heat recovery scheme.

[0084] It should be noted that by dividing the pre-warning preheating window, the frost suppression maintenance window, and the post-frost drying window based on the frost evolution process, and combining the key window coverage coefficient, threshold delay gain, and refreezing inhibition factor to comprehensively evaluate different candidate waste heat recovery schemes, the waste heat recovery effect can be systematically analyzed from the entire process of frost formation, development, and post-frost defrosting. Compared with the traditional method of selecting waste heat sources based solely on instantaneous heating capacity or a single temperature condition, this method can more comprehensively evaluate the actual contribution of waste heat recovery schemes to the heat exchanger's anti-frost performance and operational stability.

[0085] S5: Based on the optimal waste heat recovery scheme, an air preheating loop is constructed using a heat pipe heat exchanger, and the heat from the available waste heat source is transferred to the air inlet side of the heat exchanger through the air preheating loop.

[0086] Among them, a heat pipe heat exchanger refers to a heat exchange device that utilizes the phase change heat transfer principle of the working fluid inside the heat pipe to achieve efficient heat transfer. It absorbs heat through the evaporation section and releases heat through the condensation section, thereby achieving efficient heat transfer under conditions of small temperature difference. An air preheating loop refers to an airflow and heat exchange structure that establishes a heat transfer path between the waste heat source and the air entering the heat exchanger. Through this loop, the air undergoes a preheating process before entering the heat exchanger.

[0087] It should be noted that heat pipe heat exchangers have the characteristics of high heat transfer efficiency, stable operation and no need for external power drive, making the air preheating process more reliable and energy-saving. This improves the overall heat exchange efficiency of the heat exchanger and the stability of system operation under low temperature conditions while improving the waste heat utilization efficiency.

[0088] In one possible implementation, S5 specifically includes: S501: Calculate the target preheating load based on the anti-frost target.

[0089] Specifically, the target preheating temperature of the air intake side is determined by taking the larger value between the basic preheating target temperature and the dew point safety temperature, thereby ensuring that the air preheating circuit can not only meet the normal preheating requirements, but also effectively improve the anti-frost safety of the heat exchanger under low temperature conditions.

[0090] Specifically, the target preheating load is calculated as follows: First, the air mass flow rate entering the air preheating loop is obtained, and the isobaric specific heat capacity of the air is determined. Then, the target preheating temperature of the inlet air is determined according to the anti-frost control requirements, while the current inlet air temperature is measured. Next, the temperature difference between the target preheating temperature and the inlet air temperature is calculated to represent the temperature increase required for the air to rise from its current state to the target preheating state. Finally, the air mass flow rate, the air isobaric specific heat capacity, and the temperature difference are multiplied to obtain the target preheating load. This result reflects the amount of heat required per unit time to heat the air before it enters the heat exchanger to the target preheating temperature.

[0091] S502: Construct the main preheating branch of the heat pipe and calculate the air mixing ratio of the main preheating branch of the heat pipe.

[0092] Specifically, the calculation method for the air-to-air mixing ratio is as follows: First, determine the target preheating temperature that the air needs to reach before entering the heat exchanger, and measure the temperature of the unpreheated inlet air. Then, obtain the outlet temperature of the air after passing through the main preheating branch of the heat pipe, i.e., the temperature of the air after being heated by the heat pipe heat exchanger. Next, calculate the temperature difference between the target preheating temperature and the inlet air temperature, and the temperature difference between the outlet temperature of the main preheating branch of the heat pipe and the inlet air temperature. Finally, divide the former by the latter to obtain the proportion of air from the main preheating branch of the heat pipe in the total air-to-air mixture. This proportion reflects what percentage of the air needs to be heated by the heat pipe heat exchanger so that the mixed air temperature exactly reaches the target preheating temperature, while the remaining air participates in the mixing directly through the bypass branch.

[0093] S503: Determine the number of heat pipes to be activated in stages based on the target preheating load and the heat exchanger's heat exchange capacity.

[0094] Specifically, the equivalent thermal resistance of a single heat pipe module is first determined, and the logarithmic mean temperature difference between the waste heat source side and the air side is calculated to characterize the actual heat transfer driving force of the heat pipe heat exchange process. Next, the equivalent thermal resistance of a single heat pipe module is multiplied by the target preheating load, and then divided by the logarithmic mean temperature difference to obtain the theoretically required number of heat pipe modules to participate in the operation under the current preheating demand. Finally, the calculation result is rounded up to obtain the number of heat pipe modules activated in stages. This result reflects the minimum number of heat pipe modules that need to be activated simultaneously to meet the current target preheating load, thus matching the actual heat exchange capacity of the heat pipe heat exchanger with the air preheating demand.

[0095] S504: Construct a graded heat pipe preheating unit based on the number of heat pipes activated in each grade.

[0096] The number of heat pipe modules activated in stages refers to the number of heat pipe modules that need to work simultaneously according to the preheating load requirements. A staged heat pipe preheating unit is an air preheating structural unit formed by combining multiple heat pipe modules in a staged manner.

[0097] S505: Calculate the dew point safety margin and the air-side pressure drop of the main heat pipe preheating branch by combining the staged heat pipe preheating unit and the air mixing ratio.

[0098] Specifically, the dew point safety margin is calculated as follows: the air temperature after mixing the main preheating branch and the bypass branch minus the inlet air dew point temperature.

[0099] The air-side pressure drop is calculated as follows: First, obtain the air density and maximum flow velocity in the flow channel to calculate the dynamic pressure term generated by the air flow. Then, combine the heat exchanger structural parameters, including the number of rows of heat pipes or heat exchange units, and structural correction factors to reflect the cumulative resistance effect generated when air flows in a multi-row structure. Finally, multiply the above results by the Euler number to obtain the air-side pressure drop generated when air flows through the heat pipe heat exchanger.

[0100] Specifically, in efficient heat exchange management methods for heat exchangers under low-temperature conditions, although preheating the inlet air through a heat pipe heat exchanger can increase the inlet air temperature and delay frost formation, excessive air-side resistance after introducing the heat pipe heat exchanger can lead to increased fan load, decreased airflow, and even negate the benefits of preheating. Therefore, when constructing an air preheating loop, it is essential not only to consider the heat exchange effect but also to verify whether the air-side pressure drop is within the allowable range.

[0101] S506: When the dew point safety margin meets the anti-frost requirements and the air-side pressure drop does not exceed the upper limit of the pressure drop allowable limit, the air preheating circuit is determined to be completed, and the heat from the available waste heat source is transferred to the air inlet side of the heat exchanger according to the air preheating circuit.

[0102] It should be noted that those skilled in the art can set the upper limit of the allowable voltage drop according to actual needs, and this invention does not limit it.

[0103] It should be noted that by constructing the main preheating branch and the bypass mixing branch of the heat pipe and calculating the mixing ratio, the air temperature entering the heat exchanger can be flexibly adjusted according to the actual preheating requirements. Compared with the traditional fixed preheating method, it has higher adjustment accuracy and operational stability. In addition, by determining the number of heat pipes to be activated in stages according to the preheating load and constructing a staged heat pipe preheating unit, the heat exchange capacity can be matched with the air preheating requirements, avoiding the problems of insufficient heat exchange capacity or excessive equipment operation. Compared with the traditional design method that only focuses on the heat exchange effect and ignores the air resistance, this method can improve the anti-frost capability while avoiding the problems of increased fan load and decreased air volume, thereby achieving synergistic optimization of air preheating effect and system operational stability, and improving the overall efficiency of the heat exchange system under low temperature conditions.

[0104] S6: Use the heat recovered by the heat pipe heat exchanger to preheat the air entering the heat exchanger.

[0105] It should be noted that by using the heat recovered from the heat pipe heat exchanger to preheat the air entering the exchanger, the air temperature can be increased before it enters the exchanger, thereby reducing the possibility of water vapor condensing and frosting on the heat exchanger surface, thus delaying frost formation and reducing the frequency of defrosting operations. Simultaneously, by utilizing industrial waste heat for air preheating, no additional electricity or other energy consumption is required, thereby improving the system's energy efficiency and reducing operating costs. Furthermore, heat pipe heat exchangers have advantages such as high heat transfer efficiency, simple structure, and stable operation, enabling the air preheating process to proceed stably under small temperature differences. This improves the heat exchanger's anti-frost capability, extends its effective heat exchange operating time, and enhances the overall heat exchange efficiency and operational reliability of the system under low-temperature conditions.

[0106] S7: Dynamically adjust the flow rate of available waste heat source based on the changes in the operating parameters of the preheated heat exchanger.

[0107] The flow rate refers to the flow rate of the waste heat medium introduced from the available waste heat source into the air preheating circuit. The magnitude of this flow rate directly determines the amount of heat that can be transferred to the air side.

[0108] In one possible implementation, S7 specifically includes: S701: Calculate the overall anti-frost deviation of the heat exchanger based on the operating status parameters of the preheated heat exchanger.

[0109] Specifically, the preheating temperature deviation and frosting state deviation at the current moment are first obtained. The preheating temperature deviation characterizes the degree of deviation of the actual preheated air temperature from the target preheating temperature, while the frosting state deviation characterizes the degree of deviation of the current frosting sensitivity from the preset frosting threshold. Then, the preheating temperature deviation and frosting state deviation are normalized. The preheating temperature deviation is divided by the difference between the target preheating temperature and the inlet air temperature before preheating, and a minimum positive number is added to eliminate the influence of differences in temperature rise under different operating conditions. Simultaneously, the frosting state deviation is divided by the sum of the preset frosting threshold and the minimum positive number to eliminate the influence of differences in dimensions and scales under different threshold settings. Next, the normalized preheating temperature deviation and the normalized frosting state deviation are multiplied by their respective weighting coefficients. Finally, the two weighted results are summed to obtain the comprehensive anti-frost deviation at the current moment.

[0110] S702: Determine the operating mode of the heat pipe heat exchanger based on the comprehensive anti-frost deviation.

[0111] Specifically, the operating modes include at least: full preheating mode, tiered preheating mode, and bypass maintenance mode. Specifically, when the overall anti-frost deviation indicates insufficient preheating and an increased risk of frost formation, the system switches to full preheating mode. When the overall anti-frost deviation indicates that the current preheating basically meets the requirements, the system switches to tiered preheating mode. When the overall anti-frost deviation indicates that the current preheating is trending towards overheating, the system switches to bypass maintenance mode.

[0112] S703: Based on the working mode and the rate of change of the comprehensive anti-frost deviation, the flow rate of the available waste heat source is dynamically adjusted.

[0113] Specifically, after determining the current operating mode of the heat pipe heat exchanger, the overall anti-frost deviation and its rate of change are first read. The overall anti-frost deviation reflects the degree of deviation between the current preheating effect and the anti-frost requirement, while the rate of change reflects whether this deviation is widening or decreasing. Then, the waste heat source diversion flow rate is adjusted in layers based on the operating mode. When the heat pipe heat exchanger is in enhanced preheating mode, if the rate of change of the overall anti-frost deviation is greater than zero, it indicates that the risk of frost formation is still accelerating, so the diversion flow rate of the available waste heat source is increased to improve the heat supply capacity of the heat pipe heat exchanger. If the rate of change of the overall anti-frost deviation is less than zero, it indicates that the anti-frost condition is improving, so the diversion flow rate is reduced to avoid over-preheating. When the heat pipe heat exchanger is in maintenance preheating mode, only small, continuous adjustments are made to the diversion flow rate to stabilize the preheated air temperature within the target range. When the heat pipe heat exchanger is in bypass maintenance mode, the diversion flow rate is reduced to a low-flow maintenance state or shut off to reduce ineffective heating.

[0114] S704: Based on the increasing trend of air-side pressure drop and the decreasing trend of heat transfer capacity, stability constraints are applied to correct the dynamic adjustment results. in, express t The final waste heat source diversion flow rate after stability constraint correction at all times. express t The initial traffic volume obtained after dynamic adjustment at all times. This represents the weighting coefficient of the air-side blockage growth constraint. express t air-side blockage growth rate at any given time. This represents the weighting coefficient for the heat transfer attenuation constraint. express t The heat transfer attenuation rate at any given time.

[0115] It should be noted that those skilled in the art can set the values ​​of the air-side blockage growth constraint weight coefficient and the heat transfer attenuation constraint weight coefficient according to actual needs, and this invention does not limit them.

[0116] It should be noted that by constructing a comprehensive anti-frost deviation and simultaneously incorporating preheating temperature deviation and frosting state deviation for normalization and fusion, a unified quantitative evaluation of air preheating effect and frosting risk can be achieved. Compared with traditional methods that rely solely on a single temperature or pressure difference for control, this method can more comprehensively and accurately reflect the actual operating status of the heat exchanger under low-temperature conditions. Furthermore, by determining the operating mode of the heat pipe heat exchanger based on the comprehensive anti-frost deviation and dynamically adjusting the waste heat source diversion flow rate in conjunction with the deviation change rate, the system can automatically enhance preheating capacity when the frosting risk increases and promptly reduce heating intensity when the anti-frost condition improves, thereby achieving an adaptive match between preheating intensity and actual anti-frost requirements.

[0117] S8: Based on the dynamic adjustment results, determine whether the frost sensitivity index of the heat exchanger is greater than the forced defrost threshold. If so, initiate the defrost program and drain the defrost water through the drainage channels formed by the louvered fins on the air side of the heat exchanger. Otherwise, return to step S1 and continue monitoring.

[0118] The frost sensitivity index is a quantifiable indicator of the current frost risk level of a heat exchanger. This index is typically calculated by combining operating parameters and ambient air parameters; a higher value indicates a greater risk of frost formation or increased frost buildup. The defrosting procedure refers to the process of melting the frost layer on the heat exchanger surface and restoring normal heat exchange capacity through heating, reverse heat exchange, or other methods. Louvered fins are fins with a louvered structure installed on the air side of the heat exchanger. They not only increase the heat exchange area but also create drainage channels during the defrosting process.

[0119] It should be noted that those skilled in the art can set the size of the forced defrosting threshold according to actual needs, and this invention does not limit it.

[0120] It should be noted that by combining the results of dynamic adjustment to determine whether the frost sensitivity index of the heat exchanger exceeds the forced defrost threshold, it is possible to further determine whether the defrost program needs to be started after the system has been preheated and adjusted. This avoids the problems of premature or delayed defrosting in traditional timed defrosting methods and improves the accuracy of defrost control.

[0121] In one possible implementation, the following is included after S8: S9: Based on the operating results of the heat exchanger in the current operating cycle, update the air preheating parameters and waste heat recovery adjustment parameters, and generate the heat exchange management strategy for the next operating cycle.

[0122] Among them, air preheating parameters refer to key parameters used to control the air preheating process, including target preheating temperature, preheating load, and heat pipe heat exchanger operating mode switching threshold. Waste heat recovery regulation parameters refer to parameters used to control waste heat diversion flow rate, heating intensity, and regulation sensitivity during air preheating using waste heat sources. Heat exchange management strategy refers to a set of control rules formulated by the system based on operating status and control objectives to guide air preheating, waste heat recovery, and anti-frost control operations in the next operating cycle.

[0123] It should be noted that, compared with the traditional fixed parameter control method, this method can continuously optimize the control parameters based on the actual operating effect, thereby avoiding the problem of decreased control effect due to environmental changes or equipment status changes during long-term operation. At the same time, by periodically updating the air preheating intensity and waste heat recovery adjustment strategy, the waste heat utilization efficiency can be improved while ensuring the anti-frost effect, and unnecessary heating or defrosting operations can be reduced, thereby improving the overall heat exchange efficiency, system stability and energy utilization level of the heat exchanger under low temperature conditions.

[0124] In one possible implementation, S9 specifically includes: S901: Calculate the periodic heat exchange benefit and periodic frost cost based on the heat exchanger's operating results during the current operating cycle.

[0125] The calculation method for the cycle heat exchange benefit is as follows: First, determine the start and end times of the current operating cycle. Then, obtain the instantaneous effective heat exchange power of the heat exchanger at each moment within this time interval. This power can be calculated based on the air mass flow rate, air specific heat capacity at constant pressure, and the temperature difference between the inlet and outlet air of the heat exchanger, and is used to characterize the effective heat transferred by the heat exchanger to the air side per unit time. Subsequently, the instantaneous effective heat exchange power is integrated over the entire operating cycle time interval to obtain the cumulative effective heat exchange achieved by the heat exchanger within this operating cycle, and this cumulative effective heat exchange is used as the cycle heat exchange benefit. This result is used to characterize the actual heat exchange benefit level obtained by the heat exchanger through air preheating and heat exchange processes within the current operating cycle, providing an evaluation basis for subsequent updates to heat exchange management strategies.

[0126] The specific formula for calculating the cost of periodic frosting is as follows: in, This indicates the cost of periodic frosting. This represents the weighting coefficient corresponding to the increase in air-side blockage; max indicates taking the maximum value. Indicates the current running cycle. This represents the weighting coefficient corresponding to heat transfer attenuation. This represents the weighting coefficient corresponding to the periodic frosting cost during drainage time. Indicates the start time of the current running cycle. Indicates the end time of the current running cycle. This indicates the proportion of the drainage duration to the total operating cycle.

[0127] It should be noted that those skilled in the art can set it according to actual needs. , as well as The size is not limited in this invention.

[0128] Among them, the cycle heat exchange benefit refers to the comprehensive benefit index generated by the effective heat exchange capacity improvement brought about by measures such as air preheating and waste heat recovery within the current operating cycle. This index is used to reflect the improvement in heat exchange efficiency or energy utilization effect achieved by the system within this cycle. The cycle frosting cost is a quantitative index of the adverse effects caused by frosting within the same operating cycle. It comprehensively considers factors such as the increase in air-side blockage, the decrease in heat transfer capacity, and the proportion of time occupied by the drainage process, and is used to characterize the degree of negative impact of frosting on system operation.

[0129] S902: Calculate the management deviation for the current operating cycle based on the periodic heat exchange benefit and the periodic frost cost.

[0130] Specifically, the management deviation is calculated as follows: First, based on the preset heat exchange management target, a target performance index is given. The target performance index is used to characterize the expected level of efficient heat exchange management. Then, based on the actual operating results within the current operating cycle, the heat exchange management performance index for the current operating cycle is calculated. The heat exchange management performance index reflects the overall performance between heat exchange benefits and frosting costs within the current cycle. Next, the target performance index is compared with the heat exchange management performance index for the current operating cycle. The management deviation is obtained by subtracting the target performance index from the heat exchange management performance index for the current operating cycle. When the management deviation is greater than zero, it indicates that the heat exchange management effect of the current operating cycle is lower than the target management level, and the air preheating intensity or waste heat recovery regulation capacity needs to be appropriately increased in the next operating cycle. When the management deviation is less than zero, it indicates that the heat exchange management effect of the current operating cycle has reached or exceeded the target management level, and the preheating intensity or regulation sensitivity can be appropriately reduced in the next operating cycle to avoid overheating and ineffective heating.

[0131] S903: Update the air preheating parameters and waste heat recovery adjustment parameters based on the management deviation.

[0132] Specifically, the management deviation calculated for the current operating cycle is first obtained, and its sign and magnitude are determined. When the management deviation is greater than zero, it indicates that the heat exchange management effect for the current operating cycle is lower than the target management level. In this case, the air preheating intensity is appropriately increased, the waste heat source diversion flow rate is increased, or the adjustment threshold is lowered to enhance waste heat recovery capacity, thereby increasing the preheating temperature of the air entering the heat exchanger. When the management deviation is less than zero, it indicates that the heat exchange management effect for the current operating cycle has reached or exceeded the target management level. In this case, the air preheating intensity is appropriately reduced, the waste heat source diversion flow rate is decreased, or the adjustment threshold is increased to avoid overheating and unnecessary energy consumption. Subsequently, the updated air preheating parameters and waste heat recovery adjustment parameters are written into the heat exchange management parameter set to guide the air preheating control and waste heat recovery adjustment process for the next operating cycle.

[0133] S904: Generate a heat exchange management strategy for the next operating cycle based on the updated air preheating parameters and waste heat recovery adjustment parameters.

[0134] Specifically, after updating the target preheating temperature, the heat pipe heat exchanger operating mode switching threshold, and the waste heat source diversion flow rate adjustment parameters, the updated parameters are combined according to the preset control logic to form a heat exchange management strategy for the next operating cycle. The heat exchange management strategy is then written into the control parameter set or control strategy table as the basis for executing air preheating, heat pipe heat exchanger mode switching, and dynamic adjustment of waste heat source diversion flow rate in the next operating cycle, so that the heat exchanger can achieve better anti-frost preheating and heat exchange management according to the updated parameters in the next operating cycle.

[0135] It should be noted that by calculating the cycle heat exchange benefit and cycle frost cost after each operating cycle, and further calculating the management deviation to evaluate the actual effect of the current heat exchange management strategy, the periodic evaluation and feedback adjustment of the system's operating performance can be achieved. Compared with the traditional method of using fixed control parameters or experience-based control strategies, this method can continuously optimize the air preheating intensity and waste heat recovery adjustment strategy based on actual operating results.

[0136] Reference manual attached Figure 2 The diagram shows a schematic of the structure of the high-efficiency heat exchange management system for heat exchangers under low-temperature conditions provided in an embodiment of the present invention.

[0137] This invention provides a high-efficiency heat exchange management system 20 for heat exchangers under low-temperature conditions, including: a processor 201 and a memory 202; The memory 202 stores programs or instructions that can run on the processor 201. When the program or instructions are executed by the processor 201, they implement the steps of the above-described efficient heat exchange management method for heat exchangers under low-temperature conditions and achieve the same technical effect. To avoid repetition, the present invention will not elaborate further.

[0138] It should be understood that the processor 201 in this embodiment of the invention may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0139] It should also be understood that the memory 202 in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DR RAM).

[0140] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A 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, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0141] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0142] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0143] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0144] In the embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0145] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0147] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0148] This invention provides a readable storage medium that stores a program or instructions on the medium. When the program or instructions are executed by a processor, they implement the steps of the above-described efficient heat exchange management method for heat exchangers under low-temperature conditions and achieve the same technical effect. To avoid repetition, this invention will not elaborate further.

[0149] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A method for efficient heat exchange management of a heat exchanger under cryogenic conditions, characterized in that, include: S1: Real-time monitoring of the heat exchanger's operating status parameters and inlet air parameters under low-temperature conditions; S2: Based on the operating status parameters and the inlet air parameters, determine whether the heat exchanger has entered a frosting sensitive condition using the frosting status identification model; if yes, proceed to step S3; otherwise, return to step S1 and continue monitoring. S3: Based on the industrial waste heat recovery algorithm, identify available waste heat sources suitable for air preheating; S4: Determine the optimal waste heat recovery scheme based on the coverage capacity of the available waste heat source during the critical time window of the entire frosting process and the ability to inhibit refreezing after defrosting; S5: Based on the optimal waste heat recovery scheme, an air preheating circuit is constructed using a heat pipe heat exchanger, and the heat from the available waste heat source is transferred to the air inlet side of the heat exchanger through the air preheating circuit. S6: Use the heat recovered by the heat pipe heat exchanger to preheat the air entering the heat exchanger; S7: Dynamically adjust the flow rate of the available waste heat source according to the changes in the operating status parameters of the preheated heat exchanger; S8: Based on the dynamic adjustment results, determine whether the frost sensitivity index of the heat exchanger is greater than the forced defrosting threshold; if so, start the defrosting program and drain the defrosting water through the drainage channel formed by the louvered fins on the air side of the heat exchanger; otherwise, return to step S1 and continue monitoring.

2. The method for efficient heat transfer management of heat exchangers under cryogenic conditions as claimed in claim 1 wherein, The operating status parameters include inlet air temperature, outlet air temperature, air-side pressure difference, air velocity, and air flow rate; The inlet air parameters include inlet air temperature, inlet air relative humidity, and inlet air dew point temperature.

3. The method for efficient heat transfer management of heat exchangers under cryogenic conditions as claimed in claim 1 wherein, S2 specifically includes: S201: Based on the operating status parameters and the inlet air parameters, construct the input feature vector of the frosting state recognition model; S202: Construct the objective function of the frosting state recognition model; S203: Set the initial base learner for the frosting state recognition model; S204: Input the input feature vector into the frost state recognition model and output the negative gradient residual; S205: Fit the negative gradient residual using a regression tree and divide the input feature space into multiple non-overlapping leaf node regions; S206: Based on the fitting results, calculate the regional output value of each of the leaf node regions; S207: Update the frosting state recognition model based on the initial base learner and the regional output values ​​of each leaf node region until the objective function value is less than the preset objective function value, and determine the frosting sensitive prediction function; S208: Based on the frosting sensitivity prediction function, determine whether the heat exchanger has entered a frosting sensitive condition; if yes, proceed to step S3; otherwise, return to step S1 and continue monitoring.

4. The cryogenic heat exchanger high efficiency heat exchange management method of claim 1, wherein, S3 specifically includes: S301: Construct a set of candidate waste heat sources and calculate the heat supply capacity and heat supply capacity of each candidate waste heat source in the set of candidate waste heat sources; S302: Construct a preheating demand model for the air inlet side of the heat exchanger; S303: Based on the air preheating demand model on the air intake side, calculate the heat demand and heat demand of the air preheating heat sink; S304: Calculate the recoverable heat of each of the candidate waste heat sources based on the heat supply capacity and the heat demand overlap relationship; S305: Calculate the recoverable energy of each of the candidate waste heat sources based on the overlap relationship between the energy supply capacity and the energy demand; S306: Calculate the air preheating compatibility index based on the recoverable heat and the recoverable volume, combined with the air preheating compatibility degree; S307: Identify available waste heat sources suitable for air preheating based on the air preheating compatibility index.

5. The cryogenic heat exchanger high efficiency heat exchange management method of claim 1, wherein, S4 specifically includes: S401: Based on the evolution process of the frosting state, the key time windows for waste heat recovery are divided to determine the early warning preheating time window, the frost suppression maintenance time window, and the post-defrost drying time window; S402: Construct a set of candidate waste heat recovery solutions; S403: For each candidate waste heat recovery scheme in the set of candidate waste heat recovery schemes, calculate the key time window coverage factor and threshold delay gain; S404: Calculate the refreezing inhibition factor based on the drying time window after defrosting, combined with the residual water state after defrosting and the duration of low surface temperature; S405: Determine the optimal waste heat recovery scheme by combining the key time window coverage coefficient, the threshold delay gain, and the refreezing inhibition factor.

6. The high-efficiency heat exchange management method for heat exchangers under low-temperature conditions according to claim 1, characterized in that, S5 specifically includes: S501: Calculate the target preheating load based on the anti-frost target; S502: Construct the main preheating branch of the heat pipe and calculate the air mixing ratio of the main preheating branch of the heat pipe; S503: Determine the number of heat pipes to be activated in stages based on the target preheating load and the heat exchanger's heat exchange capacity; S504: Construct a graded heat pipe preheating unit based on the number of heat pipes activated in each grade; S505: Calculate the dew point safety margin and the air-side pressure drop of the main preheating branch of the heat pipe, respectively, based on the staged heat pipe preheating unit and the air mixing ratio. S506: When the dew point safety margin meets the anti-frost requirements and the air-side pressure drop does not exceed the upper limit of the pressure drop allowable limit, the air preheating circuit is determined to be completed, and the heat from the available waste heat source is transferred to the air inlet side of the heat exchanger according to the air preheating circuit.

7. The high-efficiency heat exchange management method for heat exchangers under low-temperature conditions according to claim 1, characterized in that, Specifically, S7 includes: S701: Calculate the overall anti-frost deviation of the heat exchanger based on the operating status parameters of the preheated heat exchanger; S702: Determine the operating mode of the heat pipe heat exchanger based on the comprehensive anti-frost deviation. S703: In conjunction with the aforementioned working mode, the flow rate of the available waste heat source is dynamically adjusted based on the rate of change of the comprehensive anti-frost deviation. S704: Based on the increasing trend of air-side pressure drop and the decreasing trend of heat transfer capacity, the dynamic adjustment results are corrected by stability constraints.

8. The high-efficiency heat exchange management method for heat exchangers under low-temperature conditions according to claim 1, characterized in that, Following S8, the following is also included: S9: Based on the operating results of the heat exchanger in the current operating cycle, update the air preheating parameters and waste heat recovery adjustment parameters, and generate the heat exchange management strategy for the next operating cycle.

9. The high-efficiency heat exchange management method for heat exchangers under low-temperature conditions according to claim 8, characterized in that, S9 specifically includes: S901: Calculate the cycle heat exchange benefit and cycle frosting cost based on the operating results of the heat exchanger in the current operating cycle; S902: Calculate the management deviation of the current operating cycle based on the cycle heat exchange benefit and the cycle frost cost; S903: Update the air preheating parameters and the waste heat recovery adjustment parameters according to the management deviation; S904: Generate the heat exchange management strategy for the next operating cycle based on the updated air preheating parameters and waste heat recovery adjustment parameters.

10. A high-efficiency heat exchange management system for heat exchangers under low-temperature operating conditions, characterized in that, include: Processor and memory; The memory stores programs or instructions that can run on the processor, which, when executed by the processor, implement the steps of the high-efficiency heat exchange management method for heat exchangers under low-temperature conditions as described in any one of claims 1 to 9.

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