Evaporator heat transfer information management method and system

Abstract

The present invention relates to the field of evaporator heat transfer technology, and in particular to an evaporator heat transfer information management method and system, the method comprising: obtaining the tube bundle design information of the horizontal heat exchange tube, monitoring the horizontal tube falling film evaporator, collecting and obtaining the thermal interaction performance parameters, and calculating the phase change heat transfer efficiency according to the thermal interaction performance parameters, constructing an evaporation heat transfer database for storing and managing the tube bundle design information and the thermal interaction performance parameters, and corresponding to the phase change heat transfer efficiency, extracting the influencing factors of the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishing a strong and weak effect association between each influencing factor and the phase change heat transfer efficiency, establishing a heat transfer coefficient analysis model based on the evaporation heat transfer database, inputting the tube bundle design information and the thermal interaction performance parameters into the heat transfer coefficient analysis model, and outputting the heat transfer coefficient of the horizontal heat exchange tube. Through the present invention, the influence of different operating parameters on the horizontal tube falling film evaporation heat transfer is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of evaporator heat transfer, and in particular to an evaporator heat transfer information management method and system. Background Art

[0002] As one of the key technologies to solve the global shortage of fresh water resources, seawater desalination technology has developed a variety of methods, including evaporation, membrane, electrodialysis and freezing. Among them, low-temperature multi-effect evaporation technology is widely used because it can effectively use low-quality steam for seawater desalination. Especially in China's seawater desalination industry, reverse osmosis and low-temperature multi-effect evaporation technology have become the mainstream. Among various types of evaporator equipment, horizontal tube falling film evaporator is the most widely used in actual low-temperature multi-effect evaporation desalination projects due to its compact structure, small footprint and high heat transfer coefficient.

[0003] The heat transfer coefficient of the horizontal tube falling film evaporator is affected by many factors. The horizontal heat exchange tube is the core component of the horizontal tube falling film evaporator. The heat transfer performance of the horizontal tube directly affects the operating state and working performance of the evaporation system. Under the same evaporation capacity and heat transfer requirements, when the heat transfer coefficient increases, the required heat exchange area will decrease, which can reduce the equipment investment cost and space volume of the entire evaporation system, and has many benefits. The operating parameters have a significant impact on the heat transfer of the horizontal tube falling film evaporation, and are closely related to the overall performance of the low-temperature multi-effect evaporation system. It is necessary to conduct in-depth research on this and analyze the influence trend of various parameters on the heat transfer of the horizontal falling film evaporation, so as to provide a basis for the design and operation of the horizontal tube falling film evaporation system.

[0004] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present disclosure, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art known to those skilled in the art. Summary of the invention

[0005] The present invention provides an evaporator heat transfer information management method and system, which can effectively solve the problems in the background technology.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] An evaporator heat transfer information management method and system, the method comprising:

[0008] Acquire tube bundle design information of the horizontal heat exchange tube, wherein the tube bundle design information includes tube body physical information, tube body material information, and tube bundle arrangement information;

[0009] Monitoring the horizontal tube falling film evaporator, collecting and obtaining thermal interaction performance parameters, and calculating the phase change heat transfer efficiency based on the thermal interaction performance parameters;

[0010] Constructing an evaporation heat transfer database for storing and managing the tube bundle design information and thermal interaction performance parameters corresponding to the phase change heat transfer efficiency;

[0011] Extracting the influencing factors on the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishing strong and weak effect associations between each of the influencing factors and the phase change heat transfer efficiency;

[0012] A heat transfer coefficient analysis model is established based on the evaporation heat transfer database, the tube bundle design information and thermal interaction performance parameters are input into the heat transfer coefficient analysis model, and the heat transfer coefficient of the horizontal heat exchange tube is output.

[0013] Furthermore, an evaporation heat transfer database is constructed to store and manage the tube bundle design information and thermal interaction performance parameters, and corresponding to the phase change heat transfer efficiency, including:

[0014] The tube bundle design information and the thermal interaction performance parameters are collected, and the phase change heat transfer efficiency corresponding to the tube bundle design information and the thermal interaction performance parameters is obtained, wherein the phase change heat transfer efficiency includes an evaporation heat transfer coefficient and a condensation heat transfer coefficient;

[0015] Divide the tube bundle design information and thermal interaction performance parameters into a plurality of independent variable data blocks according to sub-data items, integrate the phase change heat transfer efficiency into a dependent variable data block, and each of the independent variable data blocks corresponds to a sub-data item one by one;

[0016] Each of the independent variable data blocks is chained to the dependent variable data blocks respectively, and integrated into a data chain, each of the data chains corresponds to a single evaporation;

[0017] The historical data chain is collected and integrated into the evaporation heat transfer database.

[0018] Furthermore, a unique identifier is assigned to each component data of the evaporation heat transfer database, including:

[0019] Identify each of the independent variable data blocks and dependent variable data blocks, wherein an independent variable block key is assigned to each of the independent variable data blocks, and a dependent variable block key is assigned to each of the dependent variable data blocks;

[0020] Integrate the independent variable block key and the dependent variable block key in the data chain, and assign a chain key to each of the data chains, wherein the independent variable block key and the dependent variable block key serve as foreign keys of the chain key respectively;

[0021] The evaporation heat transfer database indexes and calls the tube bundle design information, thermal interaction performance parameters and the phase change heat transfer efficiency through the independent variable block key, the dependent variable block key and the chain key.

[0022] Furthermore, the influencing factors on the phase change heat transfer efficiency in the phase change process are extracted according to the evaporation heat transfer database, and the strong and weak interaction associations are established between each of the influencing factors and the phase change heat transfer efficiency, including:

[0023] Sorting the phase change heat transfer efficiencies in the evaporation heat transfer database, and indexing sub-data items in a plurality of tube bundle design information and thermal interaction performance parameters corresponding to the phase change heat transfer efficiencies according to the sorting results;

[0024] Establishing an influencing factor table for each sub-data item of the same item, and arranging the sub-data items in the same order according to the sorting result in the influencing factor table;

[0025] Deep learning is performed on the several influencing factor tables arranged in the same order, the influencing factor tables corresponding to the influence of the sub-data items on the phase change heat transfer efficiency are screened, and strong and weak effect associations are established according to the influence size.

[0026] Further, the influencing factor table corresponding to the influence of the sub-data item on the phase change heat transfer efficiency is screened, and a strong and weak effect association is established according to the influence size, including:

[0027] Through deep learning, each sub-data item is evaluated on the phase change heat transfer efficiency, and the influencing factor table corresponding to the influencing factor is obtained by screening as a strong and weak correlation analysis table;

[0028] Select at least one of the strong and weak association analysis tables, and at most n-1 of the strong and weak association analysis tables for permutation and combination, and take any sub-data item as the target, traverse the results of the permutation and combination, and filter the strong and weak association analysis tables containing the target item to form a number of single factor influence sets, and the single factor influence sets correspond one to one to the sub-data items obtained by the screening;

[0029] A deep learning analysis is performed on several of the single factor influence sets to obtain a mapping relationship between the screened sub-data items and the phase change heat transfer efficiency, and a strong and weak effect association is established based on the mapping relationship.

[0030] Furthermore, a heat transfer coefficient analysis model is established based on the evaporation heat transfer database, the tube bundle design information and thermal interaction performance parameters are input into the heat transfer coefficient analysis model, and the heat transfer coefficient of the horizontal heat exchange tube is output, including:

[0031] Determine the sub-data items of the input tube bundle design information and thermal interaction performance parameters, search the evaporative heat transfer database and match the sub-data items that have an impact, and index the corresponding single factor impact set;

[0032] Obtaining the strong and weak effect association established by deep learning analysis for the single factor influence set obtained by indexing;

[0033] The basic heat transfer coefficient is obtained by matching the evaporation heat transfer database, the strong and weak action correlation is converted into a correction coefficient, the basic heat transfer coefficient is corrected according to the correction coefficient, and the heat transfer coefficient of the horizontal heat exchange tube is output.

[0034] Furthermore, digital modeling of the horizontal heat exchange tube is performed according to the tube bundle design information, including:

[0035] Arranging the input tube bundle design information in sequence according to different spatial positions of the horizontal heat exchange tubes and in spatial order to generate a tube bundle spatial sequence;

[0036] Splitting the input tube bundle design information into a plurality of performance parameter units according to different attributes of the sub-data items, each of the performance parameter units corresponding to a sub-data item in the tube bundle design information;

[0037] Constructing a numbering network matrix, including a basic numbering matrix block and an attribute extension matrix block, and digitally managing the bundle space sequence and the performance parameter unit respectively;

[0038] The tube bundle spatial sequence and performance parameter units are input into the numbering network matrix to generate a heat transfer information network matrix, and digital modeling is performed on the horizontal heat exchange tubes.

[0039] Furthermore, a training set and a validation set are constructed to train and validate the calculated phase change heat transfer efficiency, including:

[0040] Filtering data information matching the tube bundle arrangement information and the thermal interaction performance parameters according to the evaporation heat transfer database;

[0041] Construct n training sets with the matched data information, and perform n verifications, selecting one of the training sets as a verification set for each verification, and obtaining verification results of the n verifications respectively;

[0042] The n verification results are averaged to obtain a comprehensive verification result, and the calculated phase change heat transfer efficiency is corrected according to the comprehensive verification result.

[0043] An evaporator heat transfer information management system, the system comprising:

[0044] A tube bundle information acquisition module is used to acquire tube bundle design information of horizontal heat exchange tubes, wherein the tube bundle design information includes tube body physical information, tube body material information and tube bundle arrangement information;

[0045] The heat transfer efficiency calculation module monitors the horizontal tube falling film evaporator, collects and obtains the thermal interaction performance parameters, and calculates the phase change heat transfer efficiency according to the thermal interaction performance parameters;

[0046] An evaporation heat transfer data module is used to construct an evaporation heat transfer database for storing and managing the tube bundle design information and thermal interaction performance parameters, and corresponding to the phase change heat transfer efficiency;

[0047] An action association establishing module extracts the influencing factors of the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishes strong and weak action associations between each of the influencing factors and the phase change heat transfer efficiency;

[0048] The heat transfer coefficient output module establishes a heat transfer coefficient analysis model based on the evaporation heat transfer database, inputs the tube bundle design information and thermal interaction performance parameters into the heat transfer coefficient analysis model, and outputs the heat transfer coefficient of the horizontal heat exchange tube.

[0049] Furthermore, the evaporation heat transfer data module includes:

[0050] The block integration unit divides the tube bundle design information and thermal interaction performance parameters into several independent data blocks according to sub-data items, integrates the phase change heat transfer efficiency into the dependent data block, and each independent data block corresponds to a sub-data item one by one;

[0051] The chain integration unit links each independent variable data block to the dependent variable data block in a chain manner and integrates them into a data chain, where each data chain corresponds to a single evaporation;

[0052] A key chain allocation unit allocates an independent variable block key to each independent variable data block, allocates a dependent variable block key to each dependent variable data block, integrates the independent variable block key and the dependent variable block key in the data chain, and allocates a chain key to each data chain, wherein the independent variable block key and the dependent variable block key are respectively used as foreign keys of the chain key;

[0053] Index calling unit, the evaporation heat transfer database indexes and calls the tube bundle design information, thermal interaction performance parameters and phase change heat transfer efficiency through independent variable block keys, dependent variable block keys and chain keys.

[0054] The technical solution of the present invention can achieve the following technical effects:

[0055] The influence of different operating parameters on the heat transfer of horizontal tube falling film evaporation is effectively solved, and the influence trend of various parameters on the heat transfer of horizontal falling film evaporation is analyzed, providing a basis for the design and operation of the horizontal tube falling film evaporation system.

[0056] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 It is a flow chart of the evaporator heat transfer information management method and system;

[0059] Figure 2 Establish a process diagram for the evaporation heat transfer database;

[0060] Figure 3 Establish a flow chart for the strong and weak interaction association;

[0061] Figure 4 It is a schematic diagram of the heat transfer coefficient flow of the output horizontal heat exchange tube;

[0062] Figure 5 Schematic diagram of the digital modeling structure of horizontal heat exchange tubes. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0064] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0065] Embodiment 1

[0066] like Figure 1 As shown, the present application provides an evaporator heat transfer information management method, the method comprising:

[0067] S10: Obtaining tube bundle design information of the horizontal heat exchange tube, where the tube bundle design information includes tube body physical information, tube body material information, and tube bundle arrangement information;

[0068] S20: monitoring the horizontal tube falling film evaporator, collecting and obtaining thermal interaction performance parameters, and calculating the phase change heat transfer efficiency according to the thermal interaction performance parameters;

[0069] S30: Build an evaporation heat transfer database to store and manage tube bundle design information and thermal interaction performance parameters, and the corresponding phase change heat transfer efficiency;

[0070] S40: extracting the influencing factors on the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishing strong and weak effect associations between each influencing factor and the phase change heat transfer efficiency;

[0071] S50: A heat transfer coefficient analysis model is established based on the evaporation heat transfer database, the tube bundle design information and thermal interaction performance parameters are input into the heat transfer coefficient analysis model, and the heat transfer coefficient of the horizontal heat exchange tube is output.

[0072] Specifically, physical information such as the diameter, length, and wall thickness of the horizontal heat exchange tube, material information such as the type of tube and its physical properties, and tube bundle arrangement information such as the tube bundle arrangement method and tube spacing are collected. Then, by installing monitoring equipment such as temperature sensors, pressure sensors, and flow meters, the thermal interaction performance parameters such as pressure, temperature, and flow on the steam side are recorded regularly or continuously. The obtained thermal interaction performance parameters are then used to calculate the phase change heat transfer efficiency. The tube bundle design information and thermal interaction performance parameters are integrated to establish an evaporation heat transfer database. The database structure is designed to achieve effective data storage, and the tube bundle design information, thermal interaction performance parameters, and phase change heat transfer efficiency can be made to correspond to each other. The key factors affecting the phase change heat transfer efficiency are analyzed through the data in the database, and the strong and weak effect associations are established according to the size of the influence. The applicable theoretical model is selected according to the principle of heat transfer, and the heat transfer theoretical model is used to evaluate the phase change heat transfer efficiency. The evaporation heat transfer coefficient and the condensation heat transfer coefficient are calculated, and finally the heat transfer coefficient of the horizontal heat exchange tube is obtained.

[0073] Through the technical solution of the present invention, the influence of different operating parameters on the heat transfer of horizontal tube falling film evaporation is effectively solved, the influence trend of each parameter on the heat transfer of horizontal falling film evaporation is analyzed, and a basis is provided for the design and operation of the horizontal tube falling film evaporation system.

[0074] Furthermore, an evaporation heat transfer database is constructed to store and manage tube bundle design information and thermal interaction performance parameters, and the corresponding phase change heat transfer efficiency, including:

[0075] Collect the tube bundle design information and thermal interaction performance parameters, and obtain the phase change heat transfer efficiency corresponding to the tube bundle design information and the thermal interaction performance parameters, wherein the phase change heat transfer efficiency includes the evaporation heat transfer coefficient and the condensation heat transfer coefficient;

[0076] The tube bundle design information and thermal interaction performance parameters are divided into several independent variable data blocks according to sub-data items, and the phase change heat transfer efficiency is integrated into the dependent variable data block, and each independent variable data block corresponds to a sub-data item one by one;

[0077] Each independent variable data block is chained to the dependent variable data block and integrated into a data chain, each data chain corresponds to a single evaporation;

[0078] The historical data chain is collected and integrated into the evaporation heat transfer database. As a preferred embodiment of the above, during the operation of the evaporator, the tube bundle design information and thermal interaction performance parameters of the horizontal heat exchange tubes can be obtained in real time through sensors and data acquisition equipment. The tube bundle design information may include, for example, tube diameter, tube length, tube material, fluid temperature in the tube, flow rate, arrangement spacing, etc. The thermal interaction performance parameters may include, for example, evaporation temperature, heat transfer temperature difference, etc. The collected data can be automatically transmitted to the evaporation heat transfer database through the data transmission module for storage and management. The collected thermal interaction performance parameters are used to calculate the phase change heat transfer efficiency and phase change heat transfer efficiency in each operation cycle. It is determined by analyzing the ratio between the actual heat used in the evaporation and condensation processes and the total input heat. The system automatically records the evaporation heat transfer coefficient and the condensation heat transfer coefficient in each operation cycle, and associates these data with the phase change heat transfer efficiency. At the same time, according to the different attributes of the sub-data items, the tube bundle design information and thermal interaction performance parameters are split into several independent data blocks. Each independent data block contains data of a specific attribute, such as tube diameter, tube material, heat transfer coefficient, etc., and the phase change heat transfer efficiency is integrated into the dependent data block as a dependent variable. Each dependent data block contains the phase change heat transfer efficiency. The specific value of the rate is obtained and associated with each attribute of the independent data block. In the database, the system links each independent data block to the dependent data block. This chain connection ensures that the correlation between each independent data item and the corresponding phase change heat transfer efficiency is retained. During the construction of the data chain, the system integrates the associated independent data blocks and dependent data blocks into a complete data chain based on the data collection and processing results of a single evaporation process. Each data chain represents a complete evaporation operation cycle, including all key parameters and efficiency indicators within the cycle. The historical data chain collected by the system will be integrated into the evaporation heat transfer database and coexist with the current data chain for subsequent analysis and comparison. All data chains, including current and historical data chains, are stored in the evaporation heat transfer database and can be sorted and indexed in chronological order or other specified order. Users can call any data chain through the system interface for data analysis, performance evaluation or trend prediction. The construction and analysis of the data chain enables operators to clearly understand the impact of various factors on the heat transfer efficiency, thereby effectively optimizing and adjusting, and improving the energy efficiency and stability of the overall system.

[0079] Further, if Figure 2 As shown in the figure, each component data of the evaporation heat transfer database is assigned a unique identifier, including:

[0080] Identify each independent variable data block and dependent variable data block, wherein each independent variable data block is assigned an independent variable block key, and each dependent variable data block is assigned a dependent variable block key;

[0081] Integrate the independent block key and dependent block key in the data chain, and assign a chain key to each data chain. The independent block key and dependent block key serve as the foreign keys of the chain key respectively.

[0082] The evaporation heat transfer database indexes and calls the tube bundle design information, thermal interaction performance parameters and phase change heat transfer efficiency through independent variable block keys, dependent variable block keys and chain keys.

[0083] As a preferred embodiment of the above, a unique independent variable block key is assigned to each independent variable data block to distinguish different independent variable data blocks. Similarly, a unique dependent variable block key is assigned to each dependent variable data block to distinguish different dependent variable data blocks. In order to realize the concept of data chain, it is necessary to establish an independent variable block table, a dependent variable block table, and a data chain table. In the data chain table, each record will contain a chain key, as well as corresponding independent variable block keys and dependent variable block keys. The independent variable block table and the dependent variable block table are respectively used as foreign keys of the data chain table. The corresponding independent variable block and dependent variable block can be queried through the chain key. When constructing the data chain, a unique independent variable block key is assigned to each data chain. A unique chain key, which can be a self-incrementing ID or a unique ID generated based on a timestamp, ensures the uniqueness of each data chain. In the data chain, the independent block key and the dependent block key are associated as foreign keys of the chain key to ensure the consistency and integrity within the data chain. In the evaporation heat transfer database, an index structure based on the independent block key, dependent block key and chain key is established, and an API interface is provided for external systems to query specific independent block keys or dependent block keys, and return related data chain information to facilitate fast search and call of data. The specified independent block key or dependent block key is quickly located through the index to obtain the complete data chain information.

[0084] Further, if Figure 3 As shown in the figure, the factors affecting the phase change heat transfer efficiency in the phase change process are extracted according to the evaporation heat transfer database, and the strong and weak effects of each factor on the phase change heat transfer efficiency are established, including:

[0085] The phase change heat transfer efficiency in the evaporation heat transfer database is sorted, and sub-data items in several tube bundle design information and thermal interaction performance parameters corresponding to the phase change heat transfer efficiency are indexed according to the sorting result;

[0086] Establish an influencing factor table for each sub-data item of the same item, and arrange the sub-data items in the same order according to the sorting result in the influencing factor table;

[0087] Deep learning is performed on several influencing factor tables arranged in the same order to screen the influencing factor tables corresponding to the influence of sub-data items on phase change heat transfer efficiency, and establish strong and weak effect associations based on the size of the influence.

[0088] As a preferred embodiment of the above embodiment, the phase change heat transfer efficiency data in the evaporation heat transfer database are sorted, and descending or ascending order can be used. According to the sorting result, the sub-data items in the tube bundle design information and thermal interaction performance parameters corresponding to the phase change heat transfer efficiency are indexed. For each sub-data item, a corresponding influencing factor table is established, and the sub-data items are arranged in the same order according to the sorting result in the table. The influencing factor table contains all relevant sub-data items and their correlation information with the phase change heat transfer efficiency. Machine learning algorithms and deep learning technologies can be used to train several influencing factor tables after being arranged in the same order. Neural networks, support vector machines or other appropriate algorithms can also be used to screen out sub-data items that have a significant impact on the phase change heat transfer efficiency through the trained model, and establish a strong and weak effect association according to their impact on the phase change heat transfer efficiency. The impact of different sub-data items on the phase change heat transfer efficiency can be quantified by using correlation coefficients, importance scores, etc.

[0089] Furthermore, the influencing factor table corresponding to the influence of the sub-data items on the phase change heat transfer efficiency is screened, and the strong and weak effect associations are established according to the influence size, including:

[0090] Through deep learning, each sub-data item is evaluated on the phase change heat transfer efficiency, and the corresponding influencing factor table is screened to obtain the strong and weak correlation analysis table;

[0091] Select at least one strong and weak association analysis table, and at most n-1 strong and weak association analysis tables for permutation and combination, and take any sub-data item as the target, traverse the results of the permutation and combination, and filter the strong and weak association analysis tables containing the target item to form several single factor influence sets, and the single factor influence sets correspond one to one with the sub-data items obtained by filtering;

[0092] A deep learning analysis is performed on several single-factor influence sets to obtain the mapping relationship between the screened sub-data items and the phase change heat transfer efficiency, and the strong and weak effect associations are established based on the mapping relationship.

[0093] As a preferred embodiment of the above, based on the constructed evaporation heat transfer database and its influencing factor table, a deep learning algorithm is used to train a model for evaluating the influence of each sub-data item on the phase change heat transfer efficiency. According to the evaluation results, the influencing factor table corresponding to the sub-data item that affects the phase change heat transfer efficiency is screened out to form a strong and weak correlation analysis table. At least one and a maximum of n-1 (where n is the total number of strong and weak correlation analysis tables) are selected from the screened strong and weak correlation analysis tables to perform permutations and combinations. With any sub-data item as the target, the results of the permutations and combinations are traversed to screen out all strong and weak correlation analysis tables containing the target item to form several single factor influence sets, ensuring that there is a one-to-one correspondence between each single factor influence set and the screened sub-data item. A deep learning analysis is performed on the constructed several single factor influence sets to obtain a mapping relationship between the sub-data item and the phase change heat transfer efficiency. According to the obtained mapping relationship, a strong and weak effect association of the sub-data item on the phase change heat transfer efficiency is established.

[0094] Further, if Figure 4 As shown in the figure, a heat transfer coefficient analysis model is established based on the evaporation heat transfer database, the tube bundle design information and thermal interaction performance parameters are input into the heat transfer coefficient analysis model, and the heat transfer coefficient of the horizontal heat exchange tube is output, including:

[0095] Determine the sub-data items of the input tube bundle design information and thermal interaction performance parameters, search the evaporative heat transfer database and match the sub-data items that have an impact, and index the corresponding single factor impact set;

[0096] Obtain the strong and weak interaction associations established by deep learning analysis for the set of single-factor influences obtained by the index;

[0097] The basic heat transfer coefficient is obtained by matching the evaporation heat transfer database, the strong and weak action correlation is converted into a correction coefficient, the basic heat transfer coefficient is corrected according to the correction coefficient, and the heat transfer coefficient of the horizontal heat exchange tube is output.

[0098] As a preferred embodiment of the above, first, the specific sub-data items of the tube bundle design information and thermal interaction performance parameters that need to be input into the heat transfer coefficient analysis model are clarified, and data matching the input sub-data items are retrieved in the evaporative heat transfer database. The independent variable data block corresponding to the input sub-data item is located through the database indexing function. For each sub-data item, the corresponding single factor influence set is indexed, wherein the single factor influence set refers to a set of influence factor tables associated with a specific sub-data item, and the strong and weak interaction associations between each sub-data item and the phase change heat transfer efficiency previously established through deep learning analysis are obtained. These associations reflect the degree of influence of each sub-data item on the phase change heat transfer efficiency. The associations can be quantitative indicators such as correlation coefficients and importance scores obtained through deep learning model training. The basic heat transfer coefficient is obtained through evaporative heat transfer database matching, and the strong and weak interaction associations are converted into correction coefficients. The basic heat transfer coefficient is corrected according to the correction coefficients, and the heat transfer coefficient of the horizontal heat exchange tube is finally output.

[0099] Further, if Figure 5 As shown, the horizontal heat exchange tubes are digitally modeled based on the tube bundle design information, including:

[0100] Arrange the input tube bundle design information in accordance with different spatial positions of the horizontal heat exchange tubes and in spatial order to generate a tube bundle spatial sequence;

[0101] Splitting the input tube bundle design information into a number of performance parameter units according to different attributes of the sub-data items, each performance parameter unit corresponding to a sub-data item in the tube bundle design information;

[0102] Construct a numbering network matrix, including a basic numbering matrix block and an attribute extension matrix block, and digitally manage the bundle space sequence and performance parameter unit respectively;

[0103] The spatial sequence of the tube bundle and the performance parameter units are input into the numbered network matrix to generate the heat transfer information network matrix and digitally model the horizontal heat exchange tubes.

[0104] As a preferred embodiment of the above embodiment, a bundle space sequence is generated according to information such as the bundle arrangement mode and the tube spacing in the bundle design information, that is, the bundle design information is input according to the spatial position and sequence of the horizontal heat exchange tubes, and the bundle design information is split into a number of performance parameter units according to different attributes of the sub-data items. Each performance parameter unit corresponds to a sub-data item in the bundle design information, and a numbering network matrix is ​​constructed, which includes a basic numbering matrix block and an attribute extension matrix block. The basic numbering matrix block represents basic spatial position information and is used to store the position information of the bundle, for example, it is composed of bundle position numbers arranged in sequence. The attribute extension matrix block represents specific attributes in the performance parameter unit and is used to store various performance parameter information of the bundle, such as heat exchange performance parameters, etc. The generated bundle space sequence and performance parameter unit are input into the numbering network matrix, the bundle space sequence is input into the basic numbering matrix block, the performance parameter unit is input into the attribute extension matrix block, the basic numbering matrix block and the attribute extension matrix block are integrated to generate a heat transfer information network matrix, and the digital modeling of the horizontal heat exchange tubes is completed.

[0105] Furthermore, a training set and a validation set are constructed to train and validate the calculated phase change heat transfer efficiency, including:

[0106] Filter data information that matches the tube bundle arrangement information and thermal interaction performance parameters according to the evaporation heat transfer database;

[0107] Construct n training sets with the matching data information, and perform n verifications. For each verification, select one of the training sets as the verification set, and obtain the verification results of the n verifications respectively.

[0108] The n verification results are averaged to obtain a comprehensive verification result, and the calculated phase change heat transfer efficiency is corrected according to the comprehensive verification result.

[0109] As a preferred embodiment of the above embodiment, data information matching the tube bundle arrangement information and the thermal interaction performance parameters is screened out from the evaporation heat transfer database, the selected data is associated with the tube bundle design information and the thermal interaction performance parameters, and accurate training and verification are performed. The screened data is used to construct n training sets, where n depends on the number of screened data. Each training set contains data points related to the tube bundle design information and the thermal interaction performance parameters, which can be used to train the model to predict the phase change heat transfer efficiency. For each training set, one of them is selected as a verification set, that is, if n training sets are constructed, n verifications will be performed, each verification using a different training set as the verification set. For each verification, the selected verification set is used to test the performance of the model, the error between the predicted value and the actual value is calculated, and the result of each verification is recorded. The average of all n verification results is calculated to obtain a comprehensive verification result. Finally, the calculated phase change heat transfer efficiency is corrected according to the comprehensive verification result.

[0110] Embodiment 2

[0111] Based on the same inventive concept as the evaporator heat transfer information management method in the aforementioned embodiment, the present invention further provides an evaporator heat transfer information management system, the system comprising:

[0112] The tube bundle information acquisition module acquires the tube bundle design information of the horizontal heat exchange tube. The tube bundle design information includes the tube body physical information, tube body material information and tube bundle arrangement information.

[0113] The heat transfer efficiency calculation module monitors the horizontal tube falling film evaporator, collects and obtains the thermal interaction performance parameters, and calculates the phase change heat transfer efficiency based on the thermal interaction performance parameters;

[0114] Evaporation heat transfer data module, which builds an evaporation heat transfer database to store and manage tube bundle design information and thermal interaction performance parameters, and the corresponding phase change heat transfer efficiency;

[0115] The action correlation establishment module extracts the influencing factors of the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishes strong and weak action correlations between each influencing factor and the phase change heat transfer efficiency;

[0116] The heat transfer coefficient output module establishes a heat transfer coefficient analysis model based on the evaporative heat transfer database, inputs the tube bundle design information and thermal interaction performance parameters into the heat transfer coefficient analysis model, and outputs the heat transfer coefficient of the horizontal heat exchange tube.

[0117] The above-mentioned adjustment system in the present invention can effectively realize the evaporator heat transfer information management method, and the technical effects that can be achieved are as described in the above-mentioned embodiments, which will not be repeated here.

[0118] Specifically, the evaporation heat transfer data module includes:

[0119] The block integration unit divides the tube bundle design information and thermal interaction performance parameters into several independent data blocks according to sub-data items, integrates the phase change heat transfer efficiency into the dependent data block, and each independent data block corresponds to a sub-data item one by one;

[0120] The chain integration unit links each independent variable data block to the dependent variable data block in a chain manner and integrates them into a data chain, where each data chain corresponds to a single evaporation;

[0121] A key chain allocation unit allocates an independent variable block key to each independent variable data block, allocates a dependent variable block key to each dependent variable data block, integrates the independent variable block key and the dependent variable block key in the data chain, and allocates a chain key to each data chain, wherein the independent variable block key and the dependent variable block key are respectively used as foreign keys of the chain key;

[0122] Index calling unit, the evaporation heat transfer database indexes and calls the tube bundle design information, thermal interaction performance parameters and phase change heat transfer efficiency through independent variable block keys, dependent variable block keys and chain keys.

[0123] Similarly, the above-mentioned optimization schemes for the system can also respectively achieve the optimization effects corresponding to the method in Example 1, which will not be repeated here.

[0124] Although the present application has been described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present application as defined therein, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. An evaporator heat transfer information management method, characterized in that: The method comprises: Acquire tube bundle design information of the horizontal heat exchange tube, wherein the tube bundle design information includes tube body physical information, tube body material information, and tube bundle arrangement information; Monitoring the horizontal tube falling film evaporator, collecting and obtaining thermal interaction performance parameters, and calculating the phase change heat transfer efficiency based on the thermal interaction performance parameters; Constructing an evaporation heat transfer database for storing and managing the tube bundle design information and thermal interaction performance parameters corresponding to the phase change heat transfer efficiency; Extracting the influencing factors on the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishing strong and weak effect associations between each of the influencing factors and the phase change heat transfer efficiency; A heat transfer coefficient analysis model is established based on the evaporation heat transfer database, the tube bundle design information and thermal interaction performance parameters are input into the heat transfer coefficient analysis model, and the heat transfer coefficient of the horizontal heat exchange tube is output.

2. The evaporator heat transfer information management method according to claim 1, characterized in that: Constructing an evaporation heat transfer database for storing and managing the tube bundle design information and thermal interaction performance parameters, and corresponding to the phase change heat transfer efficiency, including: The tube bundle design information and the thermal interaction performance parameters are collected, and the phase change heat transfer efficiency corresponding to the tube bundle design information and the thermal interaction performance parameters is obtained, wherein the phase change heat transfer efficiency includes an evaporation heat transfer coefficient and a condensation heat transfer coefficient; Dividing the tube bundle design information and thermal interaction performance parameters into a plurality of independent variable data blocks according to sub-data items, integrating the phase change heat transfer efficiency into a dependent variable data block, and each of the independent variable data blocks corresponds to a sub-data item one by one; Each of the independent variable data blocks is chained to the dependent variable data blocks respectively, and integrated into a data chain, each of the data chains corresponds to a single evaporation; The historical data chain is collected and integrated into the evaporation heat transfer database.

3. The evaporator heat transfer information management method according to claim 2, characterized in that: Allocating a unique identifier to each component data of the evaporation heat transfer database includes: Identify each of the independent variable data blocks and dependent variable data blocks, wherein an independent variable block key is assigned to each of the independent variable data blocks, and a dependent variable block key is assigned to each of the dependent variable data blocks; Integrate the independent variable block key and the dependent variable block key in the data chain, and assign a chain key to each of the data chains, wherein the independent variable block key and the dependent variable block key serve as foreign keys of the chain key respectively; The evaporation heat transfer database indexes and calls the tube bundle design information, thermal interaction performance parameters and the phase change heat transfer efficiency through the independent variable block key, the dependent variable block key and the chain key.

4. The evaporator heat transfer information management method according to claim 1, characterized in that: Extracting the influencing factors of the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishing strong and weak effect associations between each of the influencing factors and the phase change heat transfer efficiency, including: Sorting the phase change heat transfer efficiencies in the evaporation heat transfer database, and indexing sub-data items in a plurality of tube bundle design information and thermal interaction performance parameters corresponding to the phase change heat transfer efficiencies according to the sorting results; Establishing an influencing factor table for each sub-data item of the same item, and arranging the sub-data items in the same order in the influencing factor table according to the sorting result; Deep learning is performed on the several influencing factor tables arranged in the same order, the influencing factor tables corresponding to the influence of the sub-data items on the phase change heat transfer efficiency are screened, and strong and weak effect associations are established according to the influence size.

5. The evaporator heat transfer information management method according to claim 4, characterized in that: The influencing factor table corresponding to the influence of the sub-data item on the phase change heat transfer efficiency is screened, and a strong and weak effect association is established according to the influence size, including: Through deep learning, each sub-data item is evaluated on the phase change heat transfer efficiency, and the influencing factor table corresponding to the influencing factor is obtained by screening as a strong and weak correlation analysis table; Select at least one of the strong and weak association analysis tables, and at most n-1 of the strong and weak association analysis tables for permutation and combination, and take any sub-data item as the target, traverse the results of the permutation and combination, and filter the strong and weak association analysis tables containing the target item to form a number of single factor influence sets, and the single factor influence sets correspond one to one to the sub-data items obtained by the screening; A deep learning analysis is performed on several of the single factor influence sets to obtain a mapping relationship between the screened sub-data items and the phase change heat transfer efficiency, and a strong and weak effect association is established based on the mapping relationship.

6. The evaporator heat transfer information management method according to claim 5, characterized in that: A heat transfer coefficient analysis model is established based on the evaporation heat transfer database, the tube bundle design information and the thermal interaction performance parameters are input into the heat transfer coefficient analysis model, and the heat transfer coefficient of the horizontal heat exchange tube is output, including: Determine the sub-data items of the input tube bundle design information and thermal interaction performance parameters, search the evaporative heat transfer database and match the sub-data items that have an impact, and index the corresponding single factor impact set; Obtaining the strong and weak effect association established by deep learning analysis for the single factor influence set obtained by indexing; The basic heat transfer coefficient is obtained by matching the evaporation heat transfer database, the strong and weak action correlation is converted into a correction coefficient, the basic heat transfer coefficient is corrected according to the correction coefficient, and the heat transfer coefficient of the horizontal heat exchange tube is output.

7. The evaporator heat transfer information management method according to claim 6, characterized in that: Digital modeling of the horizontal heat exchange tube is performed according to the tube bundle design information, including: Arranging the input tube bundle design information in sequence according to different spatial positions of the horizontal heat exchange tubes and in spatial order to generate a tube bundle spatial sequence; Splitting the input tube bundle design information into a plurality of performance parameter units according to different attributes of the sub-data items, each of the performance parameter units corresponding to a sub-data item in the tube bundle design information; Constructing a numbering network matrix, including a basic numbering matrix block and an attribute extension matrix block, and digitally managing the bundle space sequence and the performance parameter unit respectively; The tube bundle spatial sequence and performance parameter units are input into the numbering network matrix to generate a heat transfer information network matrix, and digital modeling is performed on the horizontal heat exchange tubes.

8. The evaporator heat transfer information management method according to claim 1, characterized in that: Construct training sets and validation sets to train and validate the calculated phase change heat transfer efficiency, including: Filtering data information matching the tube bundle arrangement information and the thermal interaction performance parameters according to the evaporation heat transfer database; Construct n training sets with the matched data information, and perform n verifications, selecting one of the training sets as a verification set for each verification, and obtaining verification results of the n verifications respectively; The n verification results are averaged to obtain a comprehensive verification result, and the calculated phase change heat transfer efficiency is corrected according to the comprehensive verification result.

9. An evaporator heat transfer information management system, characterized in that: The system comprises: A tube bundle information acquisition module is used to acquire tube bundle design information of horizontal heat exchange tubes, wherein the tube bundle design information includes tube body physical information, tube body material information and tube bundle arrangement information; The heat transfer efficiency calculation module monitors the horizontal tube falling film evaporator, collects and obtains the thermal interaction performance parameters, and calculates the phase change heat transfer efficiency according to the thermal interaction performance parameters; An evaporation heat transfer data module is used to construct an evaporation heat transfer database for storing and managing the tube bundle design information and thermal interaction performance parameters, and corresponding to the phase change heat transfer efficiency; An action association establishing module extracts the influencing factors of the phase change heat transfer efficiency in the phase change process according to the evaporation heat transfer database, and establishes strong and weak action associations between each of the influencing factors and the phase change heat transfer efficiency; The heat transfer coefficient output module establishes a heat transfer coefficient analysis model based on the evaporation heat transfer database, inputs the tube bundle design information and thermal interaction performance parameters into the heat transfer coefficient analysis model, and outputs the heat transfer coefficient of the horizontal heat exchange tube.

10. The evaporator heat transfer information management system according to claim 9, characterized in that: The evaporation heat transfer data module includes: The block integration unit divides the tube bundle design information and thermal interaction performance parameters into several independent data blocks according to sub-data items, integrates the phase change heat transfer efficiency into the dependent data block, and each independent data block corresponds to a sub-data item one by one; The chain integration unit links each independent variable data block to the dependent variable data block in a chain manner and integrates them into a data chain, where each data chain corresponds to a single evaporation; A key chain allocation unit allocates an independent variable block key to each independent variable data block, allocates a dependent variable block key to each dependent variable data block, integrates the independent variable block key and the dependent variable block key in the data chain, and allocates a chain key to each data chain, wherein the independent variable block key and the dependent variable block key are respectively used as foreign keys of the chain key; Index calling unit, the evaporation heat transfer database indexes and calls the tube bundle design information, thermal interaction performance parameters and phase change heat transfer efficiency through independent variable block keys, dependent variable block keys and chain keys.

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