A method for optimizing process parameters of drying insulation paper for power manufacturing transformer

Abstract

This application provides a method for optimizing the drying process parameters of insulating paper in power transformer manufacturing, belonging to the field of process parameter optimization technology. The method includes: constructing a first initial state vector and a corresponding first drying state vector of the insulating paper at a first historical time; obtaining a first drying process index set at the first historical time; and constructing a drying process model; adjusting the parameters of the first drying process index set; inputting a first decision variable set into the drying process model to obtain a first decision quality set; collecting a first deviation quality set based on the first decision quality set; and performing drying processing through the first decision variable set. This application can solve the technical problem in the prior art where the drying process lacks a dynamic adjustment mechanism, resulting in the inability to flexibly adjust process parameters, thereby achieving real-time adjustment of the drying process and improving drying efficiency.

Description

Technical Field

[0001] This application relates to the field of process parameter optimization technology, and in particular to a method for optimizing the process parameters of drying insulating paper for power transformer manufacturing. Background Technology

[0002] With the continuous improvement of industrial automation, the requirements for precise control of the production process are also increasing. In the drying process, especially in transformer manufacturing, the drying process of insulating paper plays a crucial role in the performance, service life, and safety of the equipment. Proper drying not only affects the electrical performance of the transformer but also its long-term stability and reliability. Therefore, optimizing the drying process has become a key step in improving product quality and production efficiency.

[0003] Currently, existing drying processes largely rely on traditional, empirical control methods, lacking systematic and precise settings for parameters such as temperature, humidity, and time. These methods are based on manually set fixed parameters and cannot be dynamically adjusted in real time according to the drying progress of the insulating paper. During the drying process, the state of the equipment and raw materials changes constantly, making it difficult to guarantee the uniformity and stability of the drying process. Furthermore, due to the lack of an effective feedback mechanism, parameter adjustments in traditional drying processes are usually lagging, leading to significant fluctuations in key parameters such as temperature and humidity, potentially resulting in uneven drying, over-drying, or insufficient drying.

[0004] In summary, the existing technology suffers from a lack of precise feedback control and dynamic adjustment mechanisms in the drying process, which prevents the process parameters from being flexibly adjusted according to the actual drying progress. This further affects the stability and consistency of the drying process, thereby impacting the quality and performance of transformer insulation paper and resulting in low production efficiency. Summary of the Invention

[0005] The purpose of this application is to provide a method for optimizing the drying process parameters of insulating paper for power transformers, in order to solve the technical problem in the prior art where the lack of precise feedback control and dynamic adjustment mechanism in the drying process leads to the inability to flexibly adjust the process parameters according to the actual drying process, which further affects the stability and consistency of the drying process, and consequently affects the quality and performance of transformer insulating paper, resulting in low production efficiency.

[0006] In view of the above problems, this application provides a method for optimizing the drying process parameters of insulating paper in power manufacturing transformers, including: constructing a first initial state vector and a corresponding first drying state vector of the insulating paper at a first historical time, obtaining a first drying process index set at the first historical time, and constructing a drying process model; adjusting the parameters of the first drying process index set, inputting a first decision variable set into the drying process model to obtain a first decision quality set; collecting a first deviation quality set based on the first decision quality set; and performing drying processing based on the first deviation quality set and the first decision variable set.

[0007] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: obtaining a first vector difference between the first drying state vector and the first initial state vector; quantifying the drying quality based on the first vector difference to generate a first drying quality set; obtaining a first drying process parameter set of the first drying process index set; and constructing the drying process model using the first drying process parameter set and the first drying quality set as inputs.

[0008] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: obtaining N initial state vectors and corresponding N drying state vectors at N historical times, and obtaining N drying process parameter sets; based on the first drying quality set, adjusting the drying process model through the N initial state vectors, the N drying state vectors, and the N drying process parameter sets to obtain the adjusted drying process model as the drying process model.

[0009] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: obtaining a first drying process parameter boundary set of the first drying process index set; constructing a first drying process parameter space set based on the first drying process parameter boundary set; adjusting the first drying process parameter set based on the first drying process parameter space set to generate the first decision variable set; and inputting the first decision variable set into the drying process model to obtain the first decision quality set.

[0010] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: extracting a first drying process index and a second drying process index from the first drying process index set; obtaining the first drying process parameter boundary of the first drying process index and constructing a first drying process parameter space; obtaining the second drying process parameter boundary of the second drying process index and constructing a second drying process parameter space; identifying the intersection of the first drying process parameter space and the second drying process parameter space to obtain a first drying process parameter intersection space; obtaining M drying process parameter spaces based on the first drying process parameter space and the second drying process parameter space; and superimposing the M drying process parameter spaces on the first drying process parameter intersection space to obtain a first drying process parameter sharing space for the first drying process index set.

[0011] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: generating an initial decision variable set in the first drying process parameter shared space; inputting the initial decision variable set into the drying process model to obtain an initial decision quality set; identifying drying quality conflicts based on the initial decision quality set to obtain a conflict decision quality set; obtaining a corresponding conflict decision variable set based on the conflict decision quality set; traversing the first drying process parameter shared space and removing the conflict decision variable set to obtain a first drying process parameter conflict-free space; and extracting the first decision variable set based on the first drying process parameter conflict-free space.

[0012] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: introducing a first drying quality target corresponding to the first drying process index set; and comparing the first decision quality set with the first drying quality target to obtain the first deviation quality set.

[0013] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: determining whether the deviation of the first deviation mass set meets the preset first deviation mass set; if it does, performing drying treatment through the first decision variable set.

[0014] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: if the conditions are not met, adjusting the first decision variable set based on the first deviation quality set to obtain a first expanded / contracted decision variable set, and performing drying treatment using the first expanded / contracted decision variable set as the first decision variable set.

[0015] Preferably, the method for optimizing the drying process parameters of insulating paper for power manufacturing transformers further includes: adjusting the first decision variable set based on the first deviation quality set to obtain a first adjustment decision variable set; expanding or shrinking the first adjustment decision variable set based on the conflict-free space of the first drying process parameters to obtain a first expanded decision variable set; inputting the first expanded decision variable set into the drying process model to obtain a first expanded decision quality set; comparing the first expanded decision quality set with the first drying quality target until the deviation meets the preset first deviation quality set to obtain the first expanded decision variable set.

[0016] The technical solution provided in this application has at least the following technical effects or advantages: by realizing intelligent optimization and real-time adjustment of the drying process, the stability, uniformity and efficiency of the drying process are improved, ensuring that the quality of transformer insulation paper meets the predetermined standards, while improving production efficiency and reducing the scrap rate.

[0017] The above description is merely an overview of the technical solution of this application. To enable a clearer understanding of the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for optimizing the drying process parameters of insulating paper in a power transformer according to this application.

[0020] Figure 2 This is a schematic diagram of the process for constructing a drying process model in the method for optimizing the drying process parameters of insulating paper for power transformers according to this application. Detailed Implementation

[0021] This application provides a method for optimizing the drying process parameters of insulating paper for power transformers. It solves the technical problem in existing technologies where the lack of precise feedback control and dynamic adjustment mechanisms in the drying process leads to the inability to flexibly adjust process parameters according to the actual drying progress, further affecting the stability and consistency of the drying process, and consequently impacting the quality and performance of the transformer insulating paper, resulting in low production efficiency. By achieving intelligent optimization and real-time adjustment of the drying process, the method improves the stability, uniformity, and efficiency of the drying process, ensuring that the quality of the transformer insulating paper meets predetermined standards, while simultaneously increasing production efficiency and reducing the scrap rate.

[0022] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0023] Please see the appendix Figure 1 and attached Figure 2 This application provides a method for optimizing the drying process parameters of insulating paper in power manufacturing transformers, specifically including the following steps:

[0024] Construct the first initial state vector and the corresponding first drying state vector of the insulating paper at the first historical time, obtain the first drying process index set at the first historical time, and construct the drying process model.

[0025] Furthermore, this application also includes: obtaining a first vector difference between the first drying state vector and the first initial state vector; quantifying the drying quality based on the first vector difference to generate a first drying quality set; obtaining a first drying process parameter set of the first drying process index set, and constructing the drying process model using the first drying process parameter set and the first drying quality set as inputs.

[0026] Furthermore, this application also includes: obtaining N initial state vectors and corresponding N drying state vectors at N historical times, and obtaining N drying process parameter sets; based on the first drying quality set, adjusting the drying process model through the N initial state vectors, the N drying state vectors, and the N drying process parameter sets to obtain the adjusted drying process model as the drying process model.

[0027] Specifically, a first initial state vector and a corresponding first drying state vector of the insulating paper are constructed at the first historical time, and a first drying process index set for the first historical time is obtained. The initial state vector refers to a set of data describing the physical and chemical properties of the insulating paper at a specific historical point in time, including parameters such as temperature, humidity, moisture content, and density. The drying state vector refers to the set of values ​​for the degree of dryness of the insulating paper and the drying environment parameters at the same point in time. The drying process index set is a set of process indicators derived from multiple parameters, variables, and target results during the drying process, which can provide a quantitative basis for optimizing the drying process.

[0028] Obtain the first vector difference between the first drying state vector and the first initial state vector. This vector difference is calculated by comparing the initial state vector with the drying state vector to determine the changes during the drying process. This difference reflects the quality changes, state changes, and drying effect during the drying process, providing crucial information for subsequent quality quantification analysis.

[0029] The drying quality is quantified based on the first vector difference, generating a first drying quality set. Drying quality quantification evaluates the effectiveness and quality of the drying process based on vector differences. By quantifying key parameters such as deviations and moisture content during the drying process, a drying quality set can be generated. This set contains various quality indicators used to evaluate the quality of the current drying process and provide data support for further optimization.

[0030] A first drying process parameter set is obtained from the first drying process index set. Using this first drying process parameter set and the first drying quality set as inputs, a drying process model is constructed. The drying process parameter set refers to all important process parameters extracted from the drying process index set, including but not limited to temperature, humidity, and vacuum degree. By combining these parameters, a mathematical model can be established that describes the relationship between various parameters during the drying process and the final effect, providing a foundation for subsequent optimization and adjustment.

[0031] Obtain N initial state vectors and corresponding N drying state vectors for N historical time points, and obtain N sets of drying process parameters. Each historical time point corresponds to an initial state vector, a drying state vector, and a set of drying process parameters. N is an integer greater than 1.

[0032] Based on the first drying mass set, the drying process model is adjusted using N initial state vectors, N drying state vectors, and N drying process parameter sets to obtain the adjusted drying process model. Adjusting the drying process model involves inputting initial state vectors, drying state vectors, and drying process parameter sets from multiple historical time points. This analysis and adjustment of key parameters in the drying process model enables it to more accurately predict and control the drying process. The adjusted drying process model is the result of multiple adjustments and optimizations, and its results more accurately reflect the process changes and effects during actual drying, thereby optimizing the entire drying process.

[0033] The parameters of the first drying process index set are adjusted, and the first decision variable set is input into the drying process model to obtain the first decision quality set.

[0034] Furthermore, this application also includes: obtaining a first drying process parameter boundary set of the first drying process index set; constructing a first drying process parameter space set based on the first drying process parameter boundary set; adjusting the first drying process parameter set based on the first drying process parameter space set to generate the first decision variable set; and inputting the first decision variable set into the drying process model to obtain the first decision quality set.

[0035] Furthermore, this application also includes: extracting a first drying process index and a second drying process index from the first drying process index set; obtaining a first drying process parameter boundary for the first drying process index and constructing a first drying process parameter space; obtaining a second drying process parameter boundary for the second drying process index and constructing a second drying process parameter space; performing intersection identification based on the first drying process parameter space and the second drying process parameter space to obtain a first drying process parameter intersection space; obtaining M drying process parameter spaces based on the first drying process parameter space and the second drying process parameter space; and superimposing the M drying process parameter spaces on the first drying process parameter intersection space to obtain a first drying process parameter shared space for the first drying process index set.

[0036] Furthermore, this application also includes: generating an initial decision variable set in the first drying process parameter shared space; inputting the initial decision variable set into the drying process model to obtain an initial decision quality set; identifying drying quality conflicts based on the initial decision quality set to obtain a conflict decision quality set; obtaining a corresponding conflict decision variable set based on the conflict decision quality set; traversing the first drying process parameter shared space and removing the conflict decision variable set to obtain a first drying process parameter conflict-free space; and extracting the first decision variable set based on the first drying process parameter conflict-free space.

[0037] Specifically, a first drying process parameter boundary set is obtained from the first drying process index set. This first drying process index set includes various parameters used to evaluate the drying process, such as temperature, humidity, time, and vacuum level. The drying process parameter boundary set refers to the allowable range, or upper and lower limits, of each process parameter determined based on these index sets. This boundary set reflects the acceptable range of variation for each parameter during the drying process, ensuring that process parameter adjustments are made within reasonable limits.

[0038] A first drying process parameter space set is constructed based on the first drying process parameter boundary set. This space set is formed by combining and mapping the parameters within the boundary set, creating a multi-dimensional space that contains all possible combinations of process parameters. This space provides a reference framework for subsequent process parameter adjustments, ensuring that all reasonable parameter ranges are covered during process adjustments and avoiding unreasonable parameter combinations.

[0039] Based on the first drying process parameter space set, the first drying process parameter set is adjusted to generate the first decision variable set. By analyzing and adjusting the process parameters within the drying process parameter space set, the most suitable parameter combination for the current drying requirements is selected, generating the first decision variable set. The decision variable set contains the adjusted parameter values, used to control the specific operations during the drying process, ensuring that the expected drying effect is ultimately achieved.

[0040] This involves extracting the first and second drying process indicators from the first set of drying process indicators. The drying process indicator set contains various process parameters used to evaluate the effectiveness of the drying process. The first drying process indicator is a first type of process parameter extracted from the drying process indicator set, involving parameters affecting the initial stage of the drying process, such as temperature and humidity. The second drying process indicator is a second type of process parameter extracted from the same set of drying process indicators, typically involving parameters in the later or stable stages of the drying process, such as vacuum level and heating rate.

[0041] First, the boundary values ​​of the first drying process parameters for the first drying process index are obtained, and a first drying process parameter space is constructed. Second, the boundary values ​​of the second drying process parameters for the second drying process index are obtained, and a second drying process parameter space is constructed. The drying process parameter boundary refers to the maximum and minimum allowable values ​​of each drying process index within a certain range, representing the permissible range of parameter variation during the drying process. By obtaining these parameter boundaries, the first and second drying process parameter spaces can be constructed. The first drying process parameter space is a multi-dimensional parameter space formed based on the boundaries of the first drying process index, containing all possible combinations of the first drying process parameters. The second drying process parameter space is a parameter space constructed based on the boundaries of the second drying process index, containing all possible combinations of the second drying process parameters.

[0042] The intersection space of the first and second drying process parameter spaces is obtained by performing intersection identification. Intersection identification refers to finding the range of parameters that are commonly satisfied by both the first and second drying process parameter spaces, i.e., finding the intersection of all parameter values ​​in these two spaces. The first drying process parameter intersection space is the space composed of drying process parameter combinations that simultaneously satisfy all conditions in the first and second drying process parameter spaces, obtained during the intersection identification process.

[0043] Based on the first and second drying process parameter spaces, M drying process parameter spaces are obtained. These spaces can be further subdivided and combined to form M more drying process parameter spaces, where M is an integer greater than 1. Each space represents a set of reasonable combinations of process parameters, providing multiple feasible options for optimizing the drying process.

[0044] The spaces of M drying process parameters are superimposed on the intersection space of the first drying process parameters to obtain the first shared space of the first drying process index set. By superimposing the spaces of M drying process parameters onto the first intersection space of the first drying process parameters, a new shared space of drying process parameters can be obtained. This shared space contains all spaces that satisfy the intersection conditions and are applicable to multiple combinations of process parameters, ensuring the consistency and optimization of the drying process across multiple parameter ranges.

[0045] The first set of decision variables is input into the drying process model to obtain the first set of decision quality variables. The adjusted first set of decision variables is then used as input to the constructed drying process model for simulation or calculation, yielding quality evaluation results related to the drying process. These evaluation results constitute the first set of decision quality variables. The decision quality set reflects the actual effect of the current drying process and further guides the optimization and adjustment of process parameters.

[0046] An initial set of decision variables is generated within the first shared space of drying process parameters. This first shared space is a multi-dimensional parameter space obtained through intersection identification and superposition, containing all possible parameter combinations that satisfy different drying process requirements. By generating the initial set of decision variables within this shared space, a preliminary set of drying process control parameters can be obtained. These parameters form the basis for adjusting and optimizing the process during drying.

[0047] The initial decision variable set is input into the drying process model to obtain the initial decision quality set. The drying process model is a mathematical model that analyzes the relationship between various parameters and results during the drying process, enabling it to simulate and predict the drying effect. After inputting the initial decision variable set into the model, the initial decision quality set is obtained. The initial decision quality set refers to the set of drying process quality indicators calculated based on the drying process model; these indicators are used to evaluate the drying effect under the current decision variable set.

[0048] Based on the initial decision quality set, a drying quality conflict identification process is performed to obtain a conflict decision quality set. Drying quality conflict identification refers to checking for quality conflicts or inconsistencies between different process parameters based on the initial decision quality set. By identifying conflicts, a conflict decision quality set is generated. This conflict decision quality set contains a set of decision variables where the quality indicators of the drying process cannot meet the target requirements; these variables require further optimization and adjustment.

[0049] The conflict decision variable set is obtained by identifying the conflict decision quality set. The conflict decision variable set refers to the decision variables corresponding to the conflict decision quality set that, under the current state, cannot meet the quality requirements of the drying process and therefore need to be eliminated or adjusted. Obtaining the conflict decision variable set is to identify and eliminate process parameter combinations that lead to quality conflicts, providing a basis for process optimization.

[0050] By traversing the shared space of the first drying process parameters and eliminating conflicting decision variable sets, a conflict-free space for the first drying process parameters is obtained. During this traversal, eliminating conflicting decision variable sets removes parameter combinations that do not meet quality requirements; the remaining parameter combinations constitute the conflict-free space for the first drying process parameters. Each parameter combination in the conflict-free space ensures that the quality objectives during the drying process are met.

[0051] A first set of decision variables is extracted based on the conflict-free space of the first drying process parameters. By screening and extracting the set of decision variables from the conflict-free space of the first drying process parameters, the optimal set of decision variables that can meet the optimization requirements of the drying process is finally obtained. This set of decision variables is the parameter combination that best meets the quality requirements of the drying process after conflict elimination and optimization.

[0052] Collect a first deviation quality set based on the first decision quality set.

[0053] Furthermore, this application also includes: introducing a first drying quality target corresponding to the first drying process index set; comparing the first decision quality set with the first drying quality target to obtain the first deviation quality set.

[0054] Specifically, a first drying quality target corresponding to a first set of drying process indicators is introduced. This first set of drying process indicators includes multiple process parameters related to the drying process, used to describe various control factors during the drying process. The first drying quality target is a target quality level set based on these process indicators, including the desired drying effect, such as humidity, moisture content, and drying time. The first drying quality target serves as a standard for measuring the drying effect during the optimization process, ensuring that the predetermined quality requirements are met during the process.

[0055] The first decision quality set is compared with the first drying quality target to obtain the first deviation quality set. The first decision quality set is the result obtained by inputting the decision variable set into the drying process model, and includes the quality indicators achieved during the actual drying process. The actual results are compared with the preset first drying quality target, and the difference is calculated to obtain the first deviation quality set. The first deviation quality set represents the deviation between the actual drying quality and the target quality, reflecting the gap between the current drying process's execution effect and the target.

[0056] Based on the first set of deviation quality, the drying process is performed using the first set of decision variables.

[0057] Furthermore, this application also includes: determining whether the deviation of the first deviation quality set meets the preset first deviation quality set; if it does, performing drying treatment through the first decision variable set.

[0058] Furthermore, this application also includes: if the conditions are not met, performing feedback adjustment on the first decision variable set based on the first deviation quality set to obtain a first expanded / contracted decision variable set, and performing drying treatment using the first expanded / contracted decision variable set as the first decision variable set.

[0059] Furthermore, this application also includes: adjusting the first decision variable set based on the first deviation quality set to obtain a first adjustment decision variable set; expanding or shrinking the first adjustment decision variable set based on the conflict-free space of the first drying process parameters to obtain a first expanded decision variable set; inputting the first expanded decision variable set into the drying process model to obtain a first expanded decision quality set; comparing the first expanded decision quality set with the first drying quality target until the deviation meets the preset first deviation quality set to obtain the first expanded decision variable set.

[0060] Specifically, it involves determining whether the deviations in the first deviation quality set meet the preset first deviation quality set. The first deviation quality set refers to the set of differences between the actual drying effect and the preset quality target in the drying process. The preset first deviation quality set is a deviation tolerance range set according to process requirements and quality standards, which defines the allowable error range for drying quality. By determining whether the deviations in the first deviation quality set are within the preset tolerance range, it can be determined whether the current drying process meets the quality standards, and thus decide whether process parameters need to be adjusted.

[0061] If the conditions are met, drying is performed using the first set of decision variables. If the deviations in the first set of deviations meet the preset tolerance range, it indicates that the current drying process has met the expected quality requirements. At this point, drying can be performed using the determined first set of decision variables. The first set of decision variables contains the optimal process parameters adjusted according to the optimization model, used to actually control the drying process and ensure that drying can proceed smoothly while meeting the quality objectives.

[0062] If the conditions are not met, feedback adjustment is performed on the first decision variable set based on the first deviation quality set to obtain the first adjustment decision variable set. If the deviation of the first deviation quality set does not meet the preset tolerance range, feedback adjustment of the first decision variable set is required. Feedback adjustment involves adjusting the control parameters in the decision variable set based on the difference information in the deviation quality set to reduce the deviation and bring the drying process closer to the target quality requirements. The adjusted variable set is called the first adjustment decision variable set, which aims to optimize various process parameters of the drying process.

[0063] The first set of adjustment decision variables is expanded or reduced based on the conflict-free space of the first drying process parameters to obtain the first expanded / reduced set of decision variables. After adjustment, the first set of adjustment decision variables may need further expansion or reduction within the conflict-free space of the first drying process parameters. The conflict-free space of drying process parameters refers to the effective parameter space formed by excluding parameter combinations that do not meet quality requirements or cause conflicts. Adjustment expansion or reduction refers to further adjusting the decision variables to expand or shrink their range within the conflict-free space, thereby obtaining a more accurate and feasible first expanded / reduced set of decision variables.

[0064] The first set of expansion / reduction decision variables is input into the drying process model to obtain the first set of expansion / reduction decision quality. The first set of expansion / reduction decision variables, after adjustment, is then used as input into the drying process model for simulation or calculation to obtain new decision quality results. This forms the first set of expansion / reduction decision quality, which includes the drying effect and quality indicators brought about by the adjusted decision variables, providing feedback information for further optimization of the drying process.

[0065] The first expansion / contraction decision variable set is compared with the first drying quality target until the deviation meets the preset first deviation quality set, thus obtaining the first expansion / contraction decision variable set. The drying process is then performed using this first expansion / contraction decision variable set as the first decision variable set. By comparing the first expansion / contraction decision quality set with the preset first drying quality target, it is determined whether the drying effect meets the requirements. If the deviation still does not meet the preset target, the expansion / contraction decision variable set is adjusted until the deviation meets the predetermined quality requirements. Once the target is met, the adjusted first expansion / contraction decision variable set can be used as the new first decision variable set for formally performing the drying process.

[0066] In summary, the method for optimizing the drying process parameters of insulating paper for power transformers provided in this application has the following technical effects: by realizing intelligent optimization and real-time adjustment of the drying process, the stability, uniformity and efficiency of the drying process are improved, ensuring that the quality of the transformer insulating paper meets the predetermined standards, while improving production efficiency and reducing the scrap rate.

[0067] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0068] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for optimizing the drying process parameters of insulating paper in power transformer manufacturing, characterized in that, include: Construct the first initial state vector and the corresponding first drying state vector of the insulating paper at the first historical time, obtain the first drying process index set at the first historical time, and construct the drying process model. The parameters of the first drying process index set are adjusted, and the first decision variable set is input into the drying process model to obtain the first decision quality set. Collect a first deviation quality set based on the first decision quality set; Based on the first set of deviation quality, the drying process is performed using the first set of decision variables.

2. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 1, characterized in that, Constructing a drying process model, including: Obtain the first vector difference between the first drying state vector and the first initial state vector; The drying quality is quantified based on the first vector difference to generate a first drying quality set. Obtain the first drying process parameter set of the first drying process index set, and construct the drying process model using the first drying process parameter set and the first drying quality set as input.

3. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 2, characterized in that, Constructing a drying process model also includes: Obtain N initial state vectors and corresponding N drying state vectors at N historical time points, and obtain N sets of drying process parameters; Based on the first drying quality set, the drying process model is adjusted using the N initial state vectors, the N drying state vectors, and the N drying process parameter sets to obtain the adjusted drying process model.

4. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 2, characterized in that, The parameters of the first drying process index set are adjusted, and the first decision variable set is input into the drying process model to obtain the first decision quality set, including: Obtain the first drying process parameter boundary set of the first drying process index set; Construct a first drying process parameter space set using the first drying process parameter boundary set; The first set of drying process parameters is adjusted based on the first set of drying process parameters space to generate the first set of decision variables; The first set of decision variables is input into the drying process model to obtain the first set of decision quality.

5. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 4, characterized in that, The first drying process parameter set is adjusted based on the first drying process parameter space set to generate the first decision variable set, which includes: Extract the first drying process index and the second drying process index from the first drying process index set; Obtain the first drying process parameter boundary of the first drying process index and construct the first drying process parameter space; obtain the second drying process parameter boundary of the second drying process index and construct the second drying process parameter space. The intersection space of the first drying process parameter space and the second drying process parameter space is identified to obtain the first drying process parameter intersection space. Based on the first drying process parameter space and the second drying process parameter space, M drying process parameter spaces are obtained. The M drying process parameter spaces are superimposed on the intersection space of the first drying process parameter to obtain the first drying process parameter shared space of the first drying process index set.

6. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 5, characterized in that, The first set of drying process parameters is adjusted based on the first set of drying process parameters space to generate the first set of decision variables, including: An initial set of decision variables is generated in the first drying process parameter shared space; The initial decision variable set is input into the drying process model to obtain the initial decision quality set; Based on the initial decision quality set, a drying quality conflict identification is performed on the initial decision quality to obtain a conflict decision quality set; Obtain the corresponding set of conflict decision variables based on the conflict decision quality set; Traverse the first drying process parameter shared space, remove the conflict decision variable set, and obtain the first drying process parameter non-conflict space; The first set of decision variables is extracted based on the conflict-free space of the first drying process parameters.

7. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 6, characterized in that, Collect a first deviation quality set based on the first decision quality set, including: Introduce the first drying quality target corresponding to the first drying process index set; The first decision quality set is compared with the first drying quality target to obtain the first deviation quality set.

8. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 7, characterized in that, Based on the first set of deviation quality, a drying process is performed using the first set of decision variables, including: Determine whether the deviation of the first deviation mass set meets the preset first deviation mass set; If the conditions are met, the drying process is performed using the first set of decision variables.

9. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 8, characterized in that, Based on the first set of deviation quality, the drying process is performed using the first set of decision variables, and further includes: If the conditions are not met, the first decision variable set is adjusted based on the first deviation quality set to obtain a first expanded / contracted decision variable set, and the drying process is performed using the first expanded / contracted decision variable set as the first decision variable set.

10. The method for optimizing the drying process parameters of insulating paper in power manufacturing transformers as described in claim 9, characterized in that, Based on the first deviation quality set, the first decision variable set is adjusted using feedback to obtain a first expanded / contracted decision variable set, including: The first set of decision variables is adjusted by feedback based on the first set of deviation quality to obtain the first set of adjustment decision variables. The first set of adjustment decision variables is expanded or reduced based on the conflict-free space of the first drying process parameters to obtain the first expanded set of decision variables; Input the first set of expansion and contraction decision variables into the drying process model to obtain the first set of expansion and contraction decision quality; The first expansion / contraction decision variable set is obtained by comparing the first expansion / contraction decision quality set with the first drying quality target until the deviation meets the preset first deviation quality set.

Images