Method, device and equipment for automatically generating three-dimensional engineering drawing of transformer and medium

Abstract

The invention relates to the technical field of transformer three-dimensional drawing automatic generation, in particular to a transformer three-dimensional engineering drawing automatic generation method and device, equipment and a medium. The method comprises the steps that firstly, a transformer performance requirement parameter set is obtained, electromagnetic calculation is conducted on the performance requirement parameter set, and a transformer structure data set is obtained; obtaining a preset standardized rule base, performing three-dimensional module parameter rule matching on the transformer structure data set based on the standardized rule base to obtain a parameter mapping relation, obtaining an initial three-dimensional model parameter set, updating the initial three-dimensional model parameter set based on the parameter mapping relation to obtain a target three-dimensional model parameter set, and performing three-dimensional model parameter matching on the target three-dimensional model parameter set; and finally, checking the target three-dimensional model parameter set, and when the checking is passed, outputting the transformer three-dimensional engineering drawing based on the target three-dimensional model parameter set, thereby realizing the full-process automatic generation from the amorphous alloy dry-type transformer performance demand to the three-dimensional engineering drawing.

Description

Technical Field

[0001] This invention relates to the field of automatic generation technology of three-dimensional transformer drawings, and in particular to a method, apparatus, equipment and medium for automatic generation of three-dimensional transformer engineering drawings. Background Technology

[0002] Amorphous alloy dry-type transformers, with their excellent energy-saving characteristics and insulation performance, have been widely used in power transmission and distribution systems. Their design process places high demands on parameter accuracy and structural adaptability. In the traditional process of generating 3D engineering drawings for amorphous alloy dry-type transformers, designers often need to combine their own experience to first complete electromagnetic calculations based on the transformer's performance requirements, and then manually convert the calculated structural parameters into 3D model parameters. This process is not only time-consuming but also prone to parameter deviations due to human error. Furthermore, due to the lack of unified modeling and parameter constraint standards within the industry, different designers use different technical standards and parameter settings when conducting modeling work. This makes it difficult to achieve cross-project module reuse of the generated 3D model, and it cannot ensure that the model parameters are accurately adapted to the actual production and processing technology. In addition, the adjustment and updating of 3D model parameters lacks clear mapping logic support, relying solely on manual judgment to complete parameter corrections, which easily leads to mismatches between the 3D model and structural parameters. These problems severely restrict the design efficiency and product quality of amorphous alloy dry-type transformers, making it difficult to meet the current market demand for rapid customization and mass production of transformers. Summary of the Invention

[0003] In order to overcome the shortcomings of the prior art, the present invention aims to provide a method, device, equipment and medium for automatically generating three-dimensional engineering drawings of transformers, which realizes the fully automated generation of three-dimensional engineering drawings from the performance requirements of amorphous alloy dry-type transformers, gets rid of the excessive reliance on the manual experience of designers, effectively avoids the parameter deviation problem caused by manual operation, and ensures the accuracy of product parameters and structural adaptability.

[0004] The first aspect of this invention provides a method for automatically generating three-dimensional engineering drawings of transformers, comprising: acquiring a set of transformer performance requirement parameters; performing electromagnetic calculations on the set of performance requirement parameters to obtain a transformer structure dataset; acquiring a preset standardized rule base; performing three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain a parameter mapping relationship; acquiring an initial three-dimensional model parameter set; updating the initial three-dimensional model parameter set based on the parameter mapping relationship to obtain a target three-dimensional model parameter set; verifying the target three-dimensional model parameter set; and when the verification passes, outputting three-dimensional engineering drawings of the transformer based on the target three-dimensional model parameter set.

[0005] Optionally, in a first implementation of the first aspect of the present invention, the performance requirement parameter set includes rated capacity, rated voltage, rated frequency, and rated current; the step of performing electromagnetic calculations on the performance requirement parameter set to obtain a transformer structure dataset includes: determining the transformer core flux density based on the rated capacity, rated voltage, and rated frequency; calculating the transformer main flux and the number of turns in the high and low voltage windings based on Faraday's law of electromagnetic induction and the transformer core flux density; determining the winding current density based on the rated current and calculating the winding conductor cross-sectional area based on the winding current density; calling a pre-trained transformer performance calculation model, and performing verification and optimization processing on the transformer core flux density, the transformer main flux, the number of turns in the high and low voltage windings, and the winding conductor cross-sectional area based on the transformer performance calculation model to obtain a target intermediate derivation parameter set; and determining the core size and winding structure parameters based on the target intermediate derivation parameter set to obtain the transformer structure dataset.

[0006] Optionally, in a second implementation of the first aspect of the present invention, the transformer performance calculation model includes a performance parameter calculation module, a performance index verification module, and a parameter optimization module, which are sequentially connected. The step of verifying and optimizing the transformer core flux density, the transformer main flux, the number of turns in the high and low voltage windings, and the cross-sectional area of ​​the winding conductors based on the transformer performance calculation model to obtain a target intermediate derivation parameter set includes: performing performance calculations on the transformer core flux density, the transformer main flux, the number of turns in the high and low voltage windings, and the cross-sectional area of ​​the winding conductors based on the performance parameter calculation module to obtain a transformer performance verification parameter set; verifying the transformer performance verification parameter set based on the performance index verification module, and obtaining an out-of-standard parameter set when the verification fails; and performing multi-round iterative optimization processing on the out-of-standard parameter set based on the parameter optimization module to obtain the target intermediate derivation parameter set.

[0007] Optionally, in a third implementation of the first aspect of the present invention, the standardized rule base includes multiple transformer 3D modules and a module matching threshold corresponding to each module; the step of performing 3D module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationships includes: obtaining preset 3D module partitioning rules; performing category partitioning processing on the transformer structure dataset based on the 3D module partitioning rules to obtain multiple categorized structure data subsets; comparing each categorized structure data subset with its corresponding module matching threshold, and filtering to obtain transformer 3D modules that are compatible with each categorized structure data subset; establishing a mapping relationship between each categorized structure data subset and its corresponding transformer 3D module to generate multiple association items; and integrating all the association items to obtain the parameter mapping relationship.

[0008] Optionally, in the fourth implementation of the first aspect of the present invention, the standardized rule base further includes parameter adjustment rules. After verifying the target three-dimensional model parameter set, the method further includes: when the verification fails, obtaining the out-of-standard parameter set and the compliant parameter set in the target three-dimensional model parameter set; performing deviation correction processing on the out-of-standard parameter set based on the parameter adjustment rules to obtain a corrected parameter set; integrating the corrected parameter set and the compliant parameter set to obtain a corrected three-dimensional model parameter set, and outputting the transformer three-dimensional engineering drawings based on the corrected three-dimensional model parameter set.

[0009] A second aspect of the present invention provides an automatic generation device for three-dimensional engineering drawings of transformers, comprising: an electromagnetic calculation module for acquiring a set of transformer performance requirement parameters and performing electromagnetic calculations on the set of performance requirement parameters to obtain a transformer structure dataset; a matching module for acquiring a preset standardized rule base and performing three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain a parameter mapping relationship; a parameter update module for acquiring an initial three-dimensional model parameter set and updating the initial three-dimensional model parameter set based on the parameter mapping relationship to obtain a target three-dimensional model parameter set; and a drawing output module for verifying the target three-dimensional model parameter set and, when the verification passes, outputting three-dimensional engineering drawings of the transformer based on the target three-dimensional model parameter set.

[0010] A third aspect of the present invention provides an automatic transformer 3D engineering drawing generation device, the transformer 3D engineering drawing generation device comprising: a memory and at least one processor, the memory storing instructions; at least one processor calling the instructions in the memory to cause the transformer 3D engineering drawing generation device to perform each step of the transformer 3D engineering drawing generation method described above.

[0011] A fourth aspect of the present invention provides a computer-readable storage medium storing instructions that, when executed by a processor, implement the steps of the method for automatically generating three-dimensional engineering drawings of a transformer as described above.

[0012] In the technical solution of this invention, firstly, a set of transformer performance requirement parameters is obtained, and electromagnetic calculations are performed on the set of performance requirement parameters to obtain a transformer structure dataset. Then, a preset standardized rule base is obtained, and three-dimensional module parameter rule matching is performed on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationships. Next, an initial three-dimensional model parameter set is obtained, and the initial three-dimensional model parameter set is updated based on the parameter mapping relationships to obtain a target three-dimensional model parameter set. Finally, the target three-dimensional model parameter set is verified. When the verification passes, three-dimensional engineering drawings of the transformer are output based on the target three-dimensional model parameter set. This realizes the fully automated generation of three-dimensional engineering drawings from the performance requirements of amorphous alloy dry-type transformers, eliminating excessive reliance on the manual experience of designers, effectively avoiding parameter deviation problems caused by manual operation, and ensuring the accuracy of product parameters and structural adaptability. Attached Figure Description

[0013] Figure 1 A logic flowchart of the automatic generation method for three-dimensional engineering drawings of transformers provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of the automatic generation device for three-dimensional engineering drawings of transformers provided in an embodiment of the present invention; Figure 3 A schematic diagram of the structure of the automatic generation device for three-dimensional engineering drawings of transformers provided in an embodiment of the present invention. Detailed Implementation

[0014] This invention provides a method, apparatus, device, and medium for automatically generating three-dimensional engineering drawings of transformers. In this invention, the terms "first," "second," "third," "fourth," etc. (if present)," in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0015] For ease of understanding, the specific process of the embodiments of the present invention is described below. Please refer to [link / reference]. Figure 1One embodiment of the method for automatically generating three-dimensional engineering drawings of transformers in this invention includes: 101. Obtain the transformer performance requirement parameter set, perform electromagnetic calculations on the performance requirement parameter set, and obtain the transformer structure dataset; In this embodiment, a set of transformer performance requirement parameters is obtained, that is, the core performance indicators required for the design of amorphous alloy dry-type transformers are collected and entered, covering key requirement parameters such as rated capacity, rated voltage, rated frequency, and rated current. This provides a basis for subsequent targeted electromagnetic calculations that are adapted to the material properties and structural characteristics of amorphous alloy dry-type transformers. Electromagnetic calculations are performed on the performance requirement parameter set to obtain the transformer structure dataset. Essentially, this involves a systematic electromagnetic calculation process based on the collected performance requirement indicators and the material characteristics of amorphous alloy cores, such as high permeability, low coercivity, and low no-load loss. First, the core flux density suitable for the amorphous alloy core is selected by combining the required parameters such as rated capacity, rated voltage, and frequency. This value must ensure the electromagnetic conversion efficiency of the transformer while fully utilizing the energy-saving advantages of amorphous alloy materials. Based on this, the main flux is calculated, and then the number of turns in the high-voltage and low-voltage windings is further derived from the main flux. These two types of parameters are the core basis for subsequently determining the amorphous alloy core size and dry winding structure. At the same time, the corresponding current density is set according to the rated current. Considering the structural characteristics of amorphous alloy dry-type transformers, such as the lack of oil-immersed heat dissipation medium and relatively stringent winding heat dissipation conditions, the cross-sectional area of ​​the winding conductor suitable for dry insulation and temperature rise control requirements is calculated through the current density. This parameter directly determines the current carrying capacity and structural dimensions of the winding, and also affects the insulation design and heat dissipation layout of the dry winding. Core flux density, main flux, number of turns in high and low voltage windings, current density, and winding conductor cross-sectional area are all core intermediate parameters generated during electromagnetic calculations for amorphous alloy dry-type transformers. Their core function is to provide quantitative basis for deriving the dimensions of the amorphous alloy core and key structural parameters of the dry winding. They also form the basis for generating key performance indicators such as short-circuit impedance, no-load loss, load loss, and core flux density. By verifying these derived performance indicators, it is checked whether the no-load loss meets the expected energy-saving standards for the application of amorphous alloy materials, and whether the core intermediate parameters conform to the preset design standards and performance requirements of amorphous alloy dry-type transformers. If the indicators meet the standards, the stack thickness, column diameter, and other dimensional parameters of the amorphous alloy core, as well as the axial height and radial thickness of the dry winding, are further clarified based on the qualified intermediate parameters. If the indicators do not meet the standards, the intermediate parameters are adjusted and recalculated until the performance indicators are fully compliant.

[0016] After determining the core dimensions of the amorphous alloy core and the key structural parameters of the dry winding, based on these core structural parameters and considering the characteristics of amorphous alloy materials, insulation process requirements for dry-type transformers, and industry assembly design specifications, the matching parameters for clamps, leads, and assembly are simultaneously derived and determined: For clamp parameters, based on the overall dimensions of the core, such as core stack thickness, column diameter, and yoke height, the clamping inner diameter is determined by ensuring a close fit and allowing for assembly allowance; the fastening matching dimensions are selected according to the core stack thickness. For example, when the stack thickness is ≤300mm, a single set of pull plates is used for fastening; when the stack thickness is >300mm, a double set of symmetrical pull plates is used. The pull plate installation points are equidistantly distributed along the yoke height direction, with a spacing of 1 / 3 of the yoke height, avoiding weak areas of the core joints; combined with the amorphous alloy core... Due to its brittleness and inability to withstand excessive mechanical stress, the spacing between insulating supports is controlled at 80-120mm. The supports are made of epoxy glass cloth to avoid rigid contact damage to the iron core. Adapted to epoxy insulation processes, the thickness of the insulating protective layer of the clamps is determined according to the corresponding voltage level (3-5mm for 10kV, 5-8mm for 35kV). The protection range covers the contact area between the clamps and the iron core and windings, ensuring stable clamping while eliminating mechanical damage and insulation hazards. For lead wire parameters, specifications are determined according to current-carrying requirements, insulation standards, and spatial layout. The cross-sectional specifications are calculated based on the rated current of the high and low voltage windings and the conductor conductivity to determine the minimum current-carrying cross-section, and then increased by 10%-15% in conjunction with the spatial redundancy at the winding output end. Rectangular copper busbars (low-voltage side) or multi-strand copper stranded wires (high-voltage side) are preferred. The insulation layer thickness strictly follows GB / T 1094.Standard 3: For 10kV lead wires, the insulation layer thickness should be no less than 4mm, and for 35kV, no less than 8mm, using epoxy powder coating. The bending radius is determined based on the lead wire cross-sectional dimensions; for rectangular copper busbars, the bending radius should be no less than 3 times the conductor thickness, and for multi-strand copper wires, no less than 5 times the conductor diameter, to prevent insulation layer cracking. Fixtures are arranged with one clamp every 500mm, using an insulated snap-fit ​​structure. The arrangement path must avoid protruding parts of the core and clamps, and the distance between the clamp and the winding surface should be no less than 20mm, balancing current carrying capacity, insulation protection, and spatial adaptability. For assembly parameters, the gap is set in conjunction with air convection heat dissipation characteristics; for example, the gap between the core and winding is... The winding diameter is 15-25mm, the gap between the winding and the clamp is 10-15mm, and the gap between the clamp and the outer shell is not less than 30mm to ensure unobstructed heat dissipation. The assembly alignment benchmark is based on the core center axis, and the coaxiality error between the winding and the core is controlled within ±1mm. The clamp is precisely aligned with the core base through locating pins. The tightening torque is matched according to the bolt specifications: 45-50 N·m for M12 bolts and 80-85 N·m for M16 bolts to avoid excessive torque damaging the core. Epoxy insulating pads are used, with a spacing of 100-150mm, and are staggered from the clamp support points to ensure assembly accuracy and structural stability while reserving sufficient heat dissipation and process operation space. Finally, the dimensions of the verified amorphous alloy core and the key structural parameters of the dry winding are integrated with the clamp, lead, and assembly matching parameters determined above to form a complete transformer structure dataset. By conducting targeted electromagnetic calculations based on clearly defined performance requirements, it is possible to ensure that the resulting transformer structure dataset closely matches actual design needs, thus guaranteeing the rationality and accuracy of the structural parameters.

[0017] 102. Obtain a preset standardized rule base, and perform three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationships; In this embodiment, the pre-defined standardized rule base is built around the modular design requirements of amorphous alloy dry-type transformers, covering five major categories of modules: core, coil, clamps, leads, and assembly. It also clarifies the parameter constraints and geometric adaptation specifications for specific components under each module category. Specifically, the core module corresponds to the amorphous alloy core and core tie plate, and the rules strengthen the stress resistance and installation spacing constraints of the core tie plate to prevent brittle fracture of the amorphous alloy core due to assembly stress. The coil module corresponds to the high-voltage coil and low-voltage coil, and, in conjunction with dry epoxy encapsulation or casting processes, clarifies the winding insulation thickness, heat dissipation gap, and winding accuracy specifications. The clamping module corresponds to the transformer body cover, high-voltage upper clamp, low-voltage upper clamp, lower clamp, base, and riser, adapting to the characteristics of dry-type structures without oil tank support. It refines the clamping force parameters for the iron core and the insulation support requirements for the base. The lead wire module corresponds to the low-voltage outgoing copper busbar, zero-phase connection copper busbar, and high-voltage lead wires, based on the dry-type insulation distance standard, clarifying the copper busbar cross-sectional specifications, lead wire bending radius, and insulation wrapping parameters. The assembly module corresponds to components and processes such as final assembly, transformer body pre-assembly, lead wire assembly, and pull screws, focusing on standardizing the assembly force of amorphous alloy iron cores, the alignment accuracy of windings and clamps, and the tightening torque criteria for pull screws. Based on this rule base, 3D module parameter rule matching is performed on the transformer structure dataset. The core process involves comparing key data from the structural dataset, such as core dimensions, winding key parameters, conductor specifications, clamp installation dimensions, lead cross-sectional dimensions, and assembly datum, with the corresponding module and specific component parameter constraints and geometric adaptation requirements in the rule base. This process filters out target 3D modules that match each structural parameter. Simultaneously, it establishes a correspondence between each parameter in the structural dataset and the corresponding module and component geometric attributes and assembly parameters. Integrating all rule-validated relationships forms the parameter mapping relationship. Standardized rule constraints enable a standardized matching process, eliminating reliance on manual knowledge of amorphous alloy material properties and dry process requirements. This avoids design errors such as material damage and insulation hazards caused by human matching bias, significantly improving the efficiency and accuracy of parameter matching. The clear parameter mapping relationship provides a clear basis for subsequent 3D model parameter updates, ensuring that the 3D model accurately reflects the design intent of the structural dataset.

[0018] 103. Obtain the initial three-dimensional model parameter set, and update the initial three-dimensional model parameter set based on the parameter mapping relationship to obtain the target three-dimensional model parameter set; In this embodiment, the initial 3D model parameter set corresponds to various modules and components such as core, coil, clamp, lead, and assembly. It covers core parameters such as basic geometric dimensions, assembly positioning reference, and insulation gap, and serves as the initial basic data for model construction, acting as the initial carrier framework for model updates. Updating the initial 3D model parameter set based on the established parameter mapping relationship involves relying on the clearly defined correspondence between structural parameters and 3D module attributes. This involves replacing or correcting the corresponding basic parameters in the initial 3D model parameter set one by one with key design parameters from the transformer structure dataset, such as amorphous alloy core stack thickness, column diameter, yoke height, dry winding axial height, radial thickness, insulation thickness, clamp fastening adaptation dimensions, lead cross-sectional specifications, and assembly gaps. The update process follows the module adaptation criteria defined by mapping relationships, focusing on the compatibility between amorphous alloy core parameters and core plate stress, the matching degree between dry winding parameters and clamp insulation support, and the synergy between lead parameters and assembly process requirements. This avoids problems such as module interference and insufficient insulation distance after parameter updates, ultimately forming a target 3D model parameter set that perfectly matches the design structure dataset and meets the characteristics and manufacturing process requirements of amorphous alloy dry-type transformers. Using the initial 3D model parameters as a foundation, targeted and precise updates are achieved through parameter mapping relationships, abandoning the traditional manual adjustment of model parameters and effectively avoiding parameter deviations caused by manual operation.

[0019] 104. Verify the parameter set of the target 3D model. When the verification is successful, output the 3D engineering drawings of the transformer based on the parameter set of the target 3D model.

[0020] In this embodiment, the parameter set of the target 3D model is verified. Specifically, a multi-dimensional systematic check is conducted on the structural characteristics, process requirements, and performance standards of the amorphous alloy dry-type transformer to ensure the rationality, adaptability, and compliance of the parameter set. During the verification process, the geometric dimensional adaptability of each module and component is checked, confirming the matching degree of the amorphous alloy core stack thickness, column diameter, and clamping fastening dimensions; the coordination of the axial height and radial thickness of the dry winding with the core window height and insulation gap; and the fit between the lead cross-section specifications and the assembly channel dimensions to avoid assembly interference between modules. At the same time, for the characteristics of this type of transformer, the stress parameters of the core pull plate are specifically verified to ensure that they meet the requirements for amorphous alloy core embrittlement protection; the insulation thickness of the dry winding and the insulation distance of the lead wires meet the oil-free insulation standard; and the heat dissipation gap parameters are adapted to the dry heat dissipation process. Simultaneously, the performance indicators derived from electromagnetic calculations are correlated to verify whether the parameter set can guarantee that core performance such as no-load loss and short-circuit impedance meet the standards. Verification is conducted based on industry design specifications, modular production process guidelines, and pre-set performance requirements. Each parameter is checked and confirmed individually to eliminate issues such as parameter deviations, compatibility conflicts, and process inconsistencies. Upon successful verification, 3D engineering drawings of the transformer are output based on the target 3D model parameter set. These drawings must fully represent the 3D solid models of each module of the amorphous alloy dry-type transformer, showcasing the overall assembly relationships. They must accurately label core dimensions, assembly benchmarks, insulation requirements, and process prohibitions, clearly defining targeted technical parameters such as the stress limitations of amorphous alloy core assembly, dry-winding insulation treatment specifications, and lead arrangement processes. This provides precise technical guidance for production, assembly, and debugging. Through multi-dimensional targeted verification, design defects such as amorphous alloy core brittleness, dry-winding insulation failure, and module assembly interference are identified and mitigated in advance, ensuring that the target 3D model parameter set fully matches actual production processes and performance requirements, laying a solid foundation for subsequent production stages. The 3D engineering drawings output after successful verification are accurate, standardized, and feasible, directly guiding modular assembly and component processing in the workshop, significantly reducing rework losses due to design errors and improving production efficiency.

[0021] In this embodiment of the invention, the performance requirement parameter set includes rated capacity, rated voltage, rated frequency, and rated current. The electromagnetic calculation of the performance requirement parameter set to obtain the transformer structure dataset includes: determining the transformer core flux density based on the rated capacity, rated voltage, and rated frequency; calculating the transformer main flux and the number of turns in the high and low voltage windings based on Faraday's law of electromagnetic induction and the transformer core flux density; determining the winding current density based on the rated current and calculating the winding conductor cross-sectional area based on the winding current density; calling a pre-trained transformer performance calculation model, and performing verification and optimization processing on the transformer core flux density, the transformer main flux, the number of turns in the high and low voltage windings, and the winding conductor cross-sectional area based on the transformer performance calculation model to obtain a target intermediate derivation parameter set; and determining the core size and winding structure parameters based on the target intermediate derivation parameter set to obtain the transformer structure dataset.

[0022] In this embodiment, the rated capacity, rated voltage, rated frequency, and rated current covered by the performance requirement parameter set are the core basic indicators for carrying out electromagnetic calculations of amorphous alloy dry-type transformers and clarifying the design direction. They directly determine the transformer's operating level, energy conversion efficiency, and applicable scenarios, providing accurate input basis for subsequent electromagnetic calculations.

[0023] Electromagnetic calculations are performed on this set of performance requirements to obtain a transformer structure dataset. This process must proceed step-by-step, following a calculation logic that adapts to the characteristics of amorphous alloy materials and dry insulation processes. First, the core magnetic flux density is determined by combining the rated capacity, rated voltage, and rated frequency. Amorphous alloy materials are typically suited to a magnetic flux density range of 1.3-1.5T. For rated capacity, large-capacity transformers require a slightly lower magnetic flux density value to control overall core losses and temperature rise. Small-capacity transformers can use a higher value within the material's tolerance range to improve electromagnetic conversion efficiency. For example, small-capacity transformers generally refer to products with a rated capacity ≤1600kVA. These transformers have relatively small core volumes and weaker cumulative loss effects. Within the 1.3-1.5T magnetic flux density suitability range for amorphous alloy materials, a relatively higher value, such as 1.4-1.5T, can be selected to improve electromagnetic conversion efficiency without causing excessive temperature rise due to concentrated losses. This is combined with the rated voltage... Regarding voltage and frequency, in a 50Hz power frequency scenario, the higher the voltage level, the lower the magnetic flux density needs to be to avoid core magnetic saturation. For example, in the design of a 10kV amorphous alloy dry-type transformer, a higher value of 1.4-1.5T core magnetic flux density can be selected. This value can take advantage of the high permeability of amorphous alloy without causing the risk of magnetic saturation. When the voltage level is increased to 35kV, if the original magnetic flux density is maintained, the excitation voltage of the core magnetic circuit will increase significantly, and the core is very likely to enter the saturation region, resulting in a significant increase in excitation current, which in turn leads to excessive losses and noise. Therefore, the magnetic flux density needs to be reduced to 1.35-1.4T, which at the same time meets the material advantages of high permeability and low no-load loss of amorphous alloy, and takes into account the limit requirements of GB / T standard for amorphous alloy transformer losses. The final determined magnetic flux density ensures the high efficiency of electromagnetic conversion and avoids the problem of a surge in additional core losses and excessive temperature rise caused by excessively high values.

[0024] Subsequently, the main magnetic flux and the number of turns in the high and low voltage windings were derived based on Faraday's law of electromagnetic induction. The main magnetic flux calculation was based on the determined core magnetic flux density, and a preliminary estimate was made in combination with the effective cross-sectional area of ​​the core. The calculation formula is Φ=B×S1×Kfe (Φ is the main magnetic flux, in Wb; B is the core magnetic flux density, in T; S1 is the nominal cross-sectional area of ​​the core column, in m², which is the total cross-sectional area of ​​the theoretically designed core column laminations; Kfe is the core lamination coefficient, which is usually taken as 0.88~0.9 for amorphous alloy cores). The lamination coefficient has been incorporated into the main magnetic flux calculation process to correct the influence of air gaps and gaps on the effective magnetic conduction area of ​​the core when amorphous alloy strips are stacked, ensuring that the calculated value of the main magnetic flux closely matches the actual magnetic conduction effect. When deriving the number of turns in the high-voltage and low-voltage windings based on the main magnetic flux corrected by the lamination factor and the rated voltage, the core calculation formula for the number of turns in the high-voltage winding is N1=U1 / (4.44×f×Φ×Kp) (N1 is the number of turns in the high-voltage winding; U1 is the phase voltage on the high-voltage side, in V; f is the rated frequency, in Hz; Φ is the main magnetic flux corrected by the lamination factor, in Wb; Kp is the winding short-pitch factor, which is typically taken as 0.95~1.0 for dry windings). That is, the number of turns in the high-voltage winding is obtained by dividing the phase voltage on the high-voltage side by the product of the constant 4.44, the rated frequency, the main magnetic flux corrected by the lamination factor, and the winding short-pitch factor; the number of turns in the low-voltage winding... Based on the turns ratio, the core calculation formula is N2 = N1 × U2 / U1 (N2 is the number of turns in the low-voltage winding; U2 is the low-voltage side phase voltage, in V). This is obtained by multiplying the number of turns in the high-voltage winding by the low-voltage side phase voltage and then dividing by the high-voltage side phase voltage. At the same time, the number of turns can be finely adjusted by ±1 according to the dry winding process to ensure that the turns ratio accuracy meets the national standard requirements. During the derivation of the number of turns, the winding process and insulation layout requirements of the dry winding must be taken into account simultaneously. The value of the number of turns must be adapted to the design space of the axial height and radial thickness of the subsequent winding to ensure the compatibility of the winding with the core window height and window width, providing quantitative support for the determination of subsequent structural parameters.

[0025] Next, the winding current density is set based on the rated current, and the conductor cross-sectional area is calculated. Since amorphous alloy dry-type transformers do not have oil-immersed heat dissipation medium, winding heat dissipation relies on air convection and insulation conduction, making heat dissipation conditions relatively stringent. Therefore, the current density is usually controlled within the range of 2.5-3.5 A / mm². The specific value needs to be calibrated in conjunction with the rated current and heat dissipation scheme. For example, a lower current density is used when the rated current is larger. At the same time, the winding insulation class must be matched. The upper limit of the current density for F-class insulation windings is lower than that for H-class insulation to ensure that the winding temperature rise during operation does not exceed the standard limit. The conductor cross-sectional area is calculated based on the set current density. The calculation logic is to divide the rated phase current by the current density to obtain the winding conductor cross-sectional area. This cross-sectional area parameter directly determines the physical dimensions, current carrying capacity, and heat dissipation efficiency of the winding. It also needs to be coordinated and adapted with the number of winding turns. The larger the cross-sectional area, the larger the radial thickness of the winding. The number of turns distribution needs to be adjusted synchronously to control the overall dimensions of the winding, ensuring that it matches the core window width and clamp installation space. This is the core and key basis for winding structure design.

[0026] Based on this, a pre-trained transformer performance calculation model is invoked. This model is a multi-dimensional coupled integrated calculation model based on gradient boosting decision tree and multi-objective genetic algorithm, designed and developed for amorphous alloy dry-type transformers. It includes a performance parameter calculation module, a performance index verification module, and a parameter optimization module, which are connected sequentially. The training dataset of this model covers engineering measured data of amorphous alloy dry-type transformers, electromagnetic and thermal simulation data, and performance index limits and parameter design compliance ranges specified in relevant national standards. The algorithm fusion and training logic of each module are as follows: The performance parameter calculation module uses gradient boosting decision tree as the core, inputs amorphous alloy magnetic properties, insulation and heat dissipation parameters, and fits the output core magnetic flux density, winding parameters, etc., to accurately establish parameter mapping relationships; the performance index verification module relies on gradient boosting decision tree to predict indicators such as no-load loss and short-circuit impedance, and completes compliance verification by combining national standard thresholds; the parameter optimization module achieves multi-objective optimization through multi-objective genetic algorithm fusion, and quickly evaluates the performance of the scheme and corrects parameter deviations by combining gradient boosting decision tree. After training, each module is integrated and coupled for debugging, and then verified and iterated through engineering measured cases to complete the pre-training. The model deeply integrates core characteristic parameters, allowing for the verification of key parameters and indicators one by one. Through multiple rounds of optimization and correction, a target intermediate derivation parameter set that balances performance, process, and material characteristics is ultimately obtained. Subsequently, based on this target intermediate derivation parameter set, the core size and winding structure parameters are further determined. Specifically, by combining the core magnetic flux density, main magnetic flux, and the mechanical properties of the amorphous alloy core, core size parameters such as core column diameter, stack thickness, and yoke height are determined to ensure core structural stability and full utilization of magnetic properties. The core column diameter is calculated based on the main magnetic flux and core magnetic flux density. First, the effective cross-sectional area S2 of the core column is derived using the main magnetic flux calculation formula Φ=B×S2×Kfe (Φ is the main magnetic flux, B is the core magnetic flux density, S2 is the effective cross-sectional area of ​​the core column, and Kfe is the core lamination coefficient, typically 0.88~0.9 for amorphous alloy cores). Then, the effective cross-sectional area S2 is calculated using... The standard forming width of amorphous alloy strip (commonly 210mm, 230mm, 270mm, etc., to meet the modular design requirements of dry-type transformers) determines the actual cross-sectional area and diameter of the core column. The column diameter must be a suitable value for the amorphous alloy strip rolling process, and the effective cross-sectional area of ​​the core column must have a margin of 5% to 8% higher than the calculated value to avoid magnetic performance loss caused by air gaps in the magnetic circuit of the amorphous alloy core. The core stack thickness is derived based on the effective cross-sectional area of ​​the core column, the core column width, and the core lamination coefficient. The stack thickness calculation logic is equal to the effective cross-sectional area of ​​the core column divided by the product of the core column width and the core lamination coefficient. The lamination coefficient of amorphous alloy cores is typically taken as 0.88 to 0.9 (Determined by the surface characteristics and stacking process of the amorphous alloy strip, a commonly used value in the industry), the stacking thickness must be an integer multiple of the thickness of a single sheet of amorphous alloy strip, and the stacking thickness must be compatible with the clamping spacing requirements of subsequent clamps to ensure that the core stack is compact and free from looseness; the yoke height is determined based on the core column diameter, combined with the magnetic circuit closure requirements of the amorphous alloy core and the process limitations of the dry-type transformer body height, and is generally taken as 1.0 to 1.2 times the core column diameter; based on the number of turns of the high and low voltage windings, the conductor cross-sectional area, and the dry-type winding process requirements, combined with GB / T Standard 1094.11-2022, "Power Transformers Part 11: Dry-Type Transformers," specifies the insulation and structure of dry-type transformers. Winding structural parameters such as axial height, radial thickness, insulation thickness, and winding spacing are determined through parameter-based calculations. For example, the axial height is calculated based on the number of turns in the high and low voltage windings and the conductor diameter matching the conductor cross-sectional area, combined with the number of winding rows. The number of winding rows is a standard process adaptation parameter for amorphous alloy dry-type transformers, determined by a bidirectional adaptation between the number of turns and the core window height (the winding is an internal component of the core window; the number of winding rows must simultaneously meet the winding layout requirements of the number of turns and ensure that the theoretical axial height of the wound winding does not exceed the effective utilization range of the core window height). The calculation formula is: Axial height of winding = Number of turns. The radial thickness of the winding is calculated based on the conductor diameter corresponding to the conductor cross-sectional area and the number of parallel windings adapted to the rated current, combined with the interlayer insulation thickness of the dry-type winding and the number of winding layers. The formula is: Radial thickness of winding = (Conductor diameter × Number of parallel windings + Interlayer insulation thickness) × Number of winding layers. Here, the conductor diameter is calculated from the conductor cross-sectional area; the number of parallel windings is determined by adapting the rated current to the conductor's current-carrying capacity; the interlayer insulation thickness is selected according to the voltage level and epoxy insulation process; and the number of winding layers is derived from the total number of turns and the number of parallel windings. The insulation thickness is directly determined according to the transformer's rated voltage level. The winding spacing is determined based on the transformer's rated voltage level, combined with the insulation distance requirements of the dry-type transformer.

[0027] The clamping, lead wire, and assembly parameters are determined based on the aforementioned core dimensions and winding structure parameters, combined with the characteristics of amorphous alloy materials, dry-type process requirements, and national standards. For the clamping parameters, the core cylinder diameter, stack thickness, and yoke height are the core considerations. To accommodate the brittleness and poor resistance to excessive mechanical stress of the amorphous alloy core, the clamping inner diameter, fastening adaptation dimensions, and insulation support spacing of the clamping components are determined. Simultaneously, the clamping installation points and pull plate layout are calibrated based on the radial thickness of the winding. The insulation protection dimensions and fastening torque limits of the clamping components are clarified to ensure stable clamping of the core without mechanical damage, balancing dry-type insulation and structural stability. For the lead wire parameters, the lead wire cross-sectional specifications are determined based on the winding conductor cross-sectional area, rated current, and voltage level. The insulation layer thickness, combined with the winding axial height, lead-out position, and spatial layout of the core and clamps, determines the bending radius, fixing points, and arrangement path of the leads. This also matches the insulation distance requirements of dry-type transformers, avoiding structural interference between the leads and the windings / core, while balancing current carrying capacity and insulation safety. For assembly parameters, using the overall dimensions of the core, windings, and clamps as a benchmark, and considering the air convection heat dissipation characteristics of dry-type transformers, the assembly gaps between the core and windings, windings and clamps, and clamps and the outer shell are determined. The assembly alignment benchmarks for each component, the spacing of the insulation pads, and the overall tightening torque requirements are clearly defined. This ensures assembly accuracy and structural stability while reserving sufficient heat dissipation and process operation space, adapting to the needs of large-scale assembly.

[0028] Finally, a complete transformer structure dataset is formed through integration. The intervention of a pre-trained transformer performance calculation model enables closed-loop verification and optimization of intermediate parameters, further avoiding parameter conflicts and performance defects. The resulting transformer structure dataset can connect performance requirements with physical structure design.

[0029] In this embodiment, the transformer performance calculation model includes a performance parameter calculation module, a performance index verification module, and a parameter optimization module, which are connected sequentially. The step of verifying and optimizing the transformer core magnetic flux density, the transformer main magnetic flux, the number of turns in the high and low voltage windings, and the cross-sectional area of ​​the winding conductors based on the transformer performance calculation model to obtain a target intermediate derivation parameter set includes: performing performance calculations on the transformer core magnetic flux density, the transformer main magnetic flux, the number of turns in the high and low voltage windings, and the cross-sectional area of ​​the winding conductors based on the performance parameter calculation module to obtain a transformer performance verification parameter set; verifying the transformer performance verification parameter set based on the performance index verification module, and obtaining an out-of-target parameter set when the verification fails; and performing multi-round iterative optimization processing on the out-of-target parameter set based on the parameter optimization module to obtain the target intermediate derivation parameter set.

[0030] In this embodiment, the transformer performance calculation model consists of a performance parameter calculation module, a performance index verification module, and a parameter optimization module. Through the coordinated operation of these three modules, the quantitative calculation, compliance verification, and precise correction of intermediate derivation parameters are realized, and finally, a target intermediate derivation parameter set that adapts to the characteristics of amorphous alloy materials and the requirements of dry process is output.

[0031] Specifically, firstly, regarding the core magnetic flux density and main magnetic flux, the performance parameter calculation module relies on the preset magnetization curve and specific loss curve of the amorphous alloy material, combined with the quantitative correlation between the core magnetic flux density and the effective cross-sectional area and weight of the core, to calculate the no-load loss of the core under the corresponding magnetic flux density through the magnetic energy loss conversion method. Simultaneously, combining the correlation between the main magnetic flux and the number of winding turns and the inherent impedance characteristics of the transformer, the module derives the basic value of the voltage regulation rate through the correlation derivation method between electromagnetic induction and voltage change. Regarding the number of turns in the high and low voltage windings, the performance parameter calculation module calculates the transformation ratio accuracy using the transformation ratio calculation formula based on the matching relationship between the turns ratio and the rated voltage. Simultaneously, combining the preliminary winding structure parameters such as the axial height and radial thickness of the windings, and based on the electromagnetic coupling law between windings and the leakage magnetic circuit calculation method, the theoretical value of the short-circuit impedance is derived. Specifically, the leakage magnetic resistance and leakage magnetic potential are first calculated from the winding structure parameters to obtain the leakage inductance, which is then substituted into the core formula Z for short-circuit impedance. k =2πfL k ×10 3 (Z) k The short-circuit impedance is given in Ω; f is the rated frequency in Hz; L k The leakage inductance of the winding (in mH) is calculated, and an amorphous alloy leakage magnetic flux correction coefficient K is introduced. σ (1.02~1.05) Results adaptation and correction; For the winding conductor cross-sectional area, the performance parameter calculation module, combined with the set current density, calculates the winding resistance using R=ρlN / S3 (ρ is the conductor resistivity, l is the length of a single turn of conductor, N is the number of turns in the winding, and S3 is the conductor cross-sectional area). Based on the winding resistance, the winding copper loss is derived, which is the transformer's load loss. Then, based on the winding copper loss and the air convection heat dissipation conditions of the amorphous alloy dry-type transformer, Newton's cooling formula ΔT=P is used. Cu / (K×A) (ΔT is the estimated temperature rise in K; K is the comprehensive heat dissipation coefficient of air convection, taken as 8~12W / (m²)) K); A is the effective heat dissipation area of ​​the winding. The estimated temperature rise under rated load is calculated, and the thermal conductivity of the dry winding insulation layer is considered to accurately correct the estimated temperature rise, i.e., based on the thermal conductivity of the epoxy insulation layer (0.3~0.4 W / (m²)). The thermal resistance is calculated based on the thickness (K), and a process correction factor (0.95~1.05) is introduced. The temperature rise due to stray losses in the amorphous alloy core (2~5K) is then added to complete the multi-dimensional calibration. Finally, the modules are integrated to obtain a set of transformer performance verification parameters covering key indicators such as no-load loss, load loss, short-circuit impedance, voltage regulation, and winding temperature rise.

[0032] Then, the performance index verification module conducts compliance verification based on the industry design standards, energy-saving specifications, and dry-type process requirements corresponding to amorphous alloy dry-type transformers. During the verification process, the performance index verification module compares each performance verification parameter with the preset threshold one by one. For example, the no-load loss must meet the energy-saving level limit of amorphous alloy transformers, the winding temperature rise must match the temperature rise standard of the corresponding insulation class (F class, H class, etc.), the short-circuit impedance must be controlled within the allowable range of grid-connected operation, and the voltage regulation rate must meet the voltage stability requirements during load operation. If all parameters are within the preset threshold, it indicates that the core intermediate parameters are well adapted and no adjustment is needed. When a parameter exceeds the threshold, the module accurately locates the source intermediate parameter corresponding to the exceeding indicator, forms a clear set of exceeding parameters, and marks the exceeding item (such as excessive core magnetic flux density corresponding to excessive no-load loss, and insufficient conductor cross-sectional area corresponding to excessive temperature rise) and the exceeding magnitude.

[0033] Finally, the parameter optimization module performs multiple rounds of iterative optimization on the set of parameters exceeding the limits output by the performance index verification module. Specifically, the parameter optimization module derives parameter adjustment schemes in reverse based on the causes of exceeding the limits. For example, when the no-load loss exceeds the limit, based on the magnetic flux density adaptation range of the amorphous alloy iron core (1.3-1.5T) and the loss limit requirements in the GB / T standard, the iron core magnetic flux density is appropriately reduced by 0.05-0.1T / time. The reduction range needs to be calibrated in conjunction with the proportion of loss exceeding the limit. If the loss exceeds the limit by 5%-10%, it is reduced by 0.05T; if it exceeds the limit by 10%-20%, it is reduced by 0.08T; if it exceeds the limit by >20%, it is first reduced by 0.1T, while reserving a subsequent fine-tuning space of 0.03-0.05T, and the magnetic flux density after the reduction must not be lower than 1. 3T; When the temperature rise exceeds the standard, based on the winding current density control range (2.5-3.5A / mm²), increase the winding conductor cross-sectional area by 5%-15% per cycle, correspondingly reducing the current density to 2.2-2.8A / mm², while adapting to the heat dissipation space requirements of dry windings; When the short-circuit impedance exceeds the standard, if the impedance is too high, increase the winding spacing by 0.3-1mm per cycle, and if the impedance is too low, decrease the winding spacing by 0.2-0.8mm per cycle (the spacing adjustment must meet the insulation distance requirements of the corresponding voltage level, and the minimum insulation spacing for 10kV level is not less than 12mm), or fine-tune the number of turns of high and low voltage windings by ±1-2 turns per cycle. The number of turns adjustment must strictly follow the transformation ratio relationship to ensure that the transformation ratio accuracy deviation is controlled within ±0.5% and that the transformation ratio accuracy is not affected. After each parameter adjustment, the module will send the optimized core intermediate parameters back to the performance parameter calculation module to re-perform performance calculation and index verification to form an iterative closed loop. Through multiple rounds of iterative adaptation, various out-of-standard parameters are gradually corrected until all performance verification parameters meet the preset standards, and finally, a target intermediate derivation parameter set that takes into account electromagnetic performance, material properties, and dry process requirements is output.

[0034] In this embodiment of the invention, the standardized rule base includes multiple three-dimensional transformer modules and a module matching threshold corresponding to each module. The step of performing three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationships includes: acquiring preset three-dimensional module partitioning rules; performing category partitioning processing on the transformer structure dataset based on the three-dimensional module partitioning rules to obtain multiple categorized structure data subsets; comparing each categorized structure data subset with its corresponding module matching threshold, and filtering to obtain transformer three-dimensional modules that are compatible with each categorized structure data subset; establishing a mapping relationship between each categorized structure data subset and its corresponding transformer three-dimensional module, generating multiple association items; and integrating all the association items to obtain the parameter mapping relationship.

[0035] In this embodiment, a pre-defined standardized rule base is constructed around the modular design requirements of amorphous alloy dry-type transformers, covering five major categories of modules: core, coil, clamps, leads, and assembly. Each module corresponds to a pre-defined module matching threshold. This threshold system fully adapts to the characteristics of amorphous alloy materials and the requirements of dry-type processes. It includes not only geometric size matching thresholds, such as the stacking thickness range of the core module and the axial height matching range of the coil module, but also performance and process constraint thresholds, such as the magnetic flux density matching limit of the core module, the insulation thickness threshold of the dry winding, the clamping force threshold, and the insulation distance threshold of the leads, providing a quantitative basis for accurate module matching.

[0036] In this embodiment, a preset three-dimensional module partitioning rule is first obtained. This rule is formulated based on the structural composition and assembly logic of the amorphous alloy dry-type transformer. The dimensions are clearly defined according to module function and type. The core parameters in the transformer structure dataset are split according to the corresponding module categories, completing the category partitioning process. After partitioning, multiple categorized structural data subsets are obtained. Each subset corresponds to the exclusive structural parameters of a type of three-dimensional module. For example, the core category structural data subset covers parameters such as amorphous alloy core stack thickness, column diameter, and yoke height; the coil category structural data subset includes parameters such as dry winding axial height, radial thickness, insulation thickness, and conductor specifications; the clamp category structural data subset is determined based on core dimensional parameters such as core stack thickness and column diameter, involving clamp fastening. Parameters such as dimensions, insulation support spacing, pull plate mounting points, and insulation protection dimensions are adapted to the brittle characteristics of amorphous alloy cores and the need for stable clamping. The lead wire classification structure data subset is determined based on the cross-sectional area, axial height, and rated voltage level of the winding conductors, including parameters such as lead wire cross-sectional specifications, insulation layer thickness, bending radius, and fixing points, taking into account both current carrying capacity and insulation protection. The assembly classification structure data subset is determined based on the overall dimensional parameters of the core, coil, and clamps, covering parameters such as assembly gaps of each component, alignment references, fastening torque, and insulation pad spacing, balancing structural stability and heat dissipation requirements. This ensures that the data in each subset is highly consistent with the attributes of the corresponding module, improving comparison efficiency and screening accuracy, and avoiding deviations caused by mixing overall data.

[0037] Subsequently, each subset of the classification structure data is compared one by one with the matching threshold of the corresponding module in the rule base. Taking the core classification structure data subset as an example, stack thickness and column diameter are the core parameters for adapting the core module. They need to be compared accurately with the stack thickness range and column diameter threshold of the core module in the rule base. The yoke height is used as an auxiliary adaptation parameter for synchronous verification. Only when the core parameters fully meet the corresponding threshold requirements and the auxiliary parameters have no fundamental conflict can the core module be initially determined as an adaptation candidate. The coil classification structure data subset uses axial height and radial thickness as the core adaptation parameters and compares them with the corresponding threshold of the coil module. Insulation thickness and wire specifications are used for auxiliary verification. The clamps, leads, and assembly subsets are also processed in the same way. The priority is determined by combining the core functional attributes of each module, and multi-parameter collaborative comparison is completed. Finally, the module that matches all the parameters of the subset is selected as the corresponding module. If a parameter exceeds the threshold range during the comparison process, it will be handled according to the suitability priority: if the auxiliary suitability parameter exceeds the threshold and the deviation is within the fine-tuning range allowed by the characteristics of amorphous alloy materials and dry process, the parameter will be corrected by process (such as fine-tuning the yoke height and insulation support spacing), and then the comparison will be carried out again; if the core suitability parameter exceeds the threshold, or the deviation of the auxiliary parameter is too large to be avoided by fine-tuning, it indicates that the current classification structure data subset and the existing modules in the rule base cannot be matched. At this time, return to the transformer structure dataset generation stage, correct the corresponding core structure parameters, and after the correction is completed, re-perform module division and threshold comparison.

[0038] Based on this, a clear correspondence is established between each subset of categorized structural data and the corresponding selected 3D transformer modules, forming multiple association items. Each association item clearly defines the adaptation logic between various structural parameters within the subset of categorized structural data and the geometric attributes, assembly datum, and process requirements of the 3D module. For example, the association item between the core categorized structural data subset and the amorphous alloy core module clarifies the correspondence between the core stack thickness, column diameter, and the geometric modeling datum and mounting hole positions of the core module; the association item between the coil categorized structural data subset and the high-voltage coil module defines the winding... The system establishes several key parameters: axial height, insulation thickness, and the number of winding layers and interlayer insulation layout of the coil module; it also defines the compatibility rules between the clamping component classification data subset and the clamping module, specifying the compatibility logic for fastening dimensions, insulation support spacing, clamping range, and insulation pad arrangement; the lead wire classification data subset and the lead wire module, defining the compatibility rules for cross-sectional specifications, bending radius, lead wire current carrying capacity, and spatial wiring layout; and the assembly classification data subset and the assembly module, specifying the compatibility requirements for assembly clearance, fastening torque, alignment accuracy of each component, and structural stability. Finally, all related parameters are integrated, redundant compatibility logic is eliminated, and a complete and unified parameter mapping relationship is formed.

[0039] In this embodiment of the invention, the standardized rule base further includes parameter adjustment rules. After verifying the target 3D model parameter set, the method further includes: when the verification fails, obtaining the out-of-standard parameter set and the compliant parameter set in the target 3D model parameter set; performing deviation correction processing on the out-of-standard parameter set based on the parameter adjustment rules to obtain a corrected parameter set; integrating the corrected parameter set and the compliant parameter set to obtain a corrected 3D model parameter set, and outputting 3D engineering drawings of the transformer based on the corrected 3D model parameter set.

[0040] In this embodiment, the parameter adjustment rules in the standardized rule base are specific correction guidelines formulated by combining the material characteristics of amorphous alloy dry-type transformers, dry-type insulation process requirements, and industry design standards. They cover the adjustment logic, amplitude limits, and coordination adaptation requirements for parameters exceeding the standard in each module. They not only clarify the correction direction for a single parameter exceeding the standard, but also take into account compatibility with compliant parameters, avoiding new parameter conflicts after correction. For example, for the amorphous alloy core column diameter exceeding the standard, the rules limit the process fine-tuning amplitude to the range of 5-10mm, and simultaneously adjust the yoke height to adapt to the corrected column diameter, ensuring the core magnetic circuit closure and structural symmetry. For the winding insulation thickness exceeding the standard (not meeting the creepage distance requirements of the corresponding voltage level), the rules clearly stipulate that the insulation layer should be thickened according to the voltage level. For the 10kV level, an additional 0.2-0.3mm epoxy insulation layer should be added, and the radial thickness of the winding should be fine-tuned to reserve installation space after the insulation is thickened to adapt to the core window width layout.

[0041] In this embodiment, after verifying the parameter set of the target 3D model, if any verification fails, the parameters are first classified and split, extracting the out-of-standard parameter set that exceeds a preset threshold and the compliant parameter set that meets the standard. The out-of-standard parameter set must clearly indicate the out-of-standard items and deviation ranges, and the out-of-standard type is defined based on the characteristics of the amorphous alloy dry-type transformer. For example, winding insulation thickness not meeting dry-type creepage distance requirements, clamp fastening dimensions not matching the core embrittlement protection threshold, and lead insulation distance exceeding the standard are all included in the out-of-standard parameter set. The compliant parameter set retains the core parameters that do not require adjustment. Subsequently, based on the parameter adjustment rules in the standardized rule base, targeted deviation correction processing was carried out on the parameter sets that exceeded the standard. The correction process followed the logic and limits set by the rules. For example, if the magnetic flux density of the iron core exceeded the standard, the magnetic flux density was appropriately reduced according to the rules, and the iron core stacking parameters were adjusted simultaneously to compensate for the change in magnetic flux, taking into account both the magnetic performance and mechanical protection requirements of the amorphous alloy iron core; if the winding temperature rise exceeded the standard, the conductor cross-sectional area was increased to reduce the current density according to the rules, and the winding axial height and interlayer heat dissipation gap were finely adjusted to ensure that the corrected winding meets the current carrying requirements and is compatible with the dry heat dissipation process; if the clamp fastening parameters exceeded the standard, the fastening force and installation spacing were adjusted according to the rules to avoid mechanical damage to the amorphous alloy iron core; if the lead insulation distance exceeded the standard, the lead layout path and cross-sectional specifications were corrected in combination with the rules to ensure compliance with the dry insulation level requirements. Finally, the corrected parameter set and the compliant parameter set are integrated, duplicate parameter items are removed, and parameter association logic is calibrated to form a complete corrected 3D model parameter set. This parameter set not only solves the original out-of-standard problem, but also ensures that the parameters of each module are adapted to the material characteristics, process requirements, and performance standards of the amorphous alloy dry-type transformer, achieving overall parameter compliance and coordination. Based on this corrected 3D model parameter set, the transformer's 3D engineering drawings are output. The drawings need to be updated with the corrected core parameter annotations and the adjusted process requirements are clearly defined, such as the corrected core magnetic flux density, winding wire specifications, and clamping torque, providing accurate technical basis for production and assembly.

[0042] In this embodiment, precise and standardized correction of out-of-standard parameters is achieved through parameter adjustment rules, eliminating the blindness of manual experience-based adjustments and significantly reducing parameter correction deviations. Simultaneously, it takes into account the unique characteristics of amorphous alloy dry-type transformers, effectively avoiding potential risks such as core embrittlement, insulation failure, and insufficient heat dissipation. By separating compliant and out-of-standard parameters, only out-of-standard items are corrected, preserving the stability of compliant parameters, reducing unnecessary parameter adjustments, improving correction efficiency, and ensuring that the output 3D engineering drawings fully comply with design standards and production process requirements. This significantly reduces production rework losses caused by parameter issues, strengthens the connection between design and production, and simultaneously guarantees the energy-saving performance, operational reliability, and structural stability of amorphous alloy dry-type transformers, adapting to the needs of large-scale production.

[0043] The above describes the method for automatically generating three-dimensional engineering drawings of transformers in embodiments of the present invention. The following describes the apparatus for automatically generating three-dimensional engineering drawings of transformers in embodiments of the present invention. Please refer to [link to relevant documentation]. Figure 2 One embodiment of the transformer three-dimensional engineering drawing automatic generation device of the present invention includes: Electromagnetic calculation module 201: used to obtain a set of transformer performance requirement parameters, perform electromagnetic calculations on the set of performance requirement parameters, and obtain a transformer structure dataset; Matching module 202: used to obtain a preset standardized rule base, and perform three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationship; Parameter update module 203: used to obtain an initial three-dimensional model parameter set, update the initial three-dimensional model parameter set based on the parameter mapping relationship, and obtain a target three-dimensional model parameter set; Drawing output module 204: used to verify the parameter set of the target 3D model, and when the verification is successful, outputs 3D engineering drawings of the transformer based on the parameter set of the target 3D model.

[0044] Based on the same ideas as the methods in the above embodiments, the apparatus provided in this application can implement the methods in the above embodiments.

[0045] above Figure 2 The automatic generation device for three-dimensional engineering drawings of transformers in this embodiment of the invention is described in detail from the perspective of modular functional entities. The automatic generation device for three-dimensional engineering drawings of transformers in this embodiment of the invention is described in detail from the perspective of hardware processing.

[0046] Figure 3This is a schematic diagram of the structure of an automatic transformer 3D engineering drawing generation device 300 provided in an embodiment of the present invention. The automatic transformer 3D engineering drawing generation device 300 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 310 (e.g., one or more processors) and a memory 320, and one or more storage media 330 (e.g., one or more mass storage devices) storing application programs 333 or data 332. The memory 320 and storage media 330 can be temporary or persistent storage. The program stored in the storage media 330 may include one or more modules (not shown in the diagram), each module may include a series of instruction operations on the automatic transformer 3D engineering drawing generation device 300. Furthermore, the processor 310 may be configured to communicate with the storage media 330 and execute the series of instruction operations in the storage media 330 on the automatic transformer 3D engineering drawing generation device 300 to implement the steps of the automatic transformer 3D engineering drawing generation method provided in the above-described method embodiments.

[0047] The transformer 3D engineering drawing automatic generation device 300 may also include one or more power supplies 340, one or more wired or wireless network interfaces 350, one or more input / output interfaces 360, and / or one or more operating systems 331, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art will understand that... Figure 3 The structure of the transformer 3D engineering drawing automatic generation equipment shown does not constitute a limitation on the transformer 3D engineering drawing automatic generation equipment, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0048] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the steps of the method for automatically generating three-dimensional engineering drawings of a transformer.

[0049] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system, device, or unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0050] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0051] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for automatically generating three-dimensional engineering drawings of transformers, characterized in that, include: Obtain the transformer performance requirement parameter set, perform electromagnetic calculations on the performance requirement parameter set, and obtain the transformer structure dataset; Obtain a preset standardized rule base, and perform three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationships; Obtain an initial 3D model parameter set, and update the initial 3D model parameter set based on the parameter mapping relationship to obtain the target 3D model parameter set; The parameter set of the target 3D model is verified. When the verification is successful, the 3D engineering drawings of the transformer are output based on the parameter set of the target 3D model.

2. The method for automatically generating three-dimensional engineering drawings of transformers according to claim 1, characterized in that, The performance requirement parameter set includes rated capacity, rated voltage, rated frequency, and rated current; the electromagnetic calculation of the performance requirement parameter set to obtain the transformer structure dataset includes: The transformer core magnetic flux density is determined based on the rated capacity, the rated voltage, and the rated frequency. Based on Faraday's law of electromagnetic induction, the main magnetic flux of the transformer and the number of turns of the high and low voltage windings are calculated according to the magnetic flux density of the transformer core. The winding current density is determined based on the rated current, and the cross-sectional area of ​​the winding conductor is calculated based on the winding current density. The pre-trained transformer performance calculation model is invoked, and the transformer core magnetic flux density, transformer main magnetic flux, number of turns of high and low voltage windings and cross-sectional area of ​​winding conductors are verified and optimized based on the transformer performance calculation model to obtain the target intermediate derivation parameter set. Based on the target intermediate derivation parameter set, the core size and winding structure parameters are determined to obtain the transformer structure dataset.

3. The method for automatically generating three-dimensional engineering drawings of transformers according to claim 2, characterized in that, The transformer performance calculation model includes a performance parameter calculation module, a performance index verification module, and a parameter optimization module, which are connected sequentially. Based on the transformer performance calculation model, the transformer core magnetic flux density, the transformer main magnetic flux, the number of turns in the high and low voltage windings, and the cross-sectional area of ​​the winding conductors are verified and optimized to obtain a target intermediate derivation parameter set, including: Based on the performance parameter calculation module, the transformer core magnetic flux density, the transformer main magnetic flux, the number of turns of the high and low voltage windings and the cross-sectional area of ​​the winding conductors are calculated to obtain the transformer performance verification parameter set; The transformer performance verification parameter set is verified based on the performance index verification module. When the verification fails, the set of parameters that exceed the standard is obtained. The parameter optimization module performs multiple rounds of iterative optimization on the set of parameters that exceed the standard to obtain the target intermediate derivation parameter set.

4. The method for automatically generating three-dimensional engineering drawings of transformers according to claim 1, characterized in that, The standardized rule base includes various three-dimensional transformer modules and module matching thresholds corresponding to each module; The step of performing three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationships includes: Obtain a preset three-dimensional module partitioning rule, and perform category partitioning processing on the transformer structure dataset based on the three-dimensional module partitioning rule to obtain multiple categorized structure data subsets; Each subset of the classification structure data is compared with the corresponding module matching threshold, and the transformer three-dimensional module that is compatible with each subset of the classification structure data is selected. Establish a mapping relationship between each of the classification structure data subsets and the corresponding transformer 3D modules, and generate multiple association items; By integrating all the aforementioned related items, the parameter mapping relationship is obtained.

5. The method for automatically generating three-dimensional engineering drawings of transformers according to claim 4, characterized in that, The standardized rule base also includes parameter adjustment rules. After verifying the target 3D model parameter set, the following is also included: When the verification fails, obtain the set of parameters that exceed the standard and the set of parameters that comply with the standard from the parameter set of the target 3D model. Based on the parameter adjustment rules, the set of parameters exceeding the standard is subjected to deviation correction processing to obtain the corrected parameter set; By integrating the modified parameter set and the compliant parameter set, a modified 3D model parameter set is obtained, and a 3D engineering drawing of the transformer is output based on the modified 3D model parameter set.

6. An automatic device for generating three-dimensional engineering drawings of transformers, characterized in that, include: Electromagnetic calculation module: used to obtain the set of transformer performance requirement parameters, perform electromagnetic calculations on the set of performance requirement parameters, and obtain the transformer structure dataset; Matching module: used to obtain a preset standardized rule base, and perform three-dimensional module parameter rule matching on the transformer structure dataset based on the standardized rule base to obtain parameter mapping relationship; Parameter update module: used to obtain the initial 3D model parameter set, update the initial 3D model parameter set based on the parameter mapping relationship, and obtain the target 3D model parameter set; Drawing output module: Used to verify the parameter set of the target 3D model. When the verification is successful, it outputs 3D engineering drawings of the transformer based on the parameter set of the target 3D model.

7. An automatic device for generating three-dimensional engineering drawings of transformers, characterized in that, The automatic generation device for three-dimensional engineering drawings of transformers includes: a memory and at least one processor, wherein the memory stores instructions; At least one of the processors invokes the instructions in the memory to cause the transformer 3D engineering drawing automatic generation device to perform the steps of the transformer 3D engineering drawing automatic generation method as described in any one of claims 1-5.

8. A computer-readable storage medium storing instructions thereon, characterized in that, When the instructions are executed by the processor, they implement each step of the automatic generation method for three-dimensional engineering drawings of transformers as described in any one of claims 1-5.

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