CN-121981795-A - Transformer-based analysis and quotation method, system, equipment and medium

CN121981795ACN 121981795 ACN121981795 ACN 121981795ACN-121981795-A

Abstract

The application discloses a transformer-based analysis and quotation method, a system, equipment and a medium, wherein the method comprises the steps of obtaining a bidding document of a transformer, preprocessing the bidding document, and analyzing according to the preprocessed bidding document and a preset parameter library to determine corresponding technical parameters; and carrying out data processing on the technical parameters according to the technical specifications to determine the material model and the quota, and generating the quotation according to the material model and the quota. The method and the device accurately determine the technical parameters by preprocessing and analyzing the bidding documents through the parameter library, and rapidly determine the material model and the quota by combining technical specification processing data, thereby effectively improving quotation efficiency and accuracy, helping enterprises rapidly respond to markets and enhancing competitiveness.

Inventors

JIA JIA
QI GUANGPENG
LI WEI
TAN NINGNING
LV WENJIE
LI HAOLONG
LU YANG

Assignees

浪潮云洲工业互联网有限公司

Dates

Publication Date: 20260505
Application Date: 20251224

Claims (10)

1. The method for analyzing and quoting based on the transformer is characterized by comprising the following steps of: Acquiring a bidding document of a transformer, preprocessing the bidding document, and analyzing according to the preprocessed bidding document and a preset parameter library to determine corresponding technical parameters; determining an item list according to the bid-inviting file, and searching and matching corresponding technical specifications according to the item list; and carrying out data processing on the technical parameters according to the technical specifications so as to determine the material model and the quota, and generating an quotation according to the material model and the quota.
2. The method of claim 1, wherein the parsing is performed according to the preprocessed bidding document and a preset parameter library to determine corresponding technical parameters, and the method specifically comprises: carrying out structuring treatment on the parameter library to determine structured data, and analyzing the structured data through a preset deep learning model to extract the technical parameters; determining the process requirement of the main transformer, and carrying out preliminary screening and correction on the technical parameters according to the process requirement.
3. The method according to claim 1, wherein the data processing of the technical parameters to determine the material model and the quota is performed according to a technical specification, in particular comprising: Determining materials according to the bidding documents, wherein the materials comprise main materials, auxiliary materials and accessories, and determining corresponding technical conditions in the technical parameters according to the materials; determining the material model according to the technical conditions; And determining project requirements according to the project list, determining a quota according to the material model and the project requirements, and generating a quotation according to the material model and the quota, wherein the quotation comprises a main material, an auxiliary material, a matched set and the quota.
4. The method according to claim 1, wherein the method further comprises: uploading and checking the bid-inviting files of multiple items in batches to determine the accuracy of key materials, technical parameters and quantity in the bid-inviting files; and determining whether the bidding document accords with a preset specification, marking the bidding document which is not checked, and prompting a user to correct.
5. A transformer-based parsing and quotation system, applied to the transformer-based parsing and quotation method according to any one of claims 1 to 4, comprising: The system comprises a standard book analysis module, a standard book analysis module and a standard book analysis module, wherein the standard book analysis module is used for automatically searching and matching a technical standard book according to a project list, preprocessing the standard book, analyzing by uniformly delivering a preset deep learning model after cooperating with a parameter library, and judging and suitability processing the analyzed parameters; The technical file verification module is used for carrying out batch uploading operation on the technical files of the multiple projects, and checking the accuracy of key materials, technical parameters and the number in the technical files so as to ensure that the key materials, the technical parameters and the number meet preset specifications; the collaborative quotation module is used for generating technical quotations, providing quotation for enterprises, automatically calculating material prices, working hours and freight charges, and automatically grabbing prices in a historical price library for price checking; The knowledge base construction module is used for constructing a dynamically updated knowledge base, analyzing based on the client behavior mode and the preference to form client demand portraits, and implementing corresponding differentiation strategies by combining different client portraits to drive continuous optimization of the quotation scheme.
6. The system of claim 5, wherein the tagbook intelligent parsing module comprises: and the parameter calculation sub-module is used for determining the material model and the quota according to the parameters of the lowest temperature, the top oil temperature rise, the highest low temperature and the altitude.
7. The system of claim 5, wherein the collaborative quotation module comprises: The quotation standardization sub-module is used for carrying out standardization and standardization management on the generated quotation data so as to ensure that the quotation format is uniform and the information is complete; The historical price library sub-module is used for automatically grabbing price information in the historical price library to check prices; And the price inquiring sub-module is used for determining the price which is not contained in the historical price library and providing a price inquiring function so as to acquire market price information.
8. The system of claim 5, wherein the knowledge base construction module comprises: The portrait generation sub-module is used for generating a customer demand portrait based on the customer history behavior data and the preference analysis; And the differentiated strategy implementation submodule is used for implementing differentiated quotation strategies and service schemes according to different customer demand portraits.
9. A transformer-based parsing and quotation device, comprising: at least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores instructions executable by the at least one processor to enable the transformer based parsing and quotation device to perform the method of any one of claims 1-8.
10. A non-transitory computer storage medium having stored thereon computer-executable instructions configured to implement the method of any of claims 1-8.

Description

Transformer-based analysis and quotation method, system, equipment and medium Technical Field The application relates to the technical field of computers, in particular to a transformer-based analysis and quotation method, a system, equipment and a medium. Background The transformer is a core static electromagnetic device for realizing electric energy transmission, voltage transformation and impedance matching in an electric power system. The electromagnetic induction type transformer is based on an electromagnetic induction principle and comprises a winding, a magnetic circuit system, an insulating structure, a cooling system, a voltage regulating device, an external protection shell and the like. The core functional elements can be divided into four major types, namely a magnetic conduction loop, namely an iron core, a conductive loop, namely a winding, an insulation system and a cooling system. As key equipment of power transmission and distribution links, the transformer has a complex structure and high raw material cost. The difference of technical parameters and configuration can directly influence the production cost, and particularly in the scene of centralized batch bidding of large-scale clients, the product types, namely the main transformer and the distribution transformer, have different requirements, so that the enterprise can quickly and accurately estimate the cost and provide competitive quotation to put forward higher requirements. From the industrial application scene, the bid price of the main transformer and the bid price of the distribution transformer are obviously different. The main transformer is required to adapt to the power grid requirements of different voltage grades and capacities, the customization degree is high, but the corresponding standard-calling file standardization degree is high, the distribution transformer is influenced by the power grid transformation requirements of different areas and special configuration requirements of users although the product specifications are relatively uniform, the standard-calling file standardization degree is low, and the conditions of non-uniform parameter expression and scattered additional requirements often occur. This differentiated feature further amplifies the drawbacks of the traditional quotation pattern. In the traditional quotation management process, when transformer manufacturing enterprises deal with orders with large batches and short quotation period, the problems that the quotation flow is not smooth, the off-line flow is complex, the manual work efficiency is low, the accuracy is low, the quotation quantity and statistics conditions are not clear, historical data cannot be deposited as a knowledge base and the like are commonly caused. These problems severely restrict the agile response capability of enterprises to market dynamics, lead to lag of quotation strategies and inaccurate cost accounting, reduce quotation accuracy, and further lead to core order loss and compressed profit space. Disclosure of Invention In order to solve the problems, the application provides a transformer-based analysis and quotation method, which comprises the steps of obtaining a bid-making file of a transformer, preprocessing the bid-making file, analyzing according to the preprocessed bid-making file and a preset parameter library to determine corresponding technical parameters, determining a project list according to the bid-making file, searching and matching corresponding technical specifications according to the project list, and carrying out data processing on the technical parameters according to the technical specifications to determine a material model and a quota and generating a quotation according to the material model and the quota. In one example, analyzing according to the preprocessed bidding documents and a preset parameter library to determine corresponding technical parameters, specifically, performing structuring treatment on the parameter library to determine structured data, analyzing the structured data through a preset deep learning model to extract the technical parameters, determining the process requirements of a main transformer, and performing preliminary screening and correction on the technical parameters according to the process requirements. In one example, data processing is performed on technical parameters according to technical specifications to determine a material model and a quota, and the method specifically comprises the steps of determining materials according to the bidding document, wherein the materials comprise main materials, auxiliary materials and matching parts, corresponding technical conditions are determined according to the materials in the technical parameters, determining a material model according to the technical conditions, determining project requirements according to the project list, determining the quota according to the material model and the project requirements, and gen