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CN-121996661-A - Comprehensive evaluation method and management system for molybdenum resources

CN121996661ACN 121996661 ACN121996661 ACN 121996661ACN-121996661-A

Abstract

The invention belongs to the field of resource mineral products, and provides a comprehensive molybdenum resource evaluation method and a management system. The molybdenum resource supply and demand prediction model predicts the molybdenum supply amount, the dynamic analysis module dynamically analyzes the result according to the gradient recovery rate, and the visualization module visualizes and displays the analysis result. The method effectively solves the problems of data format and granularity through multi-source data storage and preprocessing capability, realizes the state synchronization of physical entities and digital space based on digital modeling and simulation technology, realizes the simulation prediction of the full life cycle of molybdenum resources through the integrated analysis and model construction of multi-source heterogeneous data, can flexibly evaluate the future demand of molybdenum minerals, generates graphs conforming to standard vector formats such as SVG (static var generator) based on the preprocessed data in real time, and can intuitively display the current situation and future trend of the molybdenum resources through the graphs.

Inventors

  • YUAN NINGJING
  • GENG YONG
  • GU WANG

Assignees

  • 上海交通大学

Dates

Publication Date
20260508
Application Date
20260317

Claims (10)

  1. 1. A method for comprehensively evaluating molybdenum resources, comprising: s1, integrating and preprocessing data to construct a molybdenum resource supply and demand prediction model; S2, setting a graded recovery rate scene, inputting a molybdenum resource supply and demand prediction model, and dynamically analyzing a result; and S3, visually displaying the analysis result.
  2. 2. The method for comprehensively evaluating molybdenum resources according to claim 1, wherein the step S1 includes: s1.1, collecting molybdenum resource basic data, including historical data, macroscopic data and resource recovery data, and storing the molybdenum resource basic data through a relational database, a metadata database and/or a distributed file storage system; s1.2, performing identity verification and authorization operation on an entering user, and limiting the authority range of the user for accessing and operating functions and data according to the roles and corresponding authorities of the user; S1.3, preprocessing molybdenum resource basic data, and establishing a molybdenum resource supply and demand prediction model; the historical data comprises metal molybdenum supply quantity data in 1990-2020, molybdenum metal stock quantity data in 1990-2020 and historical molybdenum ore exploration reserve quantity and production quantity data; The macroscopic data comprises predicted molybdenum demand data and calendar population data of the international energy agency; the resource recovery data includes molybdenum resource recovery data and policy guidance benchmark data that occur according to history.
  3. 3. The method for comprehensively evaluating molybdenum resources according to claim 2, wherein the step S1.3 includes: Cleaning molybdenum resource basic data, and fusing by using a data fusion technology to form a standard unified data set; normalizing molybdenum resource basic data from different sources into core fields containing molybdenum metal quantity, product form and associated ore type, and establishing a relational database; scoring different sources according to the data continuity, granularity precision and traceability by weight of 40%, 30% and 30% respectively to obtain the credibility, adopting the data with higher credibility, and adopting the missing value to extrapolate through adjacent year trend and correct and complement by industry experts; based on historical data, verifying data consistency through a matching relation between inventory and flow balance, adopting if the deviation is less than or equal to 10%, and automatically backtracking the data if the deviation exceeds 10%; and extracting the main metal yield, the associated molybdenum grade and the beneficiation recovery rate parameters according to the policy-directed reference data, and calculating the associated molybdenum yield.
  4. 4. The method for comprehensively evaluating molybdenum resources according to claim 2, wherein the step S1.3 includes: modeling everyone using metal inventory using Logistic curves: wherein X (t) represents a molybdenum metal inventory amount in the t-th year; POP (t) represents population quantity at the t-th year; x represents the saturation value of molybdenum metal stock used by people; Alpha and beta each represent different parameters; molybdenum demand for the t-th year; Molybdenum metal inventory for the t-th year; the scrapped amount of the terminal product in the t-th year is obtained; The difference between the total demand and the production of regenerated molybdenum was taken as primary molybdenum demand: Wherein, the Represents the demand of primary molybdenum in the t year; r is the regeneration content; predicting molybdenum supply by Hubbert model: Wherein, the Represents molybdenum supply amount in t years; r represents molybdenum resource reserves; 、 all representing different parameters.
  5. 5. The method for comprehensively evaluating molybdenum resources according to claim 1, wherein in the step S2, different future scene conditions are preset, and when the molybdenum renewable resource amount is calculated, a gradient recovery rate scene is set for the molybdenum resource secondary utilization potential after the end of the life cycle, comprising: when the standard recovery situation is judged, setting the rejection recovery rate of the molybdenum terminal product to be 30%; When judging to optimize the recycling situation, setting the scrapping recycling rate of the molybdenum terminal product to be 50%; and when the high-value utilization situation is judged, setting the scrapping recovery rate of the molybdenum terminal product to be increased to 70%.
  6. 6. The molybdenum resource comprehensive evaluation management system is characterized by comprising a molybdenum resource supply and demand prediction model, a dynamic analysis module and a visualization module; Integrating and preprocessing data, and predicting molybdenum supply quantity by a molybdenum resource supply and demand prediction model; The dynamic analysis module dynamically analyzes the result according to the gradient recovery rate; And the visualization module is used for visualizing and displaying the analysis result.
  7. 7. The molybdenum resource integrated assessment management system according to claim 6, comprising: Collecting molybdenum resource basic data, including historical data, macroscopic data and resource recovery data, and storing the molybdenum resource basic data through a relational database, a metadata base and/or a distributed file storage system; performing authentication and authorization operation on an entered user, and limiting the authority range of the user for accessing and operating functions and data according to the roles and corresponding authorities of the user; Preprocessing molybdenum resource basic data, and establishing a molybdenum resource supply and demand prediction model; the historical data comprises metal molybdenum supply quantity data in 1990-2020, molybdenum metal stock quantity data in 1990-2020 and historical molybdenum ore exploration reserve quantity and production quantity data; The macroscopic data comprises predicted molybdenum demand data and calendar population data of the international energy agency; the resource recovery data includes molybdenum resource recovery data and policy guidance benchmark data that occur according to history.
  8. 8. The method for comprehensive evaluation of molybdenum resources according to claim 7, wherein the pretreatment comprises: Cleaning molybdenum resource basic data, and fusing by using a data fusion technology to form a standard unified data set; normalizing molybdenum resource basic data from different sources into core fields containing molybdenum metal quantity, product form and associated ore type, and establishing a relational database; scoring different sources according to the data continuity, granularity precision and traceability by weight of 40%, 30% and 30% respectively to obtain the credibility, adopting the data with higher credibility, and adopting the missing value to extrapolate through adjacent year trend and correct and complement by industry experts; based on historical data, verifying data consistency through a matching relation between inventory and flow balance, adopting if the deviation is less than or equal to 10%, and automatically backtracking the data if the deviation exceeds 10%; and extracting the main metal yield, the associated molybdenum grade and the beneficiation recovery rate parameters according to the policy-directed reference data, and calculating the associated molybdenum yield.
  9. 9. The molybdenum resource comprehensive assessment management system according to claim 7, wherein in the molybdenum resource supply and demand prediction model, a Logistic curve is applied to model the metal inventory used by people: wherein X (t) represents a molybdenum metal inventory amount in the t-th year; POP (t) represents population quantity at the t-th year; x represents the saturation value of molybdenum metal stock used by people; Alpha and beta each represent different parameters; molybdenum demand for the t-th year; Molybdenum metal inventory for the t-th year; the scrapped amount of the terminal product in the t-th year is obtained; The difference between the total demand and the production of regenerated molybdenum was taken as primary molybdenum demand: Wherein, the Represents the demand of primary molybdenum in the t year; r is the regeneration content; predicting molybdenum supply by Hubbert model: Wherein, the Represents molybdenum supply amount in t years; r represents molybdenum resource reserves; 、 all representing different parameters.
  10. 10. The molybdenum resource comprehensive evaluation management system according to claim 6, wherein different future scene conditions are preset in the dynamic analysis module, and when the molybdenum renewable resource amount is calculated, a gradient recovery rate scene is set for molybdenum resource secondary utilization potential after the end of a life cycle, comprising: when the standard recovery situation is judged, setting the rejection recovery rate of the molybdenum terminal product to be 30%; When judging to optimize the recycling situation, setting the scrapping recycling rate of the molybdenum terminal product to be 50%; and when the high-value utilization situation is judged, setting the scrapping recovery rate of the molybdenum terminal product to be increased to 70%.

Description

Comprehensive evaluation method and management system for molybdenum resources Technical Field The invention belongs to the field of resource minerals, and particularly relates to a comprehensive evaluation method and a management system for molybdenum resources. Background Molybdenum is used as a key strategic metal and is widely and indispensible in the fields of high-end equipment manufacturing, national defense and technology industry, petrochemical industry, new energy sources which are rapidly growing, information technology and the like. However, with the rapid development of economy and the continuous advancement of resource development, management and trend evaluation of molybdenum ore resources are facing a series of problems to be solved. In different links such as original mineral processing, intermediate and final product production, mineral resource trade and the like of molybdenum ore, related data analysis is not sound, data precision is insufficient, the related industry is wide, the total amount is large, and great difficulty is brought to analysis, judgment and management of molybdenum ore situation. Meanwhile, a unified and efficient molybdenum ore resource data integration platform is lacking at present, and the refinement degree of resource management needs to be improved. The market trend and the demand change of molybdenum ore resources are difficult to accurately grasp, and the existing resource assessment method and tool are difficult to provide powerful decision support. The prior known molybdenum resource analysis tools have the following problems: The data integration and processing capability is insufficient, and most of the existing tools are focused on the management and analysis of single mineral elements, and the comprehensive consideration of multiple mineral elements and correlations thereof is lacking. The molybdenum ore resource data has wide sources, including geological exploration data, production statistics data, international trade data and the like, and has large data format and granularity difference. The existing tool has obvious short plates in the aspects of data acquisition, cleaning and standardization, and the accuracy and reliability of analysis results are affected by the problem of data quality. The analysis precision and the foreseeability are insufficient, the existing tool has obvious defects in the aspects of dynamic evaluation and trend prediction of molybdenum ore resources, and the evolution trend of the trade and consumption structure of the resources is difficult to accurately reveal. For demand assessment under different scene conditions in the future, the existing tools lack effective comprehensive assessment models and algorithm support, and cannot provide prospective reference bases for strategic decisions of enterprises and macroscopic regulation of governments. The user experience and the visualization effect are poor, the existing tool has the defects in the aspects of user interface design and data visualization, the data display is not visual enough, the user operation is complex, the use efficiency and the user experience are affected, the user is difficult to quickly understand and grasp the complex information of the molybdenum ore resources, and the practicability and the popularization value of the system are reduced. The professional requirement is high, and some professional statistical analysis software has a high threshold of entering, and is necessary to be participated by professional staff, so that the model and algorithm cannot be deeply embedded into a system tool, and a common user cannot quickly master and use the model and algorithm. Patent literature (CN 118761648A) discloses a method and a system for comprehensively evaluating light rare earth resources, which are characterized in that a digital twin model of the light rare earth resources, which is highly mapped with the physical world, is built in a digital space through connecting a database of a strategic mineral resource data center, an ontology model and a semantic association network of the light rare earth resources are built, the mass flow of the whole industrial chain is analyzed and tracked, and the supply and demand relation and the consumption trend of the light rare earth resources are revealed through data mining and machine learning algorithms. However, in the calculation process of the molybdenum resource and the light rare earth resource, the molybdenum resource and the light rare earth resource have obvious differences in calculation links such as material flow modeling, supply and demand prediction, parameter selection and the like due to differences of mineral characteristics, industrial chain structures, recovery logics, data characteristics and the like, and the recovery potential of the molybdenum resource is large, and the recovery rate is high (the regenerated molybdenum accounts for 20% -30% of the supply). Therefore, a molybdenum resource c