Rail transit physical asset handover system and method

Abstract

The application discloses a rail transit real asset handover system and method, and belongs to the technical field of rail transit asset management; the system comprises a contract data standardization module, a contract splitting module, an equipment combination module, an asset combination module, an asset handover module, a core data processing module and a system bottom layer support module; the method is based on the system and sequentially performs contract data standardization, contract list splitting, equipment combination, asset combination and asset handover. The application automatically processes non-standardized contracts, intelligently splits contracts, automatically combines equipment / assets, automatically compares accounts and reality, dynamically evaluates asset value and evaluates main data quality, constructs a ternary correlation data model of assets, equipment and contracts, integrates asset handover into the whole process of engineering construction, and solves the problems of low handover efficiency, poor data quality and weak collaboration of the prior art.

Description

Technical Field

[0001] This invention relates to the field of rail transit asset management technology, specifically to a rail transit physical asset transfer system and method. Background Technology

[0002] As a core urban public transportation infrastructure, rail transit is a typical capital-intensive industry. Its construction process is characterized by large-scale investment, numerous participating units, complex professional systems, high safety requirements, and tight schedules. Currently, most urban rail transit systems in China adopt a model of separate management between construction and operation units. During the construction phase, there are common problems such as prioritizing project construction while neglecting the needs of asset management during the operation phase, and insufficient means of asset transfer management, resulting in delayed asset transfer work and inconsistent data quality.

[0003] In existing technologies, asset transfer is mostly carried out after completion and acceptance, which is disconnected from the engineering construction process and lacks intelligent and digital support tools. This results in numerous asset classifications, a large workload, and poor collaboration among participating parties. The transfer cycle can last for more than a year, and there are also problems such as weak data correlation, lack of quantitative formulas for value assessment, and difficulties in full lifecycle traceability. Furthermore, the current transfer process suffers from a lack of algorithmic application and vague data processing details, failing to achieve intelligent and quantitative asset breakdown, combination, and value assessment, and thus failing to meet the refined management needs of asset maintenance, value preservation and appreciation, and cost reduction and efficiency improvement during the operation phase. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of low efficiency and poor data quality in the transfer of physical assets of rail transit in the prior art, and to provide a system and method for the transfer of physical assets of rail transit.

[0005] To achieve the above-mentioned objectives, this invention provides a rail transit physical asset transfer system, including a contract data standardization module, a contract splitting module, an equipment combination module, an asset combination module, an asset transfer module, a core data processing module, and a system underlying support module; The contract data standardization module is used to develop standardized contract list templates, complete standardized contract data entry, synchronize change data, and parse non-standardized contract texts. The contract splitting module is used to obtain the field location data in the contract, split the contract content, establish a splitting list, and link the splitting list with the original contract for bidirectional traceability. The equipment combination module is used to combine equipment with the same attributes and generate an equipment list that meets the granularity of operation and maintenance. The asset portfolio module is used to combine assets with the same attributes and dynamically quantify the value of the combined assets. The asset transfer module is used to generate transfer data for on-site verification. The transfer data includes asset coding, label affixing, transfer approval, and physical asset entry. The core data processing module is used to construct a ternary association model of assets, equipment, and contracts to realize the association update of asset data transfer; The underlying support module of the system is used to provide a data interface for interfacing with external systems and to perform distributed storage of various data.

[0006] Furthermore, the contract data standardization module has a pre-set standard template for the contract list, which includes asset attribute fields and product attribute fields.

[0007] Beneficial effects: Standardizing the fields for contract data entry enables the classification and aggregation of asset and product attribute data, avoiding data chaos caused by inconsistent fields. This lays a standardized data foundation for subsequent contract splitting, equipment / asset combination, and other processes. At the same time, the templated design can adapt to the personalized field requirements of different rail transit projects, improving the system's versatility.

[0008] Furthermore, the contract data standardization module includes a non-standard contract parsing unit. The non-standard contract parsing uses an NLP+BiLSTM bidirectional long short-term memory network intelligent algorithm to parse the non-standard contract content and match it with standardized fields.

[0009] Beneficial effects: By using intelligent algorithms to automatically segment, identify entities, and match fields in non-standard contract texts, the cost of manual data entry is significantly reduced, and the parsing efficiency is improved by more than 80%. At the same time, by combining with a professional corpus of rail transit, the accuracy and professionalism of the parsing results are guaranteed, and standardized and unified management of various types of contract data is achieved.

[0010] Furthermore, the contract splitting module contains an asset location data model, including location nodes for routes, location types, specific locations, subordinate locations, and functional areas. Each location node is assigned a unique 12-bit location code, which includes a 2-bit route code, a 2-bit location type code, a 2-bit specific location code, a 2-bit subordinate location code, and a 4-bit functional area code.

[0011] Beneficial effects: It constructs a five-level refined location management system, which realizes the precise positioning of asset installation location through a unique 12-digit location code, solves the problem of fuzzy and difficult-to-trace location information of rail transit assets. The segmented coding design clearly reflects the level and region to which the asset belongs, which facilitates quick retrieval and location of assets. At the same time, it provides standardized location data support for the contract list to be split by location.

[0012] Furthermore, the contract splitting module includes a contract list splitting engine. This intelligent contract list splitting engine integrates clustering algorithms based on decision trees and K-means models, and is used to automatically split the contract list according to location hierarchy, asset quantity, and installation specifications. The split content generates a unique splitting identifier based on the contract number, list line number, and location code, establishing a two-way traceability link between the split list and the original contract list. The split contract list inherits all attributes of the original list and adds installation location and location code fields.

[0013] Beneficial effects: The integration of dual algorithms enables intelligent and automated splitting of the contract list, replacing the tedious operation of traditional manual splitting. The splitting results are closely aligned with the actual installation scenarios and operation and maintenance needs of the assets. The unique splitting identifier and two-way traceability association mechanism enable full traceability of the splitting data and the original contract data, avoiding data loss or disconnection.

[0014] Furthermore, the equipment combination module includes a six-level tree-structured equipment classification and coding sub-module for equipment management. This sub-module extracts six core feature factors from the data to be combined: specialty, specifications, installation location, functional attributes, maintenance granularity, and production batch. It calculates the similarity between data points and combines multiple devices with similarity exceeding a certain threshold. The similarity calculation formula is as follows:

[0015] Among them, among them, The similarity is the core feature, with a value ranging from 0 to 1; , These are the standardized values ​​of the feature factors, ranging from 0 to 1; For feature factor weights, The system's default similarity threshold is 0.85, but it supports custom adjustments. When the similarity is greater than or equal to the threshold, devices are automatically combined.

[0016] Beneficial effects: The six-level tree-structured equipment classification and coding enables refined and hierarchical management of equipment, adapting to the management needs of multiple specialties and types of equipment in rail transit; extracting six core feature factors and combining them with cosine similarity calculations enables scientific and precise equipment combination, avoiding the subjectivity and errors of manual combination; the feature factor weights can be customized and adjusted to adapt to the operation and maintenance granularity requirements of different projects, and the combined equipment list directly matches operation and maintenance needs, reducing the workload of subsequent equipment ledger sorting.

[0017] Furthermore, the asset portfolio module dynamically quantifies the value of the portfolioed assets to satisfy the following calculation logic: Formula for calculating the original value of assets: ; Formula for calculating estimated net residual value: ; Formula for calculating annual depreciation: ; Accumulated depreciation calculation formula: ; Formula for calculating net asset value: ; in, This refers to the unit price of the equipment. For the number of devices, For installation costs, For transportation costs, Net residual value rate For the estimated service life, The formulas are based on the number of years they have been used, and all formulas can be customized according to the company's accounting system.

[0018] Beneficial effects: The systematic asset value quantification calculation formula solves the problems of vague asset value assessment and lack of unified standards in existing technologies, and realizes dynamic and accurate calculation of asset original value, net residual value, depreciation and net value.

[0019] Furthermore, the asset portfolio module constructs an asset priority evaluation index based on four dimensions: functional importance, operation and maintenance cost, usage frequency, and fault impact. A linear weighted method is used to calculate the asset priority score, as shown in the formula:

[0020] in, Standardized scores for the indicators, As the indicator weight, assets are divided into three levels according to the score: S≥8 points, priority level 1; 6 points≤S<8 points, priority level 2; S<6 points, priority level 3.

[0021] Beneficial effects: A four-dimensional asset priority evaluation system is constructed based on the core needs of operation and management, realizing the scientific and quantitative classification of asset importance; the linear weighted method is simple to calculate and the results are intuitive, and the indicator weights can be flexibly adjusted to adapt to the asset management priorities of different projects; the classification of asset priorities can provide a basis for decision-making on equipment maintenance, resource allocation, and emergency repair during the operation phase, realizing key control of core assets and routine control of general assets, and improving the refinement and efficiency of asset management.

[0022] Furthermore, the asset transfer module includes an asset coding output submodule and a label printing submodule. The asset coding output submodule generates a 10-digit digital asset code as the label coding information for asset transfer. The coding segmentation rule is as follows: ,in The professional codes are 01-99. The position type is encoded as 01-99. The specific positional codes are 01-99. The tag printing submodule uses an auto-incrementing sequence code from 0001 to 9999 to print electronic tags containing asset authorization codes.

[0023] Beneficial effects: The 10-digit segmented asset code provides a unique identifier for the asset, incorporating key information such as profession and location, which facilitates quick identification of the asset's category and location. The self-incrementing sequence code ensures the uniqueness and scalability of the code.

[0024] Based on the aforementioned rail transit physical asset transfer system, this application also provides a rail transit physical asset transfer method, which comprises the following steps: Step 1: Standardize contract data processing, develop a standardized contract list template, complete the standard contract data entry through single-line entry / batch import, perform NLP+BiLSTM intelligent parsing on non-standard contract texts, generate a chain change log after the engineering change data is submitted and synchronize it in real time, and generate a unique data identifier for archiving after all data undergoes triple verification of format, integrity and uniqueness. Step 2: Contract list splitting process, construct a five-level asset location data model and complete location code allocation, realize automated splitting of the contract list through decision tree + K-means intelligent splitting engine, generate a unique splitting identifier and establish a two-way traceability association with the original contract list, and archive the split list to the splitting database after adding fields such as location and location code. Step 3: Equipment combination processing. Import the six-level tree-structured equipment classification coding standard, extract the six core feature factors of the data to be combined and assign weights, realize the automated combination of equipment through cosine similarity calculation and K-means clustering, generate an equipment list and establish a many-to-one association mapping between the unique equipment identifier and the contract split list; Step 4: Asset portfolio processing. Import the six-level tree-structured asset classification coding standard to realize automated asset portfolio. Use standardized formulas to perform dynamic quantitative calculations of asset original value, net residual value, depreciation, and net value. Calculate asset priority scores and classify levels based on the four-dimensional evaluation system. Generate an asset list and establish a link between the asset list and the equipment list through a unique asset identifier. The list data is synchronized to the asset ledger in real time. Step 5: Asset transfer processing. The on-site physical assets are compared with the system data through a handheld terminal. The system generates a unique 10-digit asset code and prints an RFID electronic tag. After the tag is affixed, it is confirmed in the system, and a multi-party transfer approval process is initiated and a chain approval log is generated. After the approval is approved, the physical asset master data is generated. After the master data is quality assessed, it is synchronized to the external management system to complete the asset transfer.

[0025] Compared with existing technologies, the rail transit physical asset transfer system and method provided in this solution have the following significant advantages: 1. The entire handover process is made intelligent by deeply integrating intelligent algorithms. For the first time, multiple intelligent algorithms such as NLP+BiLSTM, decision tree, K-means clustering, random forest, AHP, YOLOv8, and fuzzy comprehensive evaluation are integrated into the entire process of rail transit physical asset handover, replacing traditional manual operation. This solves the problems of low handover efficiency, strong subjectivity, and large errors, improving asset handover efficiency by more than 70% and data processing accuracy by more than 99.5%.

[0026] 2. A series of standardized calculation formulas were developed for asset original value, net residual value, accumulated depreciation, similarity, priority score, etc., and quantitative indicators and calculation methods were clarified. This solved the problems of vague asset valuation and lack of unified quantitative standards in the existing technology, and provided accurate quantitative data support for asset value management and maintenance decisions throughout the entire asset life cycle.

[0027] 3. Fully disclose the core data processing details of each stage of contract data standardization, list splitting, equipment / asset combination and on-site verification, including data identification rules, storage partitions, association mapping, synchronization mechanisms and cleaning algorithms, to achieve traceability, monitoring and verification of data throughout the asset transfer process, and solve the problem of black box operation of data processing in existing technologies.

[0028] 4. By integrating asset transfer into the entire project construction process in advance and deeply combining it with the contract management process, the responsibilities of each participating party are clearly defined, and a digital data connection bridge is built between the construction and operation phases. Asset transfer can be completed within 2 months after project completion and acceptance, which is far superior to the transfer cycle of more than 1 year in existing technologies.

[0029] 5. Construct an asset-equipment-contract ternary association ER model and a dual ledger synchronization mechanism for asset ledger and equipment ledger. This enables two-way traceability of asset data from the data source, avoids secondary sorting of ledger data in later asset management, reduces the workload of establishing asset-related data to 30% of the original, and provides a complete data system for asset maintenance, fault diagnosis, value assessment, and revitalization during the operation period.

[0030] 6. The system incorporates robust underlying technologies such as distributed storage, multi-system integration, data encryption, and breakpoint resume, ensuring its stability, security, and scalability. Each module supports custom configuration, adapting to the asset transfer needs of rail transit projects of different scales and specialties, and possesses broad practicality and promotional value.

[0031] 7. A full-process data quality control mechanism was established from data entry to master data generation. Through four-fold verification, intelligent cleaning, and quantitative evaluation, the integrity, accuracy, consistency, and timeliness of the transferred data were ensured, laying a solid foundation for the subsequent application of master data and providing high-quality data support for the refined management of rail transit assets throughout their entire life cycle. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the physical asset transfer system for rail transit in Example 1; Figure 2 This is a flowchart illustrating the asset transfer process in Example 2; Figure 3 A diagram showing the fields for assets, equipment, and contracts. Detailed Implementation

[0033] The following detailed description illustrates the specific implementation method: Example 1: In this embodiment, as Figure 1 The aforementioned rail transit physical asset transfer system includes a contract data standardization module 1, a contract splitting module 2, an equipment combination module 3, an asset combination module 4, an asset transfer module 6, a core data processing module 5, and a system underlying support module 7.

[0034] The contract data standardization module 1 has a preset standard template for the contract list. Contract content is entered into the system. The contract data standardization module 1 parses the contract content and collects the parsed contract content into the standard template for the contract list. The contract content is verified through an external verification window. Once the verification is completed, a unique data identifier is generated for the contract and stored in the contract database.

[0035] Data entry / parsing requires five steps: format validation, integrity validation, uniqueness validation, standardized mapping, and storage archiving. Failure to pass validation triggers an error message and generates a correction prompt. Contracts are identified by contract number, professional code, and list line number.

[0036] The standard contract list template 1 includes built-in asset attribute fields and product attribute fields. The asset attribute fields include: specialty, material code, material name, and asset category. The product attribute fields include: brand name, model specifications, unit of measurement, quantity, unit price, tax rate, total price, supplier, manufacturer, production batch, and warranty period.

[0037] The fields in the standard contract list template are customizable for addition, deletion, modification, and configuration to adapt to the personalized needs of different rail transit projects; all fields have data type, length, and mandatory field rules set to form a standardized field rule library.

[0038] The contract data entry module provides dual-mode data entry interfaces for single-line entry and batch import. The interface has built-in data format validation rules and can be seamlessly connected to the contract management system through the API interface to achieve bidirectional real-time data synchronization.

[0039] Batch import supports formats such as Excel, CSV, and XML. After the imported data is validated by the rule base, invalid data is automatically identified and an error log is generated, indicating the location and cause of the error, ensuring data integrity and accuracy.

[0040] The engineering change data synchronization module allows the construction unit to submit a change application in the system when engineering changes occur. The system automatically records the data differences before and after the change, the reason for the change, the person making the change, and the time of the change, generating an immutable chain change log.

[0041] For the parsing of non-standard contracts, an NLP+BiLSTM bidirectional long short-term memory network intelligent algorithm is used to parse the non-standard contract text in four steps: word segmentation, entity recognition, keyword extraction, and standardized field matching. The algorithm extracts the material name, specifications, quantity, and unit price, and then matches them with standard template fields to achieve automated standardization of non-standard contract data. After review and confirmation, the data is stored in the contract database.

[0042] The system stores a professional corpus for rail transit, which covers all professional terms, contract terms, and material names in the fields of power supply, signaling, electromechanical engineering, and rail transit.

[0043] Contract splitting module 2 integrates decision tree and K-means clustering intelligent algorithms. The construction unit completes the standardization of location data and automated splitting of the contract list, achieving a precise correlation between the contract list and the actual installation location of the assets. The contract splitting process first identifies the contract's location data and generates a unique 12-digit location code. The contract number, list line number, and location code are extracted to generate a unique splitting identifier for the contract to be split, forming a bidirectional association mapping with the contract list identifier. All splitting data is stored in the distributed contract splitting database. A five-level asset location data model is constructed, including track line, location type, specific location, subordinate location, and functional area. Each location node is assigned a unique 12-digit location code: 2 digits for the track code + 2 digits for the location type code + 2 digits for the specific location code + 2 digits for the subordinate location code + 4 digits for the functional area code, ensuring the uniqueness of the location data.

[0044] Establish a one-to-one correspondence between the split list and the original contract list. The split list automatically inherits all attribute information of the original list and adds fields such as installation location, location code, installation unit, and split time. The contract split list contains complete information such as profession, material code, material name, brand name, model and specifications, unit of measurement, split quantity, unit price, total price, supplier, manufacturer, installation location, location code, split identifier, and original list identifier, realizing bidirectional traceability between split data and source data.

[0045] Through the equipment combination module 3, the intelligent algorithm of K-means clustering + cosine similarity calculation is integrated with the standardized calculation formula to complete the automated combination of equipment and form an equipment list that meets the granularity of operation and maintenance.

[0046] The equipment combination data generates a unique equipment identifier by combining the equipment code with the professional code, and establishes a many-to-one association mapping with the contract split list identifier.

[0047] A management module for equipment classification and coding standards was established, adopting a six-level tree-structured equipment classification and coding standard, sequentially from specialty, system, subsystem, equipment type, equipment to component. The system automatically synchronizes to the subsequent asset portfolio module to ensure the correlation between equipment codes and asset codes.

[0048] The automatic combination algorithm process of the equipment includes: extracting 6 core feature factors of the data to be combined: professional ( Specifications and models () ), Installation location ( ), functional attributes ( ), Operation and maintenance granularity ( ), production batch ( ), assign customizable weights to each feature factor ( ,and The cosine similarity formula is used to calculate the similarity between data, as follows:

[0049] in, , For the two sets of split list data to be compared The standardized values ​​of the feature factors range from 0 to 1. The similarity value ranges from 0 to 1. The system default similarity threshold is 0.85, which can be customized. When the similarity is greater than or equal to the threshold, devices are automatically combined.

[0050] Establish an equipment-contract split list association model, automatically bind equipment combinations with corresponding contract split lists through data tags to generate a standardized equipment list; the list fields are automatically populated through data aggregation algorithms, including equipment code, equipment name, equipment category, professional field, brand name, model specifications, unit of measurement, quantity, unit price, total price, supplier, manufacturer, installation location, location code, material code, management department, maintenance department, user department, equipment identifier, and associated split identifier information.

[0051] A database of device function associations is constructed. Based on the device's functional attributes, installation location, and operation and maintenance requirements, the Apriori association rule mining algorithm is used to identify devices with matching relationships.

[0052] The asset portfolio module 4 generates asset identifiers through unique 18-bit asset codes, establishes a many-to-one or one-to-one association mapping with equipment list identifiers, archives all intermediate data for asset value calculation in real time, stores asset list data in the distributed database asset data partition, and synchronizes it to the asset ledger.

[0053] Dynamic quantitative assessment of asset value: Through a dynamic asset value assessment model, standardized calculation formulas are established for the original value, estimated net residual value, accumulated depreciation, and net asset value of assets, enabling dynamic updating and quantitative assessment of asset value. Formula for calculating the original value of assets: ,in For the first Unit price of equipment For the first Number of devices For equipment installation costs, Equipment transportation costs; Estimated net residual value calculation formula: ,in Net residual value rate; Annual depreciation calculation formula (straight-line method): ,in The estimated useful life of the asset; the formula for calculating accumulated depreciation: ,in The useful life of the asset; Net asset value calculation formula: .

[0054] Asset priority quantification: based on functional importance ( ), Operation and maintenance costs ( ), frequency of use ( ), degree of impact of the fault ( The asset priority evaluation index system is constructed from four dimensions, and the weight of each index is determined by expert scoring. ,and The asset priority score is calculated using a linear weighting method, as shown in the following formula:

[0055] in, Standardized scores (0-10 points) are assigned to each indicator. The total priority score is 0-10 points; based on the score, assets are divided into three priorities: Level 1 assets (S≥8 points, core operation and maintenance assets), Level 2 assets (6≤S<8 points, important operation and maintenance assets), and Level 3 assets (S<6 points, general operation and maintenance assets).

[0056] Asset list generation and ledger synchronization: By using a unique asset identifier, the asset portfolio is linked to the corresponding equipment list for traceability. The equipment list data is automatically collected and supplemented with fields such as asset value, priority, and depreciation information to generate a standardized asset list. The asset list includes information such as asset code, asset name, asset category, professional category, original asset value, accumulated depreciation, net asset value, estimated net residual value, useful life, asset priority, installation location, associated equipment identifier, and management department. The list data is automatically updated to the asset ledger through a real-time synchronization algorithm.

[0057] Through the asset transfer module 6, on-site verification, asset coding, label affixing, transfer approval, and generation of physical asset master data are completed, ensuring that the transfer data is highly consistent with the physical assets.

[0058] The on-site verification process involves scanning the physical assets using a handheld terminal camera, automatically identifying the asset specifications, appearance features, and installation status, and comparing them with system data to achieve intelligent comparison between accounts and physical assets. The handheld terminal supports on-site input of comparison results, and for discrepancies, on-site photos and videos can be uploaded, along with notes on the reasons for the differences. The data is synchronized to the back-end system in real time, and the system automatically triggers a process to return discrepancies.

[0059] An automatic generation algorithm based on 10-digit digital asset codes, using coding segmentation rules: ,in: Specialty codes (01-99, set according to rail transit specialty classification); Location type code (01-99, station / section / control center); Specific location code (01-99, station number / section number); : Sequence encoding (0001-9999, auto-incrementing allocation).

[0060] The system automatically retrieves the coding program to generate a unique and non-repeating asset code. It automatically retrieves the generated codes through a code deduplication algorithm and establishes a unique binding relationship between the generated code and the asset identifier.

[0061] The automatic coding backfilling and label printing linkage module automatically fills in the asset coding field of the asset information after the asset code is generated, triggering the label printing instruction; the label content automatically collects the core asset information through a data collection algorithm.

[0062] After the tags are affixed, staff click to confirm the operation in the system. The system automatically marks the corresponding asset as verified and locks the basic information of the asset to prevent unauthorized modification. The RFID tags are linked with the system data in real time. By scanning the tags with a handheld terminal, the full data of the asset can be quickly retrieved, improving the efficiency of subsequent asset management.

[0063] The system constructs a ternary association ER model: This model establishes an asset-equipment-contract ternary association ER model, with assets, equipment, and contracts as the core entities. Each entity establishes a many-to-many / one-to-many relationship through a unique identifier, supporting bidirectional traceability queries: asset codes can be used to trace the source information of corresponding equipment and contracts, while contract numbers can be used to aggregate information on corresponding equipment and assets. It can also aggregate maintenance history, fault history, maintenance costs, and asset value changes during the operational period. An LRU caching model is constructed to cache frequently accessed data, improving system query efficiency. The cached data is updated periodically and kept consistent with the database.

[0064] Example 2: like Figure 2 and Figure 3 As shown, this invention provides a method for the transfer of physical assets in rail transit. Based on the aforementioned system, and taking a certain rail transit Line 2 project as an example, the specific implementation steps are as follows: Step 1: Standardized processing of contract data; a standard template for the project contract list is preset, with built-in standardized fields for asset attributes and product attributes. The construction unit imports the electromechanical professional contract list in batches via Excel format. The system automatically verifies the data format, finds 3 records with missing material codes, generates an error log and marks the error location. After the construction unit corrects the errors and re-imports them, the data verification passes.

[0065] The project's signaling section contained 10 non-standardized contract texts. The system used NLP+BiLSTM algorithm for intelligent parsing, and after word segmentation, it identified the core entities of signal machines, switch machines, and transponders, extracted specifications, quantities, and unit prices, and automatically matched standard template fields. After manual review, these were incorporated into the system management. Subsequently, an engineering change occurred in a switch machine contract, and the construction unit submitted a change application. The system recorded the data differences before and after the change, such as changing the model from ZD6 to ZD9, and generated a chain-like change log. The change data was pushed to subsequent modules such as contract splitting and equipment combination in real time through an incremental synchronization algorithm.

[0066] Step 2: Contract list splitting and processing; The construction unit constructs a five-level location data model for a certain rail transit line 2, assigning a 12-digit location code 020105030001 to the ticket area of ​​XX station (02=Line 2, 01=Station, 05=XX station, 03=Ticket area, 0001=Ticket vending machine installation area); Through the GIS geographic information system, the geographical location data of Line 2 and stations are automatically obtained, and after being imported into the system, hierarchical logic verification is performed to correct the error of two child nodes having no parent node, thus completing the tree-shaped location structure.

[0067] The construction unit selected a contract list line for power distribution cabinets (quantity 4 units, unit price 20,000 yuan). The system, through a decision tree + K-means clustering intelligent splitting engine, read the installation locations as two functional areas: the ticket sales area of ​​XX station and the power distribution room. It automatically split the cabinets according to the rule of 2 units / area, generating 2 contract splitting lists. The splitting lists generate unique splitting identifiers through contract number + list line number + location code, and establish a two-way association with the original contract list identifiers.

[0068] Step 3: Equipment combination processing; The operating unit imports a custom six-level tree-structured equipment classification coding standard to construct a coding catalog for: power supply specialties, power supply systems, electronic distribution systems, power distribution equipment, distribution cabinets, and distribution cabinet components; The system extracts six core feature factors from the above two distribution cabinet contract split lists, assigning weights of W1=0.2, W2=0.25, W3=0.2, W4=0.15, W5=0.1, and W6=0.1. The similarity is calculated using the cosine similarity formula, and the similarity is 0.93 ≥ 0.85 threshold. The system then automatically combines these into two distribution cabinet devices using the K-means clustering algorithm.

[0069] Step 4: Asset Portfolio Processing; The enterprise's asset management department imports the enterprise-level six-level tree-structured asset classification coding standard, assigning an 18-digit asset code 0301020500010001 (03=Power Supply Specialty, 01=Power Supply System, 02=Power Distribution System, 05=Power Distribution Equipment, 0001=Power Distribution Cabinet Code, 0001=Sequence Code) to the two power distribution cabinets and their supporting equipment. The system automatically combines the power distribution cabinets and supporting equipment into a set of power distribution assets using the random forest algorithm, generating an asset list.

[0070] The system calculates the asset value using a standardized asset value calculation formula: Ten thousand yuan, Ten thousand yuan, The asset was valued at 10,000 yuan; its priority score, calculated using the AHP algorithm, was 9.2 points, classifying it as a Level 1 asset, and the asset list was synchronized to the asset ledger in real time.

[0071] Step 5: Asset transfer processing; The four-party verification personnel carried handheld terminals to the ticket area of ​​XX station, and used professional location-based retrieval to retrieve power distribution asset data, displaying asset, equipment, breakdown list, and contract list information in a tree structure; They scanned the physical power distribution cabinet with the handheld terminal camera, identified the specification model as GGD-1000, which was consistent with the system data, and the accounts matched the physical cabinet.

[0072] The system retrieves the 10-digit asset code generation algorithm to generate the code 03-01-05-0001 (03=power supply specialty, 01=station, 05=XX station, 0001=sequence code), which is automatically filled into the asset information field. This triggers the label printing, printing an ultra-high frequency RFID electronic tag containing information such as asset code, name, and priority. After affixing the tag, the user confirms it on a handheld terminal, and the system marks the asset as verified and locks the basic information.

[0073] The system initiates a four-party approval process. During the approval process, the supervision unit completes a second data verification and approves the data after confirming that there are no problems. The other parties then complete their approvals in sequence, generating a chain-like approval log. After approval, physical asset master data is generated and split into asset ledgers and equipment ledgers using a data splitting algorithm. A two-way linkage update mechanism is established between the two ledgers. The master data quality assessment model scores 95 points across four dimensions, generating a quality assessment report. The master data is then synchronized to the enterprise asset management system and equipment operation and maintenance system via a standardized API interface, completing the asset transfer.

[0074] The above are merely embodiments of the present invention. Common knowledge such as specific structures and characteristics known in the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the technical field to which the invention pertains before the application date or priority date, are able to obtain all prior art in the field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can improve and implement the solution based on the inspiration given in this application and their own capabilities. Some typical known structures or methods should not become obstacles for those skilled in the art to implement this application.

[0075] It should be noted that those skilled in the art can make various modifications and improvements without departing from the structure of this invention, and these should also be considered within the scope of protection of this invention. These modifications and improvements will not affect the effectiveness of the invention or the practicality of the patent. The scope of protection claimed in this application shall be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A system for transferring physical assets of rail transit, characterized in that, It includes a contract data standardization module, a contract splitting module, an equipment combination module, an asset combination module, an asset transfer module, a core data processing module, and a system underlying support module; The contract data standardization module is used to develop standardized contract list templates, complete standardized contract data entry, synchronize change data, and parse non-standardized contract texts. The contract splitting module is used to obtain the field location data in the contract, split the contract content, establish a splitting list, and link the splitting list with the original contract for bidirectional traceability. The equipment combination module is used to combine equipment with the same attributes and generate an equipment list that meets the granularity of operation and maintenance. The asset portfolio module is used to combine assets with the same attributes and dynamically quantify the value of the combined assets. The asset transfer module is used to generate transfer data for on-site verification. The transfer data includes asset coding, label affixing, transfer approval, and physical asset entry. The core data processing module is used to construct a ternary association model of assets, equipment, and contracts to realize the association update of asset data transfer; The underlying support module of the system is used to provide a data interface for interfacing with external systems and to perform distributed storage of various data.

2. The rail transit physical asset transfer system according to claim 1, characterized in that, The contract data standardization module has a pre-set standard template for contract lists, which includes asset attribute fields and product attribute fields.

3. The rail transit physical asset transfer system according to claim 1, characterized in that, The contract data standardization module includes a non-standard contract parsing unit. The non-standard contract parsing uses an NLP+BiLSTM bidirectional long short-term memory network intelligent algorithm to parse the non-standard contract content and match it with standardized fields.

4. The rail transit physical asset transfer system according to claim 1, characterized in that, The contract splitting module contains an asset location data model, including location nodes for routes, location types, specific locations, subordinate locations, and functional areas. Each location node is assigned a unique 12-bit location code, which includes a 2-bit route code, a 2-bit location type code, a 2-bit specific location code, a 2-bit subordinate location code, and a 4-bit functional area code.

5. The rail transit physical asset transfer system according to claim 1, characterized in that, The contract splitting module includes a contract list splitting engine. This intelligent contract list splitting engine integrates clustering algorithms based on decision trees and K-means models. It is used to automatically split the contract list according to location hierarchy, asset quantity, and installation specifications. The split content generates a unique splitting identifier based on the contract number, list line number, and location code. A two-way traceability link is established between the split list and the original contract list. The split contract list inherits all attributes of the original list and adds installation location and location code fields.

6. The rail transit physical asset transfer system according to claim 1, characterized in that, The equipment combination module includes a six-level tree-structured equipment classification and coding sub-module for equipment management. This sub-module extracts six core feature factors from the data to be combined: specialty, specifications, installation location, functional attributes, maintenance granularity, and production batch. It then calculates the similarity between data points and combines multiple devices with similarity exceeding a certain threshold. The core similarity calculation formula is as follows: in, The similarity is the core feature, with a value ranging from 0 to 1; , These are the standardized values ​​of the feature factors, ranging from 0 to 1; For feature factor weights, The system's default similarity threshold is 0.85, but it supports custom adjustments. When the similarity is greater than or equal to the threshold, devices are automatically combined.

7. The rail transit physical asset transfer system according to claim 1, characterized in that, The asset portfolio module dynamically quantifies the value of the portfolioed assets to satisfy the following calculation logic: Original value of assets Calculation formula: ; Estimated net residual value Calculation formula: ; Annual depreciation Calculation formula: ; Accumulated Depreciation Calculation formula: ; Net Asset Value Calculation formula: ; in, This refers to the unit price of the equipment. For the number of devices, For installation costs, For transportation costs, Net residual value rate For the estimated service life, This represents the number of years the device has been used.

8. The rail transit physical asset transfer system according to claim 1, characterized in that, The asset portfolio module constructs an asset priority evaluation index based on four dimensions: functional importance, operation and maintenance cost, usage frequency, and fault impact. A linear weighted method is used to calculate the asset priority score, as shown in the formula: in, Standardized scores for the indicators, As the indicator weight, assets are divided into three levels according to the score: S≥8 points, priority level 1; 6 points≤S<8 points, priority level 2; S<6 points, priority level 3.

9. The rail transit physical asset transfer system according to claim 1, characterized in that, The asset transfer module includes an asset coding output submodule and a label printing submodule. The asset coding output submodule generates a 10-digit digital asset code as the label coding information for asset transfer. The coding segmentation rule is as follows: ,in The professional codes are 01-99. The position type is encoded as 01-99. The specific positional codes are 01-99. The tag printing submodule uses an auto-incrementing sequence code from 0001 to 9999 to print electronic tags containing asset authorization codes.

10. A method for transferring physical assets of rail transit, characterized in that, Based on the rail transit physical asset transfer system according to any one of claims 1-9, the following steps are performed: Step 1: Standardize contract data processing, develop a standardized contract list template, complete the standard contract data entry through single-line entry / batch import, perform NLP+BiLSTM intelligent parsing on non-standard contract texts, generate a chain change log after the engineering change data is submitted and synchronize it in real time, and generate a unique data identifier for archiving after all data undergoes triple verification of format, integrity and uniqueness. Step 2: Contract list splitting process, construct a five-level asset location data model and complete location code allocation, realize automated splitting of the contract list through decision tree + K-means intelligent splitting engine, generate a unique splitting identifier and establish a two-way traceability association with the original contract list, and archive the split list to the splitting database after adding fields such as location and location code. Step 3: Equipment combination processing. Import the six-level tree-structured equipment classification coding standard, extract the six core feature factors of the data to be combined and assign weights, realize the automated combination of equipment through cosine similarity calculation and K-means clustering, generate an equipment list and establish a many-to-one association mapping between the unique equipment identifier and the contract split list; Step 4: Asset portfolio processing. Import the six-level tree-structured asset classification coding standard to realize automated asset portfolio. Use standardized formulas to perform dynamic quantitative calculations of asset original value, net residual value, depreciation, and net value. Calculate asset priority scores and classify levels based on the four-dimensional evaluation system. Generate an asset list and establish a link between the asset list and the equipment list through a unique asset identifier. The list data is synchronized to the asset ledger in real time. Step 5: Asset transfer processing. The on-site physical assets are compared with the system data through a handheld terminal. The system generates a unique 10-digit asset code and prints an RFID electronic tag. After the tag is affixed, it is confirmed in the system, and a multi-party transfer approval process is initiated and a chain approval log is generated. After the approval is approved, the physical asset master data is generated. After the master data is quality assessed, it is synchronized to the external management system to complete the asset transfer.

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