Vehicle authentication detection task analysis system

Abstract

The invention discloses a vehicle authentication detection task analysis system, and the system comprises a task management center which builds a mapping relation among contract entries, customer detection standards and an internal standard library; the sample car parameter intelligent processing unit is used for capturing data through an API (Application Program Interface) of the Ministry of Communications, verifying the integrity and performing deviation early warning on additional recorded parameters; the sighting judgment core engine is used for analyzing the multi-dimensional similarity between the sample vehicle and historical data based on a random forest algorithm; and the abnormal process control gateway drives the dynamic approval workflow and is connected with a short message platform to push an encrypted link and an overtime alarm. The system integration message middleware synchronizes CSS platform data in real time, the report generation module dynamically fills a detection result through an XML template and calls RESTful API signature, and batch asynchronous processing of historical reports and compression downloading of digital watermarks are supported. According to the invention, the problems of low task analysis efficiency, flow splitting and difficulty in compliance management in vehicle authentication detection are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle authentication, and in particular to a vehicle authentication detection task analysis system. Background Art

[0002] With the rapid development of the automotive industry, vehicle certification and testing services are becoming increasingly complex, with frequent regulatory updates and a surge in data volume. The existing vehicle certification and testing task management systems have the following significant drawbacks: Inefficient task creation: Traditional systems cannot automatically link contract terms, customer testing standards, and internal standard libraries, requiring manual matching of test items with regulatory provisions. For example, electromagnetic compatibility testing for new energy vehicles requires manual linking of 32 mandatory inspection items, which is time-consuming and prone to compliance risks due to human oversight.

[0003] Insufficient reliability in prototype vehicle parameter processing: The current system relies on manual entry of prototype vehicle parameters (such as wheelbase and curb weight) and lacks an automated verification mechanism. When the deviation between the MOT's registered data and the measured values ​​exceeds a threshold, the real-time review process cannot be triggered, resulting in the return of test reports due to errors in basic parameters.

[0004] Deeming an equivalent is highly subjective: Existing technology relies on engineers' experience to determine the reusability of sample vehicle test data and lacks a quantitative analysis model. Historical test data is underutilized, and repeated testing of similar models wastes resources.

[0005] The abnormal response mechanism is lagging: The detection of abnormalities (such as battery capacity not meeting the standard or electromagnetic radiation exceeding the standard) relies on manual reporting step by step. The approval process takes a long time on average, and there is a lack of active alerts for timed and unprocessed events, which leads to longer task cycles.

[0006] In summary, the existing system has technical gaps in terms of intelligent task analysis, automated parameter processing, and real-time abnormality control. A full-link solution that deeply integrates standard library mapping, intelligent parameter verification, equivalent quantitative judgment, and dynamic workflow is urgently needed. Therefore, a vehicle certification inspection task analysis system is proposed to solve the above problems. Summary of the Invention

[0007] In view of this, an object of the present invention is to provide a vehicle authentication detection task analysis system to at least solve the above problems.

[0008] The technical solution adopted in the present invention is as follows: A vehicle certification detection task analysis system, the system comprising: The task management hub is used to create testing tasks and establish mapping relationships between contract items, customer testing standards, and internal standard libraries; Intelligent processing unit for prototype vehicle parameters, including a Ministry of Transport data capture interface, a parameter re-entry and verification engine, and an operational parameter library generator; The core engine for determining equivalents outputs equivalent determination conclusions based on multi-dimensional similarity analysis of sample vehicle parameters and historical test data; The exception process control gateway responds to parameter exceptions, report returns and task change events, and drives dynamic approval workflows.

[0009] Furthermore, the prototype vehicle parameter intelligent processing unit also includes: The data integrity verification module compares the MD5 hash value of the data returned by the Ministry of Transport API with the local cache value; The parameter deviation warning module automatically marks and triggers the review process when the supplementary parameters deviate from the standard library threshold.

[0010] Furthermore, the core engine for determining the sameness includes: The rule configuration layer supports customizing the consistency threshold of key component models and the similarity weight of detection items; At the decision execution layer, the random forest algorithm is used to calculate the feature similarity between historical detection data and the current sample vehicle.

[0011] Furthermore, the system integrates with the CSS platform through message middleware to push the following data in real time: Prototype vehicle parameter version change log; Incremental update of the deemed determination report library; Operation report electronic signature state machine flow events.

[0012] Furthermore, the report generation module includes: A report generator that dynamically populates test results into XML templates based on the operational parameter library; The total report synthesizer aggregates related sub-reports and calls the RESTful API of the three-party signing service.

[0013] Furthermore, the signature service integrates a batch processing framework, uses thread pool technology to process historical reports in parallel, and generates a ZIP compressed package with a digital watermark for download.

[0014] Furthermore, it includes an abnormal process control gateway, which connects to the SMS platform interface and pushes notifications at the following nodes: Send an encrypted link to the account manager when approving task assignments; When the process times out and is not processed, an alarm is sent to the monitoring terminal.

[0015] Furthermore, the system has a built-in knowledge graph of regulatory standards, which automatically associates inspection items with regulatory clauses during the task creation phase and generates a compliance checklist.

[0016] Furthermore, it includes a 3C auxiliary miscellaneous fee calculation engine, which dynamically generates a miscellaneous fee matrix based on the regional coefficient and detection complexity weight in the contract terms.

[0017] Furthermore, including the security authentication layer, the security authentication layer deploys a two-factor authentication gateway to implement the detection task operations in different regions: Access region lock based on GeoIP; Double verification of dynamic token TOTP and SMS verification code.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. Full-process intelligent task analysis Through dynamic mapping of contracts and standard libraries, the workload of manual core is reduced; the equivalent judgment engine adopts random forest algorithm to improve accuracy.

[0019] 2. High-precision processing of prototype vehicle data Ministry of Transportation API data integrity verification to prevent data tampering; The parameter deviation warning module automatically triggers the review process to avoid detection accidents.

[0020] 3. Real-time control of abnormal processes The response speed of dynamic approval workflow has been improved; The SMS platform pushes encrypted links and timeout alarms to shorten the problem resolution cycle.

[0021] 4. Security and cost optimization GeoIP region lock + TOTP two-factor authentication blocks illegal access; dynamic calculation of 3C miscellaneous fee matrix can reduce manual accounting costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 It is a schematic diagram of the overall structure of the system according to an embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram of the working process of the system according to an embodiment of the present invention. DETAILED DESCRIPTION The principles and features of the present invention are described below with reference to the accompanying drawings. The enumerated embodiments are only used to explain the present invention and are not used to limit the scope of the present invention.

[0025] Reference Figure 1-Figure 2 The present invention provides a vehicle certification detection task analysis system, the system comprising: The task management hub is used to create testing tasks and establish mapping relationships between contract items, customer testing standards, and internal standard libraries; Intelligent processing unit for prototype vehicle parameters, including a Ministry of Transport data capture interface, a parameter re-entry and verification engine, and an operational parameter library generator; The core engine for determining equivalents outputs equivalent determination conclusions based on multi-dimensional similarity analysis of sample vehicle parameters and historical test data; The exception process control gateway responds to parameter exceptions, report returns and task change events, and drives dynamic approval workflows.

[0026] For example, the task management center can use a mapping mechanism based on a rule engine to establish contract items (such as a list of test items), customer test standards (such as GB / T 18344-2016) is dynamically associated with the internal standard library (including 2000+ test item templates). When the customer chooses electromagnetic compatibility testing for new energy vehicles, the system automatically matches the corresponding national standard clauses and laboratory equipment parameter requirements, and generates a task work order containing 32 mandatory inspection items; the Ministry of Transport data capture interface in the sample vehicle parameter intelligent processing unit can synchronize the Ministry of Transport vehicle parameter database regularly through the HTTPS protocol, supporting incremental updates; the parameter supplement and verification engine can use a verification algorithm based on a rule library to perform compliance checks on non-standard parameters (such as the wheelbase of modified vehicles); the operating parameter library generator builds a structured database, which contains core parameters such as vehicle VIN code, engine number, and curb weight; the deemed judgment core engine can perform multi-dimensional similarity analysis by integrating vehicle structural parameters (such as chassis layout), test items (such as collision test), and historical data (test records of the same model in the past 3 years); judgment conclusion output: generate a structured report containing the judgment basis (citing specific regulatory clauses), similarity score (0-100 points), and exception list; the abnormal process control gateway can perform dynamic approval workflow, which is based on BPMN The 2.0 standard builds a configurable process that supports scenarios such as parameter anomalies (such as test values ​​exceeding the standard by 30%), report returns (customer requests for re-inspection), and task changes (increase or decrease in test items). When the actual measured battery capacity is detected to be lower than the contractually promised value, the three-level approval process of inspector → supervisor → technical director is automatically triggered.

[0027] Specific application example: When a car company submits a new electric bus certification test task: The task management center automatically links the battery safety testing clauses in the customer contract with GB38031-2020 in the laboratory standard library. The prototype vehicle parameter unit captures the basic vehicle parameters registered with the Ministry of Transport. Verification reveals a 2% deviation between the actual curb weight and the registered value, triggering a manual review. The equivalent judgment engine analyzes historical inspection data for the same vehicle model, finding a 95% similarity and recommending that some projects use historical reports. The abnormal process gateway automatically pauses the task and pushes the approval request to the designated terminal when it detects excessive electromagnetic radiation. Through the deep integration of the four-layer architecture of the task management center, the prototype vehicle parameter intelligent processing unit, the equivalent judgment core engine, and the abnormal process control gateway, the system achieves full-link intelligent management and control from task creation to report issuance, thereby meeting the complex and ever-changing certification needs in the automotive testing field.

[0028] The prototype vehicle parameter intelligent processing unit also includes: The data integrity verification module compares the MD5 hash value of the data returned by the Ministry of Transport API with the local cache value; The parameter deviation warning module automatically marks and triggers the review process when the supplementary parameters deviate from the standard library threshold.

[0029] Exemplarily, the data integrity verification module ensures the integrity of the sample vehicle parameter data obtained from the Ministry of Transport API through a double verification mechanism, specifically: Data capture phase: Call the official API of the Ministry of Transport through the HTTPS protocol to obtain basic parameters such as the model, engine number, emission standards, etc. of the sample vehicle.

[0030] Hash value calculation: Calculate the MD5 hash value of the original data returned by the API in real time.

[0031] Local cache comparison: Compare the calculated hash value with the hash value of the previous version in the system's local cache.

[0032] Consistency judgment: If the hash values ​​are consistent, the data is marked as verified and allowed to enter the subsequent processing flow; If there is inconsistency, the data retransmission mechanism will be triggered (automatically retry 3 times) and the exception log will be recorded.

[0033] In the parameter deviation warning module, standard library construction: Based on historical detection data and industry standards (such as GB / T18344-2016), a parameter standard library is constructed.

[0034] Comparison of supplementary parameters: Compare the parameters manually entered by the user (such as wheelbase and curb weight) with the parameter range of the corresponding model in the standard library.

[0035] Dynamic threshold calculation: Absolute deviation threshold: such as the wheelbase tolerance of ±5mm; Relative deviation threshold: such as the allowable error of curb weight is ±3%.

[0036] Early warning trigger: If a parameter exceeds the threshold, the system automatically marks the parameter and pushes the review task to the quality inspector's workstation.

[0037] The core engine for determining equivalents includes: The rule configuration layer supports customizing the consistency threshold of key component models and the similarity weight of detection items; At the decision execution layer, the random forest algorithm is used to calculate the feature similarity between historical detection data and the current sample vehicle.

[0038] For example, the rule configuration layer allows users to customize the consistency thresholds of key component models (such as engine model, transmission model) and the similarity weights of inspection items (such as 30% for emission inspection and 50% for safety inspection). The specific implementation method is: the front end provides a visual configuration interface, and the back end receives parameters through the API and persists them to the database.

[0039] The decision execution layer uses the random forest algorithm to calculate feature similarity based on historical inspection data and current sample vehicle parameters, and outputs a deemed judgment conclusion (such as whether it can be deemed equivalent or requires re-inspection).

[0040] Specific implementation steps: Data preprocessing: Extract sample vehicle parameters (such as wheelbase, curb weight) and test results from the historical test database.

[0041] Encode categorical features such as engine model.

[0042] Model training: Construct feature vectors (such as component consistency and detection item similarity).

[0043] Train a random forest classifier using historical data.

[0044] Real-time judgment: Input the current sample vehicle parameters and the model outputs a similarity score (0-100 points).

[0045] If the score is ≥ the threshold set in the rule configuration layer (such as 85 points), it is determined to be equivalent.

[0046] The system integrates with the CSS platform through message middleware to push the following data in real time: Prototype vehicle parameter version change log; Incremental update of the deemed determination report library; Operation report electronic signature state machine flow events.

[0047] For example, for the parameter version change log of the prototype vehicle, when the parameters are updated, the change details such as the change time, operator, and values ​​before and after the change can be sent through the message middleware.

[0048] For incremental updates of the deemed judgment report library, when a new report is generated or an old report is updated, incremental data is sent to the CSS platform instead of the full data, reducing bandwidth usage.

[0049] For the electronic signature state machine flow events of the operation report, when the status changes (waiting for signature, signing, signed, failed), event notifications are sent through the message middleware, such as the time when the signature was completed, the certificate information used, whether it was successful, etc.

[0050] The report generation module includes: A report generator that dynamically populates test results into XML templates based on the operational parameter library; A total report synthesizer that aggregates related sub-reports and calls the RESTful API of the tripartite signature service For example, the sub-report generator uses a dynamic template engine to parse XML report templates. The templates contain pre-set placeholders for test items and map fields to the operational parameter database through metadata tags. The data population mechanism utilizes MyBatis dynamic SQL technology, retrieving relevant data (such as vehicle VIN, emission standards, and safety device configuration) from the operational parameter database based on the test task ID and generating structured XML fragments according to template rules. The master report synthesizer aggregates multiple documents, using a DOM4J parser to merge sub-report XML files, locating the main report node via XPath, and inserting the sub-report content into designated sections. For third-party signature integration, the eSignbao RESTful API can be used for signature processing, with the signature results pushed to the front-end in real time. For example, after a testing agency completes certification testing for a particular truck model, the sub-report generator automatically extracts parameters such as the vehicle's wheelbase and curb weight and populates them into the "Road Transport Vehicle Fuel Consumption Test Report" template. The master report synthesizer then merges the five sub-reports and uses a third-party signature service to affix the CMA qualification seal.

[0051] The signature service integrates a batch processing framework, uses thread pool technology to process historical reports in parallel, and generates a ZIP compressed package with a digital watermark for download.

[0052] For example, the batch processing framework integrated with the signature service is developed based on the Spring Batch framework. It can support job warehouses and MySQL to store job metadata, use thread pool technology to process historical reports in parallel, and insert the report number and generation time code into the XML node through the watermark generation algorithm. OpenCV is used to overlay a semi-transparent organization logo at the bottom of the document page. The watermark content is bound to the report hash value. Modifying any field will cause the watermark verification to fail. For example, when a testing agency needs to add a new qualification seal to 5,000 test reports for the whole year of 2023: the batch processing framework automatically scans the historical report library, generates a task list and writes it to RabbitMQ, 15 threads concurrently call the signature service, and completes the processing of approximately 800 reports per hour. Each report is embedded with a watermark containing the words "2025 Qualification Review", and finally generates 5 ZIP packages (1,000 copies each) with an MD5 checksum file for download and verification.

[0053] This embodiment includes an abnormal process control gateway, which is connected to the SMS platform interface and pushes notifications at the following nodes: Send an encrypted link to the account manager when approving task assignments; When the process times out and is not processed, an alarm is sent to the monitoring terminal.

[0054] Exemplarily, the event listening and triggering logic exception process control gateway has a built-in event listener to capture the following two types of exceptions in real time: Approval task assignment event: When the detection task enters the approval stage, the system automatically identifies the person in charge of the task and generates a unique encrypted link.

[0055] Process timeout event: Through the preset SLA service level agreement timer, when the task processing time exceeds the threshold (such as no operation for 24 hours), it is automatically marked as timeout.

[0056] SMS content generation rules Encrypted link design: The task details page is encrypted using the national secret SM4 algorithm, and the link contains a dynamic token (valid for 1 hour) to ensure that only authorized personnel can access it.

[0057] Alarm information structure: includes core fields such as task number, timeout duration, and related detection items. For example: The detection system task TASK-202507-001 has timed out for 4 hours. Please log in to the system immediately to handle it.

[0058] Receiving-side permission control ensures that account managers can only receive encrypted links related to the tasks they are responsible for. Permissions are dynamically assigned based on the RBAC role-based access control model.

[0059] The monitoring terminal receives all timeout alarms and supports multi-dimensional filtering by region, task type, etc.

[0060] For example, if a truck inspection task stalls due to a parameter review delay, the system automatically triggers an approval task assignment event and sends an encrypted text message link to the pending approval page to the account manager. If the account manager doesn't handle the task within two hours, a process timeout event is triggered, and the supervisory terminal receives a timeout alert, initiating an escalation response mechanism (such as automatically assigning an alternate approver).

[0061] The system has a built-in knowledge graph of regulatory standards, which automatically associates inspection items with regulatory clauses during the task creation phase and generates a compliance checklist.

[0062] For example, the data source integrates multi-level regulatory data: including national standards such as "Technical Conditions for Motor Vehicle Operation Safety" (GB7258) and "Comprehensive Performance Requirements and Inspection Methods for Road Transport Vehicles" (GB 18565), as well as local implementation details. Structural processing: breaking down regulatory clauses into a triple structure of test items-technical requirements-compliance judgment conditions. For example: Entity 1: Braking performance detection Relationship: Based on Entity 2: Article 7.2.3 of GB 7258-2017 Attributes: No-load braking distance ≤ 3.8m (trucks with load mass ≤ 12t).

[0063] Dynamic update mechanism of the map: establish a regulatory monitoring module, subscribe to government announcement websites and industry association proposals through RSS, and automatically capture newly released or revised regulatory provisions.

[0064] An incremental update strategy is adopted to modify only the affected triple relationships, avoiding full graph reconstruction.

[0065] Automatic association process during task creation: When a user creates an inspection task, the system uses NLP technology to parse the key elements in the task description (such as vehicle type and inspection category) and extract core inspection items (such as emission inspection and rollover stability test).

[0066] Taking the inspection item as the query node, traverse the knowledge graph along the basis relationship and return all related regulatory clauses and technical requirements.

[0067] Example: Input new energy bus braking performance test, the system matches: GB 7258-2017 Article 7.2.3 (braking distance requirements) Article 5.4.1 of GB 38032-2020 (Coordination requirements for regenerative braking of electric buses) Compliance Checklist Generation: Based on the matching results, a structured list is dynamically generated, including the following elements: the name of the test item and the regulatory section to which it belongs Quantitative indicators of technical requirements (such as braking distance ≤ 4.4m) Test method standards (such as GB / T 13594-2003) Judgment rules (if the measured value ≤ the standard value, it is compliant) Specific application example: When a testing agency undertakes a batch of hybrid bus certification tasks: After the user enters vehicle model information in the task management hub, the system automatically associates 12 mandatory inspection items with corresponding regulatory provisions. The generated compliance checklist indicates that additional testing for the power battery enclosure's protection level (GB 38031-2020, Article 7.3) is required. After the inspector completes the inspection according to the checklist, the system automatically verifies compliance with all indicators, ensuring the report passes regulatory review.

[0068] This embodiment includes a 3C auxiliary miscellaneous fee calculation engine, which dynamically generates a miscellaneous fee matrix according to the regional coefficient and the detection complexity weight in the contract terms.

[0069] For example, the 3C auxiliary miscellaneous fee calculation engine is built between the contract management system and the inspection task scheduling system. By parsing the non-technical agreements in the contract terms (regional coefficient, inspection complexity weight), it dynamically generates a miscellaneous fee calculation model that complies with business rules, thereby realizing the standardization and automation of cost calculation.

[0070] Data analysis layer regional coefficient mapping: built-in fee adjustment coefficient table for provinces and cities across the country (such as Hainan Province coefficient 1.15, Northeast region coefficient 0.9), supports automatic matching through administrative division codes.

[0071] Complexity weight configuration: Set basic weights based on the classification of test items (such as safety performance testing and environmental testing), and dynamically adjust them based on the type of sample vehicle (passenger car / commercial vehicle).

[0072] Computational logic engine matrix generation algorithm: using a weighted multiplication model, miscellaneous fees = basic inspection fee × (regional coefficient + complexity weight) / 2, for example: Hainan commercial vehicle environmental protection inspection: basic fee 800 yuan × (1.15 + 1.2) / 2 = 940 yuan Threshold verification mechanism: When the calculation result exceeds the preset range (such as ±20%), the manual review process is triggered.

[0073] Dynamic update mechanism policy synchronization interface: regularly capture the latest 3C certification fee standards from the Ministry of Transport’s official website, parse the policy text through NLP technology, and automatically update the coefficient library.

[0074] Specific application scenarios When a car company carries out new car certification in Hainan: Contract analysis: The system extracts Hainan region (coefficient 1.15) and commercial vehicles (complexity weight 1.2) from the contract items.

[0075] Cost calculation: The engine automatically generates a miscellaneous fee matrix, which includes sub-items such as emission testing fees and brake performance testing fees. The calculation basis is marked for each fee.

[0076] Result output: Generate a structured expense list, synchronize it to the customer portal system, and support batch confirmation according to the inspection stage.

[0077] This embodiment includes a security authentication layer that deploys a two-factor authentication gateway to implement inspection tasks in different regions and sites: Access region lock based on GeoIP; Double verification of dynamic token TOTP and SMS verification code.

[0078] For example, the security authentication layer implements hierarchical security control through a two-factor authentication gateway: Regional access control: Based on GeoIP technology, restrict operation permissions to designated physical areas; Dynamic identity verification: Combine TOTP (time-based dynamic password) and SMS verification code to form a double verification barrier.

[0079] GeoIP access region lock IP positioning mechanism: map user IP to provincial / city-level geographic location through MaxMind GeoIP2 database; Whitelist strategy: preset areas where operations are allowed (such as Hainan Province) in the system configuration, and non-whitelisted IP addresses will be directly blocked from requesting. Dynamic task binding: When a detection task is created, it is automatically associated with the IP region of the operating terminal. Subsequent processes only allow devices in this region to access it.

[0080] Two-factor authentication process: First factor (TOTP): When logging in, users need to enter a 6-digit dynamic code generated by the authentication app, and the system verifies time synchronization (drift tolerance ±30 seconds); Second factor (SMS verification code): After TOTP verification is passed, the system will send a 6-digit random code to the reserved mobile phone number, which must be submitted within 5 minutes; Fault-tolerant design: 3 consecutive TOTP errors will trigger account lockout. If the SMS verification code fails more than 5 times, the mobile phone number will be banned from authentication within 24 hours.

[0081] Specific application scenarios: When the inspector submitted the braking performance data of a truck at the Hainan site: Region check: If the system detects that the operating IP belongs to Hainan Province, it will allow the authentication process to proceed; if it is a Beijing IP, it will be directly blocked and logged; Two-factor verification: The inspector enters the TOTP code (generated by the mobile app) and the SMS verification code; Authorization release: After passing the two-factor verification, the inspector can upload the inspection data to the task management center and trigger the compliance check simultaneously.

[0082] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A vehicle certification detection task analysis system, characterized in that: The system comprises: The task management hub is used to create testing tasks and establish mapping relationships between contract items, customer testing standards, and internal standard libraries; Intelligent processing unit for prototype vehicle parameters, including a Ministry of Transport data capture interface, a parameter re-entry and verification engine, and an operational parameter library generator; The core engine for determining equivalents outputs equivalent determination conclusions based on multi-dimensional similarity analysis of sample vehicle parameters and historical test data; The exception process control gateway responds to parameter exceptions, report returns and task change events, and drives dynamic approval workflows.

2. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: The prototype vehicle parameter intelligent processing unit also includes: The data integrity verification module compares the MD5 hash value of the data returned by the Ministry of Transport API with the local cache value; The parameter deviation warning module automatically marks and triggers the review process when the supplementary parameters deviate from the standard library threshold.

3. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: The core engine for determining equivalents includes: The rule configuration layer supports customizing the consistency threshold of key component models and the similarity weight of detection items; At the decision execution layer, the random forest algorithm is used to calculate the feature similarity between historical detection data and the current sample vehicle.

4. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: The system integrates with the CSS platform through message middleware to push the following data in real time: Prototype vehicle parameter version change log; Incremental update of the deemed determination report library; Operation report electronic signature state machine flow events.

5. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: The report generation module includes: A report generator that dynamically populates test results into XML templates based on the operational parameter library; The total report synthesizer aggregates related sub-reports and calls the RESTful API of the three-party signing service.

6. A vehicle authentication and detection task analysis system as claimed in claim 5, characterized in that: The signature service integrates a batch processing framework, uses thread pool technology to process historical reports in parallel, and generates a ZIP compressed package with a digital watermark for download.

7. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: Including abnormal process control gateway, abnormal process control gateway connects to the SMS platform interface and pushes notifications at the following nodes: Send an encrypted link to the account manager when approving task assignments; When the process times out and is not processed, an alarm is sent to the monitoring terminal.

8. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: The system has a built-in knowledge graph of regulatory standards, which automatically associates inspection items with regulatory clauses during the task creation phase and generates a compliance checklist.

9. A vehicle authentication and detection task analysis system as claimed in claim 1, characterized in that: It includes a 3C auxiliary miscellaneous fee calculation engine, which dynamically generates a miscellaneous fee matrix based on the regional coefficient and detection complexity weight in the contract terms.

10. A vehicle authentication and detection task analysis system according to claim 1, characterized in that: Including the security authentication layer, the security authentication layer deploys a two-factor authentication gateway to implement the inspection task operations in different regions: Access region lock based on GeoIP; Double verification of dynamic token TOTP and SMS verification code.

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