474results about How to "Achieve traceability" patented technology

The invention discloses a tight-lock coupler intelligent tensile testing machine and a testing method thereof, and belongs to the technical field of tight-lock coupler test.The tight-lock coupler intelligent tensile testing machine comprises a mounting bottom plate and an electric control cabinet, and a support for supporting a tight-lock coupler to be detected is mounted on the surface of the mounting bottom plate; a tensile connecting frame for connecting the tight-lock coupler is mounted on the surface of the bottom plate on one side of the support, an integrated design of'tensile force detection and visual detection 'is innovatively adopted, mechanical parameter acquisition and visual deformation observation are combined, traditional mechanical data such as tensile force and displacement are obtained, and visual characteristics such as fine deformation and crack initiation are captured; precise synchronization of pulling force application, displacement collection and camera shooting is achieved through the synchronous controller, the real-time corresponding relation of pulling force-displacement-visual deformation is established, the problems that an existing device is single in detection dimension and poor in data relevance are solved, and the potential quality hazard checking capacity and the persuasion of a detection result are improved.

The invention relates to the field of automobile electronic control, in particular to a running state monitoring method for a vehicle motor controller, which comprises the following steps: S0, determining a key running signal needing to be continuously monitored; the communication format of the key operation signal on a vehicle-mounted CAN bus is defined; the method comprises the following steps: S1, constructing and deploying an embedded operation event recording system in a motor controller; s2, after the motor controller is powered on and runs, the embedded running event recording system constructed in the S1 is started, and recording of the running event is completed; s3, continuously monitoring and accumulating the power-off dormancy times of the motor controller through the storage aging management module; and executing an erasing operation on the special storage block. According to the method, reliable storage and on-demand return of key event data can be realized on the premise of not depending on an external debugging interface and not increasing significant hardware cost, so that effective monitoring of the working state of the motor controller is realized.

The invention discloses an automatic product grabbing system and method, and relates to the technical field of industrial robots, in the system, an equipment body is provided with a grabbing station and a placing station, an inbound positioning assembly outputs an AGV tool vehicle in-place signal, and a jacking positioning assembly establishes a preset grabbing height; the visual positioning assembly collects an image output pose compensation amount, the bar code recognition assembly obtains a bar code and interacts with the manufacturing execution system to obtain a verification result, the controller issues the compensation amount to the industrial robot control end when verification is allowed, and an end effector is driven to complete positioning, locking and unlocking of grabbing locked by a tool vehicle clamp; the tray transferring and positioning mechanism completes transferring and positioning of the shipping tray, and the unlocking and locking mechanism unlocks / locks the locking block handle and conducts visual review in the placing process. By means of the technical scheme, the grabbing and placing alignment precision and the mistake proofing capacity are improved, the risks of collision, falling and locking omission are reduced, and the takt time stability and traceability are improved.

The invention discloses an electronic archive intelligent data management method and system based on a large model. The method comprises the following steps: firstly, acquiring an electronic archive file, performing unified access, identifying a text through an OCR (Optical Character Recognition) technology, and reserving original layout coordinate information; analyzing the document page by page to generate a page-level structured object containing text and position mapping; then, on the basis of a preset domain prompt template, calling a large language model to extract file metadata from the page-level object, recognizing entities and relationships in combination with file knowledge ontology, and generating a semantic triple containing an evidence source page number; and finally, fusing the metadata and the triple to construct an electronic archive knowledge graph with a page-level traceability function. According to the invention, through a whole-process semantic governance mechanism from access, analysis to knowledge generation, the problems of difficult analysis of unstructured data, weak semantic understanding and lack of traceability in traditional archive management are effectively solved, and the intelligent level and data credibility of archive governance are significantly improved.

The invention discloses a power production event type identification and grade evaluation method based on artificial intelligence, and belongs to the field of power safety production, and the method comprises the steps: receiving event description information inputted by a user, extracting event key elements through a natural language understanding model, converting the event key elements into query vectors, and obtaining the query vectors; searching related knowledge fragments in a pre-constructed electric power professional knowledge base, combining the event description information, the key elements and the knowledge fragments into enhanced cue words, inputting the enhanced cue words into a large language model subjected to field fine tuning, and finally, performing comprehensive analysis by the large language model to obtain the enhanced cue words. And generating a structured research and judgment result containing the event type, the level, the research and judgment basis and the submission requirement. According to the method, accurate and efficient research and judgment of the electric power security event are realized by fusing the retrieval enhancement generation technology and the field fine tuning large model, and interpretability and traceability of a conclusion are ensured by outputting research and judgment basis through the requirement model.

The invention discloses a Linux-oriented vulnerability repair verification method and system and a medium. The method comprises the steps of creating a test application form for a CVE vulnerability patch in a task management system, preparing a test environment for CVE vulnerability repair verification as well as a required test table, a software source and a test strategy file, and calling a tool interface to automatically trigger an assembly line; the assembly line executes the test suite in the test environment based on the test table, the software source and the test strategy file and collects an execution state, and if the execution state is failure, automatic retry can be carried out on the CVE vulnerability based on manual triggering; and finally, generating a report file, writing a verification result for the test application form in the task management system, and if the verification result is that verification is passed, issuing a service pack of the CVE vulnerability. The invention aims to realize efficient, traceable and extensible Linux vulnerability repair verification, realize full automation and intelligence of the vulnerability verification process, and improve the accuracy, traceability and expandability of verification.

The invention relates to a Keystone-based deep ground security heterogeneous data fusion method and system, and the method comprises the steps: deploying a Keystone trusted execution environment on a deep ground edge computing node, creating a security enclave, carrying out the encryption access of multi-source heterogeneous data on the basis of remote authentication and key agreement, completing the space-time alignment and feature extraction after decryption in the enclave, and carrying out the fusion of the multi-source heterogeneous data. And performing cross-modal association analysis and risk assessment based on a preset model or a rule engine to obtain a fusion result, encrypting and signing the fusion result in the enclave, distributing the fusion result to an authorized receiver through a secure channel, and realizing one-time task destruction, long-term task cycle reconstruction and key refreshing in combination with enclave full life cycle management. According to the method, the credibility and the real-time performance of heterogeneous data fusion processing in a complex scene can be improved while the confidentiality and the integrity of deep operation and maintenance data are guaranteed.

The application provides a rule object-based management method and device in an AI operating system and a readable storage medium. The method comprises: performing pre-access consistency verification on a to-be-accessed object to obtain a first verification result; if the first verification result is a verification pass, registering the to-be-accessed object, and determining a target rule object according to object description information; establishing binding association information based on the object description information and the target rule object; obtaining actual running information of the to-be-accessed object, and performing runtime consistency verification on the actual running information based on the binding association information and the target rule object to obtain a second verification result; performing a corresponding control operation according to a control strategy mapping relationship of the second verification result and the target rule object, and generating an execution archive record. The embodiment of the application can ensure that the to-be-accessed object does not run out of the access time admission condition based on the binding association information, and improve the accuracy and traceability of system operation control.

The invention relates to the technical field of data management, and discloses a medical data secure transmission method and a big data digital signature system, and the method comprises a hierarchical processing step, a privacy enhancement step, a key negotiation step, a segmented transmission step and an audit tracking step. The system comprises a signature preprocessing module, a hierarchical signature module, a privacy purification module, a verification module and a tracing module. According to the method, a risk association map is constructed through hierarchical processing, and accurate identification of data association risks is realized; privacy and availability are balanced through differentiated privacy enhancement, authorization controllability is enhanced in combination with block chain key management, large file transmission integrity and non-repudiation are guaranteed, and whole-course audit is controllable. According to the system, the relevance between the signature and the privacy feature is improved through module design, the integrity and relevance of the signature chain are guaranteed, privacy protection and verifiability are compatible, efficient verification is achieved, the dispute traceability is provided, and pediatric medical data safety is guaranteed in cooperation with the method.

The invention relates to the technical field of intelligent education, in particular to an intelligent practical operation assessment system and method based on multi-modal perception, and the system comprises a question setting and rule configuration module, a local assessment terminal, a hardware connection monitoring module and a remote management service terminal. The question setting and rule configuration module is used for generating a structured test question rule file, the hardware connection monitoring module is used for collecting conduction relation data, and the local assessment terminal comprises a man-machine interaction layer, a sensing and monitoring layer and an application logic and control layer; the remote management service terminal is used for data storage and instruction issuing. The system has the following advantages and effects: through the cooperation of the question setting and rule configuration module, the local assessment terminal, the hardware connection monitoring module and the remote management service terminal, the operation behavior and the tool state are identified; multi-mode perception, automatic monitoring and accurate scoring of electrician practical training type practical operation assessment are realized, and the objectivity, efficiency and traceability of assessment are improved.

The invention discloses a full-process visual monitoring and intelligent management method for a glass bracket production line, and relates to the technical field of industrial quality control, and the method comprises the steps: carrying out the continuous image collection of all stations of the glass bracket production line through an image collection unit, and constructing a full-process image data sequence; detecting the size of the glass bracket by using the qualified glass bracket size image database, and judging whether the size is abnormal or not; further performing defect detection on the glass bracket with the normal size, and determining whether an abnormal defect exists or not through pixel value difference analysis; and finally, summarizing the glass brackets with abnormal sizes or defects and related information thereof, and generating a visual quality report, so as to quickly position problems and optimize the production process. The comprehensive monitoring and intelligent management of the glass bracket production process are realized, and the production efficiency and the product quality are improved.

This invention relates to the field of intelligent water control terminal control and electromagnetic compatibility processing technology, and particularly to an anti-interference water control terminal control method and system with abnormal alarm. The method includes: reading raw signals in parallel from water shortage, anti-magnetic, and flow sampling interfaces; processing and mapping these signals into alarm events and writing them into a hardware alarm event set; performing board-level partitioning layout based on the information in the event set to generate a partitioning layout configuration set; configuring decoupling units, laying grounding wires and copper plating, and setting multiple grounding nodes accordingly; assigning power supplies to each detection interface to an analog power path and power supplies to the main control and communication modules to a digital power path, configuring filtering units and isolation nodes; laying grounding copper foil and vias for the crystal oscillator, and configuring metal shielding structures for key modules; reading alarm signals based on the obtained configuration set and encapsulating them into alarm messages, uploading them via Bluetooth or 4G channels, receiving management results, and generating a terminal alarm processing status. This invention improves the anti-interference capability and alarm reliability of the water control terminal through event-driven board-level layout and power supply link isolation.

This invention discloses a unified management and scheduling method, system, and storage medium for multiple workflow engines, belonging to the field of workflow orchestration and task scheduling technology. The method includes: receiving a start request for a target workflow, creating and recording a workflow instance, and determining the engine type; based on the engine type, selecting a target runtime adapter, driving the workflow instance to execute in the engine, and establishing a node execution record; when a target workflow node enters a waiting state, writing waiting and recovery information into an extended storage area; upon receiving a recovery advancement request, resuming the template workflow's progress, and verifying and auditing the recovery data; submitting the verified recovery data to the target runtime adapter, driving the target workflow node to complete the recovery advancement and triggering subsequent node scheduling, and outputting unified progress data. This invention can reduce the integration cost when multiple engines coexist, and improve cross-engine collaborative scheduling capabilities and audit traceability capabilities.

The invention discloses a multi-agent cooperative processing system for wind power fault questions and answers. The system comprises a knowledge construction agent module used for extracting a knowledge triple from an operation and maintenance document and constructing a wind power fault knowledge graph; the task planning agent module is used for analyzing a problem input by a user and generating a task execution plan; and the task execution agent module sequentially calls information extraction, protection analysis and parameter analysis agents to execute tasks, and inputs a result into a language model to generate a natural language answer with a reasoning path. According to the method, cooperative processing of knowledge integration, task decomposition and data analysis can be realized, the problems of knowledge fragmentation, term inconsistency and inexplanatory reasoning in the prior art are effectively solved, and the accuracy, reliability and traceability of wind turbine generator fault diagnosis are remarkably improved.

The present application belongs to the technical field of industrial internet security, and relates to an industrial internet vulnerability library establishment method, which solves the problems of low construction quality, weak traceability, insufficient continuous evolution ability and difficulty in supporting deep security application of the existing vulnerability library. The present application obtains industrial internet multi-source vulnerability data and external feedback data, obtains extraction results and initial confidence based on multi-source vulnerability data by adopting rule extraction and remote supervision deep learning joint extraction, divides the certainty knowledge base and the to-be-reviewed queue according to the double threshold after the confidence is optimized by the graph convolution network, analyzes the external feedback data of the samples in the to-be-reviewed queue as the instant reward signal, optimizes the sampling strategy and updates the model through deep reinforcement learning, extracts triples from the certainty knowledge base to build a knowledge graph and generate a version hash chain regularly, and obtains a structured vulnerability knowledge base containing a hash chain and confidence evaluation. The present application realizes high-precision construction and dynamic optimization of the vulnerability library.

This invention discloses a molecular genetics laboratory management system for a genetics center, belonging to the field of laboratory information management technology. It provides real-time monitoring of sample status, dynamic scheduling of subsequent tasks, and early warnings for near-expiration and overdue samples. Experimental data is collected through structured electronic task sheets, and the analyzed genetic variation information is dynamically updated to a mutation database. Historical variation data is intelligently recommended for report generation. Report content is automatically populated based on variation data and adapted to project templates. It supports configurable multi-level review processes, enabling online collaboration and operation tracking. Based on review results, first-use acceptance and automatic deduction of inventory for reagents and consumables are performed. Based on resource linkage and traceability, gene disease databases and mutation databases are collaboratively constructed. This system achieves fully automated management from intelligent sample monitoring and scheduling to automatic report generation and review, significantly improving the operational efficiency, data accuracy, and resource utilization of the genetics laboratory.

The application discloses an AI-assisted software development method based on a rule-skill-manual knowledge architecture, and relates to the technical field of AI software development, comprising: setting a constraint priority system according to the execution stage of the AI-assisted software, and constraining each stage of the AI-assisted software; controlling the switching of each stage of the AI-assisted software through a stage state inference mechanism and an artificial confirmation access control mechanism; setting a manual automatic matching and input template generation mechanism and an experience backwriting and knowledge self-growth mechanism; using a statistical quantification and effect evaluation system to statistically analyze the running results of the AI-assisted software; and limiting the execution of the specified stage of the AI-assisted software according to a focus point forced isolation mechanism. The application solves the problems of chaotic specification management, heavy artificial burden, lack of process control, low efficiency of demand specification matching and inability to deposit and iterate engineering knowledge existing in the prior art AI-assisted programming technology.

The application discloses a coal flotation oil atomization effect evaluation system adopting data modeling, and relates to the technical field of intelligent control of coal flotation process in mineral processing engineering, and comprises a data acquisition module, which is used for acquiring physical characteristic parameters of atomized oil drops and flotation process parameters in a coal flotation process in real time; and a hybrid model construction module connected with the data acquisition module and used for constructing an atomization effect evaluation model based on a mechanism model and a data-driven model. The coal flotation oil atomization effect evaluation system adopting data modeling realizes accurate quantitative evaluation of the dispersion state of atomized oil drops by constructing a multi-source data perception network and a mechanism data hybrid driving model. The double-heterogeneous verification mechanism is adopted, cross-verification of process correlation analysis and result inversion checking is performed, the evaluation result has high reliability and traceability, and the technical problem that a traditional method depends on experience and cannot objectively quantize the atomization effect is effectively solved.

The present application relates to the technical field of liquid-based bacterial automatic staining equipment, and particularly relates to a mycobacterium tuberculosis automatic staining machine. The whole machine adopts a modular integrated structure. The upper part of the machine case is integrated with a temperature control device, a track device, a sample conveying trolley and a signal receiving device, which are core staining operation components. The middle and lower parts of the machine case are drawer structures for accommodating reagents, waste liquid and a printing assembly. The present application relies on the track device to carry multiple sample conveying trolleys, realizes pipeline conveying of mycobacterium tuberculosis samples, and automatically completes the full-automatic operation of reagent filling, constant-temperature staining, negative pressure cleaning and waste liquid recovery in cooperation with multiple liquid processing workstations. Compared with the existing mycobacterium tuberculosis automatic staining equipment on the market, the present application solves the problems of sample smear falling off, cross contamination, limited continuous operation and sample transfer during operation, realizes continuous automatic completion of staining, cleaning and drying operation for a large number of samples, and is suitable for large-scale detection of mycobacterium tuberculosis in medical institutions.

This invention provides an automated testing device for UAV data links, including an industrial control computer, a display, a spectrum analyzer, a programmable DC power source, a programmable adjustable attenuator, a fixed attenuator I, a fixed attenuator II, a power divider I, a power divider II, an RF switch, a shielded box I, and a shielded box II. The software of the industrial control computer includes a system management module and an automated testing module. The advantages of this invention are: it uses general-purpose testing equipment, is based on a computer-automated program, and controls the settings of each testing device via a bus to simulate remote control, telemetry, image data transmission and reception, and bit error rate statistics; it achieves automated testing of core functional performance indicators of UAV data links such as power consumption, transmit power, spectrum, functionality, receiver sensitivity, bit error rate, and latency.

The invention discloses an EMIR verification method and system, a computer and a storage medium. The method comprises the following steps: appointing a time sequence library file directory, an RC file path and a constraint file path when an automatic script runs; traversing a time sequence library directory through an automatic script, analyzing time sequence library files, and extracting a PVT condition and an RC model corresponding to each file; automatically classifying and mapping the extracted PVT condition and RC model according to a preset classification rule to generate a multi-process corner combination; automatically generating a multi-mode multi-corner-point MMMC configuration file according to the multi-process corner point combination, and outputting a traceable mapping list and an association table; in a chip physical implementation process, dual-stage EMIR verification is executed in a power supply planning stage and a verification stage. According to the method, the MMMC configuration file matched with the angular point is automatically analyzed based on the time sequence library, and staged EMIR verification is combined in the physical implementation process, so that the overall design efficiency and reliability are improved.

The invention relates to the technical field of pet medical information, and discloses a pet cloud medical record management method and system, and the method comprises the steps: collecting pet health data through a user terminal, and the pet health data comprises video and text description; uploading the video to a video processing module, automatically editing the video through the video processing module, and extracting key segments; the text description and the key segments are integrated, and a structured pet electronic medical record is generated through a medical record generation module; storing the pet electronic medical record to a cloud storage server, and storing the hash value of the pet electronic medical record to a block chain network; and according to a user instruction, safe sharing and multi-terminal synchronization of the pet electronic medical record are realized through the safety control module. According to the method, the problem that the pet cannot know the pain point of the illness state by himself / herself is solved, the behavior performance of the pet can be effectively recorded and traced, the burden of a pet owner for sorting data is relieved, and meanwhile, a more intuitive and complete diagnosis and treatment basis is provided for veterinarians.

The invention discloses a regional prospecting method and system based on multi-element space coupling of a metallogenic system, and belongs to the technical field of mineral resource prospecting prediction and comprehensive modeling of the metallogenic system. The method comprises the following steps: acquiring multi-source spatial data covering a mine concentration area; according to a process mechanism of a metallogenic system, converting and constructing the multi-source spatial data into a background domain, a transmission domain, an ore containing domain and a target domain to indicate spatial distribution indexes; constructing a comprehensive metallogenic potential index for representing a spatial distribution pattern of the regional metallogenic potential; an uncertainty prediction index is constructed based on the consistency deviation degree between the domain index responses and the local difference, and synchronous credibility quantification is carried out on the comprehensive mineralization potential evaluation result; and in combination with a joint discriminant relationship between the mineralization potential index and the uncertainty index, performing classified screening and target region delineation on the regional mineralization abnormal unit, so as to realize continuous quantitative prediction of the regional scale mineralization potential and optimization of the prospecting target region, and provide a mineral geological exploration service developed by using a high technology.

The application provides a medicine distribution verification method and system based on image recognition. The delivery process including a continuous action sequence is forcibly guided and verified, which fundamentally eliminates cheating behaviors such as pre-stored photos and staged photos. The system verification must rely on specific actions completed in real time, which improves the cost of fraud. At the same time, the verification process is visualized, standardized, automated, evidence-based and traceable. Through the collection and fusion analysis of action information such as action video, environmental continuous parameters and medicine packaging information, the compliance, effectiveness, authenticity and continuity of the medical and pharmaceutical delivery process are ensured, and an unalterable verification record is generated, solving the credibility and traceability problem of the end verification of medicine distribution.

The application relates to the technical field of standard gas preparation, and discloses a pressure method for preparing carbon dioxide and carbon stable isotope standard gas, and a system thereof. The method comprises the following steps: obtaining basic parameters for gas preparation, calculating core pressure control parameters of gas preparation operation based on the mass conservation of carbon dioxide and the mass conservation of carbon stable isotopes, and sequentially completing the steps of filling decarburization atmosphere through an adsorption tube, filling high-concentration raw material gas through a quantitative ring, and supplementing the final pressure with ambient atmosphere, so as to complete the preparation of standard gas. The method can accurately control the carbon dioxide concentration and the carbon stable isotope value simultaneously, is suitable for a conventional pressure method gas preparation device, has high preparation precision and strong repeatability, and meets the high-precision standard gas use requirements of atmospheric observation, equipment calibration and the like.

The invention provides a method and system for collecting working state data of a manufacturing execution system, and the method comprises the steps: obtaining an equipment working data set, a personnel working video set and a workpiece information set, and respectively extracting a corresponding equipment working feature sequence set and a corresponding workpiece feature sequence set, performing illumination compensation, foreground segmentation and time window splitting on the personnel operation video set, and performing multi-dimensional attitude decoupling, action semantic recognition and production rhythm modeling on the personnel operation video set after the time window splitting to obtain a personnel action feature sequence set; performing dynamic time warping, beat alignment and feature binding based on the production task order to obtain a multi-modal production feature sequence set, and performing collaborative feature enhancement and dimension reduction compression to obtain a multi-modal working time sequence feature sequence set; and by taking the production task order as an edge index, constructing a dynamic hypergraph model of the multi-modal working time sequence feature sequence set, and carrying out man-machine collaborative analysis on the dynamic hypergraph model to obtain a working state data sequence.

The invention provides a non-field supervision report verification method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, compliance verification is carried out on report data based on a preset verification rule base, and fluctuation analysis is completed in combination with a logic association relationship between indexes, so that the verification efficiency of a non-field supervision report is improved. And when verification or analysis is not passed, a problem reason explanation containing a specific value, an index meaning and a logical relationship of the associated index is generated, so that the problems that in the prior art, verification depends on a static table formula, cross-period comparison is manually carried out, only a binary verification result can be output, and the verification efficiency is low can be solved. According to the method, the technical effects of improving comprehensiveness and accuracy of report data verification, realizing traceability of error reasons, and further improving supervision data submission quality and risk identification efficiency are achieved by solving the problem that the specific numerical details and logic principles of potential errors cannot be traced.

This invention discloses an industrial material inspection method and system based on feature extraction and contrast enhancement, belonging to the field of image inspection technology. It includes: S1, acquiring the transmitted signal using a digital flat panel detector and generating an original digital image based on the differences in X-ray absorption by different materials or defects; S2, performing uniformity correction and normalization enhancement on the original digital image, and achieving preliminary differentiation of different material regions; S3, dividing the original image data into processing domains based on the preliminary differentiation results, and performing differentiated enhancement processing based on the local feature attributes of each processing domain to generate a binary feature image. By integrating X-ray penetration imaging, multi-dimensional image enhancement, and a deep learning-driven intelligent rating system, this invention fundamentally solves the key technical bottlenecks in traditional industrial material inspection, such as inconsistent image quality, lack of material identification, and strong subjectivity in rating, achieving an automated, intelligent, and objective upgrade in industrial material defect detection.

This application relates to an event-driven method and computing device for recognizing revenue from intra-group transactions. The method includes: acquiring a transaction order and determining its type; if the transaction order is an intra-group transaction order, acquiring its triggering event; if the triggering event is a key business completion event, generating a cost recognition voucher for the purchaser of the transaction order and a revenue recognition voucher for the seller of the transaction order; wherein the key business completion event represents a business operation event indicating that the relevant performance obligations have been fulfilled. This achieves a fundamental shift from employee-based identification and triggering to system-based perception and response, improving the timeliness and accuracy of financial processing, thereby reducing operating costs and increasing processing efficiency.

This application discloses a method and system for determining pollution causes based on the correlation between atmospheric diffusion conditions and emission contributions, relating to the field of atmospheric pollution cause identification. The method includes: aligning meteorological, emission, and receptor observations to a unified spatiotemporal reference to obtain multi-source baseline data; calculating a diffusion stability index characterizing vertical mixing and horizontal transport using meteorological monitoring, generating time-varying diffusion condition weights; generating a time-response diffusion kernel from the emission source to the receptor point using a diffusion model under unit emission conditions, and constructing diffusion-contribution correlation information with observed concentrations to characterize the temporal coupling strength; establishing a diffusion-contribution dynamic optimization model, using diffusion condition weights to constrain the coupling relationship, and iteratively solving for time-varying contribution coefficients based on the convergence target of simulated and observed concentrations, outputting the dynamic contribution of each source and the pollution cause. Thus, time-varying diffusion conditions are explicitly introduced into the source contribution inversion framework, achieving stable separation and reliable attribution of source contributions.