519 results about "Invalid Data" patented technology

The invention discloses a multi-stage equipment energy efficiency optimization control system and method for an efficient machine room, and relates to the technical field of equipment optimizing.The method comprises the steps that environment parameter data and design parameter data of a refrigerating machine room are obtained, an environment correction factor is analyzed, and the cold load rate is dynamically corrected based on the environment correction factor; on the basis of preset delay time, phase-space reconstruction is carried out on the historical corrected cold load rate sequence, the final embedded dimension is analyzed, and a hybrid prediction model is constructed on the basis of the final embedded dimension; matching optimal operation parameters based on physical resonance characteristics of equipment in combination with comprehensive energy efficiency indexes of the machine room; and performing data structure compression on the optimal operation parameters and the comprehensive energy efficiency indexes of the corresponding machine room, performing screening analysis on data points, and updating a parameter library. And invalid data interference is reduced, so that the system can realize self-adaptive optimization in long-term operation, and the data storage and calculation efficiency is improved.

The invention discloses a real-time interaction and intelligent management method for a multi-dimensional data space, and relates to the technical field of data interaction management, and the method comprises the following steps: I, collecting multi-source data, including structured data, unstructured data and spatio-temporal data, in real time through a diversified collection terminal, and dynamically adjusting the sampling frequency based on a data entropy value, carrying out cross-device space-time synchronization calibration and edge end lightweight processing on the acquired data; iI, preprocessing the data flow in real time, fusing the multi-modal data, and the like. According to the method, the sampling frequency is dynamically adjusted based on the data entropy value, and in combination with edge end lightweight processing, invalid data transmission is reduced, and the key data acquisition efficiency is improved; hot data is stored in a time sequence database and a memory database, real-time monitoring of an emergency scene and second-level response of emergency command are supported, dynamic capacity expansion and shrinkage of computing resources are matched, edge-cloud end collaboratively distributes tasks, network delay is reduced, and system stability and response speed in a high-concurrency scene are guaranteed.

The invention relates to the technical field of data processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data migration method, device, equipment and medium based on task offload, which comprises the following steps: scanning a source end directory hierarchy and a target end directory hierarchy, and generating source end file metadata and target end file metadata; files are classified into source-end unique files, target-end unique files and two-end shared files based on file paths, and the files are transmitted to a comparison processing module; generating a source end newly-added migration task, a difference coverage migration task and a target end deletion migration task; and transmitting the migration task to a migration processing module and executing the migration task to generate a migration result. According to the method, source-end unique files, difference files and target-end redundant files are processed in a classified mode, full-amount migration is disassembled into incremental tasks to be executed in a split mode, and the invalid data transmission amount is reduced; a difference coverage task is generated based on double comparison of metadata and content, repeated coverage of homonymous files is avoided, and redundant data is automatically cleaned.

A hotspot data elimination and maintenance method in a distributed cache system comprises the steps that the access frequency, the time locality score, the service weight and the real-time data popularity value of data are acquired, and the dynamic priority score of the data is generated; determining failure data based on the dynamic priority score; dividing the data into hot spot area data, temperature spot area data and cold spot area data, when the cache space is insufficient, preferentially eliminating the data with the lowest dynamic priority score and the retention benefit value lower than a preset threshold value in the cold spot area data, and if the cache space is still insufficient, performing data elimination on the temperature spot area data according to the latest access time of the temperature spot area data; packaging the cold point area elimination data, the warm point area elimination data and the failure data into a final transaction message; and broadcasting the final transaction message through a preset protocol, and performing distributed consistency maintenance operation on the final transaction message through the receiving node. According to the invention, intelligent and efficient cache data elimination and consistency maintenance management can be realized.

The invention discloses an MQTT message transmission optimization method and system. The method comprises the steps of analyzing a theme, extracting a device type, a data feature and a geographic position triple, calculating a hash value, and mapping a device to a specified Broker fragment cluster node to generate a fragment mapping table; processing the equipment data in the edge domain in the fragment mapping table through an edge calculation layer, removing invalid data according to a preset rule, merging the equipment data in the same fragment node, and embedding a fragment node ID for an aggregation message generated after merging; identifying a fragment node ID and routing to a target fragment node, positioning a corresponding shared memory pool, and writing the message into the shared memory pool; and responding to a direct access request of the client, so that the client directly accesses the data from the shared memory pool through the user mode network stack. According to the method, the problem of uneven load is effectively solved, multiple times of state switching in the data transmission process is avoided, and the MQTT message transmission efficiency is improved while the transmission cost is reduced.

The invention provides a cache cleaning method and device based on large model reasoning. The method comprises the following steps: monitoring the cache capacity of a hash table cache pool; when the current cache capacity of the hash table cache pool is greater than or equal to a preset capacity threshold value, obtaining access information corresponding to one or more cache entries, and screening a first to-be-cleaned cache entry through a preset cache cleaning algorithm according to the access information; and / or obtaining importance information corresponding to one or more cache entries, and screening a second to-be-cleaned cache entry meeting an importance cleaning rule according to the importance information; and according to the first to-be-cleaned cache entry and / or the second to-be-cleaned cache entry, cleaning the cache in the hash table cache pool, and updating the cache capacity of the hash table cache pool. According to the method and the device, the cleaned cache items are identified and determined according to the access information and / or the context importance information of the cache items, so that the cache redundancy and the accumulation of invalid data are reduced, and the cache management efficiency is improved.

The invention relates to the technical field of logistics management, and discloses an operation and control analysis method, device and equipment based on logistics transportation, and a medium, and the method comprises the steps: carrying out the preprocessing of to-be-controlled waybill data, removing invalid data, and screening an effective delivery record as a judgment basis; establishing a multi-layer affiliation relationship according to the judgment basis and marking label information; inputting the waybill data, the corresponding multi-layer affiliation relationship and the label information into an abnormal path identification model, and outputting an abnormal type corresponding to the waybill data, wherein the abnormal type at least comprises trunk line empty running, advanced departure and non-network area recovery type anomalies; and generating an abnormal path trend according to the waybill data and the corresponding abnormal type, and generating delivery optimization information according to the abnormal path trend, the delivery vehicle corresponding to the waybill data and the main delivery area so as to perform delivery optimization on the waybill data within the set time and distance range. The method is suitable for intelligent management of logistics enterprises on delivery path optimization, transport capacity scheduling and operation efficiency improvement.

The invention provides a multi-source log fusion driven database monitoring method and system, and relates to the technical field of computers.The method comprises the steps that format analysis processing is conducted on multi-source heterogeneous logs of a to-be-monitored database on the basis of a dynamic analysis template library, and initial database logs are obtained; performing data preprocessing on the initial database log based on a rule engine to obtain a database log; and performing streaming processing on the database log to obtain a log event stream, and sending the log event stream to the server side, so that the server side detects the log event stream based on the log anomaly detection model and the associated alarm analysis engine, and generates a monitoring analysis result of the to-be-monitored database. By means of the mode, the technical bottleneck that heterogeneous database logs are difficult to analyze is broken through, the problem that the terminal is poor in database log format compatibility can be solved, invalid data transmission between the terminal and the server side is effectively reduced, and the database monitoring effect is improved.

The application discloses a safety production monitoring data management method and device, equipment and a storage medium, and comprises the following steps: acquiring real-time production data in the production process of an enterprise in real time and storing the real-time production data into a preset database; extracting multi-source time sequence data from the preset database to generate an original data set; screening out data that does not conform to a preset rule in the original data set to generate a primary selected data set; according to the strong time correlation characteristics of the dangerous chemical production data in the primary selected data set, eliminating invalid data through a preset validity rule to generate an effective data set; periodically extracting data from the effective data set, and displaying the management result of the time sequence data in a trend chart through a preset visual display model. The application can improve the accuracy of analysis results when analyzing safety production monitoring data.

The invention relates to the technical field of computer vision and edge computing collaborative optimization, in particular to a continuous domain adaptation method based on cloud collaboration, which realizes real-time performance optimization of a lightweight model of end equipment through an uncertain guided sample screening mechanism (UGS) and an undetectable jointly guided dynamic visual cue update strategy (VUPLU). Specifically, invalid data transmission is reduced through UGS, distribution difference between data of a source domain and data of a target domain is reduced through cross-domain alignment, input features are reconstructed through visual prompt prompt, soft supervision signals of a teacher model and VUPLU dynamic parameter updating are combined, environment interference is effectively removed, the model generalization ability is improved, and the method has the advantages of being high in practicability and easy to popularize. The problems of false label noise, low communication efficiency, unstable parameter updating and the like in a traditional method are solved, and the end-cloud cooperative reasoning precision and universality are remarkably improved.

The invention discloses a data forwarding processing method and system for a campus network, and the method comprises the steps: controlling a plurality of independent cameras to generate a multicast video stream carrying a permission identifier according to an access control terminal triggering event; the method comprises the following steps: synchronously creating (S, G) table entries with permission marks and never expired (*, G) table entries on a path multicast router according to a first video stream data packet received by a multicast source side designated router source DR; according to an IGMP join message which is sent by a receiver and carries a permission identifier, through a matching result of an RP comparison (*, G) table entry output interface permission and a multicast data permission identifier, whether a data stream is forwarded along a shared tree (RPT) is decided; and according to a matching result of the permission identifier of the new receiver and the pruned (S, G) flow permission, activating a pruning state on the multicast path and recovering data flow forwarding. According to the embodiment of the invention, occupation of invalid data streams on campus network bandwidth can be reduced, and the overall utilization rate of network resources is improved.

The invention discloses a garbage collection optimization method and device, equipment and a medium. The invention relates to the technical field of solid state disks, which comprises the following steps that: a global invalid data bit chart is established in a host memory, each table item in the global invalid data bit chart corresponds to a physical block, and a bitmap bit in each table item corresponds to a physical page in the physical block; bit values corresponding to the bitmap bits comprise a first bit value and a second bit value; responding to a data updating event through an access acceleration engine so as to dynamically update the bit value of the corresponding physical page in the global invalid data bit graph; and when garbage collection is triggered, screening the physical page of which the bit value is the second bit value in a to-be-collected source physical block according to the global invalid data bit chart and the access acceleration engine to perform validity verification and data migration, and skipping the physical page of which the bit value is the first bit value. According to the invention, the garbage recycling efficiency is improved.

The invention relates to the technical field of communication security, and particularly discloses a communication terminal information acquisition method and system. The method comprises the following steps: acquiring an original data stream of a communication terminal, and generating a task queue through data source marking, dynamic load balancing and protocol packaging; performing desensitization, metadata annotation and lightweight encryption on the task data to form an encrypted data block; secure transmission is realized through transmission channel selection and quality monitoring; decrypting the received data to generate a time sequence database record; generating a rule update package based on invalid data detection and machine learning analysis; and finally, outputting a standardized data set through filtering and verification. According to the invention, efficient acquisition, secure transmission and intelligent processing of mass communication data are realized, and the real-time performance and accuracy of data processing and the load balancing capability of the system are effectively improved.

The invention relates to the technical field of data destruction, in particular to a cloud-based safe destruction system for archival data, which comprises a fingerprint chain construction module, a compression boundary analysis module, a mapping path checking module, a disturbance destruction control module and a boundary fracture identification module. According to the method, through joint processing of each field label, the sequence index and the byte length in the field structure set, the static mapping path is screened and extracted by utilizing double conditions that the pointing frequency is zero and the path span number is consistent in the path identification, so that repeated writing or invalid data residue is avoided; in the destroying process, through content disturbance and logic offset writing of a middle pointer number, visual evaluation of a closed-loop effect of a destroying chain and combined propulsion of multiple structural level operations and a path control mechanism are realized, and structural clearness, path breakage and link irreversibility of a data destroying target are realized; and the irrecoverability and the security integrity of the data termination process are improved.

The invention belongs to the technical field of wireless communication, and particularly relates to an Internet of Things oriented 5G communication module data transmission system, which comprises a communication decision module, a channel state prediction module and a data transmission module which are in communication connection in sequence, and is characterized in that the communication decision module adopts a quantum genetic algorithm, encodes decision variables by quantum bits, and transmits the decision variables to the channel state prediction module; a lightweight scheduling strategy is generated through population iteration, the too high requirement of a complex optimization algorithm on the computing power of an equipment end is avoided, and a low-power-consumption microprocessor is adapted; meanwhile, the collection frequency is dynamically adjusted according to edge node requirements, invalid data collection is reduced, and equipment energy consumption is reduced. The channel state prediction module trains a model by maximizing an average reward value and realizes accurate prediction in combination with an LSTM model of an attention mechanism, and the data transmission module dynamically adjusts a compression encryption strategy according to a channel state, so that the transmission energy consumption is reduced while the safety is guaranteed, and the energy consumption upside down is avoided.

The invention discloses a data caching system and method and electronic equipment, and relates to the technical field of data storage, and the method comprises the steps: screening valid units in original input data, and carrying out centralized storage to prevent invalid data from occupying caching resources; an annular register array is segmented and spliced into a continuous data sequence covering a head-to-tail connection area, and the problem of fracture during cross-boundary reading is solved. Therefore, the problem of overflow or invalid reading caused by low storage efficiency, cross-boundary read data breakage and mismatching of read-write rhythms in the original data cache containing valid and invalid units is solved, and the effects of improving the cache utilization rate, ensuring continuous output of cross-boundary valid data and improving the data interaction stability and efficiency are achieved.

The invention belongs to the technical field of intelligent control, and discloses a robot visual interaction control method and device, electronic equipment and a storage medium, when the electronic equipment is started, an ROS2 communication environment is initialized, and a Qt graphical user interface is loaded; whenever any user interface subpage on the Qt graphical user interface is detected to be switched from the hidden state to the display state, adding one to the count value; when any user interface sub-page is detected to be switched from the display state to the hidden state, subtracting one from the count value; when the count value is changed from 0 to 1, starting ROS2 topic subscription; when the count value is changed from 1 to 0, the ROS2 topic subscription is canceled; by introducing a dynamic binding mechanism of the interface visibility and the ROS2 subscription state, the data subscription is automatically cancelled when the interface component is hidden, so that the continuous receiving and processing of background invalid data streams can be avoided, the CPU resource occupancy rate and communication resources are effectively reduced, the communication load and processing overhead are further reduced, and the operation fluency and response speed are improved.

The invention discloses a non-intrusive image capturing and storing device and a non-intrusive image capturing and storing method. Relates to the technical field of security data storage, and solves the problems of acquisition blind areas, low data credibility and invalid data redundancy caused by a traditional software-level screenshot technology. The video conversion processing module is directly connected with a target host video output link through a standard video interface, the whole device is independent of a host system, does not depend on host permission, does not perform data interaction or protocol communication with a host, and avoids a collection blind area caused by insufficient permission or protection interception; the control processing module encrypts the frame-cut image to protect data security; the control processing module only triggers frame interception when detecting that the image is obviously changed, so that undifferentiated acquisition is avoided, redundant data irrelevant to auditing is reduced from the source, and the storage and operation cost of subsequent auditing analysis is reduced; the protection operation of the safety protection module is executed through a hardware interface and does not depend on host software logic, so that protection failure caused by remote control of a host is avoided.

The invention relates to the technical field of data processing, in particular to a real-time data aggregation optimization method and system based on incremental calculation. The invention discloses a real-time data aggregation optimization method and system based on incremental calculation. The method comprises the following steps of data receiving and preprocessing, incremental calculation model construction, data aggregation and storage, data updating and maintenance, and query and analysis. Data receiving and preprocessing: receiving data streams from a plurality of data sources in real time, performing cleaning operation on the data streams to remove invalid data, performing format conversion to unify a data format, and allocating a unique identifier and a record timestamp to each processed data record; according to the method, only the change part of the data needs to be calculated through the incremental calculation model, so that the calculation amount is greatly reduced, and the efficiency of real-time data aggregation is improved; compared with a traditional method and system, the calculation time can be shortened by more than 50% when large-scale real-time data are processed.

The invention provides a federal retrieval enhancement generation method oriented to multiple data sources. The method comprises the following steps: initializing the reliability of federal data sources; dividing a user query field to obtain the reliability of the federal data source to the user query field; selecting a target data source from the federated data source; performing local retrieval on the target data source to obtain candidate answers; estimating the confidence of the candidate answers; according to the confidence coefficient, filtering the candidate answers, and generating a user query answer; and according to the confidence, updating the reliability of the federal data source, and performing confidence estimation on the candidate answers, so that a confidence estimation result has rich semantic information and can be well identified and utilized by a large language model, thereby being beneficial to solving the conflict problem between exogenous knowledge and model endogenous knowledge, and improving the reliability of the model. And through federal data source quality detection of feedback iteration, reliability evaluation of the data source is continuously converged to the domain knowledge accuracy, efficient and accurate detection of the data source quality is realized, and query of invalid data sources and low-quality data sources is effectively reduced.

According to the QLC medium write amplification optimization method and device, by responding to a data write-in request, metadata of a RocksDB database is written into a metadata pool formed by TLC media, and user data is written into a data pool formed by QLC media. The service load monitoring module is used for collecting operation state data, and the intelligent load analysis module is used for judging whether the current state is in a non-service or low-service load state or not. In a low-load or non-business state, closing a garbage collection (GC) mechanism, and only executing Purge operation to recycle invalid data; and under a normal load, the GC trigger condition is controlled according to the storage space utilization rate and the data block life cycle set by the dynamic threshold configuration module. And obtaining the write-in data volume of the QLC medium through the SMART interface, and calculating the write magnification to evaluate the optimization effect. The method can be applied to electronic equipment such as a server, the write magnification of the QLC medium is effectively reduced, the service life of the QLC medium is prolonged, and the performance and stability of a storage system are improved.

Multiple guard rows are included in a region of memory. Accesses to the region of memory are monitored and a revolver technique using the guard rows is enabled in response to the number of accesses to the region of memory equaling or exceeding a threshold amount within a given interval of time. The guard rows are moved around the region of memory with one or more non-guard rows being situated between the guard rows. A guard row refers to a row of the region of memory that stores invalid data, whereas the one or more non-guard rows store valid data. After being moved, accesses to the region of memory are monitored and after another threshold number of accesses to the region of memory the guard rows are moved again. This process continues with the guard rows being moved, e.g., in a circular manner, through the region of memory.

The invention provides a sparse adaptation circuit and a network-on-chip sparse data processing method, the sparse adaptation circuit is embedded between a network interface unit (NIU) and a router of an NoC system, and the sparse adaptation circuit comprises an input processing module, a compression engine and an output processing module; the sparse detection unit is used for performing real-time zero value detection on the data stream received from the network interface unit NIU to generate sparse identification information; the compression engine is coupled with the sparse detection unit and is used for carrying out dynamic compression coding on the data stream based on the sparse identification information; and the output interface is used for sending the processed data flow to a router in a format conforming to the network-on-chip protocol. In the network-on-chip, a hardware method is adopted to identify a data packet containing a large number of zero values in AI calculation and compress the data packet into a data packet only containing valid data, so that the problems of low transmission efficiency, waste of power consumption and the like caused by the fact that on-chip bandwidth is occupied by invalid data are avoided.

The invention belongs to the technical field of intelligent humanoid robots, and discloses a remote operation data acquisition and data closed-loop system for an intelligent humanoid robot, which builds an instruction, action and acquisition ternary time sequence synchronization mechanism through a time sequence coordination module, realizes dynamic coordination of the three parts by using a time sensitive network technology, effectively reduces time sequence deviation, and improves the system performance. Meanwhile, a space-time alignment algorithm of the data processing module is combined, so that the consistency of the multi-modal data in time and space dimensions is guaranteed; acquired data can accurately fit human operation logic and a robot action state, the optimization efficiency of a data closed loop is improved, and the requirements of high-precision operation scenes such as complex assembly and flexible material processing are successfully met; a quantitative association system of data quality and control effects is established by means of the evaluation module, invalid data such as sensor faults and action fuzziness can be screened in real time, and occupation of redundant storage and computing resources is reduced.

The invention provides a data returning method and device and terminal equipment, and is suitable for the technical field of data processing, and the method comprises the steps: carrying out the classification processing according to the working condition data of to-be-returned equipment, and obtaining the class information of the working condition data of the to-be-returned equipment; identifying the to-be-returned equipment state data to obtain identification information of the to-be-returned equipment state data; generating a plurality of initial to-be-returned data sets according to the return time information, the to-be-returned equipment working condition data category information and the to-be-returned equipment state data identification information; screening the plurality of initial to-be-returned data sets to obtain a target to-be-returned data set; and performing to-be-returned data extraction processing on the target to-be-returned data set to obtain target to-be-returned data so as to return the target to-be-returned data. The method and the device are used for filtering invalid data in the equipment working condition data and the equipment state data, the data return efficiency and accuracy are improved, and therefore the strict requirement of the industrial Internet of Things for equipment full-life-cycle data management is met.

The invention provides a solid state disk wear leveling method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the steps of determining a target recovery group corresponding to target data in a solid state disk SSD based on type characteristics of the target data; based on the cold and hot characteristics of the target data, writing the target data into a target data block corresponding to the cold and hot characteristics in the target recovery group; in response to the fact that the effective data proportion in the recycling unit is lower than a first threshold value, executing a first garbage recycling strategy; the first garbage recycling strategy recycles invalid data in the recycling group corresponding to the recycling unit; in response to the fact that the effective data proportion in the recycling unit is not lower than the first threshold value, executing a second garbage recycling strategy; the second garbage recycling strategy is used for recycling data in different data blocks in the recycling unit based on the wear degrees of the different data blocks in the recycling unit. Therefore, the response speed and recovery efficiency of the SSD can be improved, and the service life of the SSD is prolonged.

The invention provides an electric power communication SDH network operation state real-time monitoring system and method, and the system comprises a multi-protocol adaptive collection module which carries out the collection of network element information, performance information, alarm information and equipment information of an electric power communication SDH network according to a preset strategy, performing standardization processing on the acquired multi-source heterogeneous data through a protocol analysis engine module to obtain structured data; the intelligent data screening and deconstruction module is used for analyzing, associating and identifying the structured data to obtain a key business entity; the lightweight packaging module is used for carrying out serialization and compression optimization on the key business entities to obtain lightweight packaging data; and the rendering module is used for carrying out real-time rendering on the basis of the lightweight packaging data to obtain a real-time visual operation state of the electric power communication SDH network. According to the invention, the acquisition efficiency is optimized, real-time monitoring is supported, the bandwidth cost is reduced, invalid data transmission is reduced by 80%, and the fault positioning time is compressed from an hour level to a minute level.

The invention discloses a question-answer pair generation and fine tuning data set construction method oriented to a vertical field. The method comprises the following steps: downloading a patent data set of a target vertical field from patent literatures disclosed by an official patent database; patent texts are selected, technical viewpoints are extracted one by one to generate'answers', corresponding'questions' are matched with the'answers', and then question and answer pairs are generated; labeling each question and answer pair; checking each question and answer pair, and marking the question and answer pairs which do not pass the checking as invalid data; inputting a question-answer pair data set through the audited question-answer pairs; performing data cleaning on the question and answer pairs; and constructing a high-quality fine-tuning data set. According to the method, the patent text is taken as a data entry, the reliability and the cost efficiency are both considered by endowing the unique traceability code and a man-machine cooperation mechanism of'manual extraction + AI generation + manual auditing ', the data traceability is ensured, and the model illusion risk is remarkably reduced, so that the technical landing of intelligent research and development in the vertical field is realized.

The invention discloses a technical trade measure data automatic sharing method and system based on artificial intelligence, and belongs to the technical field of data sharing, and the method comprises the steps: a control center receives a technical trade measure new version data entry signal, carries out the judgment of a target data sharing reliability decision pool, and carries out the data sharing; if the judgment result of the target data sharing reliability decision pool is a secondary judgment pool, re-judgment of the target data sharing reliability decision pool is carried out, and if the re-judgment result of the target data sharing reliability decision pool is an experimental sharing pool, the formal sharing qualification of the target data is confirmed, and the automatic sharing process of the target data is executed. The method can guarantee the safety and stability of data sharing, accurately judges the actual application value of the data through experimental sharing and sharing value scoring analysis, ensures that the data entering a wide sharing link can provide an accurate basis, continuously monitors the data of the observation pool, reasonably cleans invalid data, improves the data management efficiency, and is suitable for popularization and application. And the accuracy, reliability and practicability of data sharing are improved.

The invention discloses a harmonic traceability method and device based on power grid topology, a terminal and a medium, and the method comprises the steps: collecting multi-source data, tracking a harmonic back propagation path, and screening key nodes; collecting equipment features, waveform features and time sequence features based on the key nodes, constructing a harmonic source feature library, and performing per unit value conversion on harmonic power features of the key nodes; calculating the matching degree between the key node and the target type equipment in the feature library by using the harmonic source feature library, and determining a harmonic source node and a potential harmonic source node according to the matching degree; calculating the contribution degree based on the per-unit value, and determining a target harmonic propagation path and a target harmonic source on the path; according to the method, a harmonic propagation path is accurately tracked through double criteria, key nodes are screened, and invalid data processing is reduced; meanwhile, the influence weight of each node is determined through hierarchical calculation of contribution degrees, the traceability precision is effectively improved, and the harmonic risk of the power grid is reduced.