417results about How to "Achieve sharing" patented technology

The invention discloses a knowledge and data fused chronic disease collaborative management method and system, and relates to the technical field of medical management. Comprising the following steps: generating a feature data set, processing the feature data set by using a feature gain modeling method, and generating an enhanced feature data set; dynamically generating a chronic disease comprehensive knowledge graph, performing node supplementation and weight optimization on the knowledge graph, and generating a specific knowledge sub-graph of the patient; carrying out multi-time sequence prediction by utilizing the specific knowledge sub-graph, and carrying out short-term and long-term trend prediction; a patient health track model is constructed through the state transition probability in combination with the prediction result; according to the dynamic risk labeling result of the health track model, the health state of the patient is comprehensively evaluated in combination with the specific knowledge sub-graph, and personalized management suggestions are generated according to the evaluation result. According to the collaborative management platform, cooperation between different medical institutions and medical staff can be promoted, information sharing and resource integration are realized, and the overall level of medical services is improved.

The invention discloses a display panel and a display device. The display panel comprises a substrate, a light-emitting device layer and a light shielding layer. The light-emitting device layer comprises a plurality of first pixels and a plurality of second pixels, the plurality of first pixels are distributed in a plurality of shared pixel strip-shaped areas extending in the first direction, and the plurality of second pixels are distributed in a plurality of peep-proof pixel strip-shaped areas extending in the first direction; the plurality of shared pixel strip-shaped areas and the plurality of peep-proof pixel strip-shaped areas are sequentially arranged at intervals in the second direction, the light shielding layer comprises first light shielding parts, and the first light shielding parts are stacked at the interval positions of the second pixels in the first direction. The color cast phenomenon of the whole display panel is reduced.

The invention provides a memory access instruction processing method and a processor, and relates to the technical field of data processing, and the method comprises the following steps: splitting a target vector memory access instruction into a plurality of target vector memory access micro-operations based on a memory access width, combining the target scalar memory access instruction with at least one unexecuted scalar memory access instruction into a target scalar memory access micro-operation; executing each target vector memory access micro-operation, and / or executing a target scalar memory access micro-operation; the memory access width is determined based on a number of data cache banks in a data cache in the processor and a bit width of the data cache banks. According to the memory access instruction processing method and the processor provided by the invention, resources can be more reasonably allocated for vector memory access and scalar memory access during data memory access through splitting of the vector memory access instruction and merging of the scalar memory access instruction, and maximum resource sharing of the vector memory access and the scalar memory access is realized.

The invention discloses a road right sharing configuration method and a traffic control system, and relates to the technical field of special vehicle road right sharing, and the method comprises the steps: obtaining the real-time position and speed information of a common vehicle and a special vehicle at an intersection; determining the traffic flow condition of the current intersection by using a traffic flow prediction model; according to the real-time position and speed of the special vehicle and the traffic flow condition of the current intersection, the period and phase duration of the signal lamp are dynamically adjusted through a bidirectional dynamic green wave algorithm, a signal lamp control strategy is obtained, and it is ensured that the special vehicle can pass through the intersection without stopping; configuring intersection signal lamps according to the signal lamp control strategy; according to the invention, through combination of prediction of the traffic flow condition of the intersection and the real-time position of the special vehicle, the period duration and the phase duration of the signal lamp at the intersection are automatically adjusted, the influence on common vehicles at other phases is reduced as much as possible while the special vehicle is ensured to pass through the intersection without stopping, thereby realizing dynamic distribution and sharing of the road right of the special vehicle, and improving the traffic safety. And the utilization rate of special lane resources is furthest improved.

The invention discloses an automatic stereoscopic warehouse goods sorting system and method, and relates to the technical field of intelligent sorting, the system comprises an input layer, a storage layer, an execution layer, a control layer and a management layer, the input layer comprises a bar code RFID scanning system, a machine vision identification system, a sensor and an input terminal, the storage layer comprises a three-dimensional goods shelf, a tray goods shelf system and a storage management system, the execution layer comprises a stacking machine, a conveying belt, a sorting robot and a carrying vehicle, and the control layer comprises a programmable logic controller, a monitoring and data acquisition system and a communication network. According to the automatic stereoscopic warehouse goods sorting system and method, efficient cooperative work among equipment can be achieved, and the goods processing speed and efficiency can be improved.

The invention discloses a multi-service scheduling optimization method for infrastructure safety management. The multi-service scheduling optimization method comprises the following steps: intelligently acquiring structured and unstructured data from a plurality of service systems; cleaning, filtering and formatting the collected data, analyzing by using a data fusion technology, and extracting comprehensive information useful for safety and quality management; based on multi-objective optimization, a self-adaptive scheduling algorithm is designed, and resources, tasks and manpower are automatically allocated; the method comprises the following steps: constructing a digital twin model of the infrastructure, performing omnibearing real-time monitoring on the infrastructure through a synchronous virtual and physical system, and simulating risk points and potential problems; an intelligent monitoring feedback loop is used for detecting abnormal behaviors and potential risks; on the basis of real-time monitoring and feedback, the scheduling process is continuously optimized, and the adaptability of a scheduling algorithm is improved by applying machine learning and a prediction model. The method has the advantages that data of multiple service systems can be integrated, and data sharing and fusion analysis are realized.

The invention discloses an efficient regulation and control system and method for plateau low-oxygen environment damage, and relates to the technical field of human body low-oxygen damage analysis, detection and regulation and control, and the system comprises a data monitoring module, a signal screening module, a decision oxygen distribution module and a monitoring interaction module; the data monitoring module is used for acquiring a physiological state related to the plateau hypoxia adaptive capacity in real time; acquiring physiological data with high modeling value through an optimization algorithm by using a signal screening module based on test data, and constructing a discrete state space model of a physiological state; an oxygen distribution concentration decision is determined through a predictive control algorithm by utilizing a decision oxygen distribution module, so that oxygen supply regulation and control are realized; and the monitoring interaction module is used for storing, recording and displaying data, issuing an alarm and predicting dangerous conditions. Therefore, by means of the method, effective oxygen supply, blood oxygen dynamic monitoring and real-time alarming can be achieved, and health and safety of individuals in oxygen-deficient environments such as high-altitude areas and the like are guaranteed.

The invention provides a collaborative parking method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent parking. The method comprises the following steps: acquiring a predicted parking path of each vehicle in a preset scene through a preset rule; whether path conflicts and space occupation conflicts exist among the vehicles or not is detected according to the predicted parking paths, and when the path conflicts and / or the space occupation conflicts exist among the vehicles, the predicted parking paths of the vehicles with the path conflicts and / or the space occupation conflicts are optimized. According to the method, the predicted parking path of each vehicle in the preset scene is obtained through the preset rule, so that the predicted parking path of each vehicle can be determined, information sharing among vehicles of different brands and models can be realized, and then path conflicts and space occupation conflicts among the vehicles are detected according to the predicted parking paths, so that the parking efficiency of the vehicles is improved. At the moment, the predicted parking path is optimized, orderly and efficient parking among multiple vehicles in the parking lot is achieved, and the parking efficiency and the space utilization rate are improved.

The invention provides a GPU-based data processing method and device, electronic equipment and a medium, and relates to the technical field of chips, in particular to the technical field of GPU memories. According to the implementation scheme, a first matrix to be processed and a second matrix to be processed are obtained from a global memory of a GPU; storing the first matrix into a first sub-memory of a shared memory corresponding to a target thread block in a GPC (Graphics Processing Cluster); storing the second matrix into a second sub-memory of the shared memory corresponding to the target thread block; performing multiplication operation on the first matrix and the second matrix in the shared memory; the third matrix obtained through multiplication operation is stored in a shared GPC memory of a plurality of thread blocks in a GPC of the GPU, the plurality of thread blocks comprise target thread blocks, and the shared GPC memory is addressed uniformly for the plurality of thread blocks; and performing reduction operation on the third matrix in the shared GPC memory.

The invention provides a federated learning-based chip manufacturing process parameter optimization method and system, and relates to the technical field of chips, and the method comprises the steps: collecting multi-factory process parameters and yield data, screening key parameters through wavelet transform and dual evaluation, and constructing a deep Q network model; ethnic group division is carried out based on process trajectory similarity, differential privacy and homomorphic encryption are adopted to protect data security, and ethnic group optimization is realized through an attention mechanism and knowledge distillation; and setting a third-level time window monitoring yield, and dynamically adjusting an optimization strategy. According to the method, the chip manufacturing yield can be effectively improved, data privacy is protected, and intelligent optimization of process parameters is realized.

The invention discloses a hydroelectric generating set health state assessment method based on multi-dimensional data, and the method comprises the steps: S1, obtaining the operation data of a hydroelectric generating set, and carrying out the data preprocessing; s2, sensing data extraction is carried out on the preprocessed hydroelectric generating set operation data; s3, performing anomaly detection on the operation sensing data of the hydroelectric generating set; s4, carrying out sensing abnormal frequency statistics on the operation sensing abnormal data of the hydroelectric generating set; s5, thermal efficiency and operation water conservancy efficiency calculation is carried out on the operation sensing data of the hydroelectric generating set, and operation performance index analysis is carried out; s6, performing health state calculation according to the analyzed hydroelectric generating set operation performance index data; and S7, constructing a health assessment model to assess the health state of the hydroelectric generating set, uploading assessment data to the cloud platform, and executing a preset health early warning task. According to the method, the health state is calculated by combining the operation performance index and the sensing abnormal frequency data, so that more comprehensive health assessment is realized.

The invention discloses an Internet of Things authentication method and system, and relates to the technical field of Internet of Things. The system comprises a quantum machine learning behavior analysis module, a multi-factor authentication module, a block chain and intelligent contract module, an edge computing authentication processing module, a self-adaptive authentication strategy and risk assessment module, a privacy protection and data desensitization module and a cross-platform interoperation module. According to the invention, the security, efficiency and flexibility of the Internet of Things authentication system are significantly improved, so that the system can efficiently identify abnormal behaviors of equipment, effectively prevent potential security threats, significantly reduce authentication delay, and improve the response speed and user experience of the system. Therefore, the problems existing in the aspects of safety, authentication efficiency and expandability of a traditional authentication method are solved, and a safer, more efficient and more extensible authentication mechanism is provided for the Internet of Things equipment.

The invention discloses an intelligent beam field construction management system based on BIM and GIS, and relates to the technical field of beam field construction management. Main parameters of a beam field construction environment can be fully covered by deploying a temperature and humidity sensor, an air quality sensor, a noise sensor, a wind speed and direction sensor and a rainfall sensor; spatial data association is performed on the BIM model by using a spatial analysis tool in a GIS platform, geographic information and construction in the BIM model are subjected to geographic space matching, and the accuracy of an association result is ensured through verification, so that data integration and sharing are facilitated, the use efficiency of the data is improved, and the method is suitable for popularization and application. A construction supervisor can monitor the construction progress according to the tracking data recorded in real time, a construction plan is adjusted in time, and smooth construction is ensured.

The invention relates to the technical field of medical apparatuses and instruments, in particular to a medical apparatus and instrument state management system based on the Internet of Things technology, which can remotely monitor and manage medical equipment and medical consumables in the whole period. Through the combination of the equipment sensor, the Internet of Things platform and the mobile terminal application, medical equipment management personnel can know information such as the operation state, the energy consumption condition, the maintenance period and the operation time of the medical equipment in real time, meanwhile, preventive maintenance can be carried out, related faults can be handled in time, and the quality and efficiency of medical services are improved. By means of intelligent remote monitoring and management, information islands are eliminated, efficiency is improved, data unification and sharing among all systems and departments are achieved, and the purpose of conducting real-time remote monitoring and management on medical instruments in the whole period is achieved.

The invention provides a desulfurization absorption tower system monitoring method, device, equipment and medium, and belongs to the technical field of thermal power desulfurization. The method comprises the following steps: acquiring numerical values of a plurality of monitoring devices of the desulfurizing absorption tower system; based on the emergency level of the data type of the numerical value of each monitoring device and the operation state of each monitoring device, evaluating the numerical value of each monitoring device to obtain a score of the numerical value of each monitoring device; calculating the average value of the scores of the numerical values of the monitoring devices to obtain the score of each sub-device of the desulfurizing absorption tower system, and calculating the average value of the scores of each sub-device of the desulfurizing absorption tower system to obtain the score of the desulfurizing absorption tower system; and the score of the numerical value of each monitoring device, the score of each sub-device of the desulfurization absorption tower system and the score of the desulfurization absorption tower system are transmitted to a DCS system for layered and graded display. According to the invention, real-time monitoring and early warning, efficient fault diagnosis, data integration and sharing and visual display are realized, and the equipment operation management efficiency and operation convenience are improved.

The invention discloses an online knowledge base platform for ensuring knowledge content quality and contributor rights and interests and a business model of the online knowledge base platform, and relates to the field of online knowledge bases. The platform integrates block chains, data encryption and artificial intelligence technologies, and aims to improve the quality of knowledge content and protect the rights and interests of contributors. The platform mainly comprises a block chain system, a data encryption system, an artificial intelligence system, a member management system, an auditor evaluation system, a knowledge content collection system, a knowledge content auditing system, an incentive management system, a template management system, a fund management system, a suggestion supervision system, a point transaction system, an advertisement management system and the like. Through a decentralized knowledge management mechanism, a contributor auditing and evaluating mechanism, a knowledge content providing and auditing mechanism and a contributor right protection mechanism, high quality of knowledge base content and fair reward of contributors are ensured, and sharing and communication of knowledge are promoted.

The invention relates to the field of information technology application, and discloses a product manufacturing whole process BOM data structured construction method and related equipment, and the method comprises the steps: obtaining defect BOM data of an order output result of an ERP system; according to the defect BOM data, data features of ABOM, MBOM and EBOM are reversely analyzed and traced, and an analysis result is obtained; according to the analysis result, the ABOM, the MBOM and the EBOM are reconstructed to obtain a BOM data structure; the BOM data structure transmits the obtained data features to an ERP system, and BOM data structured construction work in the whole product manufacturing process is completed. According to the method, result defect BOM data is output through an enterprise resource planning system, BOM data characteristics in various BOM data driving business operation are reversely analyzed, difference removal, same storage and combination are carried out, a product design source EBOM model is reconstructed, and finally a'three-in-one 'simplified new BOM reconstruction model for driving enterprise business operation based on the source EBOM as a product digital main line is realized.

The invention discloses a surveying and mapping geographic information data acquisition system based on cloud computing, and relates to the technical field of natural resource management, a data acquisition module is used for acquiring observation point height G, observation point latitude W and adjacent point data, a data processing module is used for operating a data processing algorithm and outputting evaluation data of surveying and mapping geographic information, and the surveying and mapping geographic information is acquired based on the evaluation data. The data processing module is used for processing the real elevation of the ground and deeply analyzing the processed data, the data visual module is used for displaying a data acquisition result and an evaluation report, the system is optimized and adjusted, and the data processing module comprises a unit for reflecting the corrected real elevation of the ground, a unit for comprehensively evaluating the horizontal position precision and a unit for comprehensively evaluating the geographic information data quality. The surveying and mapping geographic information data acquisition system has the beneficial effects of improving the data precision, optimizing the data processing flow, enhancing the system adaptability and improving the decision support capability, and the effects jointly promote the intelligent and modern development of the surveying and mapping geographic information data acquisition system.

The invention discloses a new energy automobile charging detection system, and relates to the field of new energy automobiles, and the system comprises a battery state monitoring module which is used for collecting and analyzing the health condition, residual capacity and chargeable quantity parameters of a battery in real time. The system has the beneficial effects that the charging strategy is modulated in real time through the battery state monitoring module and the intelligent charging control module, the charging efficiency is high, and the damage to the service life of the battery is reduced; a safety protection module is arranged, the states of the battery pack and the charging system are monitored in real time, response to abnormal conditions such as short circuit, over-temperature and over-current is fast, and potential safety hazards are reduced; the user interaction module is arranged, the user interactivity is high, and a user can know the charging state and the battery health condition in real time and flexibly adjust charging setting according to requirements; and a cloud data management module is arranged to deeply analyze the charging data, so that decision support is provided, and remote data access and sharing are realized.

The invention discloses a feature extraction method based on a multi-view interactive neural network, and the method comprises the steps: constructing a multi-scale convolutional neural network based on multiple modules, achieving the extraction of multi-scale feature information through a parallel multi-core, and designing the cross-layer connection of a plurality of network modules to achieve the feature interaction among the multiple modules. Information sharing is completed; constructing an interactive Transform network based on local and global features, applying a lightweight residual block in the network to realize local association of the global features, and applying a lightweight convolutional layer to replace a traditional convolutional block to reduce time consumption cost; features extracted by a multi-module multi-scale convolutional neural network and a feature interactive Transform network are fused, and the method is applied to multi-spectral target recognition. According to the method, global and local information is interactively interpreted in the network optimization process, so that feature information is richer, and finally, target recognition performance with relatively high precision is obtained.

The invention relates to the technical field of computers. The invention specifically discloses a vehicle insurance claim settlement amount prediction method and device, a medium and equipment. The method comprises the following steps: based on a plurality of local sample claim settlement data, using a predetermined initial prediction model to carry out federated model training in this round, and obtaining a first current model parameter; receiving a second current model parameter broadcasted by each non-target client; performing parameter aggregation processing based on the first current model parameter and each second current model parameter to obtain a current aggregation model parameter; at least based on the current aggregation model parameters, determining whether a preset training stop condition is met or not, if the training stop condition is not met, carrying out next-round federated model training until the preset training stop condition is met, and obtaining a target prediction model based on the current aggregation model parameters corresponding to the training round number; and predicting the claim settlement data of the target vehicle based on the target prediction model to obtain a target claim settlement amount. The accuracy of the prediction result can be improved.

The invention relates to the technical field of robots, and discloses a robot space positioning and map reconstruction system based on binocular vision and inertial navigation, and the system comprises a binocular camera module which is used for obtaining a stereo image of a surrounding environment; and the inertial measurement unit is used for providing acceleration and angular velocity information. According to the robot space positioning and map reconstruction system based on binocular vision fused inertial navigation, through fusion of the binocular camera and the IMU, the positioning precision and robustness of the system are improved, the system adopts a deep learning algorithm and an optimized feature matching algorithm, the accuracy and reliability of feature extraction and matching are improved, and the system is suitable for popularization and application. According to the system, the visual feature points and IMU data are combined, high-precision positioning is achieved, meanwhile, system parameters are adjusted through the reinforcement learning technology, the intelligence and adaptability of the system are improved, remote transmission and sharing of data are achieved through the wireless communication module, and the manageability and maintainability of the system are improved.

The invention discloses a financial risk control system based on big data and a block chain. An operation method of the system comprises the following steps of 1, performing liquidity monitoring on funds of a borrower by connecting a data source; 2, realizing risk assessment by monitoring related industry information of the borrowers; thirdly, borrower industry risk assessment is achieved through a comprehensive risk scoring system; 4, the repayment ability of the borrower is comprehensively evaluated and uploaded to a block chain for storage, and the industry risk evaluation module is used for collecting and analyzing industry data, constructing an industry network atlas, evaluating a risk transfer model and deeply knowing the incidence relation between different industries; and the comprehensive risk score and block chain storage module is used for comprehensively considering individual and industry risks, generating a comprehensive risk score, and realizing safe and non-tampering data storage through a block chain, and the financial risk monitoring system has the characteristic of more comprehensive and accurate financial risk monitoring.

The invention provides a multi-source software-defined science and education resource recommendation method and system based on a knowledge graph, and the method comprises the steps: constructing an artificial intelligence knowledge graph based on the relation between artificial intelligence knowledge entities; obtaining science and education resource data of a science and education institution, extracting knowledge entities in the science and education resource data, and connecting the knowledge entities to the artificial intelligence knowledge graph to obtain a science and education resource knowledge graph; extracting local resource features / user features based on a graph neural network to obtain local resource features and user features of each client; constructing a local knowledge graph based on the science and education resource knowledge graph, and performing model training by taking the local resource features of each client as initial features until the model converges; and inputting the users and the resources into the graph neural network for prediction, and recommending the resources with high scores to each user. According to the scheme, the relationship between knowledge entities in the field of artificial intelligence is effectively extracted, a structured knowledge graph is formed, and the recommendation precision is improved.

The invention relates to an ocean temperature difference energy driven buoy autonomous power generation hydraulic system and a working method thereof, and belongs to the technical field of hydraulic systems. The power generation hydraulic system comprises a rubber leather bag, an energy accumulator, a pilot control valve bank, a turbine shaft assembly, a power generator, an oil tank, an upper pressure-resistant shell, a lower pressure-resistant shell and an integrated end cover, the upper pressure-resistant shell and the lower pressure-resistant shell are connected in a sealed mode through the integrated end cover, and the pilot control valve bank, the turbine shaft assembly and the oil tank are arranged on the upper side of the integrated end cover; the turbine shaft assembly is connected with a generator, a rubber bag is arranged on the lower side of the integrated end cover, an energy accumulator is arranged in the rubber bag, the space between the energy accumulator and the rubber bag is filled with hydraulic oil, and the space between the rubber bag and the lower pressure-resistant shell is filled with a phase change working medium. The pilot control valve group is designed, the opening pressure is set by an external mechanical spring, an oil way is automatically conducted after the opening pressure is reached, the energy loss between an oil inlet and an oil outlet is extremely small, and the advantages of no electric energy consumption and low failure rate are achieved.

The invention discloses a distributed online adaptive task planning system for an unmanned aerial vehicle group, and relates to the technical field of unmanned aerial vehicle task planning. The system comprises a data acquisition and processing module, a task planning and distribution module, a path planning module, a load configuration module, a real-time monitoring and adjusting module, a cooperative control module, a real-time communication module and an optimization module, and generating a task planning scheme and performing task allocation by applying an online optimization algorithm and a self-adaptive technology. According to the invention, the task planning and distribution module integrates advanced algorithms and technologies to perform task planning and task distribution, so that each unmanned aerial vehicle can bear appropriate task load, an unmanned aerial vehicle / vehicle cluster can autonomously and efficiently complete diversified tasks in a complex environment, intelligent scheduling, path optimization and cooperative operation of the unmanned aerial vehicles / vehicles are realized, and the unmanned aerial vehicle / vehicle cluster is enabled to be more intelligent. And the self-organization capability, the dynamic adaptability and the collaborative operation efficiency of the unmanned aerial vehicle group are improved.

The invention discloses a low-altitude unmanned aerial vehicle group double-frequency link emergency networking method and system, and the method comprises the steps: constructing a low-frequency control link of low-altitude unmanned aerial vehicles, and enabling the low-frequency control link to adopt a full-distributed control link networking mode; secondly, network control data are shared through the low-frequency control link, global information of the control link is obtained, and the global information comprises unmanned aerial vehicle positioning information, a physical environment and communication resources; then, according to the global information, constructing a high-frequency data link, and performing data transmission through the high-frequency data link; and finally, based on the low-frequency control link and the high-frequency data link, constructing a double-frequency link emergency network by adopting a high-low frequency combination mode. According to the method, a more stable and more reliable control network can be formed, more timely control information support is provided for construction of a high-frequency data link, and the problems of data retransmission and the like under the high-dynamic topology of the unmanned aerial vehicle are better solved.

The invention discloses a file data circulation security system based on a block chain technology, and the system deploys block chain nodes based on the block chain technology, and constructs a block chain network system. An upper-layer application is established on the basis of digital identity authentication, a security policy smart contract, process management and control and uplink log auditing, and the upper-layer application comprises a block chain background management module, a file storage cloud service module and a component core capability module; in a business application level, a data owning party and a data using party can realize safe circulation of data through encryption authorization and authorization decryption services provided by the platform. According to the method, data privacy can be protected, data traceability and non-tampering performance are achieved, and meanwhile efficient data circulation and cross-platform interoperability can be achieved.

The invention discloses a data security flow method based on access control encryption in a cloud edge environment, and belongs to the field of data security flow. The method specifically comprises the following steps: firstly, building a cloud edge environment simulation scene; and the receiving domain authorization mechanism outputs the receiving domain public key and the receiving domain private key. Then, the n sending domain authorization mechanisms jointly execute an algorithm to obtain a sending domain public key and respective authorization keys; each sending domain authorization mechanism independently operates a partial encryption key generation algorithm to obtain a respective partial encryption key, and a sender operates an encryption key aggregation algorithm to obtain an aggregation encryption key. Then, the receiving domain authorization mechanism obtains the decryption key and returns the decryption key to the receiver; a sender uses an aggregation encryption key to encrypt plaintext data m and uploads the encrypted plaintext data m to an edge node, and a purified ciphertext is generated through a purification algorithm and uploaded to a cloud server. And finally, after the user retrieves the purified ciphertext, decrypting the purified ciphertext by using a decryption key to obtain a message m. According to the method, the security circulation requirement of the privacy data in the cloud edge environment is met.

The invention belongs to the technical field of power transmission line erection equipment, and particularly relates to a stretching system. The stretching system comprises a plurality of traction devices and a plurality of tension devices, the traction devices and the tension devices are each provided with a driving power source, due to the fact that the capacities of the driving power sources are different and the power consumption of the electric devices is different, the driving power sources of the electric devices can have different electric quantity conditions, and even part of the driving power sources can have a power lack state. Therefore, the operation efficiency of the electric equipment with the driving power supply in the power-deficient state is reduced. In the application, mutual charging is realized through the power supply modules of the electric devices, so that energy sharing of the electric devices in the stretching system is realized, the electric devices can maintain normal operation efficiency for a long time, reasonable utilization of energy is further realized, the operation efficiency of the stretching system is improved, and the purposes of saving energy and reducing consumption are achieved.