222results about How to "Complete efficiently" patented technology

The invention discloses a photovoltaic cleaning robot based on automatic path planning and an operation method thereof, relates to the technical field of robots, and solves the problem of cleaning blind spots in an existing cleaning robot and the endless loop risk of a path planning algorithm. According to the invention, the surface information of the photovoltaic panel is accurately captured through the multispectral acquisition module, a high-resolution and high-definition comprehensive image is generated through the data fusion processing module, then dirt is accurately identified on different scales by using a multi-scale pyramid structure and an adaptive feature fusion mechanism, and an attention mechanism and environmental perception data are combined, so that the real-time performance of the system is improved. The recognition threshold is dynamically adjusted, and misrecognition and missing detection are reduced; and finally, enabling the robot to autonomously learn in a complex environment and optimize an obstacle avoidance strategy through a dynamic obstacle avoidance algorithm based on deep reinforcement learning. The intelligent level and the cleaning effect of an existing photovoltaic cleaning robot are greatly improved.

The invention discloses a VR-based unmanned aerial vehicle inspection method and system, a storage medium and a program product, and the method comprises the steps: calculating a low-polygon terrain model, and carrying out the subdivision smoothing processing, and obtaining a three-dimensional terrain image; matching and registering the panoramic image sequence and the three-dimensional topographic image to obtain a point cloud map; generating a virtual mining area environment map; calculating image quality parameters; when the image quality parameter is lower than a preset threshold value, generating a semi-real and semi-virtual fusion display picture; transmitting the semi-real and semi-virtual fusion display picture to a VR helmet for display, and synchronizing the attitude information of the unmanned aerial vehicle to the VR helmet; when it is determined that a fatigue feature appears according to the brain wave data, the unmanned aerial vehicle is controlled to be switched to a preset autonomous flight mode; constructing a virtual anti-collision boundary; and obtaining an optimized flight path according to the virtual anti-collision boundary, and controlling the unmanned aerial vehicle to inspect according to the optimized flight path. The continuity and reliability of the inspection task are improved, and the safety risk of the inspection task is reduced.

The invention relates to the technical field of space positioning and path planning, in particular to a three-dimensional space positioning and path planning method for an unmanned aerial vehicle tower. The method comprises the following steps of performing accurate longitude and latitude height data acquisition based on a laser range finder to generate accurate longitude and latitude height data; obtaining tower equipment parameters; performing inspection point three-dimensional coordinate calculation according to the tower equipment parameters and the tower three-dimensional coordinate system to generate inspection point three-dimensional coordinate data; cruise point comprehensive constraint range data are obtained according to the unmanned aerial vehicle flight association data and the polling area terrain data, and cruise point comprehensive constraint range data are generated; performing cruise node three-dimensional coordinate design on the three-dimensional coordinate data of the inspection point according to the cruise point comprehensive constraint range data to generate cruise point three-dimensional coordinate data; and performing optimized cruise path planning processing according to the cruise point three-dimensional coordinate data to generate optimized cruise path data. According to the invention, more accurate unmanned aerial vehicle tower space positioning and path planning are realized.

The invention relates to the technical field of unmanned aerial vehicle flight planning, and discloses an unmanned aerial vehicle cluster optimal path planning method and system, and the method comprises the steps: firstly constructing an unmanned aerial vehicle flight state prediction model and a path planning decision model, predicting the future state of an unmanned aerial vehicle, and making a decision of an optimal path; the two models are trained innovatively by adopting a dual machine learning algorithm, the accuracy of model prediction and decision making is improved, the path planning result is effectively corrected and optimized by constructing a residual error fitting model, and the planning robustness is enhanced. According to the method, the dynamic flight state, the environment uncertainty and the task target diversity of the unmanned aerial vehicle are comprehensively considered, and the unmanned aerial vehicle cluster optimal path planning instruction conforming to the actual flight condition can be generated in real time. The method improves the task execution efficiency and safety of the unmanned aerial vehicle cluster, is suitable for multiple fields of military reconnaissance, disaster rescue, logistics distribution and the like, and has a wide application prospect and an important practical value.

The invention discloses a gas leakage point leakage detection system and method based on an e-dog, and belongs to the technical field of gas leakage detection. Through the autonomous navigation capability of the mobile platform module, the system can automatically avoid obstacles in a complex environment and inspect along a predetermined path, optimizes the inspection path in real time after finding a gas leakage point, improves the inspection efficiency, guarantees the high-density inspection of a key area, and the rapid movement and precise positioning capability of an e-dog, and improves the inspection efficiency. The gas leakage detection is quicker and more efficient, the risk that personnel enter a dangerous environment is reduced, the system has the functions of autonomous navigation, obstacle avoidance, remote control and the like, the intelligent level of detection is improved, the system is suitable for detection requirements of various complex environments and different types of gases, and through cooperative work of the gas detection module and the data acquisition and processing module, the detection efficiency is improved. The gas concentration data can be accurately acquired, the position of the leakage point can be judged, and the leakage point can be quickly and accurately positioned based on the combination of the GPS and the gas concentration data.

The invention provides an interactive BIM modeling method and system based on a large model. The method comprises the steps that a target tool set description document corresponding to a target project class is determined; receiving a task instruction input by a user, and performing task splitting by the project class large model according to a task intention of a currently executed task to obtain at least one subtask; the calling project class large model determines a tool calling instruction according to the task intention of the currently executed subtask and the target tool set description document; the tool calling instruction is sent to a tool calling module, and the tool calling module carries out compliance verification on the tool calling instruction; the tool calling instruction is processed, an execution instruction of the BIM application is generated, an execution result is received and returned to the project class large model, and the project class large model presents the execution result to a user. According to the method disclosed by the invention, the BIM modeling task is completed through simple natural language input, the operation complexity can be reduced, and a designer is helped to complete the modeling task more efficiently.

The invention discloses a radar and video information fusion coding method for vehicle over-limit early warning. The method comprises the following steps: acquiring three-dimensional point cloud data through a radar module; measuring three-dimensional sizes of length, width and height of the target vehicle in real time; a video information acquisition module is used for acquiring vehicle image data, and the video data identifies license plate numbers and vehicle appearance features through an improved YOLO deep learning algorithm to assist in judging whether a vehicle exceeds a limit or not; the vehicle three-dimensional size measured by the radar is compared with the standard size in the database through the data processing module, whether the vehicle exceeds the limit or not is judged through a threshold value method, radar data and video data are effectively fused through an algorithm, and the fused data are compressed. The radar and video information fusion technology is utilized, an efficient coding scheme is combined, the high-precision and high-efficiency vehicle over-limit early warning function can be achieved, and the method is suitable for complex road environments and variable traffic scenes.

The invention discloses a power grid construction subpackage management and control method based on big data, and the method comprises the following steps: collecting the data of a power grid construction site in real time, carrying out the preprocessing, and carrying out the storage through a distributed storage system; generating a comprehensive evaluation report by using the residual neural network and the graph convolutional network; adopting a particle swarm optimization algorithm to carry out subpackage provider selection and task allocation; predicting the construction progress through a long short-term memory network; performing image analysis on the video stream of the construction site by using a residual neural network and a single-time multi-frame detection algorithm; a Bayesian network and a multi-layer perceptron are used to predict construction risks, an isolated forest algorithm is used to carry out abnormal value detection on data, and a risk early warning report is generated and notified to related personnel. According to the invention, big data, deep learning and reinforcement learning technologies are fully combined, the power grid construction subpackage management and control method based on big data is described in detail, and the method has the advantages of high construction efficiency, accurate risk prediction and resource optimization.

The invention provides an infrared weak and small target detection method and system, electronic equipment and a storage medium, and belongs to the technical field of target detection, and the method comprises the steps: improving a YOLOv8 model for the features of an infrared weak and small target image; and performing target detection on the infrared weak and small target image by using the improved YOLOv8 model. According to the invention, a stronger infrared weak and small target detection capability is provided for the YOLOv8 model, and the problem of target detection precision bottleneck of a traditional model in a complex scene is effectively solved.

The invention discloses a computer network security transaction optimization system, and belongs to the technical field of network transaction security. The system comprises an identity verification authorization module, a transaction request processing module, a security monitoring protection module, a transaction intelligent optimization module, a transaction auditing management module and a transaction report analysis module, protection is enhanced by analyzing a user behavior mode, additional verification is triggered when abnormality is detected, the risks of identity false use and fraud are reduced, and the safety of the transaction is improved. Network traffic is monitored in real time, potential attack behaviors are identified and blocked, through transaction request checking and dynamic request scheduling strict auditing, node loads are monitored in real time, transaction requests are intelligently scheduled, system overload or bottleneck is avoided, standby nodes are automatically started, stable operation under the high concurrency condition is guaranteed, and the system reliability is improved. The method enhances the adaptation to the increase of the transaction flow and the change of the network environment, improves the security, efficiency and transparency of the transaction through the transaction audit management and report analysis, and guarantees the stability and compliance of the financial transaction environment.

The invention discloses a double-arm collaborative operation method suitable for a transformer substation tubular bus carrying electrified robot, and relates to the technical field of power system automation. Comprising the following steps: comparing an electromagnetic change threshold value with a dynamic threshold value to obtain an electromagnetic environment change parameter and an early warning signal; adjusting the control parameters of the robot and the sensitivity of a sensor through the early warning signal; determining a strong electromagnetic field area through the electromagnetic environment change parameters, and planning an inspection path of the robot; and according to the inspection path, carrying out tubular bus-bar drainage wire lapping / dismounting operation at the target position. According to the method, the electromagnetic environment change in the transformer substation is monitored in real time, the electromagnetic change threshold value is determined and compared with the dynamic threshold value, and the early warning signals of different levels are generated, so that an operator can be reminded in time or robot parameters can be automatically adjusted, and equipment faults or safety accidents caused by a strong electromagnetic field are avoided.

The invention discloses a data processing method and system for video monitoring AI intelligent identification equipment, and the method specifically comprises the steps: obtaining the real-time video data of the video monitoring AI intelligent identification equipment of all factory monitoring areas, and forming an environment feature vector according to the real-time video data; dividing all factory monitoring areas into a plurality of environment categories based on the environment feature vectors, and determining a central monitoring area of each environment category; based on the central monitoring area, training a universal recognition model for each environment category, and adjusting the universal recognition model by adopting a transfer learning method to obtain a specific recognition model for each factory monitoring area in each environment category; and deploying the specific identification model to the video monitoring AI intelligent identification equipment of each corresponding factory monitoring area. According to the invention, the intelligent level and the identification precision of the factory video monitoring system are obviously improved, the resource distribution is optimized, and the operation cost is reduced.

The invention discloses an underground space layout scheme VR visual interaction device and interaction method. The interaction device comprises a three-dimensional graphic processing unit, a virtual reality interaction terminal, a design software synchronization interface and a collaborative design communication module, wherein the virtual reality interaction terminal, the design software synchronization interface and the collaborative design communication module interact with the three-dimensional graphic processing unit. The three-dimensional graphic processing unit adopts a high-performance graphic processor and a special graphic acceleration chip, converts two-dimensional plane layout data into a three-dimensional space model and performs real-time rendering; the virtual reality interaction terminal serves as a direct interface for user experience and is integrated with the three-dimensional graphic processing unit through a low-delay wireless transmission module. The design software synchronization interface realizes data exchange with external design software and synchronizes modification to the three-dimensional graphic processing unit; and the collaborative design communication module is used for supporting real-time collaboration and communication of multiple users in the virtual environment. According to the method, high-performance hardware and special software are combined, so that rapid visualization and real-time interaction of underground space layout are realized.

The invention relates to the technical field of information collection, in particular to an intelligent medical waste collection vehicle information collection method based on the Internet of Things, and the method comprises the following steps: binding a unique RFID tag for each medical waste container; the intelligent medical waste collection vehicle is provided with an RFID reader, and the RFID reader automatically reads the RFID tag of the medical waste container when the medical waste container is loaded. Performing multi-label reading optimization based on intelligent conflict detection and resolution; according to the method, priority ranking is carried out, dynamic optimized reading of conflicting labels is achieved, the mechanism effectively avoids reading conflicts in a multi-label environment, the overall reading efficiency of the system is improved, meanwhile, it is ensured that high-risk waste information can be preferentially and timely obtained, and the accuracy and reliability of information collection are remarkably improved.

The invention relates to the technical field of gate channel target image recognition, and particularly discloses a gate channel target recognition detection method and system, and the method comprises the steps: collecting image data, carrying out the image preprocessing steps, such as illumination compensation and noise removal, extracting the brightness features and texture features in an image, and calculating the visibility coefficient of a target region. According to the method, high identifiability of the target is kept under various illumination conditions, the final identification accuracy of the target in different environments is evaluated by comprehensively analyzing the visibility coefficient and the identification confidence of the target, so that the image preprocessing and target identification algorithms are dynamically adjusted, the target can be rapidly and accurately identified, and the identification accuracy of the target is improved. The target identification efficiency in the gate channel is improved, the high efficiency and robustness of the system under the complex illumination condition are ensured, and the method has practical value and application prospect.

The invention provides a virtual debugging method and system for a plate glass production line, a storage medium and equipment, and the method comprises the following steps: carrying out the system analysis and modular design of the plate glass production line, and determining the overall layout of the plate glass production line and the design variables of all modules; building a plate glass production line three-dimensional model based on the overall layout and the design variables of the modules; building a communication channel among the three-dimensional model of the plate glass production line, corresponding physical entity equipment and an MES system based on a digital twinning technology, and obtaining a virtual simulation result of the plate glass production line; and adjusting design variables of the three-dimensional model of the plate glass production line based on the virtual simulation result. According to the virtual debugging method for the plate glass production line, each link of the production line can be accurately simulated and optimized in a virtual environment, so that potential problems are eliminated before actual production, and the production efficiency and the product quality are improved.

The invention provides a distributed computing system based on pre-scheduling resource collaborative adaptation, and relates to the technical field of resource collaborative allocation systems. The distributed computing system based on pre-scheduling resource collaborative adaptation aims at solving the problems that in the prior art, resource scheduling is not flexible, and application configuration and resource scheduling are lack of coordination. By introducing a dynamic scheduling mechanism of the resources, organic combination of resource pre-scheduling and flexible allocation is realized. Meanwhile, through cooperation of application configuration and resource scheduling, optimal distribution and execution of calculation tasks are achieved, the system is composed of a server side and a client side, the client side has pre-scheduling resources and is used for feeding back the resource state in real time and receiving and executing the calculation tasks, and the server side is responsible for monitoring and scheduling of global resources and task distribution. And through a designed heuristic collaborative adaptation algorithm, the server can dynamically schedule resources in the pre-scheduling resources, and high efficiency and stability of task execution are ensured.

The present invention relates to the technical field of power transmission line operation robots, and discloses an obstacle-crossing mechanism and method of an intelligent acceptance robot suitable for overhead power transmission lines, including an adjustable lifting leg fixing device and a lifting leg rotating device, wherein the adjustable lifting leg fixing device includes a parallelogram frame with four arms movably connected, and the frame is provided with a lateral adjustment mechanism for adjusting the spacing between opposite sides, and the lifting leg rotating device includes a plurality of lifting leg bodies, and the bottom of each lifting leg body is adjustable in horizontal position at the four vertices of the frame through a rotating drive assembly, and the top is provided with a wheel-foot driving assembly for hanging power transmission lines. The present invention can realize single-line obstacle crossing and double-line obstacle crossing, so that the operation robot has a strong adaptability, improves the adaptability of the entire system under different environmental conditions, and enhances the robot's anti-interference ability and operation reliability. Through this optimized design, the robot can complete the inspection task of the power transmission line more efficiently and stably.

The invention relates to the technical field of rail transit, in particular to a rail transit vehicle robot intelligent operation and maintenance system based on digital twinning. The system is composed of a digital twin model construction module, a real-time monitoring and data analysis module, an intelligent decision and task planning module, a robot execution module and a feedback and optimization module. The invention provides a rail transit vehicle robot intelligent operation and maintenance system based on digital twinning, and aims to improve the operation and maintenance efficiency and safety of a rail transit vehicle, reduce the operation and maintenance cost and reduce the risk of manual operation through advanced data acquisition, analysis, modeling and robot control technologies.

The invention discloses a power transmission line field data acquisition system based on unmanned aerial vehicle vision. According to the invention, the CNN is used to extract the features of the visual image and the infrared image, and the 3D-CNN is used to process the laser radar data, so that the system can capture the multi-aspect information of the power transmission line. Information about the state of the power transmission line can be provided from different angles through data of different modes, fusion of the multi-mode data is beneficial for improving the accuracy and robustness of fault detection, the LSTM network is used for processing time series data, the system can better understand the change of the data along with time, the LSTM can process the series data, and the fault detection accuracy and robustness of the power transmission line can be improved. And the change trend of the fault along with time is captured, so that the fault is predicted and diagnosed more accurately. The weights of different modal data are determined through the single-layer sensor, and the system can automatically learn the importance of each modal data to final fault detection so as to reduce prediction errors, thereby improving the accuracy and reliability of fault detection.

The invention discloses an assembly type prefabricated building installation construction management method and system, and relates to the technical field of building construction.Intelligent terminal equipment is arranged for personnel and equipment on a construction site, and real-time interaction and cooperative work between the personnel and the equipment are achieved through the indoor positioning technology and the wireless communication technology; according to the intelligent collaborative operation management mode, various state information of construction site personnel and equipment can be accurately mastered in real time, and task allocation and operation sequence optimization are carried out based on the information, so that the construction personnel can be engaged in work which is most matched with the skills of the construction personnel at the most appropriate time, and the working efficiency is improved. Construction equipment can be fully and reasonably utilized, idle and waste of personnel and equipment are avoided, waiting time and resource mismatching phenomena in construction are reduced, and therefore the construction period is greatly shortened.

The present invention relates to the technical field of pork detection, and proposes a real-time detection device for pork storage and transportation, comprising an adsorption member, the adsorption member having an adsorption end, the adsorption end being used to absorb a part of the pork; a cutting member having a connecting portion and a cutting portion, the connecting portion having a rotating end and a mounting end, the rotating end being rotatably arranged on the adsorption member, the cutting portion being located at the mounting end, and the distance from the rotating end to the mounting end being greater than the distance from the rotating end to the adsorption end. Through the above technical solution, the problems of detection efficiency, labor cost, cross infection, etc. existing in the manual cutting sampling detection in the prior art are solved.

The invention relates to the technical field of robot communication control, in particular to a recoverable buoy system for a modular underwater robot and a control method.The buoy comprises a shell, a communication module and an acquisition module, and an adjusting module comprises a buoyancy adjusting mechanism and a gravity center adjusting mechanism; the buoyancy adjusting mechanism adjusts the action of an electromagnetic valve according to the buoy depth to realize buoyancy adjustment, and the gravity center adjusting mechanism adjusts the gravity center position according to a preset gravity center position and a gravity center adjusting curve; the power module comprises a first power set and a second power set. The control module is used for determining the adjusting mode of the buoyancy adjusting mechanism, the adjusting mode of the gravity center adjusting mechanism and the adjusting mode of the power module. And the power supply module realizes effective positioning and flexible release and recovery of the buoy, and promotes the same-speed cooperative movement and real-time communication of the buoy and the underwater robot.

The utility model provides a methanol catalytic synthesis system utilizing carbon dioxide in dry quenching circulating gas, which is characterized in that an inlet of a desulfurizing tower of a dry quenching circulating gas decarburization system is used for introducing the dry quenching circulating gas, and a purified gas outlet of the desulfurizing tower is connected with a gas inlet of a decarburization absorption tower; an absorption liquid outlet of the decarburization absorption tower is communicated with an absorption liquid inlet of the desorption tower, an absorption liquid outlet of the desorption tower is communicated with an absorption liquid inlet of the decarburization absorption tower, a flue gas outlet of the desorption tower is communicated with an inlet of the CO2 separation device through the flue gas cooler, and a CO2 gas outlet of the CO2 separation device is communicated with an inlet of the catalytic reactor through the compression device; a hydrogen outlet of the coke oven gas hydrogen production system is communicated with an inlet of the catalytic reactor through the compression system, and methanol is synthesized from carbon dioxide generated by a dry quenching production unit in a coking plant and hydrogen generated by a coke oven gas unit in the catalytic reactor, so that effective utilization of resources is realized.

The invention discloses a full-hydraulic crawler-type orchard plant protection robot and a control method thereof. The robot comprises a crawler chassis system, a plant protection device, a power system, a hydraulic transmission system and a control system, and the crawler chassis system is used for walking; the plant protection device is used for protecting plants; the power system is used for providing power for the crawler chassis system and the plant protection device; the hydraulic transmission system is used for transmitting power of the power system to the crawler chassis system and the plant protection device; and the control system is used for monitoring the environment, controlling the hydraulic transmission system, driving the crawler chassis system to walk according to a planned path and driving the plant protection device to perform plant protection according to a preset target. By using the robot for operation, the labor intensity of agricultural operation personnel is greatly reduced, effective separation of people and pesticide is realized, and the body health of the operation personnel is guaranteed.

The invention discloses an infrared simulation method and system based on a neural network and GPU parallel computing, and belongs to the field of infrared simulation. Fitting an all-weather atmospheric transmittance and a radiation value received by the earth surface by using an atmospheric model; preprocessing the infrared simulation data, and calculating a patch shielding probability value and a patch temperature value in a simulation scene by using a distributed GPU parallel framework; wherein the number of sampling points is dynamically adjusted through an adaptive patch sampling method in combination with the geometric area and complexity of a patch so as to calculate a patch shielding probability value, and the patch shielding probability value is introduced when a patch temperature value is calculated; and optimizing the surface patch temperature value to obtain a surface patch steady-state temperature value, calculating the radiation brightness of a specified wave band according to the surface patch steady-state temperature value, and finally rendering to obtain an infrared simulation image of a specified view angle under the specified wave band. The method solves the problems that in the prior art, radiation value and temperature field calculation is complex, shielding calculation efficiency is low, heat conduction simulation capacity is insufficient, and self-adaptive sampling is not fine enough.

The invention relates to a multi-robot collaborative operation control method and device, equipment and a medium. The method comprises the steps that a robot type set, a task type set, a robot task matching matrix, a maximum income matrix, a quotation matrix and a maximum quotation vector are acquired; allocating the to-be-allocated tasks in the task type set to the robots in the robot type set by adopting a preset auction algorithm according to the robot task matching matrix, the maximum income matrix, the quotation matrix and the maximum quotation vector, so as to determine an optimal allocation relationship between the to-be-allocated tasks and the robots; and a robot position set corresponding to the robot without the task allocation, an expected position set and the distance between the robot and the target position are obtained, and the optimal target position of the robot without the task allocation is determined by adopting a preset Hungary algorithm according to the robot position set, the expected position set and the distance between the robot and the target position. The method can effectively reduce the cost and improve the task execution efficiency.

The invention provides a grinding robot and a grinding process, and belongs to the technical field of building construction equipment, and the grinding robot comprises an equipment base, a grinding execution mechanism and an equipment box body. A moving assembly is arranged at the lower end of the equipment base; the grinding executing mechanism comprises a lifting assembly, a mechanical arm and a plurality of grinding heads, the lifting assembly is arranged on the upper end face of the equipment base, the mechanical arm is mounted at the upper end of the lifting assembly, and a grinding head mounting part is arranged at the end, away from the lifting assembly, of the mechanical arm; the equipment box body is arranged on the upper end face of the equipment base, a main control module and a power module are arranged in the equipment box body, and an input module is arranged on the outer side face of the upper end of the equipment box body; and one of the plurality of polishing heads is selected to be detachably mounted on the polishing head mounting part according to preset polishing area layout information provided by the input module. According to the polishing robot, automatic polishing operation on the whole wall can be achieved, and high automation, intelligence and flexibility are achieved.

The application provides a universal connection structure of an electric resectoscope, a laser scope and a shaving scope, and belongs to the technical field of medical devices, and comprises the following: a Z-shaped endoscope, which has a device channel at the distal end; an inner sheath, which is connected with a first connector at the distal end, and the proximal end and the distal end of the first connector are respectively provided with a first connecting part and a second connecting part, and a containing hole penetrating through both ends is further formed in the first connector; an outer sheath, which is connected with a second connector at the distal end, and the outer end of the second connector is provided with a third connecting part, the third connecting part is detachably connected with the first connecting part, and a water inlet valve and a water outlet valve, which are in communication with the inside of the second connector, are connected to the peripheral side of the second connector; and an adapter pipe, which is respectively provided with a fourth connecting part and a fifth connecting part at both ends, and the fifth connecting part is used for detachable connection with the third connecting part. When the operation mode is changed in the operation, the outer sheath and the endoscope do not need to be taken out and replaced, the universal electric resection ring, the laser fiber, the shaving cutter head and the cold knife device of a conventional size can be installed, and the diameter of the outer sheath is reduced.

The invention relates to the technical field of information processing, and discloses an ERP (Enterprise Resource Planning) system-based document automatic transmission method, which comprises the following steps of: 1, based on an ERP system, establishing an online data collection module, a user interface and self-service learning module, a user interface calculation module, an ERP system evaluation module and an ERP system management module; step 2, historical user demand collection, new demand collection and receipt type and management problem collection are carried out in an online data collection module; 3, designing an interactive course, a simulation operation and a self-service guide in the user interface and self-service learning module, and designing a plurality of query modes; 4, performing data calculation in a user interface calculation module; 5, the ERP system evaluation module summarizes the results of all the calculation formulas, and comprehensively evaluates the performance and the user satisfaction of the user interface and the self-service learning module; and step 6, the ERP system management module formulates and executes rectification measures according to an evaluation result.