1073 results about "Personal computer" patented technology

The invention discloses an industrial personal computer and multi-graphics card collaborative parallel computation acceleration system, which relates to the technical field of industrial resource allocation and parallel computation, and comprises a resource monitoring and predicting module, a resource management module and a prediction type resource preparation module, the task splitting and collaborative execution module comprises a task splitting module, a cross-node collaborative module and a collaborative operation engine; the intelligent scheduling and dynamic resource allocation module comprises an intelligent scheduler, a dynamic resource allocation module and a conflict avoidance module. According to the method, the GPU video memory utilization rate, the core utilization rate, the temperature, the video memory fragment rate, the available video memory total amount, the CPU core total utilization rate, the load condition and the idle core number index are collected in real time through a resource monitoring module, and the video memory capacity, the GPU core occupancy rate and the CPU load requirement are predicted in advance before a task is submitted in combination with a gradient boosting decision tree and a neural network prediction model; and resources are reserved, so that the scheduling delay is remarkably reduced, and the scheduling hit rate is improved.

The invention belongs to the crossing field of industrial control and edge computing, and particularly relates to an industrial personal computer data security dynamic protection method and system based on AI edge computing. Firstly, industrial control data encryption and standardization preprocessing are achieved through a hardware-level trusted execution environment; secondly, performing real-time anomaly detection on the encrypted data stream based on an AI model, generating a threat score by combining industrial control protocol feature analysis, and forming an edge layer intelligent detection capability; the authentication mode is dynamically switched based on the threat score, and self-adaptive strategy adjustment is realized in a fog layer; then optimizing edge resource allocation according to the threat index and the equipment load, and constructing a cloud elastic scheduling mechanism; and finally, a security system covering data encryption, real-time detection, dynamic protection and resource optimization is formed through grading component cooperation, and the method is suitable for real-time threat detection and self-adaptive response in an industrial internet scene.

Methods and systems are provided for improving remote computing experiences. The methods leverage modified PC or console architectures, which enable both local and remote console connections. The systems operate with multiple devices through a peer-to-peer connection. In the context of gaming, the systems are engineered to address obstacles such as low upstream rates and limited bandwidth or quality of service. An AI trained on play style is used as a substitute for a low bandwidth client. Also, methods are provided for inviting remote players, transferring control to a remote user, managing controller connections, and addressing low bandwidth situations using adaptive bitrate. The enhancement of connection, single encoding, and transmission processes contributes to a superior computing and / or gaming experience for all players, irrespective of their bandwidth or quality of service. Related networks, models, apparatuses, devices, techniques, articles, architectures, packets, manifests, tables, data storages, and graphical user interfaces are provided.

The invention provides a machine vision solution automatic generation method based on a large language model. The module comprises a workflow agent, a parameter agent, an algorithm agent, a workflow engine and a pre-implementation operator library. According to the method, many problems in a traditional workflow-based machine vision solution construction process are solved to a great extent, including that workflow construction highly depends on personal experience of engineers, algorithm parameter performance is sensitive and difficult to adjust, and an application iteration debugging period is long. Besides, the method provided by the invention has multiple flexible deployment modes, the method can be deployed in carriers such as a client field industrial personal computer, a client field private cloud server, a public cloud server and the like, and a machine vision solution automatic generation task is completed. The solution deployment efficiency of a machine vision provider is greatly improved, and the personnel cost of the machine vision provider is reduced; the method is of great significance in improving the efficiency of the last kilometer of a machine vision industry chain.

The invention relates to the technical field of real-time kernel performance testing of special chips, in particular to a special chip real-time performance evaluation method based on an FPGA (Field Programmable Gate Array), which comprises the following steps: (1) aiming at a real-time system on an ASIC (Application Specific Integrated Circuit) chip, setting an external interrupt source and an interrupt service program through a hardware interrupt controller; (2) two tasks with the same priority are created, scheduling of the tasks is achieved through time slice rotation, and a real dynamic load scene is simulated; (3) configuring an external FPGA (Field Programmable Gate Array) to generate a square wave signal to trigger external interruption of the ASIC chip, receiving a feedback signal, and connecting the FPGA and the GPIO through an external physical connecting line to form a hardware interruption triggering-response closed loop; and (4) realizing nanosecond timestamp capture through a counter built in the FPGA, acquiring time delay data, calculating interrupt response time, and transmitting the time delay data to a PC (Personal Computer) through a UART (Universal Asynchronous Receiver / Transmitter) to calculate a maximum value, a minimum value, an average value and a data jitter range of test data. The method can effectively solve the problem that the traditional internal closed-loop test cannot reflect the real interruption randomness and the dynamic load.

The invention discloses a pulsed neutron generator control system based on LabVIEW, and the system comprises a neutron generator industrial personal computer which operates a virtual human-computer interaction interface developed based on LabVIEW; the console core board carries a DSP main control chip and is embedded into a real-time operating system; the driving sampling board is connected with the console core board and is integrated with a signal conditioning circuit; the neutron generator industrial personal computer communicates with the console core board through a Modbus protocol, and controls and drives the sampling board to output control signals of the three independent power supply ion sources, the storage and the acceleration pole to the neutron tube; wherein the console core board generates three paths of PWM signals with the PWM frequency of 2.5 kHz and the step length of 8191, and the three paths of PWM signals are converted into analog control signals through the driving sampling board. According to the control system, the PWM control precision is greatly improved, the voltage control precision is improved to 0.012% (100% higher than that of a conventional scheme) through the combination of the 8191 step length (13-bit resolution) and the 2.5 kHz frequency, and the neutron yield fluctuation is controlled within + / -1.5%.

The invention relates to the technical field of industrial automation online monitoring, in particular to a fault monitoring and self-recovery method and system for an industrial personal computer, and the method comprises the steps: detecting and regulating the external environment temperature of the industrial personal computer to accord with a starting mechanism before power-on, and starting industrial personal computer equipment; hardware information of the industrial personal computer is read, circulation monitoring is carried out, whether hardware faults exist or not is checked, and parameter data of the industrial personal computer are synchronously collected; and through the prediction model, the processed parameter data is evaluated, whether non-hardware abnormity exists is judged, and fault self-recovery and abnormity processing are carried out. According to the invention, real-time monitoring is carried out through the MCU before and after the industrial personal computer is started, so that the real-time performance and accuracy of fault detection are improved; fault recovery is automatically carried out according to a fault analysis result, manual intervention is reduced, and downtime and maintenance cost are reduced; through environment monitoring and control, stable operation of the industrial personal computer in an extremely complex industrial environment is ensured; and through real-time monitoring and fault prediction, production interruption is avoided, and the production efficiency is improved.

The invention provides a dam safety monitoring system lightweight construction method and device, and the method comprises the steps: deploying a protocol conversion gateway, carrying out the protocol analysis and data standardization processing of an existing heterogeneous sensor, generating data in a unified format, and supporting the network disconnection caching and automatic supplementary transmission; deploying a data processing module on a local server or an industrial personal computer based on an edge computing architecture, performing feature extraction and multi-scale fusion analysis on acquired data, and performing data compression by adopting an improved revolving door algorithm; constructing a lightweight anomaly detection model, training by using historical data to generate a normal mode template library, calculating a dynamic time warping distance between new data and a template in real time, and triggering early warning when the distance of a plurality of continuous cycles exceeds a preset threshold value; the sampling frequency of the sensor is dynamically adjusted according to the real-time data analysis result, key parameters are collected in a high-frequency mode, non-key parameters are collected in a low-frequency or intermittent mode according to the change rate prediction result, and therefore the system resource use efficiency is optimized.

The invention relates to an automatic test method and system for the zero offset of a hemispherical resonator gyroscope. The automatic test system composed of a double-shaft servo turntable control module, a gyroscope control module and a PC (Personal Computer) upper computer is built; a servo turntable control instruction and a gyroscope control instruction are sent through a serial port according to a certain program through an automatic test logic built in a PC upper computer, a gyroscope vibration mode angle is controlled to be automatically switched from 0 degree to 360 degrees (the step length can be set), and turntable angle and gyroscope vibration mode angle data under each vibration mode angle are synchronously collected; and substituting the acquired data into the error model, completing zero offset error parameter identification by adopting a nonlinear least square method, generating an error compensation formula, and writing the error compensation formula into a gyroscope control unit in real time to realize compensation.

The invention discloses a low-resource and low-energy-consumption remote sensing image brain-like computing system based on an FPGA (Field Programmable Gate Array), which belongs to the cross technical field of brain-like computing and remote sensing information processing, and comprises a data interaction module which is used for high-speed data transmission between a PC (Personal Computer) end and the FPGA and comprises a PCIe (Peripheral Component Interconnect Express) interface sub-module and a data transmission control sub-module; the storage control module is used for data interaction control of the off-chip DDR and the on-chip BRAM and providing efficient data supply for the processing engine; the processing engine module is used for simulating a brain-like pulse neural network to complete convolution calculation of the remote sensing image; comprising a convolution processing sub-module, a data storage sub-module, an input buffer sub-module and an output buffer sub-module. According to the low-resource and low-energy-consumption remote sensing image brain-like computing system based on the FPGA, the brain-like pulse neural network is adopted, the BRAM is allocated to store the intermediate computing result, and the computing unit is designed in combination with SNN characteristics, so that energy consumption and resource waste are effectively reduced, and computing efficiency is improved.

The invention discloses a quadruped robot system for indoor fire rescue. The quadruped robot system comprises a quadruped robot body, a main control unit carried by the robot, a sensing unit, a navigation unit, an execution unit and a motion control unit. The main control unit comprises two high-performance industrial personal computers which respectively process a motion control algorithm and a visual perception algorithm. The industrial personal computer communicates with other sensors through an IP and a serial port, and wirelessly communicates with the rear end of the fire-fighting command center through a TCP. After the fire-fighting command center issues a rescue task to the quadruped robot, the robot constructs a global map through the laser radar, and searches a fire source and trapped persons through the depth camera. When the robot recognizes the target, the robot sends the target position to the rear end of the fire-fighting command center, automatically avoids obstacles, and navigates to the target position to execute fire extinguishing and rescue work. The firefighter can be helped to quickly find a fire source and trapped persons, determine the positions of the trapped persons in the map, and guide the firefighter to reach the area to carry out rescue.

The embodiment of the invention discloses electronic equipment and a pressing type pop-up locking assembly, the pressing type pop-up locking assembly can be applied to electronic equipment such as a mobile phone, a tablet personal computer and a notebook computer, is used for realizing switching of working modes of a specific function module in the electronic equipment, and can increase applicable scenes of the function module in the electronic equipment. The pressing type pop-up locking assembly comprises a mounting table unit and at least one locking release unit. The mounting table unit comprises a table body and an elastic reset piece, and the table body is switched among a release position, a first locking position and a first pressing position in the first direction. The lock release unit includes a locking mechanism and an unlocking mechanism. The locking mechanism comprises a first locking block and a first elastic piece; the first locking block is switched between the second locking position and the first avoiding position in the second direction. The unlocking mechanism comprises an unlocking block, and the unlocking block drives the first locking block to move to the first avoiding position. The pressing type pop-up locking assembly is novel in structural design, easy to operate and high in interactivity.

A system for simulating automatic labeling of steel coils on a production site comprises a PLC industrial personal computer used for collecting information of the steel coils, issuing the information of the steel coils needing to be labeled to a label printing and stripping device, sending a label taking instruction to an industrial six-axis robot and sending a labeling instruction to a labeling head after receiving a movement completion signal; the label printing and stripping device is used for printing a label containing the steel coil information based on the steel coil information, stripping the corresponding label after printing is completed, and feeding back a label printing and stripping completion signal to the PLC industrial personal computer; the industrial six-axis robot is used for controlling the labeling head to move to the label taking position of the label printing and stripping device after receiving the label taking instruction, sucking the label stripped by the label printing and stripping device through a vacuum chuck on the labeling head, controlling the labeling head to move to the steel coil after taking the label, and feeding back a movement completion signal to the PLC industrial personal computer; and the labeling head is used for carrying out labeling operation after receiving the labeling instruction, and labeling the labels on the corresponding steel coils.

The invention provides a numerical simulation method and system constructed based on a neural network and an iterative approximation method. The method comprises the steps that a to-be-solved partial differential equation is determined; constructing a precise solution data set; establishing a deep learning objective function network; constructing a loss function; training the network through the random training set; and outputting the prediction solution. According to the method, the time variable is used as network input, continuous time prediction under single-round training is realized, and the problem that a traditional discrete model needs multiple times of iterative training is solved; tasks such as target detection and image classification can be executed, screen and back images of the mobile terminal / tablet personal computer are input in product defect detection, and defect existence, position or type are output; and inputting a sea surface image in sea surface ship identification, and outputting existence, position or type of the ship. According to the method, the number of training iterations in a Burgers equation experiment is reduced by 19.3%, and full-time-domain repeated training of a traditional discrete model is eliminated; internal point sampling is avoided through time semi-discretization, and the calculation efficiency is remarkably improved.

The invention provides a PC (Personal Computer) end quantitative model reasoning method. The method comprises the following steps: S1, loading input information; s2, deserializing the model; s3, operator calculation is carried out; and S4, storing the data, and selecting a dump data result. The quantitative model reasoning on the PC end is used for simply reasoning the model, verifying the result of the model and obtaining the data of the network layer of each stage reasoned in the model, and the PC end reasoning is used for correcting the data, assisting the quantitative model, reasoning the float model, post-quantitative model and training the quantitative model and verifying the correctness of the data. According to the method, model reasoning is convenient and effective, model data verification is facilitated, and data information of a quantitative model is provided.

The invention relates to an SOP chip packaging body defect detection method and system based on improved YOLO-v8, and the method comprises the following steps: S1, collecting and marking SOP chip packaging body defect pictures, and constructing an SOP chip packaging body defect data set; s2, performing data enhancement on the SOP chip package defect data set; s3, the YOLO-v8s model is optimized according to the defect characteristics of the SOP chip packaging body, and an SOP-YOLOv8s target detection model is obtained; s4, carrying out the training of an SOP-YOLOv8s target detection model through the SOP chip packaging body defect data set after the data enhancement; s5, constructing an SOP chip packaging body defect detection system, and deploying the trained SOP-YOLOv8s target detection model to an industrial personal computer system; and S6, acquiring an image through the industrial camera, and transmitting the image to the SOP-YOLOv8s target detection model for detection to obtain the package defect type of the SOP chip to be detected. The method and the system are beneficial to improving the defect detection precision and speed of the SOP chip packaging body.

The invention relates to the field of temperature control, in particular to a temperature control method and system for an industrial personal computer mainboard. The method comprises the following steps: acquiring a CT imaging structure diagram of a mainboard; performing inter-component physical connection analysis and component spatial topology mining on the mainboard CT imaging structure diagram, and constructing a mainboard three-dimensional topological structure model; calculating a real-time temperature value of each mainboard assembly; carrying out time sequence temperature fluctuation analysis and dynamic temperature distribution rendering on the mainboard three-dimensional topological structure model based on the real-time temperature value of each mainboard assembly so as to construct a dynamic heat distribution twinborn model; obtaining a mainboard state monitoring log; and carrying out load fluctuation trend evolution analysis on the mainboard state monitoring log, and carrying out multi-period periodic association mining so as to generate a multi-time-sequence load fluctuation evolution rule. Through efficient and dynamic temperature cooling control, long-term stability and reliability of mainboard performance are achieved.

The invention provides a material light guiding method. The method comprises the following steps that row indicator lights are installed on each row of goods shelves, and layer indicator lights are installed on each layer of goods shelves. All the indicating lamps are connected to the central control system through the wireless network controller; the central control system maintains a database and records position information of all goods and corresponding goods allocation numbers. After an operator inputs a query instruction through the tablet personal computer or the PC, the system searches the goods allocation number corresponding to the goods in the database according to the instruction, and sends a signal through the network controller to activate the row indicator light and the layer indicator light of the corresponding goods shelf; the system introduces an adaptive learning algorithm, and can automatically adjust the display mode of the indicator lamp according to historical operation data and real-time environment change. Through combined use of the row indicating lamps and the layer indicating lamps, the goods picking personnel can quickly locate the target goods allocation without assistance of handheld equipment, so that the goods picking speed is remarkably improved, the guiding accuracy is ensured, and errors caused by manual misoperation are reduced.

We provide a blockchain automatic registration device for documents such as official daily reports and medical records that ensures the authenticity of business records, simplifies certification, and prevents tampering. [Solution] The system is equipped with an input means for acquiring electronic records entered or edited by users from a personal computer or tablet terminal, a communication means for sending or transferring the electronic records to a central information processing device, a processing means for hashing and digitally signing the electronic records, and a registration means for automatically registering the processing results obtained by the processing means in a blockchain, and is configured to automatically execute based on the electronic records.

The utility model discloses an extensible laser which comprises a machine table, a double-shaft carrying table and a lifting module are arranged on the machine table, an industrial personal computer is fixedly installed on the side face of the lifting module, the lifting module is connected with the lifting carrying table in a driving and lifting mode, and two lasers are arranged on the lifting carrying table in a sliding mode. The precise adjusting mechanism can be used for installing and connecting a plurality of lasers and galvanometers, and can be used for precisely adjusting each galvanometer, so that not only is the efficiency improved, but also the product quality is guaranteed; the working range of the multiple galvanometers is expanded, multiple products are coded or cut at the same time, and efficiency is improved; through the precise adjusting mechanism, the height distance of the galvanometers is changed, the focusing range is more precise, the distance between the galvanometers is changed, and the marking, punching and cutting range is better expanded.

The invention relates to a welding problem tracing method and device, computer equipment and a storage medium. The method comprises the following steps: performing data acquisition on process data, service information system data and quality manufacturing data of a terminal industrial personal computer, and performing data rough classification according to relevancy of the data and process quality to form rough classification data; performing data cleaning and data standardization on the rough classification data to obtain various welding process data sets and storing the welding process data sets in a database; selecting process parameters according to the various welding process data sets to construct a welding problem traceability model, and training the welding problem traceability model based on a welding process quality traceability process; and the trained welding problem traceability model is utilized to carry out influence factor positioning and sorting, traceability is carried out to obtain process parameters generated by unqualified welding products and the proportion of the influence factors, and the process parameters and the proportion are output. According to the method, efficient and accurate prediction can be provided for the welding process quality problem, and the traceability precision of the welding process quality problem can be improved.

The invention relates to the technical field of deep learning image processing, in particular to a RetinexNet improved low-illumination image enhancement method based on a CMOS image sensor and electronic equipment, and the method comprises the following steps: S1, collecting and preprocessing an image; s2, decomposing the network model; s3, a blind de-noising network model is established; s4, a brightness adaptive adjustment model; s5, performing image fusion module and output; compared with the prior art, the method has the advantages that the brightness, detail recovery and noise suppression effects of the low-illumination image can be remarkably improved, and the method has remarkable advantages in image quality, structure retention and visual effect, and is particularly suitable for image enhancement in a low-illumination environment; the method provided by the invention can be widely applied to the image enhancement aspect of mobile equipment in a low-light environment, such as a smart phone, a tablet personal computer, a notebook computer, a digital camera, a security camera and the like, so as to capture and transmit image and video signals.

The invention provides a tunnel deformation monitoring system and method based on array laser. The system comprises a data acquisition module, an edge control master station and a cloud platform, the data acquisition module comprises a data acquisition terminal and a protection box; a laser ranging module, a sensor module, a first communication module and a processor in the data acquisition terminal are arranged based on the overall supporting structure, the laser ranging module monitors the distance of the tunnel structure in real time, and the sensor module acquires real-time monitoring data to assist in analyzing a deformation monitoring result; the processor is used for controlling the laser ranging module and the sensor module to process the collected data; the edge control master station comprises an industrial personal computer, a second communication module, a network module and an alarm module and is used for analyzing and identifying abnormal data and generating a matched instruction; by adopting the scheme, the problems that the operation convenience is insufficient, the monitoring is easily interfered and the monitoring performance is insufficient in the traditional technology can be solved, data acquisition parameters are flexibly configured, and the accuracy of a monitoring result is ensured on the basis of saving energy consumption.

The invention relates to a vibration acquisition and monitoring device for vehicle-mounted equipment. The device comprises an acceleration sensor module, a vibration acquisition and monitoring module and a control module, wherein the acceleration sensor module is used for detecting three-axis acceleration of the detected vehicle-mounted equipment in real time; the signal conditioning module is used for carrying out blocking filtering and denoising on the three-axis acceleration original data and then sending the three-axis acceleration original data to the MCU processing module; the MCU processing module is used for performing frequency spectrum calculation according to the three-axis acceleration to obtain a power spectrum density PSD and a corresponding RMS value, and recording and storing the power spectrum density PSD and the corresponding RMS value; the data communication module is connected with the MCU processing module and is used for realizing communication with an upper PC (Personal Computer) and vehicle-mounted equipment; and the power supply module is used for providing low-noise stable power supply for each module. Compared with the prior art, the method has the advantages of high real-time performance, stability, reliability, low power consumption, small measurement error and the like.

According to the penetration test system and method for the vehicle-mounted controller, various types of communication interfaces and equipment interfaces are integrated in the industrial personal computer, so that the rigid requirements for communication configuration in various test scenes are met. Furthermore, through division of a bus security test module, a system security test module and a communication security test module, each module can independently construct connection with a target vehicle-mounted controller based on a Vector tool chain, an ADB / SSH, a wireless network card and a Bluetooth adapter, parallel execution of multiple test cases is supported, and the test cases do not interfere with one another; and synchronous promotion of safety tests such as bus diagnosis, system login, wireless communication and the like is realized. The upper computer serves as a control core and can automatically drive any module or multiple modules to work cooperatively according to the target test case, and test instructions are issued in a unified mode through the VT test system, so that the test preparation time and the execution period are greatly shortened, and the effect of improving the penetration test efficiency of the vehicle-mounted controller is achieved.

The invention discloses a water quality and water level simultaneous monitoring device and method and belongs to the technical field of water quality and water level monitoring. The device comprises a shell, and a water quality data acquisition module, a water level data acquisition module, a power supply module and a PC (Personal Computer) upper computer which are positioned in the shell, power is supplied through the power supply module, the water quality data acquisition module is a hyperspectral camera system, the water level data acquisition module is a radar position finder, and control and data processing functions are integrated in the upper computer. A hyperspectral camera system and a radar position finder are fused and work cooperatively, the hyperspectral camera system monitors water quality, and the radar position finder obtains water level data. And meanwhile, a water level dynamic compensation mechanism is introduced, so that accurate quantification is realized, and the influence of water level change on water quality parameter inversion is compensated. When the real-time water level deviates from the reference water level, an inversion result is corrected in real time according to a dynamic compensation algorithm, spectral signal distortion caused by water level fluctuation is effectively inhibited, the accuracy and reliability of monitoring data are ensured, powerful support is provided for water environment monitoring and management, and the application range is wide.

The invention relates to the technical field of video monitoring, in particular to an efficient and rapid development and data optimization configuration method for a PC client in the video monitoring industry. A system architecture comprising a public bottom layer, a business data layer and an interface layer is constructed. The public bottom layer provides a bottom layer business data interface to guarantee a data source; the business data layer is responsible for data processing and management, and a business data agent of the business data layer can flexibly synchronously or asynchronously acquire data and monitor updating; the interface layer is based on an MVC framework and generates a configuration file through an interface designer, the interface management module effectively manages layout and interaction of the interface unit, and the interface unit obtains data from the business data layer to achieve dynamic display. According to the system and the method, rapid interface configuration in which non-developers can participate is realized, the development efficiency is improved, data management is optimized, the user experience is enhanced, good expandability and maintainability of the system are ensured by virtue of layered and modular design, and diversified requirements of PC client development in the video monitoring industry are effectively met.

The invention relates to a cloud PC (Personal Computer) server, which comprises a 3U standard on-rack server and comprises a computing blade provided with a case, a fan module, a power supply module, a network switching module and a main control management module responsible for monitoring and managing the running state of system hardware, the number of the calculation blades is 24, and each calculation blade can operate independently; the fan module adopts a heat dissipation mode of front air inlet and rear air outlet; the number of the power supply modules is two, and current-sharing hot backup is allowed. The network switching module is provided with two sets of mutually independent and physically isolated networks. The method has good expansibility and universality, and is high in reliability.

The self-adaptive welding device comprises a robot, a robot controller, an industrial personal computer, a visual assembly and a welding gun, a visual processing module, a welding seam contour recognition module, a welding seam precision adjustment module and a track generation module are arranged in the industrial personal computer, and the visual assembly is used for conducting multi-angle shooting on a workpiece; the visual processing module is used for identifying geometrical characteristics of a main pipe and a branch pipe of the workpiece; the weld contour recognition module is used for recognizing a weld contour; the welding seam precision adjusting module is used for refining the precise position of the welding seam point at the junction of the main pipe and the branch pipe through a calibration method; the track generation module is used for generating a welding track; and the robot controller receives the welding track and controls the welding gun to move according to the welding track to execute welding operation. According to the method, the reasonable robot welding posture is automatically matched, the track continuity and the welding process stability are improved, through automatic track planning and execution, it is ensured that the quality of each welding seam is stable, and manual operation errors are reduced.

To give an appropriate advice to a batter by combining an ultra-small camera attached to a helmet and analysis by AI in order to improve the ability of the batter to hit a ball.SOLUTION: A system includes: an ultra-small camera that can be attached to a brim portion of a helmet; means that captures a batting video of a batter by means of a smartphone camera; means that transfers the captured video to a cloud (a smartphone / a personal computer); means for AI to recognize personal information of the batter and a type of a pitcher and to analyze a pitch type, speed, trajectory and batting form; and means for the AI to advise how to swing a bat and how to train to increase probability of hitting.SELECTED DRAWING: Figure 1