39 results about "Infrared vision" patented technology

The invention discloses a device and a method for mobile detection of internal and external defects of a pipeline weld joint based on infrared-vision, and aims to solve the problems of poor flexibility of an existing device and low efficiency and high false detection rate of traditional detection. The device comprises a moving trolley, a camera mechanism and a laser excitation mechanism. The moving trolley is a carrier; the laser excitation mechanisms are installed on the two sides of the front end of the trolley, pose regulation and control are achieved through the transmission and tail end fine adjustment mechanism, and stable thermal excitation is provided. The camera mechanism is installed above the trolley, comprises a transverse / longitudinal movement and fine adjustment mechanism, can deflect and rotate to achieve accurate imaging, and is compact in overall structure and high in flexibility. The method comprises the following steps: constructing a space-time two-dimensional synchronous acquisition framework by adjusting a detection position; segmenting the infrared data by adopting a convolutional neural network containing attention weight, extracting a temperature anomaly region and core feature parameters, and inputting the temperature anomaly region and the core feature parameters into a Transform model for prediction after environmental parameter correction; and in combination with a temperature difference and area grading judgment rule, inner and outer defect grades are distinguished, efficient detection is realized, the detection rate is high, and the false detection rate is low.

The invention provides a conveyor state monitoring device and method based on machine vision, and the device comprises a monitoring cabin which can autonomously reciprocate along a rigid guide rail at one side of a conveyor, automatic charging piles are arranged at the two ends of the guide rail, and the monitoring cabin is integrated with an infrared thermal imager, a visual camera and a sound sensor. A vibration sensor and an incremental photoelectric encoder are arranged along the line. A processor is arranged in the monitoring cabin, and time alignment, feature extraction, fusion of a multi-scale feature fusion model and three-level decision judgment are carried out on infrared signals, visual signals, sound signals and vibration signals on the basis of encoder timestamps. According to the method, fault diagnosis and false alarm filtering are achieved by controlling inspection of a monitoring cabin, multi-source data preprocessing, confrontation feature fusion network processing and three-level progressive judgment, and accurate positioning is achieved based on the mapping relation between encoder pulses and support numbers. According to the invention, the monitoring coverage range is expanded, the endurance continuity is improved, the data transmission stability is improved, and the false alarm rate is reduced.

The invention relates to a smoke identification and classification early warning method, which comprises the following steps: carrying an infrared camera, an infrared spectrum sensor and a temperature and humidity sensor on an unmanned aerial vehicle, and carrying out a smoke inspection activity on a set target area; the method comprises the following steps: acquiring an infrared visual image, infrared spectrum data and environmental parameters of a target area by using an unmanned aerial vehicle, and preprocessing the acquired data; the infrared spectrum data comprises the concentration of CO2 and the concentration of CO, and the environmental parameters comprise the temperature, the humidity and the wind speed; multi-modal data fusion is carried out on the preprocessed data to construct a fusion feature vector, and a trained deep learning classification model is used to identify the smoke type according to the fusion feature vector; and determining an early warning level according to the identified smoke type, and dynamically realizing early warning triggering based on the early warning level and a set grading response rule. According to the method, accurate distinguishing and early warning decision making can be carried out on smoke in the urban comprehensive treatment complex environment.

The invention discloses a mobile audio-visual cooperative unmanned aerial vehicle detection system, and belongs to the technical field of intelligent detection and automatic control. The system comprises a mobile ROS unmanned vehicle platform, an audio-visual perception module, an embedded processing unit and an execution mechanism. The mobile ROS unmanned vehicle platform comprises a motion control system, a serial port communication module and a wireless communication module; the audio-visual perception module comprises an infrared visual acquisition unit and a four-channel audio acquisition array and is used for acquiring infrared image information and acoustic signals of the unmanned aerial vehicle; the embedded processing unit comprises a multi-modal data fusion processor and a motion cooperation controller and is used for synchronously processing the infrared image information and the acoustic signal and generating a control instruction; the execution mechanism comprises a two-degree-of-freedom steering engine holder and a self-adaptive cruise system. According to the invention, through audio-visual cooperation and dynamic mode switching, a fixed detection scene is not needed, continuous tracking of the unmanned aerial vehicle and blind area complement detection can be realized, and detection continuity and accuracy are improved.

The application discloses an infrared image generation method and system based on a physical prior constraint generative adversarial network, relates to the field of infrared image generation, and aims to solve the problems of insufficient physical reality and lack of representation ability of infrared radiation characteristics of the existing infrared image generation method. The application first designs a physical prior knowledge learning network, which is used to learn the prior representation related to the infrared radiation characteristics from the infrared image, and realizes the prediction of the infrared radiation related parameters through a deep learning network. Secondly, a generative adversarial network based on the physical prior constraint is designed based on the proposed physical prior knowledge learning network, the physical prior features are introduced into the image generation process, and the learning ability of the generator to the overall distribution of the infrared radiation and the representation ability of the generator to the infrared radiation characteristics are enhanced. The method breaks through the limitation that the traditional generator only relies on shallow texture mapping. The application is suitable for the fields of visible light to infrared image generation, infrared vision algorithm research and development.

The invention relates to the technical field of image recognition, in particular to a tunnel lining hollowing imaging method and system based on infrared vision fusion, and the method comprises the steps: carrying out the synchronous triggering collection through an infrared thermal imager and a visible light camera in a set mode along the axis of a tunnel, and obtaining an infrared image and a visible light image; feature point extraction and matching are carried out on the infrared image and the visible light image, a projection matrix is calculated based on successfully matched feature point pairs, and a registration visible light image is generated; carrying out the recognition and extraction of a hollowing feature region of the registered visible light image, and carrying out the fusion based on an obtained hollowing feature mask, and obtaining a hollowing fusion imaging image; and a three-dimensional point cloud model of the tunnel lining is generated based on the visible light image, and the hollowing fusion imaging graph is mapped to the three-dimensional point cloud model to mark hollowing, so that a temperature abnormal area can be quickly and accurately corresponding to the specific position of the tunnel lining.

The invention discloses a multi-camera cooperative state estimation method based on active infrared visual features, and belongs to the technical field of image processing and computer vision. The existing visual marking technology depends on ambient light and is poor in performance under dark light or complex illumination, the observation visual field of a single camera or a fixed camera is limited, distortion exists, and consequently the pose resolving precision and robustness are insufficient. According to the method, active infrared visual feature marking is adopted, dependence on ambient light is avoided, and feature point information is stably provided. And efficient and accurate feature point identification and matching are realized through multi-camera collaborative observation in combination with binarization processing of dynamic threshold adjustment, geometric feature screening and a matching algorithm. And carrying out pose calculation by using a PnP algorithm, and checking the goodness of fit between the axis and the gravity direction. Meanwhile, multiple cameras are dynamically scheduled to rotate cooperatively according to the observation quality, and the observation view is expanded. The method is mainly used for accurate positioning of targets such as an unmanned aerial vehicle, significantly improves the environmental adaptability and observation stability of the system, reduces the deployment cost, and improves the pose calculation precision and robustness.

The invention discloses an infrared-vision cooperative tracking navigation method applied to a mobile robot and a related device, and relates to the field of robot navigation. Judging whether the infrared tracking is in a normal state or a failure state: in the normal state, generating an infrared tracking motion control signal in combination with a path surface reflected light intensity analog signal and a PID control algorithm so as to control the mobile robot to perform tracking motion; and in a failure state, starting a top camera to acquire a path image, and generating a visual tracking motion control signal in combination with the path surface image and a PID control algorithm so as to control the mobile robot to perform tracking motion. Through automatic conversion and synergistic effect of infrared and visual tracking, stable and accurate tracking navigation is realized, and the problem that tracking stability and accuracy are difficult to consider in the current tracking navigation field is solved.

The invention discloses an infrared safety belt applied to normative wearing of an infrared visual detection safety belt. The safety belt comprises warp yarns and weft yarns, the warp yarn comprises first polyester FDY high-tenacity yarn and second polyester FDY high-tenacity yarn, the first polyester FDY high-tenacity yarn is the polyester FDY high-tenacity yarn with the reflectivity larger than or equal to 70%, and the second polyester FDY high-tenacity yarn is the polyester FDY high-tenacity yarn with the reflectivity lower than 30%; according to the black or colored infrared safety belt produced by the preparation method, the identification degree under an infrared camera can be greatly improved, and the problem of misjudgment under the condition that the infrared camera detects a safety belt system due to insufficient light or passenger clothes and a braid are made of the same material is solved.

The application belongs to the technical field of cleaning unmanned aerial vehicles, and discloses a multi-mode intelligent cleaning unmanned aerial vehicle system suitable for photovoltaic panels; the system comprises an unmanned aerial vehicle and a cleaning control unit; the unmanned aerial vehicle is provided with an infrared vision sensor, a laser radar and a cleaning module; the cleaning module is arranged at the bottom of the unmanned aerial vehicle; the cleaning control unit comprises an AI control navigation module; the AI control navigation module is arranged at the central position of the unmanned aerial vehicle body and connected with a flight control bus; the infrared vision sensor and the laser radar are fused to accurately identify the contaminated area; in combination with the parameterized control of the cleaning execution mechanism, the system can maintain good coverage and adhesion under the wind field, reduce the consumption of cleaning agents and water, and improve the cleaning quality and system reliability.

The application discloses a kind of low-illumination condition fast moving target multi-view cooperative tracking method and device, the method includes low-illumination condition fast moving target multi-view tracking algorithm and unmanned aerial vehicle cluster cooperative tracking algorithm;Multi-source environment perception is carried out using millimeter wave radar sensor, RGB vision sensor and infrared vision sensor carried by unmanned aerial vehicle;Multi-source perception data is normalized in time and space dimensions by three space-time heterogeneous alignment algorithm;Multi-source fusion perception data after space-time normalization is input into multi-source fusion perception feature calculation network to calculate the world coordinates of the tracked target under the current frame;The calculation result is compared with the calculation result of last frame, to judge the change of the position and moving direction of the tracked target in world coordinate system;The world coordinate information of the tracked target is shared through cluster communication, and the trajectory of unmanned aerial vehicle cluster is formulated and updated using multi-agent reinforcement learning, to realize unmanned aerial vehicle cluster cooperative tracking.

This document relates to a connecting element (10) comprising a first part (20a) and a second part (20b) manufactured by additive manufacturing, the first part (20a) comprising a first frame (21a) intended to be fixed to one of two parts, the second part (20b) comprising a second frame (21b) intended to be fixed to the other of two parts, the first part (20a) comprising at least one first half-arm (23) extending from the first frame (21a) in a connection direction (X), each of said at least one first half-arm (23) comprising a tubular cavity (25) housing at least one portion (26) of a second half-arm (24) of the second part (20b), the second half-arm (24) extending from the tubular cavity (25) to the second frame (21b) in the connection direction (X), an elastomer (30) being annularly intercalated in the tubular cavity (25) between the first half-arm (23) and the second half-arm (24).

The application discloses a multi-source data fusion cooperative target positioning method and system based on infrared vision, and the method comprises the following steps: deploying an infrared point light source beacon on the ground and starting when the signal is disturbed; acquiring an infrared point light source beacon image by using an infrared camera carried by a UAV; and analyzing the infrared point light source beacon image by using a constructed visual navigation relative positioning algorithm to complete the UAV target positioning in the state that the signal is disturbed. The application adopts infrared vision to support all-weather positioning and is not limited by illumination conditions; meanwhile, the positioning error is less than or equal to 5% by fusing IMU and visual data through EKF. In addition, the application adopts a unique layout and waveband design of the infrared beacon, can effectively resist electromagnetic interference, and can realize 24-hour continuous operation without cumulative error.

The present application relates to the technical field of image recognition, and particularly relates to a tunnel lining hollowing imaging method and system based on infrared vision fusion, infrared thermal imagers and visible light cameras are synchronously triggered and collected in a set manner along a tunnel axis to obtain infrared images and visible light images; feature points of the infrared images and the visible light images are extracted and matched, and a projection matrix is calculated based on the matched feature points to generate a registered visible light image; a hollowing feature region of the registered visible light image is identified and extracted, and fusion is performed based on a obtained hollowing feature mask to obtain a hollowing fusion imaging image; a tunnel lining three-dimensional point cloud model is generated based on the visible light image, and the hollowing fusion imaging image is mapped to the three-dimensional point cloud model to label the hollowing, so that a temperature abnormal region can be quickly and accurately corresponded to a specific position of the tunnel lining.

An optimized electronic face bow system based on binocular infrared vision and passive infrared target, comprising: a three-ring passive infrared target, a binocular infrared camera and a control module connected with the binocular infrared camera, after the control module triggers the left eye infrared camera and the right eye infrared camera to synchronously expose globally and collects the binocular infrared image, the actual relative attitude, the actual included angle, the baseline relationship and the continuous motion trajectory of the upper and lower jaw target plates of the three-ring passive infrared target are calculated. Through the special structure of the infrared target and the joint optimization algorithm, the continuous, stable and low-latency jaw bone motion trajectory can be obtained, and the repeated positioning error of the target plate center is less than 0.02mm.

The invention relates to a full-automatic sound control respiratory tract sputum cleaning device special for old people, and belongs to the technical field of medical instruments, the device comprises a fixed base, an inflatable flexible limiting pillow integrated with a multi-mode sensor is arranged on the fixed base, and the inflatable flexible limiting pillow is used for supporting the head of a patient and collecting physiological signals; the double-shaft linkage positioning mechanism is arranged above the fixed base, comprises a horizontal sliding base and a semi-arc sliding arch frame, and is used for driving the execution assembly to move; the execution assembly comprises an automatic telescopic sputum aspirator and an infrared vision fusion positioning module and is used for accurate positioning and operation. The central controller is integrated in the equipment and used for processing multi-mode signals, intelligently making decisions and coordinating actions of all mechanisms. The respiratory tract secretion state early-stage automatic identification and on-demand intervention can be achieved, safe and soft whole-process automatic sputum clearing operation is completed through accurate positioning and force feedback control, the aspiration pneumonia risk is effectively reduced, the discomfort of a patient and the workload of nursing personnel are relieved, and the nursing quality and efficiency are improved.

The utility model discloses die cutting visual inspection equipment, and particularly relates to the technical field of visual inspection, the die cutting visual inspection equipment comprises a casing and an infrared visual sensing head, the infrared visual sensing head is fixed inside the casing, and a linkage protection assembly is arranged outside the infrared visual sensing head; the linkage protection assembly comprises a protection shell frame arranged outside the infrared vision sensing head, the protection shell frame is in sliding connection with the machine shell, one side of the protection shell frame is fixedly connected with an L-shaped strip, and the outer wall of the L-shaped strip is in sliding connection with a sleeving block. According to the utility model, the balancing weight moves leftwards through the linkage protection assembly and the vertical cover plate, the lower surface of the vertical cover plate does not contact with the upper surface of the outer wall of the infrared vision sensing head any more, the protection shell frame protects the outside of the infrared vision sensing head, and meanwhile, the vertical cover plate provides protection for one end part of the infrared vision sensing head. And the infrared vision sensing head is prevented from being damaged.

The invention discloses an unmanned ship autonomous berthing navigation system and method based on infrared vision tight coupling. The system comprises an infrared visual perception module, a visual processing module and a multi-sensor fusion pose estimation module, an active infrared light source array is installed at a berth, and an improved deep learning target detection network is adopted at an unmanned ship end to carry out light source array detection; secondly, information fusion of heterogeneous and asynchronous multiple sensors is realized in a sliding window through a constructed tight coupling integrated navigation system based on factor graph optimization; according to the method, infrared light source array detection can be carried out, robust visual feature extraction and fusion of heterogeneous and asynchronous multi-sensor information under complex illumination changes are ensured, distance and attitude estimation of the unmanned ship relative to a berth light source array is realized, vulnerability of a single sensor is overcome, and the method is suitable for large-scale popularization and application. Accurate self state and relative berth attitude information are provided for autonomous berthing of the unmanned ship, and long-term navigation consistency is improved.

The present invention relates to a vehicle glazing (1) comprising: - a glazed element (10) having an outer face (11) and an inner face (12), - at least one plate (80) having a body (85), said plate (80) having a housing (83) for the reversible attachment of an infrared vision system (7) with a field of vision to an inner face (82) of the plate (80), - an infrared vision system (7) with a field of vision comprising a light source, - an optical device (9) located between said light source (71) and said outer face (11) of the glazed element (10), said optical device (9) being located at a distance between said light source and said inner face (12) of the glazed element (10). (Fig. 2)

This invention discloses a laser debonding device and method. The device includes: a laser emitter; a beam splitter that splits the received initial laser into a first laser directed towards a focal spot analyzer and a second laser directed towards a sacrificial layer of the bonded member, wherein the distance from the beam splitter to the focal spot analyzer and the sacrificial layer is the same; an infrared vision component that acquires an infrared spot image of the second laser on the sacrificial layer; and a controller configured to: acquire the spot size of the first laser via the focal spot analyzer, wherein the spot size of the first laser is equal to the spot size of the second laser; initially adjust the working distance from the laser emitter to the sacrificial layer to achieve an optimal spot size for the second laser; finely adjust the working distance from the laser emitter to the sacrificial layer by acquiring the infrared spot image of the second laser via the infrared vision component; and, in response to the laser emitter being adjusted to the optimal working distance, perform laser scanning debonding on the sacrificial layer. This invention can quickly and accurately find the optimal working distance of the laser emitter.

The invention discloses a pipe network leakage detection system based on an infrared visual image. The system comprises a distributed sensor network, a dynamic trigger module, an image positioning robot, a three-dimensional reconstruction module, a multi-mode leakage identification module and a health map generation module. According to the pipe network leakage detection system based on the infrared visual image, the multi-mode sensor network and the infrared double-spectrum image processing technology are fused, high-precision and automatic detection of pipe network leakage is achieved, a dynamic triggering mechanism is combined with temperature and pressure abnormity judgment, a three-dimensional reconstruction engine and an image positioning robot work cooperatively, and the detection precision of the pipe network leakage is improved. The leakage space positioning precision is enhanced, the multi-mode identification module and the health map generation mechanism further support the intuitive visualization and trend analysis of the pipe network state, and the whole system has the effects of high sensitivity, low false alarm rate and high expansibility, and is especially suitable for underground pipe network intelligent monitoring scenes in a complex environment.

The invention relates to a glazing (1) for a motor vehicle comprising: - a glazed element (10) having an outer face (11) and an inner face (12); - at least one plate (80) having a body (85), the plate (80) having a housing (83) for the reversible attachment of an infrared vision system (7) having a field of view to an inner face (82) of the plate (80); - an infrared vision system (7) having a field of view and comprising a light source; - and an optical device (9) located between the light source (71) and the outer face (11) of the glazed element (10), the optical device (9) being located at a distance between the light source and the inner face (12) of the glazed element (10).

The invention discloses a PTV flow field measurement system and method based on a high-energy laser array and infrared vision, and the system comprises an infrared camera shooting and image collection system, a laser array system and a control system, and the infrared camera shooting and image collection system is connected with the control system. The laser array system comprises a laser array device, a first unmanned aerial vehicle carrier and a flow field measurement area; the first unmanned aerial vehicle carrier carries a laser array device, and the laser array device is used for heating the surface layer of a water body to be measured in a flow field measurement area; the infrared camera shooting and image acquisition system comprises an infrared camera and a second unmanned aerial vehicle carrier, the second unmanned aerial vehicle carrier carries the infrared camera, and real-time images of the surface flow field are obtained through the infrared camera. According to the invention, a surface water body heated by high-energy laser is used as a passive tracer, so that the manufacturing, scattering and recycling processes of traditional entity tracer particles are completely omitted, and the problem of unbalanced distribution caused by uneven density of the entity particles and material waste and water body pollution caused by incomplete recycling are avoided.

The application discloses a gesture control method and system based on UWB radar and multi-modal deep learning, and the method comprises the following steps: synchronously collecting UWB radar signals, infrared video streams and IMU signals of gestures through a UWB radar, an infrared camera and an inertial measurement unit, and performing timestamp alignment and labeling on the collected signals to construct a three-modal vehicle-mounted gesture dataset; performing pretreatment and feature extraction to obtain a UWB radar comprehensive feature set, an infrared vision comprehensive feature set and an IMU comprehensive feature set; inputting the feature set into a feature fusion and gesture recognition model based on cross-modal attention, obtaining a gesture category probability distribution through multi-modal joint feature representation, and converting the gesture category probability distribution into a function instruction based on a gesture-instruction mapping table; and training the model by using an adaptive reweighting and adversarial training strategy. The application solves the problems of low recognition accuracy and poor robustness of the prior art in a vehicle-mounted complex environment, and significantly improves the naturalness, safety and intelligent level of gesture interaction.

The application relates to a smoke identification and classification early warning method, which comprises the following steps: carrying an infrared camera, an infrared spectrum sensor and a temperature and humidity sensor on a UAV to carry out smoke inspection activities on a set target area; collecting infrared visual images, infrared spectrum data and environmental parameters of the target area by using the UAV, and pre-processing the collected data; the infrared spectrum data comprises the concentrations of CO2 and CO, and the environmental parameters comprise temperature, humidity and wind speed; performing multi-modal data fusion on the pre-processed data to construct a fusion feature vector, and identifying a smoke type according to the fusion feature vector by using a trained deep learning classification model; determining an early warning level according to the identified smoke type, and dynamically realizing early warning triggering based on the early warning level and a set classification response rule. The application can accurately distinguish and make early warning decisions on smoke in a complex environment of urban comprehensive management.

The invention discloses a control system of a multi-sensor integrated intelligent detection robot, and provides a multi-sensor intelligent detection scheme integrating acoustics, infrared, vision, noise and laser radar aiming at the problems of low efficiency, high risk and more detection omission of traditional manual inspection. The control system processes multi-source information through a data fusion algorithm to realize accurate identification of equipment defects; an autonomous navigation and dynamic path planning algorithm is adopted, so that the robot can autonomously avoid obstacles and efficiently move in a complex environment; and a dynamic obstacle avoidance mechanism based on a virtual repulsive force field is introduced to realize real-time safe obstacle avoidance. The system supports remote monitoring and manual intervention, has modular expansion capability, is widely applicable to automatic detection and health management of industrial equipment such as pressure pipelines and pressure containers, and remarkably improves the safety, accuracy and intelligent level of detection.

The application provides a chip bonding device and method. The chip bonding device comprises: a bonding head for adsorbing a chip to be bonded and adjusting the pose of the chip; an infrared vision system for penetrating the chip to collect images of a first mark on the back of the chip and a second mark of a target bonding position of the chip; and a controller configured to: acquire images with the first mark and the second mark via the infrared vision system; analyze the images to determine the poses of the first mark and the second mark in the images; adjust the pose of the bonding head according to the pose difference of the first mark and the second mark in the images to align the chip with the target bonding position; and bond the chip to the target bonding position via the bonding head. The application can avoid additional errors caused by using a calibration sheet as an intermediate medium in the bonding process, improve bonding accuracy, simplify the bonding process, thereby improving bonding efficiency and improving equipment productivity.

The present application relates to the technical field of blast furnace front equipment state monitoring, and discloses a blast furnace residual iron eye intelligent monitoring method based on infrared vision and temperature measurement fusion, comprising the following steps: synchronously receiving an infrared image sequence and blast furnace operation condition data, calculating an image quality score and determining effectiveness; when determined as effective, fusing a health reference temperature field paradigm and historical effective infrared image data to generate a dynamic baseline temperature field model, and separating a thermal anomaly object from a temperature residual matrix of the current frame infrared image and the dynamic baseline temperature field model; extracting an instantaneous multi-dimensional feature vector of the thermal anomaly object, and performing continuous frame correlation matching to construct a life cycle trajectory; calculating individual evolution characteristics and group collaborative evolution characteristics based on the life cycle trajectory; dynamically calculating a weight based on the blast furnace operation condition data and weighted fusion to obtain a comprehensive risk score, and outputting an equipment health state grade. The present application can improve the accuracy of residual iron eye area abnormal temperature rise identification and state evaluation.

The present application relates to the technical field of robot control, in particular to a visual servo docking method, device, equipment and medium. The infrared visual marker of the present application is not affected by external environmental light, so that even if the external environmental light changes, high-quality images can still be collected, so that the position of the leader robot can be accurately located based on the high-quality images. Moreover, the present application considers disturbance data when calculating the control information required to be applied to the follower robot, so that the follower robot can overcome external interference under the action of the control information, thereby enabling the follower robot to accurately complete docking with the leader robot.

The application discloses a table tennis automatic penalty electronic net system based on vibration and infrared fusion, comprising: a data acquisition device for acquiring occlusion contour area data and occlusion duration data collected by an infrared array; a feature processing device for performing connected domain analysis on the occlusion contour area data to obtain occlusion volume features; and a matching comparison device for comparing the occlusion volume features in the fusion feature set with a preset volume threshold to obtain a volume comparison result. The technical scheme of the patent innovatively fuses the occlusion volume features of infrared vision and the wideband vibration time-frequency features of piezoelectric sensing, completely solves the industry pain point that a complex near-table confrontation is easy to misjudge a player's hidden violation (such as slightly touching the net with clothes) as a legal ball wiping net in terms of physical nature, and ensures the absolute fairness of the event judgment.