328 results about "Machine vision system" patented technology

The invention discloses an aluminum alloy surface defect detection method and system using deep learning, and relates to the related field of detection performed in combination with deep learning, and the method comprises the following steps: carrying out image acquisition on an aluminum alloy finished product, constructing a surface image data set to extract multi-scale surface features, and constructing a feature enhanced image set to carry out defect detection, and a defect detection result is obtained to dynamically optimize aluminum alloy production process parameters, and a process adjustment instruction is generated and fed back to a production system. The technical problems that traditional detection mostly depends on manual visual inspection or a machine vision system based on rules, imaging distortion, small defect missing detection and process adjustment are caused are solved, and the technical effects that deep learning is conducted through the double-branch network, the defect detection efficiency and the production yield are improved, and control over the aluminum alloy manufacturing quality is met are achieved.

The invention discloses an AOI optical scheme automatic optimization method based on reinforcement learning, and belongs to the technical field of automatic optical detection. According to the method, a reinforcement learning technology is applied to automatic adjustment of optical schemes in a machine vision system, wafer images under different optical schemes are collected by using an AOI system, and scoring is performed by using a plurality of semantic segmentation models; constructing and training a non-reference image quality evaluation network, evaluating the optical imaging quality in real time, and designing a reward function on the basis; by using the Actor-Critic algorithm, the intelligent agent can autonomously learn an optimal parameter adjustment strategy, quickly adapt to different scenes, realize dynamic optimization of light source parameters and remarkably improve image quality, and an efficient and intelligent solution is provided for efficient application of a machine vision system in a complex industrial environment.

The invention relates to the technical field of spraying process control, and discloses a spraying process self-adaptive adjustment method based on temperature measurement. The method comprises the steps that target coating parameters and base material physical property data are obtained, and initial spraying control parameters are generated through a first intelligent calculation model in combination with historical process data and real-time environment monitoring data; when spraying is executed, heat distribution data of a spraying area are collected in real time through a temperature sensing device, and according to the difference between the heat distribution data and a preset target temperature interval, technological parameters are dynamically corrected through a first self-adaptive regulation and control algorithm; meanwhile, a machine vision system is used for capturing actual coating morphological characteristics, and after the actual coating morphological characteristics are compared with target parameters, excitation parameters are adjusted in a partitioned mode through a second self-adaptive regulation and control algorithm so as to optimize uniformity; and collecting whole-process data, comprehensively evaluating the whole-process data through the second intelligent calculation model to generate a process optimization instruction, and updating the first intelligent calculation model and the first self-adaptive regulation and control algorithm parameters according to the process optimization instruction.

A system including: a robotic frame including at least an actuated arm, a machine-vision system including at least a camera, the machine-vision system communicatively connected to a computing device, the computing device including at least a processor and a memory communicatively connected to the at least a processor, the memory storing instructions configuring the at least a processor to: receive image data from the at least a camera, the image data including at least two captured viewpoints of a produce item, extract at least an object-level visual feature from the image data using a machine vision model, assign a defect classification label to the produce item as a function of the at least an object-level visual feature, and control the at least an actuated arm to perform a handling operation on the produce item as a function of the defect classification label.

A kaleidoscopic laser beam projector (KLBP) system that employs a single moving structure to project patterns of sweeping laser beams with diverse sweep directions and emission apertures. The system comprises a collimated light source, a spinning mirror deflector (“spindle / flutter mirror”) at the center, and a stationary kaleidoscopic mirror containing multiple facet mirrors arranged in a concave fashion around the spindle mirror. As the spindle mirror rotates, it directs laser beams in a radially whirling movement toward the facet mirrors, which then subdivide these beams into multiple short strokes and redirect them outward in different directions. Various embodiments include configurations with diffractive optical elements (DOEs) for beam splitting, different kaleidoscopic mirror geometries (hexagonal, octagonal, etc.), and innovative flutter mirror mechanisms that create controlled angular variations during rotation. The system enables a “4×1” configuration that replaces traditional “4×4” systems requiring eight motors and multiple moving structures. The KLBP system offers significant advantages including mechanical simplicity, reduced size and weight, improved energy efficiency, enhanced reliability, cost-effectiveness, and modular configurability. The diverse beam incidence angles enable superior illumination of complex three-dimensional objects for applications in machine vision systems, precision metrology, gap and flushness inspection, and robot-assisted assembly of complex structures.

The invention discloses a building solid waste road performance index and multi-path utilization scene intelligent evaluation method. The method comprises the steps that the mass content of red bricks, the mass content of needle-sheet-shaped particles and the particle gradation in building solid waste particles are obtained through a machine vision system; the pavement performance indexes, namely CBR value, water absorption rate and crushing value, of the building solid waste are obtained through tests; according to the influence rules of the mass content of the red bricks, the mass content of the needle-sheet-shaped particles and the grain composition in the building solid waste particles on the building solid waste road performance indexes, an estimation model of the building solid waste road performance indexes is established. According to the method, the mass content of the red bricks, the mass content of the needle-sheet-shaped particles and the grain composition in the building solid waste particles are obtained in real time on the basis of machine vision, the road performance indexes of the building solid waste are predicted through the prediction model of the road performance indexes of the building solid waste, and the detection efficiency and accuracy are improved.

The invention discloses a double-arm citrus picking robot and a picking method, and belongs to the technical field of agricultural automation equipment. The robot comprises a crawler-type moving chassis, a symmetrically-arranged double-mechanical-arm system, a machine vision system, a citrus collecting bin and a control system. The double-mechanical-arm system adopts a main and auxiliary collaborative framework, the tail end of a main mechanical arm is integrated with a clamping jaw and vacuum suction disc parallel mechanism, an auxiliary mechanical arm is provided with a rotary circular saw blade, and lossless clamping of fruits and precise cutting of fruit stems are achieved. The machine vision system realizes high-precision citrus identification under complex illumination by improving a YOLOv5 network and fusing an HSV dynamic threshold value and Focal Loss optimization; graded path planning is combined with an A * algorithm and an RRT * algorithm, and motion safety of the mechanical arm is ensured through bounding box collision detection. The picking method comprises the steps of three-dimensional semantic map construction, collaborative grabbing and cutting, lossless transfer and the like. The problems that a single-arm robot is low in efficiency, fruits are prone to being damaged, fruit stems are not thoroughly treated and the like are solved, and the robot is suitable for automatic orchard harvesting in hilly areas.

The present invention relates to an integrated vision acquisition module for tunnel apparent defects, mainly used for solving the problems in existing detection devices of low integration level, complex debugging, low acquisition accuracy, poor environmental adaptability and the like. The vision acquisition module consists of a mounting back plate, a housing, a machine vision system, an integrated control system, a heat dissipation mechanism, a protective mechanism, and a wire arrangement mechanism. The machine vision system is encapsulated inside the mounting back plate and the housing, the heat dissipation mechanism is mounted on the back of the mounting back plate, the protective mechanism functions among the mechanisms of the vision acquisition module, and the integrated control system and the wire arrangement mechanism are mounted in the center of the front of the mounting back plate. The vision acquisition module uses a modular design, can implement accurate digital imaging of tunnel full-sections, has an overall protection grade of IP65 and good heat dissipation performance while maintaining a high degree of modularity, is adapted to different tunnel profile sections, and can complete rapid and non-contact detection of apparent defects in tunnel lining such as cracks, water leakage, and exfoliation and defects in ancillary facilities such as signal mechanisms, optical cables, and communication cables.

The invention discloses an appearance, flavor and taste coupled edible mushroom grading and sorting device and method. The device comprises a hardware part and a software part. Hardware comprises an airflow setting device, a conveying belt, an industrial camera, a light source, a pneumatic electromagnetic valve, an industrial personal computer and other main components. And software functions: while controlling the conveyor belt to rotate, acquiring images of the dried edible mushrooms by using the industrial camera, processing the images, obtaining the appearance quality of the edible mushrooms in real time, obtaining the content of main flavor components and the rehydration ratio of the edible mushrooms according to the appearance quality by using a built-in database, and outputting the grade of the dried edible mushrooms. And the corresponding electromagnetic valves of the corresponding grades are controlled to act, and the dried edible mushrooms are blown into the frames of the corresponding grades. According to the device, the machine vision system and the air-blowing type executing mechanism are used for grading the dried edible mushrooms, the appearance, the smell and the taste are combined, a multi-index fusion grading method is formed, and the grading accuracy and consistency are improved.

The invention relates to a flexible material cutting robot with a leveling function and a cutting method thereof, and belongs to the technical field of flexible material cutting, the flexible material cutting robot comprises a master control layer, a sensing layer, an execution layer and an interaction layer, the master control layer adopts a central control module, the sensing layer adopts a data acquisition unit, the execution layer is a hardware action unit, and the interaction layer adopts a man-machine interface. The central control module is provided with a digital twin engine and a multi-physics field collaborative optimization algorithm library, the data acquisition unit comprises a machine vision system and a material characteristic self-identification unit, and the hardware action unit comprises a multi-stage tension collaborative leveling module, a vacuum adsorption type dynamic cutting platform and a multi-axis linkage cutting head group. According to the invention, through closed-loop control of material characteristic sensing, dynamic leveling, self-adaptive adsorption and energy matching cutting, zero-deformation precise cutting of high-end flexible materials is realized, and the system is particularly suitable for high-value material processing in the fields of aerospace, medical equipment and the like.

Systems and methods are disclosed herein for identifying cable damage using machine vision, such as on a cable being fed down a wellbore from a cable spool in an oil and gas operation. An example method can include providing a camera directed toward a cable that is winding upon, or unwinding from. a cable spool. The method can also include capturing a plurality of frames of images of the cable by the camera. such as by capturing video. The captured frames can be cropped to remove portions of the frames that do not include the cable. The method can further include processing the cropped frames using a machine-learning model. The machine-learning model can be trained using images of known cable damage as inputs so it can identify new instances of damage. The machine-learning model can further classify each cropped frame as including damage or not including damage.

The present disclosure provides a system, apparatus and method for controlling welding based on artificial intelligence. The artificial intelligence-based welding control system according to an embodiment of the present disclosure may include a machine vision system configured to photograph at least a portion of a welding object through a camera, and transmit the photographed image (hereinafter, “photography image”) to a relay system; the relay system configured to receive the photography image from the machine vision system, recognize a welding position of the welding object from the received photography image based on a pre-trained first artificial intelligence model, determine whether the recognized welding position is included in a designated position range, and when the recognized welding position is included in the designated position range, transmit the recognized welding position to a welding system; and the welding system configured to receive the welding position from the relay system, and perform welding at the received welding position.

Various example embodiments are presented herein for supporting object detection in a machine vision system. Various example embodiments directed to supporting object detection in a machine vision system may be configured to support range extension for object detection in a machine vision system. Various example embodiments directed to supporting object detection in a machine vision system may be configured to support flexible and efficient range extension for object detection in a machine vision system. Various example embodiments for flexible and efficient range extension for supporting object detection in a machine vision system may be configured to support flexible and efficient range extension for object detection in a machine vision system based on use of image slices.

Various example embodiments for supporting object detection in machine vision systems are presented herein. Various example embodiments for supporting object detection in machine vision systems may be configured to support range extension for object detection in machine vision systems. Various example embodiments for supporting object detection in machine vision systems may be configured to support elastic and efficient range extension for object detection in machine vision systems. Various example embodiments for supporting elastic and efficient range extension for object detection in machine vision systems may be configured to supporting elastic and efficient range extension for object detection in machine vision systems based on use of image slicing.

The invention provides automatic particle image velocity measurement equipment and a control method. The automatic particle image velocity measurement equipment comprises a three-axis lead screw open T-shaped sliding table, a four-axis lead screw closed gantry sliding table, a machine vision system, a PIV system, a controller and an automatic equipment control system, the machine vision system collects an image of the experimental model, the controller compares the image of the experimental model with a database, when the matching rate is larger than or equal to a preset percentage, feature matching is completed, a measurement result and a decision instruction are generated, and the automatic equipment control system controls the sliding table to move according to a given motion path. And meanwhile, the high-speed camera is controlled to trigger double-frame exposure according to given exposure parameters, and real-time cross-correlation analysis is carried out to obtain velocity field data, so that automatic PIV measurement is realized. According to the method, the problems of long time consumption, low efficiency and high operation repeatability caused by frequent manual calibration of PIV equipment in the experiment process are solved, a large amount of manpower and time cost is saved, and the research speed is increased.

The invention provides a belt type dried beancurd stick microwave drying device and method based on the expansion degree, the drying device is mainly divided into four heating areas, each heating area only depends on microwave heating, each heating area is provided with a moisture exhaust fan and a fresh air valve, and the drying device is provided with a machine vision system used for controlling equipment operation. Whether the dried beancurd sticks exist in the corresponding area of each magnetron group is judged through the machine vision system, the on-off of the magnetrons is automatically controlled, and the no-load phenomenon of the magnetrons is avoided. On the premise of ensuring safe production, the working number of magnetrons in different areas, starting and stopping of a moisture removal fan and opening and closing of a fresh air valve are controlled through the expansion degrees of the different areas of the dried beancurd sticks in combination with appearance colors, so that the local charring phenomenon caused by over-high microwave drying power, untimely evaporation of moisture on the surfaces of the dried beancurd sticks or over-high temperature is avoided; the expansion degree consistency of different batches of dried beancurd sticks is ensured, and the automation degree of equipment is improved.

The invention discloses a fresh pepper sorting device based on machine vision. The fresh pepper sorting device is characterized by comprising a vibration feeding system, a conveying system, a machine vision recognition system and a sorting system. Vibration feeding movement of the vibration feeding system is achieved through an electromagnet, recognition of the machine vision system is achieved through a CCD industrial camera, and conveying movement of the conveying system is achieved through a motor. The invention is applied to the technical field of sorting machines. The automatic sorting device is designed for solving the problems that a traditional manual sorting mode is high in labor intensity, severe in working environment, low in sorting efficiency and poor in sorting quality. The whole device has the advantages of full-automatic intelligent equipment, rapid, efficient and accurate sorting of the fresh chilies and intelligent and integrated sorting work are achieved, the production efficiency is improved, the sorting period of the fresh chilies is shortened, and the fresh chilies sorting device can be widely applied to the related fields of the sorting industry and is efficient.

The invention discloses a double-layer composite quartz crucible surface defect detection method based on machine vision, and relates to the technical field of crucible surface defect detection, and the method comprises the following steps: a conveyor belt conveys double-layer composite quartz crucibles to a detection area at a preset speed to ensure that each crucible can move in sequence on a production line; and a detection visual field of a machine vision system is stably entered. According to the method, key features such as the microstructure change index and the crack interval variability index are extracted, so that a machine vision system can identify complex defects more accurately, and misjudgment and missing detection are avoided. According to the method, the detection precision of complex defects is improved by enhancing image processing. And in combination with a machine learning model, the system intelligently evaluates the defect complexity and dynamically adjusts the conveyor belt speed. For simple defects, the high speed is kept, so that the production rhythm is not influenced; for complex defects, the speed of the conveyor belt is reduced, and time is provided for detailed analysis, so that the defect recognition rate is improved, and the product quality is ensured while efficient production is ensured.

At least some embodiments described herein are directed to a machine vision method, which involves capturing both a two-dimensional (2D) image of an object to identify a barcode and determine 3D features, and a three-dimensional (3D) image of the environment. The 3D image data is examined for the presence of the 3D object features. If a feature is missing, a digital fault detection signal is provided. If a feature is present, at least one parameter of the machine vision system is adjusted. The method also includes decoding the barcode and determining the object's orientation based on the barcode location in the 2D image.

A ton bag opening deviation rectifying device belongs to the field of packaging machinery and comprises a machine frame, a machine vision system is arranged above the front portion of the machine frame, a longitudinal translation mechanism is arranged on the machine frame, a transverse translation mechanism is arranged on a transferring frame of the longitudinal translation mechanism, a swing mechanism is arranged on a transverse moving frame of the transverse translation mechanism, and a rotating frame is arranged on the swing mechanism. A supporting plate for supporting ton bags is arranged at the upper end of the rotating frame, the rotating mechanism drives the rotating frame and the supporting plate to rotate in the horizontal plane, the machine vision system recognizes and positions bag opening positioning color blocks on the ton bags below so as to determine the position deviation of the bag openings of the ton bags, and the machine vision system controls actions of the longitudinal translation mechanism, the transverse translation mechanism and the rotating mechanism. And the bag opening of the ton bag A with the position deviation is adjusted to the target position. According to the ton bag opening deviation rectifying device, the positions of bag openings of ton bags can be accurately rectified before the bags are opened, so that the bag opening conditions are met, the bag opening rate of the whole stack of ton bags is greatly improved, and the packaging efficiency of equipment is improved.

The utility model relates to the technical field of scribing machine vision system lighting assemblies, and discloses a scribing machine annular light cleaning device which comprises an annular light source arranged in an inner cavity of a light source shell, a lens blowing plate is detachably installed on the upper portion of the light source shell, and an air connecting pipe connector is communicated with the lens blowing plate. An air flow guide channel is arranged between the lens air outlet plate and the light source shell, positive pressure air fed by the air connecting pipe connector is blown out from a center hole in the middle of the light source shell along the air flow guide channel, and an air exhaust effect from top to bottom is formed between the light source shell and a center hole of the lens air blowing plate. According to the utility model, the adsorption effect from top to bottom is formed by utilizing the power of airflow, so that the air blowing cleaning of pollutants on the surface of a workpiece on the working disc and the air suction cleaning of pollutants in an internal channel of a light source are effectively realized.

The invention discloses a target detection method and device based on visual identification. The method comprises the following steps: acquiring relative coordinates between an image acquisition part and a detection surface of a detection object; when the relative coordinate is not consistent with the reference coordinate, determining a first coordinate difference value; when the relative coordinate is not within the coordinate error range, adjusting the image acquisition component until the relative coordinate is consistent with the reference coordinate; when the relative coordinates are consistent with the reference coordinates, controlling an image acquisition component to perform image acquisition on the detection object to obtain a plurality of images; determining second relative coordinate differences between the plurality of images and the reference image, and selecting a target image; and performing target detection according to the target image. The technical problem that in the prior art, a machine vision system adopts depth-of-field limitation of a fixed camera, so that all targets cannot be ensured to be within the depth-of-field range of the camera when the heights of different models of recognized targets are changed, and recognition cannot be possibly caused is solved.

A method for three-dimensional (3D) field calibration of a machine vision system includes receiving a set of calibration parameters and an identification of one or more machine vision system imaging devices, determining a camera acquisition parameter for calibration based on the set of calibration parameters, validating the set of calibration parameters and the camera acquisition parameter, and controlling the imaging device(s) to collect image data of a calibration target. The image data may be collected using the determined camera acquisition parameter. The method further includes generating a set of calibration data for the imaging device(s) using the collected image data for the imaging device(s). The set of calibration data can include a maximum error. The method further includes generating a report including the set of calibration data for the imaging device(s) and an indication of whether the maximum error for the imaging device(s) is within an acceptable tolerance and displaying the report on a display.

The invention discloses a device and a method for compaction response determination and flow monitoring in vacuum infusion, and belongs to the technical field of composite material manufacturing. The device comprises a vacuum laying layer, a material injection barrel and a resin trap, the device comprises a support, a thickness measuring unit, a pressure measuring unit, a temperature measuring unit, a quality measuring unit, a machine vision system, a pressure control unit and a data acquisition control unit. The method comprises the steps of S1, a layer laying stage; s2, a degassing stage; and S3, a glue injection stage. S4, a post glue injection stage; and S5, a data processing stage. According to the invention, compaction response measurement and resin flow monitoring are integrated in one device, so that synchronous monitoring and correlation analysis of two key attributes of a material are realized; the thickness measurement precision reaches 0.001 mm, the pressure measurement precision reaches 0.1 kPa, the machine vision measurement precision reaches 0.01 mm, and the high-precision requirement is met; the flow conditions of the upper surface and the lower surface of the material can be monitored at the same time, and comprehensive understanding of three-dimensional flow behaviors is provided; the flow front detection algorithm is simple, efficient and high in automation degree.

A Kaleidoscopic Geometric Vision Platform (KGVP) that transforms three-dimensional (3D) machine vision through an optical system that creates multiple virtual laser projectors from a single moving component. A spindle mirror mechanism (SMM) rotates a reflective surface to sweep collimated laser beams in circular patterns. These beams strike a series of kaleidoscopic mirror facets (KMFs) arranged concentrically around the SMM in a concave configuration. Each KMF redirects the rotating beam, creating a virtual projector with a distinct origin point and sweep direction. As the SMM completes one rotation, it generates N distinct laser trajectories (where N equals the number of KMFs), each sweeping from a different virtual origin point. Event-based cameras / sensors positioned strategically around the KMFs detect laser light reflected from object surfaces with microsecond precision. The KGVP triangulates 3D surface coordinates by determining correspondence between detected light and specific virtual projectors based on precise timing information. This approach eliminates the computational complexity typically required for multi-view feature matching, as the KGVP can unambiguously identify which virtual projector created each detected event. With calibration, the KGVP can establish the exact 3D positions of all virtual projector origins and their beam trajectories and build look-up tables that optimize triangulation accuracy. The KGVP enables real-time 3D surface reconstruction with high precision while using far fewer mechanical components than conventional machine vision systems.

The invention relates to the technical field of brake component detection, and discloses a brake spring piece flatness intelligent detection system and method based on machine vision. The method comprises the steps of obtaining historical brake spring piece image data, and generating a standard flatness curve according to the historical brake spring piece image data; real-time brake spring piece image data are collected through a machine vision system, and a real-time flatness curve is generated; calculating a flatness deviation curve according to the real-time and standard flatness curve; analyzing the matching degree of the deviation curve and a reference defect model, and determining the flatness state of the brake spring piece; and finally, dynamically adjusting detection parameters based on the flatness state, and generating an optimized detection scheme. According to the method, non-contact detection is realized by taking historical data as a reference and depending on machine vision, flatness deviation can be accurately presented, defect properties corresponding to the deviation can be determined, a detection scheme can be dynamically optimized, detection consistency, efficiency and adaptability are improved, manual dependence and part abrasion are reduced, and the method is suitable for batch detection scenes of the brake spring pieces.

The invention discloses a metal polishing surface quality real-time monitoring system and method based on machine vision, and relates to the technical field of surface detection, and the method comprises the following steps: carrying out grid processing on a metal workpiece surface image collected by a machine vision system, dividing the whole image into a plurality of sub-regions with the same size according to a preset grid rule, and a local area basis is provided for subsequent feature extraction and polishing state analysis. According to the method, the overall polished surface is split into a plurality of local sub-regions through image gridding processing, so that finer optical feature extraction and polishing state recognition are realized, and normal and over-polished regions are accurately distinguished. Exposure parameters are dynamically adjusted according to different area states, local overexposure is inhibited, texture details are recovered, and the defect signal contrast is improved. Finally, according to the scheme, the defect of global exposure control is effectively overcome, high-precision and high-stability real-time monitoring of metal polishing surface defects is achieved, and the consistency and reliability of surface quality detection are improved.

Methods and systems are provided for commissioning machine vision systems. The methods and systems described herein may automatically configure, or otherwise assist users in configuring, a machine vision system based on a specification package.

The invention relates to the technical field of commercial vehicles, in particular to a vehicle shock absorber damping force dynamic adjustment method based on road feature recognition, and introduces a machine vision technology to detect road features in the vehicle driving direction. Through the machine vision system, the vehicle can identify the unevenness features of the road in advance, including the feature types and the spatial positions thereof, and feed back the information to the control system in real time. And the control system adjusts the damping force of the shock absorber in advance according to the previewed road characteristics. Specifically, training and optimization are carried out based on an improved YOLOV8 model, road feature classification information and detection frame position information from the trained model are received in real time through a semi-active controller, and a preset control algorithm is executed according to information returned by the model to adjust the damping force of the shock absorber in advance. According to the method, preview control is carried out in the semi-active suspension by recognizing road excitation, and the problem that the vibration reduction effect of the semi-active suspension is not ideal due to response time lag of the vibration damper is solved.

The invention relates to the field of material thermal expansion testing, and provides a thermal expansion measuring device and method for gradient materials, and the device comprises an array probe module, a machine vision system, a temperature control system, a driving mechanism, a control module and a housing. The probe array module comprises probes arranged at equal intervals, and the bottom ends of the probes are in direct contact with the surface of a sample; the driving mechanism drives the probe array to scan along a sample component gradient direction; the machine vision system is used for collecting a probe top end image and combining an image processing algorithm to achieve full-area analysis of gradient components. Compared with existing equipment, the thermal expansion behavior of samples such as component gradient materials and composite materials can be represented, the thermal expansion behavior characterization device is particularly suitable for thermal expansion behavior characterization of key components such as aerospace gradient coatings and nuclear reactor cladding materials, and a reliable testing means is provided for design optimization of functionally gradient materials.