3761 results about "Light reflection" patented technology

The invention discloses a PCB three-proofing coating quality detection method and system. The method comprises the steps that a visible light reflection image of the surface of a PCB and scattering spectrum data of a near-infrared band are acquired; performing spatial filtering processing on the visible light reflection image to extract interface area pixels, calculating coating layer thickness gradient distribution based on Mie scattering characteristics in scattering spectrum data, and fusing to generate an edge gradient distribution map; and according to the gradient amplitude change rate in the edge gradient distribution map, segmenting the effective coverage area of the coating layer by adopting a self-adaptive dynamic threshold algorithm, and extracting curvature extreme point density and boundary fractal dimension parameters at the segmentation boundary. According to the invention, three technical barriers of difficult microdefect capture, unmeasurable interface performance and delayed failure risk in traditional detection are solved, and two-dimensional accurate diagnosis of the structural compactness and interface reliability of the coating layer is realized.

The invention discloses a weldment welding seam automatic detection method and device based on machine vision, and relates to the technical field of machine vision intelligent detection. The weldment welding seam automatic detection method and device based on machine vision comprises the steps that S1, surface images and forming feature data of a weldment are collected and preprocessed to construct a standardized image feature data set; s2, the boundary clearness of the weld joint is evaluated by combining the edge strength and the contour coherence, and the main contour extraction range is dynamically adjusted; s3, analyzing abnormal focusing characteristics of the candidate area, and adjusting a defect labeling range and a detection priority; and S4, integrating the boundary definition and the abnormal focusing features, analyzing the structure abnormality, and dynamically controlling and verifying a resource allocation strategy. The problems that in the weldment detection process, obvious light reflection and texture blurring phenomena exist in a heat affected area at a weld joint, a traditional image enhancement and edge extraction algorithm is difficult to stably recognize microdefects, and the credibility of a detection result is reduced are solved.

A medical device operating as a stylet is described. The medical device can include an insulating layer (or sheath) encapsulating both a multi-core optical fiber and a conductive medium. The optical fiber can include a cladding and a plurality of core fibers spatially arranged within the cladding. Each of the core fibers can include a plurality of sensors distributed along a longitudinal length of that corresponding core fiber and each of these sensors can be configured to: (i) reflect a light signal of a different spectral width based on received incident light, and (ii) change a characteristic of the reflected light signal for use in determining a physical state of the multi-core optical fiber. The conductive medium can provide a pathway for electrical signals detected at a distal portion of the conductive medium. The conductive medium may be concentric to the cladding, but separate and adjust thereto.

A system, apparatus and method directed to detecting damage to an optical fiber of a medical device. The optical fiber includes one or more core fibers each including a plurality of sensors configured to (i) reflect a light signal based on received incident light, and (ii) alter the reflected light signal for use in determining a physical state of the multi-core optical fiber. The system also includes a console having non-transitory computer-readable medium storing logic that, when executed, causes operations of providing a broadband incident light signal to the multi-core optical fiber, receiving reflected light signals, receiving reflected light signals of different spectral widths of the broadband incident light by one or more of the plurality of sensors, identifying at least one unexpected spectral width or a lack of an expected spectral width, and determining the damage has occurred to the optical fiber based on the identification.

The invention discloses a container number tallying identification method, and relates to the technical field of container intelligent tallying. According to the technical key points, the method comprises the following steps: deploying a multi-modal sensing device, carrying out initial calibration, and pre-training an improved YOLOv7-tiny target detection model, a transformer-based cGAN character segmentation model and a lightweight CNN-transformer-capsule network integrated hybrid recognition model; through cooperative collection of multi-modal data of the multi-modal sensing device, the system can effectively integrate texture information of RGB images, a space structure of depth images and three-dimensional coordinates of point cloud data, the problem that traditional single visual recognition is affected by illumination, shielding and the like is solved, a self-calibration mechanism corrects space-time deviation of a sensor in real time, and the accuracy of recognition is improved. The system can still accurately extract container number characteristics in complex scenes such as strong light reflection, low illumination at night, character abrasion and the like.

The invention relates to the technical field of assembly production lines, and particularly discloses an assembly production line workpiece defect detection method and system based on machine vision. The method aims at accurately detecting the workpiece defects of the assembly production line, firstly, position information of a lens, a workpiece and a light source of a machine vision device is obtained, a basis is provided for subsequent calculation, the detection accuracy is ensured, and then the incident angle of the mirror surface is determined according to the characteristic information of the lens, influences reflected light and imaging and is a key parameter. Then obtaining imaging influence factors according to workpiece characteristics, measuring interference of workpiece surface characteristics on imaging, providing a basis for optimizing reflectivity, calculating specular reflectance through light source position information, reflecting light reflection conditions, combining the specular reflectance and the reflection conditions to obtain collaborative optimization specular reflectance, more accurately evaluating the influence of reflection on imaging, and finally, determining the influence of reflection on imaging. If the reflectivity is greater than a preset threshold value, correction is carried out, a correction angle is obtained to adjust a lens detection angle, misjudgment caused by mirror reflection is reduced, and the detection precision is improved.

The invention relates to a brightness control method and system for a vehicle-mounted head-up display and the display. A dynamic adaptation model based on ambient light intensity is constructed by combining human eye visual adaptation characteristics and HUD field angle characteristics, visual adaptation behaviors of human eyes under different illumination conditions can be simulated, and the brightness of the HUD is automatically adjusted according to different light intensity changes, so that information display better conforms to the visual comfort of the human eyes. According to the invention, the maximum HUD display brightness acceptable by human eyes under different illumination conditions can be calculated, the brightness adjustment values under different illumination conditions are dynamically calculated by using the De Boer coefficient, and the brightness of the HUD display is adjusted in real time according to the external light environment, so that the brightness adaptive dynamic closed-loop adjustment is realized, the HUD is effectively prevented from being too bright under low ambient light, and the HUD display quality is improved. The visual blinding phenomenon caused by instantaneous strong light reflection or bright element emerging in a dark scene is avoided, the function safety level of the vehicle-mounted HUD system is remarkably improved, and the ISO 26262ASIL-B level safety requirement is met.

Systems, methods, and non-transitory computer-readable media containing instructions are disclosed for detecting and utilizing facial skin micro-motion. In some non-limiting embodiments, detection of facial skin micro-motion occurs using a speech detection system that may include a wearable housing, a light source (coherent light source or incoherent light source), a light detector, and at least one processor. The one or more processors may be configured to analyze light reflections received from the facial region to determine facial skin micromotion, and extract meanings from the determined facial skin micromotion. Examples of meanings that may be extracted from the determined facial skin micromotion may include words spoken by the individual (silent or voiced), an identity of the individual, an emotional state of the individual, a heart rate of the individual, a respiratory rate of the individual, or any other biometric, emotion or speech related indicator.

The invention discloses a wind power blade defect detection method based on acoustic emission, and relates to the technical field of wind power blade detection.The wind power blade defect detection method comprises the steps that multiple lasers, a multispectral camera, a thermal imaging sensor and a plurality of acoustic emission sensors are carried on an unmanned aerial vehicle, and multiple multispectral images and thermal imaging images within fixed time are obtained; a multispectral image total discrimination sequence and a thermal imaging image total discrimination sequence are obtained through processing, suspicious pixel points in the two sequences are mapped into actual three-dimensional coordinates of the wind power blade, a light reflection defect area and a thermal distribution defect area are obtained through fitting, the intersection of the two areas is obtained, and a specific area of the wind power blade defect is obtained. And positioning the region by using an acoustic emission sensor to obtain a to-be-detected acoustic signal, denoising by combining LMD with MFSE, extracting a feature vector, and substituting the feature vector into a GRU wind power blade defect judgment model to judge whether an internal fault exists or not. According to the invention, comprehensive perception and correlation judgment of internal and external defects of the wind power blade are realized.

The invention relates to the technical field of chemical production process monitoring, and provides a chemical storage tank liquid level real-time monitoring method and system based on image recognition, which can automatically generate an accurate illumination threshold value by applying big data analysis and machine learning technologies, can adapt to illumination changes of different chemical scenes, and can realize real-time monitoring of the liquid level of a chemical storage tank. The accuracy of liquid level monitoring under various illumination conditions is greatly improved; for image enhancement and correction, the system adopts a local region adaptive adjustment histogram equalization and optimization CLAHE technology and constructs a feature database assisted threshold segmentation and environmental parameter dynamic adjustment SFS model, so that dark environment images can be enhanced more excellently, strong light reflection can be removed, and reduction liquid level details can be cleared; according to the system, a dynamic weight updating mechanism is created for the first time, the weight is adjusted in real time according to the liquid level change and the image quality, interference of a single image is effectively avoided, and the monitoring reliability is remarkably improved.

A medical device system includes a stylet with an optical fiber and a console operatively coupled to the stylet. The optical fiber can include an electrically conductive concentric tube configured to transmit electrical signals and a plurality of core fibers within the concentric tube. Each of the plurality of core fibers can include a plurality of sensors, and each the plurality of sensors can be configured to reflect a light signal of a different spectral width based on received incident light and change a characteristic of the reflected light signal based on a condition experienced by the stylet. The console includes one or more processors and a non-transitory computer-readable medium with logic that causes operations including providing an incident light signal to the optical fiber and receiving reflected light signals of different spectral widths of the received incident light by the plurality of sensors.

The invention discloses a film material surface defect detection method and system based on machine vision, and relates to the technical field of machine vision. Joint modeling is carried out by utilizing a local reflectivity difference value Ploc (x, y) of a pixel coordinate (x, y), a local stacking disturbance index S (x, y) of the pixel coordinate (x, y) and a local gray variance Wvar (x, y) of the pixel coordinate (x, y) in a film material image irradiated by a dual-angle light source, and the detection sensitivity of asymmetric optical disturbance caused by trace salt mist deposition is enhanced. Compared with the current situation that a traditional visual detection method is insufficient in response to early corrosion spots, the method has the advantages that a light reflection subsurface corrosion map can be effectively formed through quantitative combination of two factors of reflection anomaly and structural disturbance in the image, and rapid positioning and early warning of the membrane material salt spray corrosion initial stage are achieved.

The invention discloses a liquid medicine foreign matter detection method and system based on machine vision, and the method comprises the steps: obtaining multiband spectral data of a liquid medicine sample, and carrying out the normalization processing to generate a liquid medicine background standard spectral feature template; comparing the refractive index spectral characteristics of the template and the foreign matter-containing liquid medicine, and recording the surface roughness scattering mode and polarized light reflection angle change data of a foreign matter area; calculating a spectrum peak displacement quantized value according to the polarized light data, and extracting foreign matter edge spectrum gradient information in combination with a threshold value; calculating a transparency spectral attenuation coefficient based on the edge gradient information, and obtaining spectral contrast enhancement factors of different foreign matters in combination with the spectral response characteristic data; and if the enhancement factor does not reach the standard, adjusting the spectrum correction parameter and recalculating, fusing the scattering mode and the multi-angle incident spectrum response result to carry out consistency verification, and obtaining a final identification result containing the foreign matter material type and the danger level. The method can improve the drug detection accuracy and guarantee the drug quality safety.

The invention relates to the technical field of image analysis, in particular to a cushion foaming forming quality detection method and system based on machine vision, and the method comprises the steps: collecting image data, carrying out the iterative screening of the image data, and selecting a detection sample; the method comprises the following steps: collecting a three-dimensional point cloud of a detection sample, calculating the flatness of a seat cushion by using the three-dimensional point cloud, carrying out modeling by using polarized light reflection to obtain surface cell uniformity, and carrying out feature extraction on the three-dimensional point cloud through a three-dimensional mapping model to generate a three-dimensional semantic model; extracting mechanical characteristics by using the time sequence pressure map, and generating a cushion digital model; variational self-coding is carried out on the cushion digital model, and an abnormal feature map is generated; performing information extraction and pixel-by-pixel multiplication on the abnormal feature map by using a learnable convolutional layer to generate an abnormal enhanced map; and inputting the abnormal enhancement graph and the seat cushion digital model into a multi-channel network model for final evaluation. According to the method, the image data is analyzed, and the performance of the cushion is subjected to index quantification, so that the deep detection of the quality of the cushion is realized.

The invention relates to the technical field of surface detection, and particularly discloses multi-angle detection equipment for a chip tray, the multi-angle detection equipment for the chip tray achieves the purpose of cleaning and detecting the surface of the tray, an equipment base and an equipment support integrally support the equipment, and a fixing device fixes the tray, so that the detection efficiency is improved, and the detection cost is reduced. The tray is vertically inserted into the top of the fixing device, the fixing device fixes and rotates the tray and cooperates with the detection device for illumination and multi-angle shooting through light reflection, the detection efficiency is improved compared with a traditional plane shooting visual detection scheme, the influence on the surface of the tray is reduced by fixing the two sides of the tray, and the detection accuracy is improved. Therefore, secondary damage caused by surface damage in the detection process is avoided, and the protection device drives the light source of the detection device to adjust the distance, so that optical detection on different areas of the surface of the tray is realized, and the overall flatness of the surface of the tray can be quickly detected.

The present invention relates to a method and apparatus for calculating and evaluating the loss of light collection efficiency of a heliostat. 【Solution means】The present invention simulates the pulsating wind load distribution of a heliostat at different elevation-azimuth angles by CFD calculation, extracts the aerodynamic admittance function and shape parameters, constructs a pulsating wind load spectrum prediction model, calculates the pulsating wind load spectrum by combining the attitude parameters of the heliostat, applies the pulsating wind load spectrum to the structural model of the heliostat mirror by finite element analysis, obtains the instantaneous dynamic response, displacement and strain distribution characteristics of the heliostat, simulates the influence of mirror deformation on the light reflection path, quantifies the instantaneous influence on the light collection efficiency of the deformed mirror, and generates a dynamic curve of the change of light collection efficiency over time.

The invention provides a high-reflection plane metal part defect detection method and system based on a composite polarized light source, and a medium. The method comprises the following steps: illuminating a high-reflection plane metal part based on the composite polarized light source, adjusting a light source polarization angle and an LED wave band combination to construct a shooting environment, and collecting an image sequence; calculating a polarization intensity distribution parameter for the image sequence based on the relationship between the polarization intensity and the Stokes parameter to obtain a polarization intensity distribution image; analyzing the polarization intensity distribution image based on a polarized light reflection model, and outputting a specular reflection component and a diffuse reflection component; fitting the specular reflection component and separating the diffuse reflection component to obtain a reflection-removed image; based on an image enhancement algorithm, edge enhancement is carried out on the reflection-removed image to obtain an enhanced image, and based on a defect identification algorithm, the enhanced image is analyzed to obtain defect information; by removing the diffuse reflection component and reconstructing the image, the mirror interference is effectively stripped, and the defect identification precision is improved.

The invention discloses a control management method and system for an LED backlight source, and relates to the technical field of backlight source control. The video decoding module is used for analyzing an input video signal and extracting an image brightness distribution entropy value and a color gamut coverage degree; the backlight partition regulation and control unit is used for dynamically adjusting a backlight partition topological structure; the prediction compensation module is used for generating a future frame brightness change trend and correcting a current backlight driving signal by using a feedforward compensation coefficient; the photoelectric sensing array is used for measuring the reflection characteristic of ambient light in real time; and the collaborative dimming controller is used for acquiring the type information of the playing equipment and loading a differential dimming strategy library. By dynamically analyzing video content characteristics, ambient light conditions and equipment information source types and adjusting a backlight partition structure and brightness output in real time, the HDR scene switching response speed is remarkably improved, the dark field gray scale identification degree is enhanced, backlight instantaneous peak power consumption is reduced, the non-linear brightness requirement of streaming media content is met at the same time, and the real-time performance of the system is improved. And better visual experience is provided for the user, and energy consumption optimization is realized.

The invention discloses a control method of a video monitoring system, which relates to the technical field of video monitoring, and comprises the following steps of: acquiring continuous image frames through the video monitoring system, extracting brightness channels, edge structures, direction gradients and contrast changes of images, constructing a reflective perception vector group, and calculating an included angle change trend by combining a target motion direction vector, determining whether a reflection offset condition consistent with the target direction appears in a picture in a camera attitude control process; after it is determined that the reflection offset condition consistent with the target direction appears in the picture, the inter-frame change tensor of the target area and the reflection area is extracted, and a time sequence track consistency matrix is constructed; according to the invention, the problem of wrong adjustment of the camera caused by misjudgment of light reflection in video monitoring is solved, attitude regulation and control based on image displacement abnormal mode recognition are realized, and the tracking stability and the monitoring accuracy are improved.

The invention discloses a photovoltaic POSS (polyhedral oligomeric silsesquioxane)-containing antireflection film coating liquid and a preparation method thereof, the coating liquid comprises the following raw materials in parts by weight: 80-100 parts of modified emulsion, 10-15 parts of modified graphene, 3-5 parts of sodium dodecyl benzene sulfonate, 1-3 parts of triethylene tetramine and 40-60 parts of deionized water, a modified additive in the coating liquid contains a polyhedral oligomeric silsesquioxane structure, the polyhedral oligomeric silsesquioxane structure can form uniformly-distributed nanopores and is matched with a two-dimensional honeycomb lattice structure in the graphene oxide, the surface roughness can be increased, the microstructure can scatter incident light and reduce specular reflection, so that the surface light transmittance is improved, and meanwhile, the modified additive molecule contains a fluoroalkyl structure, so that the surface light transmittance is improved. The fluoroalkane has a high refractive index, so that light reflection can be reduced, and the light transmittance is further improved.

The invention provides a dark image preprocessing method and device based on machine vision, equipment and a medium, and relates to the technical field of agricultural automation, and the method comprises the steps: constructing a multi-scale Retinex enhanced fusion adaptive gamma correction illumination compensation model, carrying out the processing of an original garlic seed screening image through the illumination compensation model, eliminating illumination unevenness and light reflection interference, and obtaining an original garlic seed screening image; obtaining a first garlic seed screening image; according to a texture complexity detection method based on a gray-scale guide map, designing an adaptive joint bilateral filter, and processing the first garlic seed screening image through the adaptive joint bilateral filter to obtain a second garlic seed screening image; and performing multi-resolution contrast enhancement processing on the second garlic seed screening image through a pyramid decomposition and entropy-driven partitioning strategy to obtain a preprocessed garlic seed screening image. According to the method, the defect detection accuracy and the classification efficiency can be effectively improved under the conditions of high noise and complex backgrounds, and robust visual preprocessing support is provided for subsequent automatic sorting.

The invention discloses an endoscope image processing method and system for improving image quality, and relates to the technical field of image processing.The method comprises the steps that a highlight reflection area of an endoscope image is extracted by setting a detection and extraction mechanism of the highlight reflection area; the method comprises the following steps: dividing an image of which a highlight reflection region is extracted into a base layer and a detail layer, performing global illumination adjustment on the base layer, performing detail enhancement on the detail layer, and fusing the enhanced base layer and detail layer to obtain a pre-enhanced image; if the pre-enhanced image extracts an over-high-brightness area, repairing a high-brightness reflection area and outputting the high-brightness reflection area; according to the method, global enhancement of the endoscope image is realized through highlight reflection area detection, image hierarchical processing and highlight reflection area repair, and the visibility and availability of the endoscope image are improved.

The invention discloses a multi-mode three-dimensional tactile sensing device, method and system based on light reflection and resistance, and the device comprises a hemispherical flexible layer, four silicone rubber columns, a thermistor layer, a piezoresistive film layer composed of four piezoresistive sensing units, a light reflection film layer, an optical fiber sleeve, a transmitting optical fiber, and a receiving optical fiber. The top ends of the silicone rubber columns are connected to the lower portion of the hemispherical flexible layer and evenly distributed in four quadrant areas in the hemispherical flexible layer, the thermistor layer is located below the silicone rubber columns, and all the piezoresistive sensing units of the piezoresistive film layer are arranged below the thermistor layer and correspond to the silicone rubber columns in a one-to-one mode. The light reflecting film layer is located below the piezoresistive film layer, the optical fiber sleeve is arranged below the light reflecting film layer, and terminals of the transmitting optical fiber and the receiving optical fiber are coaxially arranged in the optical fiber sleeve at intervals, so that an optical fiber bundle is formed. The system is low in cost, wide in application scene and capable of achieving three-dimensional force and multi-mode sensing.

The invention provides a plastic packaging barrel online defect detection method and system based on machine vision and deep learning. According to the method, visible light and thermal image data, aligned in time, of the surface of the plastic packaging barrel are collected, the dynamic range of a thermal image is expanded to enhance the identification degree, then highlight interference is compensated through the mapping relation between a thermal image stable area and a visible light reflection area, and surface reflection suppression is achieved; superposing the processed dual-mode data to generate a multi-mode fusion image, dynamically adjusting the temperature reference value of the fusion image based on the thermal conductivity of the material and the environment temperature of the production line, and positioning an abnormal temperature region; and finally, extracting topological contours and temperature diffusion characteristics of the regions, and inputting a deep learning model to judge material structure attributes and spatial positions of the defects so as to finish online detection. According to the method, thermal and visual data are fused to enhance the perception capability on fine structure defects, and the precision and robustness of online detection of the plastic packaging barrel in a complex illumination environment are remarkably improved.

The invention discloses an electronic component surface quality detection method and system based on machine vision. The method comprises the steps of original image acquisition, image basic processing, image illumination reflection decoupling, quality detection model construction and component surface quality detection. The invention relates to the technical field of electronic component image processing, in particular to an electronic component surface quality detection method and system based on machine vision, and the method comprises the steps: collecting an original image to obtain an original component detection image; an image basic processing method of image cleaning, image enhancement and image standardization is adopted; an image illumination reflection decoupling method is adopted, so that illumination non-uniformity and reflection interference are eliminated, and the contrast ratio and detectability of a defect area are improved; the fusion feature defect detection model is adopted for element surface quality detection, multi-scale defects can be effectively processed, and the detection precision and the anti-interference capability are remarkably improved.

The invention provides probe type mineral multi-element laser-induced breakdown spectroscopy detection equipment. The equipment is characterized in that a sealed quartz optical window is mounted on the side surface of a probe box; the laser faces the sealed quartz optical window and emits laser pulses to the detected mineral; the convex surface of the quartz crescent focusing lens faces the laser, the concave surface of the quartz crescent focusing lens faces the sealed quartz optical window, and laser pulses are focused on the surface of detected mineral to generate plasma; the dichroscope is used for reflecting the plasma emission light to the double-lens group; the emitted light is converged through the double-lens group to form a plasma image with weakened chromatic aberration; the spectrograph is coupled with the plasma image through an optical fiber mechanism and records spectrums of different wavebands; therefore, after the focus point of the reflected light of the crescent focusing lens is pushed far to the laser, the optical element is prevented from being damaged; the imaging chromatic aberration of a plasma image is reduced by the double-lens group; the optical fiber mechanism balances spectral intensities of different wavebands and suppresses a continuous spectrum through spatial resolution.

The invention discloses an automatic laser control system and method based on LRC, and belongs to the technical field of automatic laser control, and the system comprises an intra-cavity light reflection existence judgment module, a laser first adjustment module, a mode jump sensitive area judgment module and a laser stability re-judgment module. Real-time monitoring and intelligent judgment of the operation state of the laser can be achieved, working parameters and control strategies of the laser are dynamically adjusted according to key influence factors such as intracavity light reflection and mode jump sensitive areas, the laser output stability and the light beam quality are improved, mode interference and jump risks are reduced, and the laser quality is improved. And the automation level and reliability of the system are improved.

The invention relates to the technical field of picture recognition, and discloses a picture detection method and device, equipment and a medium, and the method comprises the steps: carrying out the portrait direction confirmation of a certificate picture, obtaining a certificate picture in a straightening state, obtaining a highlight region of the certificate picture in the straightening state, judging whether the highlight region is a light reflection region, and if not, carrying out the recognition of the certificate picture; if yes, sending the certificate picture in the straightening state to a server, otherwise, acquiring a non-reflective area picture of the certificate picture in the straightening state, identifying character area incomplete features and portrait area incomplete features in the non-reflective area picture, and identifying a complete character area according to the character area incomplete features by utilizing a character area boundary identification model; identifying a complete portrait area according to the incomplete features of the portrait area by utilizing a portrait area boundary identification model, segmenting a key information area of the certificate picture in the straightening state according to the complete character area and the complete portrait area to obtain a key information picture, and sending the key information picture to a server, and the accuracy and efficiency of picture detection are improved.

The invention discloses a plane finishing system suitable for a large-size workpiece, and belongs to the technical field of ultra-precision plane machining equipment. The problems that in the prior art, deformation and secondary deformation exist in the machining process and the detection process of surface shape finishing machining equipment for large-size and large-weight workpieces, so that the machining efficiency is low, and the machining precision is difficult to guarantee are solved. Comprising a control center, and a first-stage platform, a second-stage platform, a first-stage leveling assembly, a second-stage leveling assembly, a processing device, a clamping assembly, a laser interferometer and two groups of laser reflection assemblies which are in signal connection with the control center, each laser reflection assembly comprises a laser, a laser reflector and a photosensitive position sensor. The method is used for plane finishing of large-size workpieces.

The invention discloses a cable delivery detection system based on an image recognition technology. The cable delivery detection system comprises a light source, an optical medium marking module, an electromagnetic excitation module, a load module, an optical imaging module, a defect analysis module and a central processing unit. The light source is arranged along the axial direction of the cable, comprises multiple groups of sub-light sources, and irradiates the surface of the cable at a preset incident angle by adjusting light through the polaroid and the wavelength adjusting unit; the optical medium marking module is used for pasting a reflective marking layer containing a fluorescent layer and a thermochromic layer on the surface of the cable; the electromagnetic excitation module generates a high-frequency alternating electromagnetic field with a specific frequency in the cable; the load module applies a multi-axial bending load to the cable; the light imaging module collects light reflection data in a stroboscopic mode around the circumference of the cable. The defect analysis module determines cable defects according to the fluorescent layer deformation points. According to the system, multi-dimensional and high-precision detection is realized, the detection efficiency and accuracy are improved, the anti-interference capability is enhanced, and the cable delivery detection requirement is met.