1127 results about "Linear array" patented technology

The invention discloses an intelligent control and detection system for precision coating uniformity, and relates to the technical field of non-contact thickness measurement, the system comprises a spectrum confocal chromatography detection module, a non-contact multi-wavelength full-breadth detection module, an optical flow field dynamic measurement module and the like, a data processing unit is combined with a model to generate an evaluation model, and the evaluation model is used for evaluating the coating uniformity. The system has the advantages that multi-layer coating structure data are obtained in a full-breadth mode through a linear array sensor of the spectrum confocal chromatography detection module, a slurry full-breadth flow velocity vector field is analyzed in combination with the optical flow field dynamic measurement module, and the flow velocity measurement accuracy is improved. And the data processing unit fuses the multi-modal data to generate an evaluation model, and the regulation and control strategy generation module outputs an instruction containing edge air pressure regulation, so that accurate control over coating uniformity is achieved, damage to a base material is avoided, material waste and manual debugging time consumption are reduced, and the production efficiency and the product yield are remarkably improved.

The invention relates to the technical field of grain detection, and discloses a grain broken rice rate online detection method and system based on image analysis. A grain broken rice rate online detection method based on image analysis comprises the steps of intelligent illumination control and high-speed synchronous imaging, self-adaptive image enhancement based on reinforcement learning, multi-stage parallel particle detection and segmentation, multi-modal feature deep fusion, robust classification based on ensemble learning, intelligent quality control and process optimization. And continuously learning and updating knowledge. A clear image is obtained through a multi-angle linear array camera and a stroboscopic light source, a reinforcement learning agent is adopted to carry out adaptive image enhancement, a deep learning network is used to carry out particle detection segmentation, multi-dimensional features are extracted, accurate identification is realized through an integrated classifier, and a digital twin model is established to carry out process parameter optimization. According to the invention, accurate online detection of the broken rice rate of grains can be realized in a high-speed flowing state, and the detection efficiency and accuracy are improved.

The invention provides a coherent signal arrival direction estimation method and device based on a deep convolutional network, and belongs to the field of array signal processing. The method comprises the following steps: receiving a to-be-detected signal containing a coherent signal by using a uniform linear array antenna to obtain an array receiving data matrix and extract a covariance matrix; forming an input feature vector by right upper triangular elements divided from a diagonal line in the covariance matrix, inputting the input feature vector into a covariance estimation model formed by a deep convolutional network, obtaining an estimation value of the right upper triangular elements under an ideal incoherent condition, and reconstructing the estimation value to obtain a covariance matrix estimation value; and performing characteristic decomposition on the covariance matrix estimation value, and generating a spatial spectrum by using a MUSIC algorithm to obtain an estimation result of the signal arrival direction. According to the method, the noise-containing mixed signal covariance matrix is mapped into the ideal incoherent noise-free signal covariance matrix through a physical constraint supervised learning framework, so that the estimation precision and robustness of the MUSIC algorithm in a coherent scene are improved.

The invention relates to the technical field of satellite internet, and discloses a low-orbit satellite phased array multi-beam interference modeling and suppression method and system, and the method comprises the steps: selecting a Kaiser window as a core filtering method, and achieving the optimization of beam characteristics through the dynamic adjustment of a shape parameter beta; generating an initial beam directional diagram based on a digital phase matching method, and multiplying the Kaiser window function coefficient by the excitation weight of the 64-array-element linear array element by element to realize spatial domain weighted filtering; the method comprises the following steps: constructing a training data set containing multi-scene interference characteristics, calculating a corresponding covariance matrix and an accurate inverse matrix thereof to form a sample pair, designing a deep neural network architecture, inputting a flattened covariance matrix vector, and learning a complex nonlinear mapping relation from the covariance matrix to the inverse matrix through a multi-layer full-connection structure; a mean square error is used as a loss function to constrain network output precision, and a multi-beam interference system model is constructed; according to the invention, stable and efficient communication of the low-orbit satellite system in a complex electromagnetic environment and under rapid channel change is ensured.

The invention relates to the field of artificial intelligence and computer vision, discloses an AI vision-driven polyester fabric pilling detection method and system, and aims at solving the problems that traditional manual visual inspection is low in efficiency and high in subjectivity, and existing machine vision is insufficient in sensitivity to low-contrast tiny defects. The method comprises the steps that fabric images are collected through a high-resolution linear array camera and a multi-channel self-adaptive LED light source, after non-uniform correction and self-adaptive filtering, the fabric images are input into a three-level convolutional network to extract multi-scale texture features, and then unified representation is generated through cross-scale attention fusion; according to the technical scheme, high-precision recognition of pilling with the diameter smaller than 0.5 mm is achieved, the detection rate is increased by 42%, the false alarm rate is lower than 3%, full inspection of a 60-meter / minute production line is supported, structured quality data are output, and the intelligent and quantitative level of online quality inspection in the textile industry is remarkably improved.

The invention relates to the technical field of size detection, in particular to a component size detection system based on machine vision, which comprises an interference area identification module, an edge repair module, a structure clustering module, a distortion analysis module and an attitude restoration module. According to the method, the gray level change trend of each pixel and the adjacent points in the image is obtained, the high-reflection suspected interference area is identified, the edge response cancellation processing is executed, and linear interpolation compensation is carried out by combining the effective edge response values of the adjacent areas; after a continuous contour trend is constructed, clustering and sub-grouping division are carried out according to an included angle difference trend between contour geometric vectors, a three-axis direction response linear array variation amplitude is extracted to construct a distortion curvature mapping table, existence of non-equal-interval deformation is judged, reverse angle compensation is applied, and a three-axis intersection point convergence process is completed through a nonlinear optimization algorithm; and according to the three-dimensional coordinates, calculating a geometric dimension and outputting a detection result, thereby realizing self-adaptive detection of different postures and surface interference component dimensions.

The invention discloses a multi-scale linear array camera splicing method and system based on point cloud. The method comprises the following steps: completing acquisition and preprocessing of point cloud data and image data of a target area; determining an overlapping region range between adjacent images; extracting spatial structure characteristics in the point cloud data, and performing multi-scale hierarchical decomposition on the point cloud through a multi-scale segmentation method; meanwhile, multi-scale image feature extraction is carried out on the images of the linear array camera; solving gradients in X and Y directions by adopting an optical flow method aiming at any pixel in the overlapping region, and calculating a motion vector between the pixels; fusing the optical flow information obtained under each scale, and constructing a globally consistent optical flow vector field; according to the fused optical flow vector, calculating to obtain a geometric transformation matrix of the whole overlapping region; and after image transformation and alignment are completed through the transformation matrix, fusion processing is carried out on overlapped areas. And the unification of the visual effect and the spatial integrity of the spliced image is ensured.

The invention discloses a multi-light-spot anti-interference deformation measuring device and method based on stroboscopic energy spectrum.The multi-light-spot anti-interference deformation measuring device comprises a point light source, a first cylindrical mirror is arranged below the point light source, a first linear array sensor is arranged below the first cylindrical mirror, and the first linear array sensor is electrically connected with a data acquisition device; light emitted by the point light source passes through the first cylindrical mirror and then is focused into a line segment to be imaged on the first linear array sensor, and the first linear array sensor converts optical signals of the focused line segment into digital signals and outputs the digital signals to the data acquisition device. According to the multi-light-spot anti-interference deformation measuring device, a multi-dimensional displacement sensor measuring system is established by applying the cylindrical mirror, the linear array sensor and the point light source, a displacement measuring system with high precision, high resolution and high sampling rate can be realized, and the multi-light-spot anti-interference deformation measuring device is few in related components, small in size, simple to maintain, low in cost, high in system stability and easy to popularize. The method is more suitable for outdoor multi-point monitoring of engineering structures.

Base station antennas include a reflector, a first linear array of radiating elements extending forwardly from the reflector, the radiating elements in the first linear array configured to operate in a first frequency band, and a second linear array of radiating elements extending forwardly from the reflector, the radiating elements in the second linear array configured to operate in the first frequency band. These antennas further include an isolation wall that is positioned in between the first linear array of radiating elements and the second linear array of radiating elements. This isolation wall comprises at least one partially reflective surface that is configured to reflect, on average as a function of frequency, between 20% and 80% of incident radiation in the first frequency band.

The invention relates to an intelligent wind power blade defect identification method based on phased array detection, which aims at the anisotropic characteristic of a wind power blade glass fiber reinforced composite material, and can flexibly adjust the sound beam angle, effectively penetrate through the material and inhibit the scattering of an ultrasonic signal through a low-frequency linear array probe with characteristic parameters and an electronic focusing technology. Defects in different directions such as impurities perpendicular to layers, cracks in the fiber direction, wrinkles and the like can be accurately detected, meanwhile, by combining wavelet packet transformation noise reduction and a feature extraction algorithm, the distinguishing capacity of defect echoes and noise in complex materials is remarkably improved, the method is adaptive to complex structures and material characteristics of wind power blades, the application range of the detection technology is expanded, and the detection efficiency is improved. An ultrasonic phased array detection technology and an intelligent algorithm (a K-means clustering algorithm and a YOLOv8 target detection model) are deeply fused, the limitation that traditional detection depends on manual analysis is broken through, and a full-process automatic detection system of data acquisition, feature extraction and intelligent recognition is constructed.

The invention relates to the technical field of array antennas, in particular to a sparse linear array beam forming method and system with unit rotation and mutual coupling considered. Array elements are obtained, Euler angle derivation is carried out on rotation of the array elements around the z axis, and a radiation electric field after rotation is obtained; setting a beam forming target according to the electric field of the radiation field; according to a beam forming target, optimizing the position, the rotation angle and the excitation phase of an array element by adopting a random optimization algorithm, and generating an initial beam scheme; an active directional diagram is extracted from the initial beam scheme according to full-wave simulation, the active directional diagram is combined with a CAL-SAPSO algorithm to optimize the array element position, the rotation angle and the excitation phase, and a final array element directional diagram is generated; according to the invention, by introducing array element rotation and considering a mutual coupling effect, efficient beamforming of the sparse wiring array is realized, the radiation characteristic of the antenna array can be adjusted more finely, the peak side lobe level and the cross polarization level are effectively reduced, and the overall performance of the system is improved.

An optical arrangement for a LIDAR system includes a laser, scanner, fold mirror, lens, and sensors. Adding a wedge-shaped optical element creates an auxiliary field of view, when positioned to overlie an edge portion of the lens. The wedge-shaped optical element may have a variable transparency preventing reception by the sensors of excessive signals from close targets. The sensors may be: a plurality of sensors with unique lengths / widths, arranged to form a linear array; or sensors with the same length / width, but positioned to form an arcuate shape, compensating for an arcuate scan line; or two columns of sensors, one with a field of view in focus at far field positions, and the other in focus at near field positions, correcting for parallax effect / error; or a column of highly sensitive sensors surrounded by a plurality of guard rail sensors having higher immunity to damage from stray laser light.

The invention discloses an overlay error real-time correction system based on image recognition and dynamic fitting, and belongs to the field of semiconductor advanced packaging and manufacturing. The system comprises an image acquisition module, an error decoupling module and a dynamic compensation module to form closed-loop control. The image acquisition module adopts a high-resolution linear array CCD (Charge Coupled Device) and an AI (Artificial Intelligence) algorithm to realize high-speed and high-precision mark identification and error quantization; the error decoupling module performs decoupling and trend prediction on system errors and random errors by using PCA, a region weight matrix, LSTM and the like; and the dynamic compensation module realizes mu s-level partition graph compensation by a DMD optical system based on an error thermodynamic diagram through heterogeneous platform operation. The system supports the real-time processing of more than 100Hz, the average overlay error is less than or equal to 0.3 mu m and the response time is less than 5 seconds in the FOPLP and other processes, the problems of lag, low precision and the like of the traditional method are effectively solved, and the manufacturing yield and the production line efficiency are remarkably improved.

The invention discloses a filter tip modeling parameter visual identification and adjustment method, and relates to the technical field of filter tip production, a laser diameter measuring instrument and a linear array camera are used for synchronously collecting peripheral images of a filter tip, and high-precision and consistent size and gray scale double baselines are generated; a texture segmentation technology is adopted to identify a suspected recess area and generate a recess position vector, a confocal displacement sensor is utilized to carry out local depth walk-up to obtain depth distribution data, and a size compensation coefficient is generated and a size matrix is corrected through Gaussian process regression; statistical threshold analysis is conducted on the corrected size matrix, when parameters exceed the limit, the gap of a forming nozzle is adjusted, the size stability of the filter tip is ensured, the adjustment result and related data are written into a manufacturing knowledge base, follow-up batch optimization is supported, and the measurement reliability and the production line efficiency are improved; tiny recesses on the surface of the filter tip can be effectively identified and compensated, and the measurement accuracy and the assembly stability of modeling parameters are ensured.

The invention relates to a high-signal-to-noise-ratio ultrasonic imaging method and device for internal defects of a curved surface component, a medium and a product, and belongs to the technical field of ultrasonic imaging. According to the method, a linear array ultrasonic probe is adopted to carry out single-time ultrasonic excitation on a curved surface component, a full-matrix echo signal is obtained, first arrival time extraction is carried out on the collected signal, an ultrasonic incident angle is estimated, and discrete coordinates of the surface of the component are obtained; the method comprises the following steps of: fitting a curved surface model, constructing an equivalent virtual array model, calculating transmitting and receiving delay time of each pixel point, realizing initial full-focusing beam forming of signals, estimating an expected signal variance and a noise variance based on maximum likelihood estimation, constructing an initial coherent beam forming machine and performing iterative updating, and finally forming a beam. And taking the coherent beam synthesizer obtained by iteration as a weighting factor, acting on an initial beam synthesis signal for weighting, and completing image reconstruction. The method has the advantages of being high in calculation efficiency, low in system overhead, high in imaging signal-to-noise ratio and the like, and accurate imaging can be achieved in a curved surface structure scene.

The invention belongs to the technical field of data processing methods, and particularly relates to a tension detection method and system for yarn conveying to solve the technical problem that a detection method in the prior art is low in precision, and the method comprises the following steps: S1, collecting multi-modal vibration data of a yarn in a preset detection area, the multi-modal vibration data comprises a yarn vibration displacement time sequence image obtained based on a linear array camera and a vibration acoustic signal obtained based on an acoustic sensor; s2, constructing a space-time joint feature vector representing the vibration dynamic characteristics of the yarn; s3, separating out pure yarn vibration characteristics influenced by background vibration of the rejecting equipment; and S4, determining the instantaneous tension of the yarn by solving the inverse problem of the nonlinear wave equation coupled with the tension, the bending moment and the air damping. The linear array camera and the acoustic sensor are adopted, multi-mode and multi-dimensional information collection of yarn vibration is achieved, space-time joint feature vectors are constructed, and complex vibration behaviors of yarn can be represented more comprehensively and accurately.

The invention discloses a vector flow velocity measuring device and method based on a bidirectional scanning spectral domain optical coherence tomography technology. Comprising a super light-emitting diode light source, an optical fiber coupler, a polarization controller, an interferometer comprising a sample arm and a reference arm, and a collimating lens, the collimating lens, the grating, the focusing lens group and the linear array camera are sequentially connected through a light path; the linear array camera, the computer and the two-dimensional galvanometer are sequentially connected through a line; according to the method, the fixed bias vector velocity is introduced by utilizing the bidirectional scanning technology, the dynamic light scattering optical coherence tomography method and the Doppler optical coherence tomography method are combined, decoupling of each parameter of the vector flow velocity is efficiently and accurately realized, and a quantitative index is provided for vector flow velocity analysis. The vector flow velocity measuring device based on the bidirectional scanning spectral domain optical coherence tomography technology is simple in system setting and low in cost, the time resolution is improved by about 2.5 times, and the measuring time is shorter.

The invention relates to the field of underwater sound signal processing, in particular to an underwater DOA (direction of arrival) estimation method based on graph nerves and a convolutional neural network, which comprises the following steps: 1, establishing a linear array, and enabling narrow-band signals to simultaneously reach an underwater sound array; 2, performing signal preprocessing to obtain a signal covariance matrix, and performing normalization processing; 3, extracting correlation between array elements and spatial features of array signals, and performing data supplementation on sparse linear array information; 4, forming a double-branch structure, enhancing the information aggregation capability, and extracting features from a space path and a time domain path; and 5, constructing an adjacent matrix, filling node features of damaged array elements, adopting a double-branch structure, extracting spatial features and time domain features, carrying out feature integration, and outputting a DOA estimation result. The spatial correlation between array elements is extracted and the array sparsity problem is processed by using the graph neural network, and the time domain features of the signals are extracted in combination with the convolutional neural network, so that more accurate and more robust DOA estimation can be realized under the conditions of low signal-to-noise ratio and array sparsity.

The invention provides a calibration method suitable for a single-camera high-precision scanning system. The calibration method comprises the following steps: S1, carrying out area array mode calibration on a linear array camera; by adjusting the exposure time of the line-scan digital camera, moving the base station to image at different positions of the checkerboard, and solving internal parameters and distortion parameters of the line-scan digital camera; s2, line scanning mode calibration; performing line scanning imaging on the checkerboard to obtain pixel coordinates of angular points of the checkerboard; and separating the actual rotation angle of the checkerboard from the projection error, and further deducing the rotation angle of the real camera, thereby completing calibration. According to the calibration requirement of the linear array camera in a scanning imaging scene, a two-stage algorithm combining area array mode modeling and linear scanning imaging correction is provided, and the problem that a traditional calibration method is not applicable under the condition that a single camera is fixed and moves in a single direction is effectively solved.

The invention specifically discloses a satellite navigation interference source positioning method based on a distributed unmanned aerial vehicle, and relates to the technical field of satellite navigation interference resistance. According to the method, firstly, an unmanned aerial vehicle cluster carrying uniform linear array antennas is deployed in a target area, and after parameters of a system are initialized, all unmanned aerial vehicles synchronously collect interference signals and estimate the direction of arrival (DOA) of an interference source; then performing dual-domain interference suppression based on DOA information, calculating an interference source coordinate in combination with an unmanned aerial vehicle coordinate, and performing noise reduction; planning a path by using a path planning model of a multi-modal Markov decision process and a reinforcement learning algorithm to realize tracking of a dynamic interference source; and finally, judging and outputting a final coordinate through Euclidean distance convergence. The method solves the problems of limited coverage of a traditional fixed monitoring station and insufficient positioning precision of a single unmanned aerial vehicle, can efficiently position dynamic and multiple interference sources, improves the positioning precision and the anti-interference capability, reduces the deployment cost, and is suitable for satellite navigation interference source positioning in a complex environment.

The invention discloses a railway freight car loading state detection method based on image recognition, and particularly relates to the field of railway freight car loading state detection.The method comprises the steps that in the process that a railway freight car passes through an image collection area, carriage image frames are collected at a constant frame rate through linear array imaging equipment; an image sequence is constructed based on the wheel axle displacement, the acquisition timestamp and the frame number, the image sequence comprises a main image frame, a relay interpolation frame and an interpolation pseudo frame, and the main image frame, the relay interpolation frame and the interpolation pseudo frame are arranged to support time domain modeling of subsequent state response changes. The dynamic capture and accurate identification of the instantaneous abnormal state of the loading structure are realized by constructing an anchor point tracking graph and combining a time sequence rhythm modeling and similarity discrimination mechanism of a disturbance behavior. The problems that in the prior art, an identification system lacks the space-time continuous modeling capacity for the short-time change state, and an abnormal judgment blind area and misjudgment distortion exist are solved.

The invention relates to the technical field of multispectral imaging, in particular to a multispectral photon counting single-pixel imaging device and method, the imaging device comprises a detection assembly and a processing assembly, and the detection assembly comprises a laser source loading optical pulses at a certain frequency; the spatial light modulator is used for undersampling according to the loaded negative W-based pattern to obtain a light signal of the to-be-detected object; the time domain disperser is used for dividing each optical signal into light splitting signals belonging to m spectral bands according to wavelength mapping; the photoelectric detector linear array comprises m detection elements arranged in a linear array, and the m detection elements are used for respectively detecting light intensity signals of the light splitting signals in the corresponding spectral bands to obtain m groups of light intensity signals; the processing assembly collects light intensity signals according to spectral bands and reconstructs spectral images according to the light intensity signals of each spectral band, and m spectral images are obtained. According to the invention, the imaging time is shortened, the imaging cost is reduced, and the multispectral imaging effect in a photon sparse application scene is realized.

The invention relates to the technical field of machine vision detection, and particularly discloses a high-temperature medium-thickness steel plate contour detection device which comprises a detection room, the detection room is arranged above a roller way, and an industrial air conditioner is arranged in the detection room; a first window and a second window are arranged at the bottom of the detection room, bottom-layer optical glass is mounted at the first window and the second window, a linear array camera mechanism and an area-array camera mechanism are arranged in the detection room, the linear array camera mechanism is arranged corresponding to the first window, and the area-array camera mechanism is arranged corresponding to the second window; a laser and a velocimeter are mounted on the area-array camera mechanism, a laser line of the laser on the steel plate is in the advancing direction of the steel plate, and the laser line of the laser and a laser point of the velocimeter are on the same straight line; and heat insulation cotton is arranged on a room body of the detection room. The detection room is installed above the roller way, all components for detection are installed in the room, maintenance and installation are implemented in the room, walking safety of personnel is guaranteed, and the dustproof problem can be solved.

The invention discloses a self-recognition gluing system which comprises a positioning mold and a gluing device, the gluing device is integrated with a glue gun, a glue cleaning scraper, a multi-axis movement assembly and a glue overflow detection module, a two-dimensional contour and three-dimensional point cloud model is constructed through fusion of a linear array visual sensor and a laser distance measuring sensor, preset gluing path deviation is compared in real time, and the glue overflow detection module is used for detecting glue overflow. The system comprises a driving glue cleaning scraper, a bearing platform, a glue gun, an AI self-learning module and a motion error compensation module, wherein the driving glue cleaning scraper is used for realizing self-adaptive glue cleaning through a flexible hinge, a force control sensor and a shape memory alloy mechanism; a variable-density gluing path can be generated, the glue overflow risk can be predicted, process parameters can be optimized, through multi-sensor fusion detection, intelligent control and self-adaptive mechanism design, the problems that a traditional gluing system is insufficient in positioning precision, incomplete in detection and poor in glue cleaning flexibility are solved, and the automation and intelligence level of sealing ring gluing is remarkably improved.

The invention discloses a multi-mode control method for voice interaction and gesture recognition of an atmosphere lamp, and belongs to the field of intelligent control. The method comprises the following steps: S1, constructing a multi-mode sensing module, and arranging a bidirectional linear array microphone, a dual-lens infrared depth camera and a space calibration laser transmitter; s2, extracting voice features by adopting an extended spectrogram domain attention network, and generating a first semantic vector; s3, dynamic attitude features are extracted through the time-airspace sparse convolutional network; s4, performing modal alignment and cooperative coding on the two semantic vectors based on a bidirectional gating fusion mechanism, generating a joint interaction instruction vector, and solving modal conflicts by a time sequence synchronization and confidence regulation strategy; s5, inputting the vector into a multi-task intention classifier, analyzing a user intention and outputting a unique atmosphere lamp control code; and S6, transmitting the control code to a driving unit to realize light control. The beneficial effects are that voice and gesture fusion control is realized, and atmosphere lamp interaction intelligence and response precision are improved.

The invention relates to the technical field of industrial visual inspection, and discloses an asynchronous exposure double-view-field imaging system and method, and the system can achieve the merging of independent view field images collected by two parallel lenses into a single linear array camera through a reflector and a non-polarization beam splitting cube based on the asynchronous exposure double-view-field imaging system. Meanwhile, in cooperation with precise time sequence control, the system drives two independent stroboscopic light sources to be synchronous with line trigger signals of the camera, different view fields are alternately illuminated in odd-even line periods, the camera is made to perform asynchronous exposure, and two paths of image information are collected in a time-sharing mode; and finally, reconstructing two complete, independent and seamlessly spliced detection images from the interleaved data streams through an odd-even line separation algorithm. According to the invention, with the hardware cost of a single camera, the detection visual field is obviously expanded, the detection efficiency and the image geometric precision under the high-line scanning frequency are ensured, and the excellent balance of the performance, the cost and the efficiency is realized.

A hybrid scanning antenna including: a reflector having a focal line; a first mechanical movement to move the reflector about a first axis; a second mechanical movement to move the reflector about a second axis; a linear array fixedly disposed along the focal line to electronically scan at a scan angle about a third axis; and a controller to control the first mechanical movement, the second mechanical movement and the scan angle of the linear array to orient the hybrid scanning antenna to a look angle of a remote transceiver.

The invention discloses a roll-to-roll laser cutting equipment online alignment and trajectory interpolation control method, which relates to the technical field of laser cutting alignment and trajectory interpolation, and comprises the following steps: marking a reference point for an adhesive film; monitoring a datum point on the surface of the adhesive film through a linear array camera and recording datum data; analyzing the deformation data and the displacement data through the reference data; performing compensation alignment on the cutting head based on the deformation data and the displacement data to obtain a compensation cutting point, and controlling the cutting head to start cutting from the compensation cutting point; a cutting shape is obtained, the interpolation track of the cutting head is analyzed through an interpolation algorithm, and the cutting head is controlled to cut the adhesive film according to the interpolation track; the method is used for solving the problems that according to an existing laser cutting alignment and track interpolation technology, alignment cannot be conducted on a product in advance, compensation for deformation of the product is lacked, the laser cutting efficiency is low, and the size error of the cut product is large.

The invention discloses a cage stranded wire pitch measurement method and system based on a line-scan digital camera, and belongs to the technical field of industrial detection. The method adopts an image acquisition mode of cooperative work of an encoding wheel, an encoder and the line-scan digital camera, feeds back the motion speed of a stranded wire in real time through the encoder and accurately controls the line scanning frequency of the line-scan digital camera; the image acquisition rate and the stranded wire movement speed are strictly synchronized; intelligent calculation of the pitch of the stranded wire is realized based on dynamic gray analysis, and the method comprises the following steps: establishing a dynamic conversion model of pixel-physical size by integrating multi-dimensional information including the number of single stranded wires, view parameters of a linear array camera and image resolution; and dynamically calculating an optimal segmentation threshold of a local area by adopting a gray threshold segmentation algorithm and collecting gray distribution characteristics of a complete stranded wire image. According to the invention, non-contact pitch measurement with micron-order precision can be realized, the product quality stability is greatly improved, and key technical support is provided for industry intelligent upgrading.

The invention relates to the technical field of water quality surveying and sampling devices, in particular to a water quality surveying device for mining exploration, which solves the problem that the existing water quality detecting and sampling equipment is single in detection data when detecting sample water after sampling, and comprises a pull rope, a shell and a rotary water pipe, the pull rope is sleeved with two first lifting seats in an up-and-down movable mode, the power assembly drives the two first lifting seats to be close to or away from each other, an intermediate rotating plate is arranged on the side face of the upper first lifting seat in a circular array rotating mode, and a rotary trigger rod is arranged on the side face of the lower first lifting seat in a circular array rotating mode. The device can be matched with a sampling hole, the conventional sampling function is realized, the sampling range is expanded after the device goes deep into an underground river, more comprehensive sample water with different depths is obtained, data during sample water detection are more comprehensive, and the detection accuracy is improved. And the water quality pollution condition can be known more clearly.