88results about How to "Improve detection ability" patented technology

The invention relates to a light and miniature big-target-surface low-light lens, and the lens comprises a front lens group A, a diaphragm B and a rear lens group C, wherein the front lens group A, the diaphragm B and the rear lens group C are sequentially arranged in an incident direction of an optical path. The front lens group A includes a positive meniscus lens A1, a negative meniscus lens A2,a biconcave lens A3 and a biconvex lens A4, wherein the positive meniscus lens A1, the negative meniscus lens A2, the biconcave lens A3 and the biconvex lens A4 are sequentially arranged in an incident direction of the optical path. The biconcave lens A3 and the biconvex lens A4 are in close connection with each other as a first bonding group. The rear lens group C includes a biconcave lens C1, abiconvex lens C2, a biconvex lens C3, a plano-convex lens C4 and a negative meniscus lens C5, wherein the biconcave lens C1, the biconvex lens C2, the biconvex lens C3, the plano-convex lens C4 and the negative meniscus lens C5 are sequentially arranged in an incident direction of the optical path. The biconcave lens C1 and the biconvex lens C2 are in close connection with each other as a secondbonding group. The invention also relates to an imaging method of the lens. The lens is reasonable in design, effectively improves the imaging quality under the requirement of the large target surfaceof the lens, reduces the number of optical lenses, and realizes light and miniature lens. The lens has strong light collecting and light transmitting ability, and the target surface of the lens is large. The lens is high in optical resolution, is large in angle of view, and is large in observable range.

The invention relates to the technical field of electrical detection, in particular to a multi-stress coupling environment reliability testing method for an electricity consumption information acquisition terminal. Comprising the steps of applying a combined stress field to an electricity utilization information acquisition terminal through an environment test box; acquiring power utilization information acquisition terminal parameters; the method comprises the following steps of: capturing metering pulse response and carrier communication interaction signals of an electricity utilization information acquisition terminal under the excitation of a combined stress field by utilizing an electrical sensor, extracting carrier signal-to-noise ratio data and metering reference drift data, and generating a reference voltage compensation coefficient and an impedance matching threshold value; projecting the carrier signal-to-noise ratio data to an impedance matching threshold value, and constructing a stress failure envelope surface according to a hardware overload protection threshold value; and mapping the communication quality distortion residual vector to a stress failure envelope surface, and calculating a reliability life prediction value. According to the method, a uniform excitation environment is constructed, and performance degradation of different dimensions is uniformly quantified into accumulative stress damage integral, so that the comprehensive anti-interference capability of the terminal in a multi-stress coupling environment can be truly reflected.

This invention discloses an artificial intelligence-based method and system for the inspection and control of power distribution networks using unmanned aerial vehicles (UAVs). Relating to the field of UAV power inspection technology, the method includes: adjusting the UAV's pose in real time based on target perception feedback during the inspection process to actively align with the target and acquire images of power components; uploading valid images from the selected images to a cloud-based management platform; identifying power component entities in the selected images and constructing a spatial semantic graph based on the spatial distribution relationships between components; performing topological logic reasoning and feature consistency analysis on the spatial semantic graph to identify abnormal component states and determine the power logic attributes of faulty components; generating maintenance instructions based on the identified abnormal states and power logic attributes and pushing them to the terminal. This invention addresses the problems of high redundancy in original images, insufficient physical positioning accuracy leading to ambiguity in component logical identity identification, and difficulty in identifying long-tail atypical hidden dangers during power distribution network inspection.

The invention provides a multi-band composite high-integration TR assembly. The multi-band composite high-integration TR assembly comprises a shell, a front multi-layer board, a back multi-layer board, a C / X / Ku band receiving and transmitting circuit, a C / X / Ku band single receiving circuit and a Ka band receiving and transmitting circuit, wherein the front multi-layer board and the back multi-layer board are connected in the shell, the C / X / Ku band receiving and transmitting circuit is connected with the front multi-layer board, and the Ka band receiving and transmitting circuit is connected with the back multi-layer board. The low-cost scheme design of an all-solid-state microwave multilayer board suitable for batch production and testing is adopted, ports and transmission line layout are reasonably designed, multi-band composite mode transmission is achieved in the form of the front face and the back face, a C / X / Ku-band transmitting circuit and an H-polarization receiving circuit are integrated on the front face, and the transmission efficiency is improved. A C / X / Ku frequency band V polarization receiving circuit and a Ka frequency band receiving and transmitting circuit are integrated on the reverse side, different functional circuits are respectively transmitted through a microstrip line and a strip line through an interface circuit structure covering 1-40 GHz and an in-board vertical transition structure, the isolation degree of different circuits is improved, mutual crosstalk between different signals is avoided, and the transmission efficiency is improved. And the functions of high integration, high consistency, ultra wide band, numerical control phase shift, numerical control attenuation and the like of the assembly are realized.

The invention relates to the technical field of data processing and state monitoring, and discloses an intelligent ring main unit fault real-time diagnosis method and system, and the method comprises the steps: constructing a fault feature over-complete dictionary; collecting and preprocessing high-frequency operation data streams of the ring main unit in real time; carrying out online sparse decomposition and manifold mapping based on the dictionary, and converting a high-dimensional signal into a low-dimensional sparse coefficient and manifold features; and a lightweight classification model is used for rapid reasoning, and fault early warning and data uploading are triggered when abnormity is detected. The system comprises a data acquisition module, a preprocessing unit, an edge computing engine, an intelligent diagnosis module and a communication gateway. According to the method, depth dimension reduction and feature enhancement are realized through a manifold sparse coding technology, the bandwidth pressure and the calculation overhead are reduced on the premise of ensuring the fault feature integrity, and the real-time performance and the accuracy of diagnosis are improved.

The invention discloses an optical lens imaging system and an optical lens defect detection method, and relates to the field of optical lens detection.The system comprises a conveying belt, a large-face transmission imaging module, a large-face reflection imaging module, a small-face reflection imaging module, a small-face transmission imaging module and a control module, and different types of light sources are arranged at four detection points respectively. Multi-angle imaging is carried out from the upper direction and the lower direction of a lens, a grating modulation technology is adopted for parallel light transmission point positions, the internal defect display effect is enhanced through differential processing, and the detection method comprises the steps that preprocessing such as segmentation, difference, enhancement and registration is carried out on six images; constructing a multi-branch feature extraction network, and adopting a priori guided feature fusion mechanism; constructing a defect detector comprising classification, positioning and quantification; according to the invention, comprehensive detection of defects on the surface and inside of the lens is realized, the sensitivity is high, the efficiency is high, the structure is compact, and the method is suitable for industrial mass production.

The application discloses a kind of pulse Doppler radar weather cloud clutter automatic filtering methods, belong to radar data processing technical field.The method utilizes the statistical characteristics of weather cloud clutter on radar echo spectrum diagram, and the spatial position and motion characteristics of radar track in monitoring area, realizes the automatic identification and effective elimination of weather cloud clutter, reduces false track, and improves the detection performance of radar to "low, slow and small" target.

The invention relates to a road boundary width identification method and device, a radar and a readable storage medium. The method comprises the following steps: obtaining point cloud information collected by a vehicle radar, performing position division on all static point clouds according to a plurality of distance resolution units preset in a plurality of target detection directions of the vehicle radar and transverse positions of the static point clouds, and determining a target distance resolution unit where a peak value of the number of the point clouds in each target detection direction is located; for each target detection direction, determining the single-side road boundary measurement width of the current frame in the corresponding target detection direction according to the distance value corresponding to the target distance resolution unit; filtering the single-side road boundary measurement width of the corresponding current frame according to the road width historical information to obtain the filtered single-side road boundary width of the current frame; and false targets in the stationary point cloud can be detected based on the single-side road boundary width of the current frame. By adopting the method, the detection performance of the radar in a closed scene can be improved.

This invention relates to the field of optoelectronic detection technology and discloses an online detection system for screen color uniformity based on dynamic rotating polarization spectrum. The system includes an online transmission module for carrying and driving the illuminated screen under test to move continuously along a set direction at a set speed; and a combined optical encoding module, positioned above the screen under test, comprising a static spatial-spectral phase delay mask and a continuously rotating polarization modulator arranged sequentially along the beam propagation direction. By driving the screen to continuously translate using the online transmission module, and cooperating with the continuously rotating polarization modulator and hyperspectral acquisition module to acquire dynamic spatiotemporal aliasing data, the accuracy of the spectral dimension can be guaranteed. Furthermore, by extracting high-precision chromaticity parameter matrices and multidimensional polarization distortion feature matrices from the decoupled and reconstructed optimal polarization spectral tensor solution, the system's ability to detect complex internal quality problems can be significantly enhanced.

The invention relates to the technical field of crossing of artificial intelligence and software engineering, and discloses an AI generation code recognition method based on a multi-modal feature fusion model, which comprises the following steps of: obtaining global features of a method source code sample to be recognized, and performing word processing on the whole source code by adopting a sub-word level word processing strategy; distinguishing the sub-words based on the sub-word types to realize sub-word level separation modeling of the code stream and the annotation stream; carrying out fusion through bidirectional cross attention to obtain window-level local semantic representation; splicing the window-level text local representation and the method-level global feature to obtain a window-level fusion vector; inputting the window-level fusion vector into a classifier to obtain a window-level probability set; when the maximum probability in the window-level probability set is larger than a threshold value during prediction, the method is judged to be AI code generation, and otherwise, the method is judged to be human compiled code. According to the method, the generalization ability of the model can be improved, and the detection ability of local AI generated fragments and the engineering application feasibility are improved.

The application provides an instance constraint change detection method and device for broken image patches of remote sensing images, and relates to the technical field of intelligent remote sensing image processing. The method comprises the following steps: performing image slicing on the obtained front and rear time-phase images and inputting the images into a pre-trained instance constraint change detection network (including a backbone network, a feature fusion module, an instance constraint decoding module and an instance constraint loss, the instance constraint loss is used to calculate the loss of each change patch in the image during model training, and the loss of all change patches is accumulated for gradient update), to obtain a predicted change map containing the patches; then, small patch filtering, hole filling and contour simplification are performed to obtain a patch optimization result; finally, raster filling and vector conversion operations are performed to generate a target change vector result. The application can accurately detect the change area, ensure the accuracy and recall rate, and take into account the integrity and smoothness of the change patch, thereby significantly improving the precision of change detection.

The present application belongs to the technical field of ground laser radar forestry data processing, and discloses a broad-leaved forest single tree segmentation method and system based on branch information guidance, taking ground-based laser radar broad-leaved forest point cloud as a processing object, using RANSAC cylindrical fitting to combine the growth characteristics of the tree trunk to detect the tree trunk; starting from the top of the tree trunk in the low vegetation area, the tree branches are extracted by segmenting and growing the branches and combining the thickness changes of the branch segments; starting from the end of the branch, the tree crown leaf point cloud is segmented by layer-by-layer growth. The present application has stronger trunk detection capability under the conditions of lush low vegetation and complex terrain; on the other hand, the present application can accurately segment the tree crown when the large and small crowns are intertwined and the multiple crowns are closely surrounded. The algorithm is efficient, simple and easy to use, and has great practical significance for improving the semantic understanding ability of forest scenes, assisting forest resource investigation, vegetation ecological research, and satellite remote sensing product calibration and verification.

The invention relates to the technical field of gas sensing, and discloses a cavity enhanced spectral absorption gas detection system and method based on AR-HCF, and the system comprises a light source part, a transmission part, a gas chamber part, a signal detection part and a demodulation part; the air chamber part is a mode interferometer, the mode interferometer is composed of a single-mode fiber (SMF), a gradient refractive index multimode fiber (GIF) and an anti-resonance hollow-core fiber (AR-HCF), the gradient refractive index multimode fiber is welded to the output end of the single-mode fiber, the anti-resonance hollow-core fiber is welded to the output end of the gradient refractive index multimode fiber, and the gradient refractive index multimode fiber and the anti-resonance hollow-core fiber are welded to the output end of the gradient refractive index multimode fiber. According to the AR-HCF-based cavity enhanced spectral absorption gas detection system, the gas sensing unit is of an all-fiber structure, so that the AR-HCF-based cavity enhanced spectral absorption gas detection system is small in size, high in electromagnetic interference resistance, low in cost and convenient to integrate.

This application discloses a code scanning method, electronic device, storage medium, and computer program product, relating to the field of image processing technology. The method includes, in response to a code update, identifying a changed file representing the code update and performing change dependency parsing on the changed file; if the parsing result indicates that the changed file has dependencies, then determining the dependent files corresponding to the dependencies based on the dependency graph corresponding to the changed file, wherein the dependency graph represents the logical dependencies between the application layer, business logic layer, and data processing layer; determining a change set containing the changed file and all dependent files, and scanning and analyzing the updated code of the changed file within the change set and the code in the dependent files that has a strong correlation with the updated code. This application improves the accuracy of code scanning.

Embodiments of the present application provide a medical image synthesis device and method. The method comprises: obtaining a first medical image and a second medical image; registering the first medical image and the second medical image; determining first parameter values of each pixel position on the registered first medical image and second parameter values of each pixel position on the second medical image; multiplying the first parameter values and the second parameter values on the same pixel positions of the registered first medical image and the second medical image, and generating a synthesis image data according to the multiplication result. Therefore, the multiplication of the first parameter values and the second parameter values is equivalent to amplifying the difference of pixel values of the positions of normal tissue and lesion tissue, so that the contrast and resolution of the synthesis image are higher, thereby making the lesion area clearer and improving the lesion detection efficiency.

A target detection and tracking method and storage medium combining radar and infrared thermal imaging are disclosed. The method includes the following steps: Step S1: Acquiring millimeter-wave radar data and raw infrared thermal imaging data within a given space; Step S2: Performing imaging processing on the radar and infrared data respectively, removing background from the radar imaging results; Step S3: Performing time-dimensional registration on the infrared imaging results based on the radar refresh rate; performing CFAR detection processing on the matched results and clustering to output the target point cloud and centroid; Step S5: Using the transformation relationship between the spatial three-dimensional coordinate system and the infrared two-dimensional image coordinate system, obtaining the set of pixel positions of the target in the two-dimensional infrared thermal image; Step S6: Performing thermal feature calculation; Step S7: Outputting the target feature information. The storage medium is used to implement the above method. This invention has the advantages of simple principle, wide applicability, and high detection accuracy.

The application discloses an interferometric constellation orbit optimization method based on a second-order state transition tensor and belongs to the field of space technology. The method of the application is as follows: an orbit dynamics model and a configuration stability index model of an interferometric constellation spacecraft are established, an orbit deviation propagation expression is given based on a second-order state transition tensor, and a second-order analytical mapping expression of configuration stability of the interferometric constellation and initial orbit deviation is derived; an iterative deviation of the initial state of the spacecraft is given; an initial value of the constellation configuration with strong stability is obtained through iteration, the constellation configuration satisfying long-term stability is obtained through recursive initial value, the interferometric constellation is realized to be long-term stable according to the constellation configuration, and the detection precision of the interferometric constellation is improved. The application has the advantages of high-precision space measurement constellation configuration stability, high efficiency, is favorable for fast iterative optimization of the high-precision space measurement constellation configuration, and is favorable for improving the stability and detection performance of the high-precision space measurement constellation configuration.

The application provides a detector pixel structure and an electronic detector. The detector pixel structure comprises a semiconductor substrate, a first and a second conductive type heavily doped layer, an insulating layer, an upper electrode, a lower electrode, an electron channel hole electrode, a metal protection ring and a doped ring; the doped ring is located in the semiconductor substrate and outside the first conductive type heavily doped layer and is exposed on the first surface of the semiconductor substrate; the insulating layer extends from the surface of a non-detection area to the surface of the semiconductor substrate, and the upper electrode extends from the surface of the non-detection area to the surface of the insulating layer; the electron channel hole electrode is located on the sidewall of the semiconductor substrate and is electrically connected to the lower electrode at one end and extends to the side surface of the insulating layer at the other end; and the metal protection ring is located on the surface of the semiconductor substrate and outside the upper electrode. The application can effectively avoid the image distortion caused by the deviation of the electron beam propagation direction, reduce the leakage current of the detector, improve the breakdown voltage and thus improve the detection performance.

The application discloses a method for improving star detection capability by fusing energy and polarization information, and belongs to the technical field of star sensor detection. In order to solve the problem of insufficient star detection capability of a near-earth space all-time star sensor in a strong atmospheric background light interference environment, the star sensor integrated with a micro-polarization plate array is used to obtain four gray star images through one-time exposure of the sky; a polarization degree calculation value is calculated to obtain a polarization degree star image and determine a sky background polarization degree; a polarization degree segmentation threshold is set; the polarization degree star image is subjected to threshold segmentation to obtain a polarization degree star image segmentation result; a weight coefficient is determined according to the ratio of the radiant energy of the star and the sky background; the sky background polarization degree is compared, and the gray star image or the accumulated star image with the highest signal-to-noise ratio is subjected to weighted processing based on different conditions to obtain a final high signal-to-noise ratio star image after processing. The star detection capability is effectively improved.

The invention discloses a method for detecting small defects on the surface of lightweight steel, and belongs to the technical field of industrial machine vision. The method is based on an improved YOLOv8n architecture and cooperatively works through three core technical means: firstly, a Swin Transform module is introduced into a backbone network to model long-distance spatial dependence and suppress complex background interference; secondly, a high-resolution P2 detection branch is constructed, shallow details and up-sampling semantic features are fused, and microdefect characterization is enhanced through bidirectional refining circulation; finally, P2 exclusive adaptive threshold focus loss ATFL is adopted, threshold update is only limited to P2 detection branch samples, and precise optimization of difficult and tiny defects is achieved in cooperation with a gradient directional return mechanism. According to the scheme, the detection recall rate and the positioning precision of the tiny defects are effectively improved while the model parameter quantity is remarkably reduced, and high-precision and light-weight industrial deployment is realized.

The invention discloses a multi-base passive radar weak target detection method based on multi-channel space-time joint accumulation, and relates to the technical field of radar communication, and the method comprises the steps: constructing a multi-base passive radar system observation model, obtaining a direct wave signal and an echo signal, and carrying out the sampling and preprocessing of the direct wave signal and the echo signal; constructing a target detector, and updating the target detector into a simplified form expressed by the target motion parameters to obtain a first target detector; processing the first target detector by adopting a signal framing processing mode to obtain a second target detector; and processing and solving the second target detector by adopting a standard discretization mapping mode so as to realize detection of the weak target and obtain an estimation parameter of the weak target. According to the method, on the premise of ensuring relatively low calculation complexity, efficient collaborative accumulation of multi-channel signals is realized, and the detection performance of the system in a low signal-to-noise ratio and high maneuvering target environment is improved.

The invention provides an intelligent medical insurance compliance examination method and system based on graph retrieval enhanced generation, relates to the field of medical informatization and artificial intelligence, and solves the technical problem that recessive medical insurance violation behaviors with context dependence and structure combination cannot be effectively identified in the prior art. The method comprises the following steps: constructing a compliance knowledge graph; extracting clinical entities from the diagnosis and treatment records, and mapping the clinical entities to corresponding nodes in the compliance knowledge graph; based on the mapped clinical entity as a query starting point, executing multi-hop graph retrieval in the compliance knowledge graph to obtain a policy rule sub-graph related to the current diagnosis and treatment behavior, and generating a compliance review result through structured reasoning; constructing a violation risk propagation model based on the historical auditing data, and performing violation risk assessment on the diagnosis and treatment behaviors to obtain a risk early warning level; and generating an audit priority queue for the plurality of to-be-audited diagnosis and treatment records based on the violation confidence and the risk early warning level. The method and the device are used in a medical insurance compliance examination process.

The application provides a collimation system based on a MEMS mirror and a laser radar, the collimation system based on the MEMS mirror comprises: a laser emission unit for emitting a modulated laser beam; a front light beam shaping unit for shaping the laser emitted by the laser emission unit; a MEMS mirror scanning unit for scanning a field of view of a to-be-measured plane after resonant reflection of the light beam shaped by the front light beam shaping unit by using a MEMS mirror; and a rear collimation unit for performing secondary shaping on the light beam reflected by the MEMS mirror scanning unit, so that the edge light beam and the center light beam deflected by the MEMS mirror have equal optical paths at an entrance pupil of the rear collimation unit. The collimation system based on the MEMS mirror can improve the energy coupling efficiency of the system, reduce the beam divergence angle and the system volume, and make the ranging capabilities of the center field of view and the edge field of view uniform.

The utility model discloses a kind of equipment for the water-tight test of automobile lamps, it is related to automobile lamps detection technical field, including workbench, protective pad is fixedly installed on workbench, adjusting unit and clamping unit, adjusting unit is fixedly installed with sealing unit. Advantageous effect lies in the collaborative sealing of air bag and movable rod, in combination with the real-time regulation and control of air pressure sensor, ensure sealing effect, effectively reduce the influence of leakage on detection result, when detecting, the pressure change in the car lamp is compared with the reference pressure of contrast bin in real time, if the difference between the two exceeds the set threshold, determine that there is leakage in car lamp, reduce the interference of temperature fluctuation to pressure detection through temperature detection mechanism, can identify small leakage, reduce the error of detection, through vibration motor to vibrate car lamp on workbench, simulate the bump, vibration and so on in vehicle driving, stimulate the gap leakage caused by vibration, ensure the accuracy of detection result.

The application discloses a pipe network construction detection and repair system and method based on a ground radar and a robot, which comprises a robot body and a ground radar rotatable above the robot body, and further comprises a mud brushing mechanism arranged on the top of the robot body, which is used for cleaning the inner wall of the pipeline before the ground radar detects; a gap cleaning mechanism arranged in the mud brushing mechanism, which is used for cleaning the dirt in the gap of the pipeline; and a softening mechanism located on the gap cleaning mechanism, which is used for softening the dirt before the gap cleaning mechanism cleans, so as to avoid damaging the pipeline by the gap cleaning mechanism; and the mud brushing mechanism is arranged, so that the dirt on the inner wall of the detection area of the pipeline can be removed before the ground radar detects, and the detection accuracy of the ground radar is avoided from being affected by the dirt.

The invention discloses a methane smoke plume recognition and emission estimation method based on multi-constraint background selection, and belongs to the technical field of greenhouse gas remote sensing monitoring and hyperspectral inversion. According to the method, satellite-borne or airborne short-wave infrared hyperspectral observation data is subjected to preprocessing such as radiometric calibration, atmospheric correction and noise suppression, a multi-constraint background pixel screening model including same-column consistency constraint, spectrum slope consistency constraint and diffusion distance constraint is constructed, and a background spectrum library is automatically obtained; based on the background library, an enhanced matched filtering algorithm is adopted to extract the methane concentration enhancement amount, and the system deviation and the false alarm rate are remarkably reduced. A smoke plume area is accurately extracted through spatial filtering, morphological segmentation and connected domain analysis, and the methane emission flux is inverted by combining an integrated quality enhancement (IME) emission estimation model with meteorological wind field data.

The present application relates to the technical field of underground structure detection, and discloses a background noise empirical Green function interpolation method based on a conditional diffusion model, which comprises the following steps: collecting empirical Green function signals between station pairs formed by all seismographs in a target area and position coordinates of all seismographs as a training data set; inputting the empirical Green function signal containing noise, position coordinates of two seismographs in a station and a current denoising step number into a denoising neural network; taking the original empirical Green function signal in the training data set as a training target, inputting corresponding position coordinates of any two target points without seismographs into the trained denoising neural network, and generating an interpolated empirical Green function signal between the two target points. The method is more accurate than a traditional empirical Green function signal interpolation algorithm, can replace real observation data to a certain extent in a scenario where the number of seismographs is insufficient, and improves the underground structure detection capability.

This invention discloses a three-dimensional detection method and system for steel plate edge defects based on full-matrix capture-full-focus imaging, belonging to the field of ultrasonic non-destructive testing technology. The method includes: acquiring raw waveform data and encoder position information using full-matrix capture (FMC); performing three-dimensional reconstruction calculations using the full-focus imaging (TFM) method to obtain three-dimensional volume data; binarizing the three-dimensional volume data according to set edge geometric boundary conditions and generating a three-dimensional edge mask to extract candidate edge defect regions; calculating the three-dimensional defect volume and two-dimensional projected area of ​​the candidate edge defect regions and obtaining the ratio data; triggering an upgrade operation for the evaluation level of the candidate edge defect regions when the ratio data exceeds a set threshold, and outputting the evaluation result including the edge defect. This invention effectively eliminates the detection blind spots of traditional scanning of steel plate edge regions, truly reflects the three-dimensional spatial distribution of defects in the length, width, and thickness directions of the plate, and achieves highly reliable three-dimensional detection and quantitative evaluation of steel plate edge defects.

The application discloses a cross-medium Snell window edge peripheral vision imaging optical system, and belongs to the optical technical field. The system is sequentially composed of a pressure-resistant protection window G1, a light path folding mirror G2, a wedge-shaped mirror G3, a focusing lens group G4, a front fixed imaging group G5 and a rear fixed imaging group G6 from the object side. The system is adapted to a 2048*2048 high-resolution detector with a pixel size of 5.5 microns, and has a Snell window edge peripheral vision panoramic imaging function through a peripheral scanning mode. The application overcomes the technical bottleneck of the underwater air-to-Snell window edge peripheral vision imaging optical design, provides a static sealing panoramic scanning imaging and compact optical module, and provides a new solution for the underwater air-to-Snell window edge peripheral vision imaging detection of an underwater submarine.

This utility model discloses a rotary intelligent parcel sorting and security inspection integrated device, comprising: a ring-shaped rotating platform with a drive mechanism at its edge for driving the ring-shaped rotating platform to rotate around its own central axis; multiple parcel carrying units, each parcel carrying unit having a recessed shelf on its top and connected to a support box on the ring-shaped rotating platform; a support frame, coaxially sleeved on the outside of the ring-shaped rotating platform; a multi-module security inspection module group, which is set on the inner peripheral wall of the support frame, with its detection end facing the radial center of the ring-shaped rotating platform; an AI processing module, which is located on the top of the support frame, and the input end of the AI ​​processing module is electrically connected to the multi-module security inspection module group; and a sorting execution mechanism. This utility model has the following advantages: realizing all-round, blind-spot-free security inspection of parcels; improving sorting accuracy and efficiency; constructing an intelligent decision-making closed loop; optimizing spatial layout and operational stability; and enhancing environmental adaptability.