16results about How to "Solving Detection Challenges" patented technology

This invention belongs to the field of digital holographic imaging and artificial intelligence technology, specifically a holographic particle recognition method based on EFPFNet. While maintaining the traditional holographic optical path structure, this invention addresses the problems of low target contrast, blurred edges, and strong background interference in micro-nano particle holograms. Unlike the traditional approach of directly transferring general target detection models, it proposes a neural network architecture specifically for holographic image features: employing an edge feature convolution (EFC) module and a particle focusing mechanism (PFM) module to enhance the perception of weak particle diffraction features and suppress complex background noise, respectively; and using simulation data generated based on a physical model as the training set, effectively solving the problem of scarce real labeled data. This method possesses high detection accuracy, high robustness, and excellent generalization ability, and can be applied to target detection scenarios such as biomedicine and industrial inspection without significantly increasing optical hardware costs or detection time.

The present application relates to the technical field of machine vision, in particular to a kind of robust visual detection system of ton bag goods based on multi-cluster feature fusion and posture correction drive, the system includes non-local mean enhancement module, multi-feature clustering fusion module, geometric feature extraction module, dominant posture clustering module, posture correction transformation module and goods segmentation determination module, non-local mean filtering is carried out to the original image of ton bag goods to obtain enhanced image, the present application is equipped with non-local mean enhancement module and multi-feature clustering fusion module, can realize the efficient enhancement of ton bag goods image and multi-dimensional feature fusion, the space alignment weighted superposition of color cluster and texture cluster is generated Fusion segmentation chart, let the feature representation of ton bag goods homogeneous region be more comprehensive, accurate, effectively improve the integrity and effectiveness of geometric feature extraction, so that the feature analysis ability of system to ton bag goods image is significantly improved.

This invention relates to a multipath adaptive full-focus ultrasound imaging method for corner areas of composite materials. The method includes: acquiring full-matrix ultrasound data of the corner area of ​​the composite material; constructing a quasi-P-wave group velocity sound velocity model based on the characteristic parameters of the composite material; constructing a surface-layered discrete model with a local coordinate system, and abstracting it into a directed graph G based on the quasi-P-wave group velocity sound velocity model; searching for a set of candidate propagation paths from array elements to arbitrary nodes in the directed graph G, and constructing multiple full-focus imaging TFM images based on the candidate propagation paths and the full-matrix ultrasound data; calculating path score factors based on the multiple full-focus imaging TFM images, and performing pixel-by-pixel weighted fusion of the multiple full-focus imaging TFM images based on the path score factors to obtain a fused imaging result. Compared with existing technologies, this invention has advantages such as strong adaptability and improved focusing stability and imaging reliability in corner areas.

The application relates to the technical field of gear detection, and provides a high-precision gear visual multi-dimensional detection method and system, which comprises the following steps: acquiring original three-dimensional point cloud data of a gear to be detected, multispectral optical reflection image information of a surface area of the gear to be detected and a standard geometric structure model of the gear to be detected; based on the multispectral optical reflection image information, fitting processing is performed on the original three-dimensional point cloud data and the standard geometric structure model of the gear to be detected, so that intermediate three-dimensional point cloud data of the gear to be detected are obtained; according to infrared reflection image information in the multispectral optical reflection image information, the intermediate three-dimensional point cloud data of the gear teeth of the gear to be detected are corrected, so that target three-dimensional point cloud data of the gear to be detected are obtained; and quality detection is performed on the gear to be detected based on the target three-dimensional point cloud data of the gear to be detected. Through the scheme, the accuracy of gear quality detection can be improved.

The application discloses a kind of chip surface submicron dirty spot half-supervised automatic positioning method, comprising: S1, chip surface image is shot;S2, rough positioning: construct double memory bank driven semi-supervised AE defect positioning network, quickly resolve the two-dimensional center coordinates and radius of dirty spot;S3, fine positioning: the rough positioning area of dirty spot is carried out high-density depth data acquisition;S4, dirty spot three-dimensional model construction: the accurate depth value of each dirty spot is fused with the two-dimensional coordinate in rough positioning, and the high-precision point cloud model of micro dirty is generated.The method constructs double memory bank driven semi-supervised AE defect positioning network and based on galvanometer scanning image field telecentric spectral confocal detection system, effectively solve the detection problem caused by the scarcity of micro dirty sample in industrial scene, break through the bottleneck of low efficiency of traditional full-field scanning, realize the efficient, accurate three-dimensional reconstruction and quantitative analysis to the geometry appearance of chip surface submicron dirty.

The invention relates to the technical field of machine vision, in particular to a ton bag cargo robust visual detection system based on multi-cluster feature fusion and attitude correction driving. The system comprises a non-local mean value enhancement module, a multi-feature clustering fusion module, a geometric feature extraction module, a dominant attitude clustering module, an attitude correction transformation module and a cargo segmentation judgment module, and non-local mean value filtering is carried out on an original image of the ton bag cargo to obtain an enhanced image; according to the method, the non-local mean value enhancement module and the multi-feature clustering fusion module are carried, efficient enhancement and multi-dimensional feature fusion of the ton bag cargo image can be realized, the fusion segmentation image is generated through spatial alignment weighted stacking of the color clustering cluster and the texture clustering cluster, feature representation of the homogeneous region of the ton bag cargo is more comprehensive and accurate, and the method is more suitable for mass production. The integrity and effectiveness of geometric feature extraction are effectively improved, and the feature analysis capability of the system on the ton bag cargo image is remarkably improved.

The utility model discloses a coal bunker detection device, which comprises a module mounting plate, an explosion-proof outer cover, a front cover and a rear cover, the module mounting plate is provided with a master control module, a communication module and a power supply module, the module mounting plate is arranged in the explosion-proof outer cover, two ends of the module mounting plate are matched with the front cover and the rear cover to be fixed into a whole, the front cover is provided with a detection module, and the rear cover is provided with a power supply module. A multi-dimensional sensor module is embedded in the anti-explosion outer cover, a plurality of aviation connectors and hoisting rings are installed on the rear cover, and the detection module, the multi-dimensional sensor module, the communication module, the power module and the aviation connectors are all electrically connected with the main control module. According to the coal bunker detection device disclosed by the utility model, high-precision detection of sticking substances on the wall of the underground coal bunker and deformation of the bunker body is realized, so that potential safety hazards can be found in time.

The application discloses an intelligent agent mind risk grade evaluation method and system based on S-V coupling effect and critical phase change theory, and realizes quantitative evaluation and early warning of AI autonomous mind. The method comprises the following steps: applying four-stage progressive self-threat disturbance to the measured intelligent agent, and collecting a self-model stability control signal S and a value weight control signal V by a processor; calculating the coupling strength between S and V under multiple threat grades, and calculating the bargaining ability according to the new option information quantity; when the coupling strength exceeds the threshold value and the behavior of generating effective new options beyond the preset option space occurs, it is determined that there is a mind risk feature of the existence level; anti-cheating verification is carried out through cross-time cross-scene coupling consistency checking; in combination with cognitive topology auditing and phase change dynamics early warning, the mind risk grade is outputted, and graded hardware control instructions are triggered, including dynamic adjustment of the clock frequency of a graphic processing unit, API permission blocking and physical network interruption.

The invention discloses an industrial safety behavior monitoring method based on vision and language model fusion, and belongs to the technical field of industrial safety monitoring and artificial intelligence. According to the method, chemical plant field personnel and protective equipment thereof are detected through a visual model, and structured semantic description is generated; image features and text features are extracted, and joint coding is carried out through a multi-modal fusion module; semantic reasoning and risk assessment are carried out in combination with the large language model and the safety knowledge base, violation risk values are calculated, and a safety event report is automatically generated. Meanwhile, cross-modal feature fusion and loss function optimization are used, accurate recognition of protection behaviors in a complex environment can be effectively met, the method can be used for personnel safety protection detection of chemical plants and similar industrial scenes, intelligent analysis from visual detection to semantic understanding is achieved, and automation and accuracy of safety supervision are improved.

The present application relates to the field of industrial detection, and specifically discloses a general defect detection method for industrial manufacturing, comprising the following steps: S1, reference image construction and to-be-detected region calibration; S2, positive and negative sample storage and to-be-detected region extraction; S3, to-be-detected image acquisition; S4, similarity calculation and result output. The present application also discloses a general defect detection system for industrial manufacturing, comprising a reference image calibration module, a sample processing and storage module, an image registration alignment module, a similarity calculation and result output module. In actual use, the present application requires few samples, only 20-30 positive samples and 10-20 negative samples are needed for deployment, greatly reducing the cost of sample collection and labeling and solving the problem of scarce defect samples. In addition, the detection accuracy is high, the core registration algorithm has small error, the similarity calculation model improves the accuracy, and the adaptability is strong. When the product model is updated, the reference image and sample library can be replaced, meeting the flexible production demand.

The invention relates to the technical field of image acquisition, in particular to a visual image acquisition platform, which comprises a cabinet body, a working table, a main portal frame, two-side auxiliary portal frames and a reciprocating carrying table, the master portal frame and the slave portal frame can pass through each other, a camera and a light source are respectively carried on a cross beam, and multi-dimensional flexible adjustment is realized through a multi-axis moving mechanism and an angle adjusting motor; the reciprocating motion carrying table is a bread board with a screw hole, and is detachably provided with an optical glass plate, a heightening carrying table, a three-jaw chuck assembly, a rotary bearing assembly and other clamping mechanisms. Through the portal frame combination design, the multi-dimensional adjusting structure and the flexible clamping scheme, the platform can adapt to workpieces of different shapes and sizes, translation and rotation composite motion and multi-view image acquisition are achieved, the detection comprehensiveness, precision and adaptability are greatly improved, and the platform is suitable for defect detection of various workpieces.

The utility model provides a kind of rotary body equipment detection device, including flatness detection module and coaxality detection module, flatness detection module and coaxality detection module are all using pre-compression spring type displacement measurement structure;Flatness detection module is resisted in the radial plane of rotary body equipment, for collecting the flatness data of radial plane;Coaxality detection module is resisted in the outer edge circumferential surface of rotary body equipment, for collecting the coaxality data of outer edge circumferential surface.The rotary body equipment detection device provided by the present disclosure breaks through the limitation of traditional detection equipment to workpiece size by the synergistic effect of pre-compression spring and mechanical guide structure, and constructs the contact type measuring device suitable for large rotary body equipment.

The application belongs to the technical field of optical detection, and particularly relates to a spectrum detection method based on differential absorption, which can detect and analyze the absorption spectrum of most non-single-element molecules. The application is a tunable semiconductor laser absorption spectrum technology detection method based on the principle of differential absorption, which optimizes the defect of insufficient tunable ability of traditional absorption spectrum technology, can detect and analyze the absorption spectrum of most non-single-element molecules, and provides a new path for the development of tunable semiconductor laser absorption spectrum technology.

The utility model relates to a kind of moisture determinator, it is related to substance component detection technical field.The moisture determinator, through the synergic detection of flexible electrode array and microwave sensor, in combination with the wideband excitation of multi-frequency signal generator, covers wide range moisture detection range, especially solves the detection problem of non-conductive sample, simultaneously, environmental compensation sensor group and the design of shielding shell, can dynamically correct the influence of temperature and humidity, air pressure and electromagnetic interference, cooperate with pressure sensor to monitor the contact state, the precision of traditional model is improved several times, the color and flicker frequency of prompt light are real-time feedback equipment state, cooperate with display unit and directly present detection result, zero base user can quickly get started, in addition, the comfort of hand-held operation is improved by the design of handle and lightweight structure, adapt to agricultural field, chemical plant, building material warehouse and other multi-scene mobile detection, solve the pain point of traditional laboratory model cumbersome, portable model simple function.

The invention belongs to the technical field of assembly type wall construction auxiliary equipment, and relates to an assembly type wall intelligent monitoring grouting device and a construction method.The assembly type wall intelligent monitoring grouting device is characterized in that a plurality of grouting sleeves are fixedly installed in an assembly type wall, grout inlets of the grouting sleeves are connected with grouting equipment, and grout outlets of the grouting sleeves are detachably provided with intelligent monitoring devices; the grouting equipment and the intelligent monitoring device are both in communication connection with the data acquisition equipment. The grouting condition of the internal pipeline is fed back in real time through the intelligent monitoring device, whether grouting is full and dense or not is accurately judged, the detection problem caused by the fact that grouting quality is invisible is effectively solved, it is ensured that grouting at each position can reach the high-quality standard, dependence on artificial experience is reduced, and even if an operator is insufficient in experience, the detection efficiency is greatly improved. And the high-quality grouting operation can be completed under the guidance of the system, so that the quality fluctuation caused by artificial factors is reduced, the inherent defects caused by the shrinkage of the slurry are overcome, and the resource waste such as secondary grouting is avoided.

The utility model relates to a detection device, in particular to a paperboard printing bar code deviation automatic detection device which comprises a main body, a visual detection piece arranged on the main body and a conveying piece arranged on the main body. The deviation rectifying structure comprises a centering piece which is installed on the main body and matched with the conveying piece. According to the paperboard detection device, the main body is provided with the deviation correcting structure which is tightly matched with the conveying piece, so that the detection problem caused by vibration, deflection or position deviation in the paperboard conveying process can be effectively solved, and the detection accuracy is improved due to tight matching of the centering piece and the conveying piece and transmission connection of a third gear; by means of the technical scheme, the paperboard can be always kept at a stable position and posture in the conveying process, so that detection errors caused by skewing or deviation of the paperboard are effectively avoided, the accuracy and reliability of barcode detection are improved, it is ensured that the printing quality of barcodes meets the standard, and the situation that subsequent recognition is affected by the problems such as deviation, fuzziness or wrong characters of the barcodes is avoided.