45results about How to "Realize high-precision detection" patented technology

The invention relates to the technical field of handbag material surface defect image detection, in particular to an environment-friendly handbag material surface defect image detection method and system, and the method comprises the following steps: obtaining image data of the surface of an environment-friendly handbag material; dividing the image data into a plurality of local areas; for each local area, extracting image features representing visual features of the local area; establishing a normal feature range of the local area, and continuously adjusting the normal feature range in combination with the environment information; comparing the current image feature with the continuously adjusted normal feature range to identify an abnormal region deviating from the continuously adjusted normal feature range; and according to the image feature mode of the abnormal region, natural textures and defects are distinguished, and defect information is output. According to the method, natural textures and real defects on the surface of the environment-friendly handbag material can be effectively distinguished, potential defects with low contrast and fuzzy edges can be identified, and the accuracy and reliability of detection are improved.

This invention relates to the field of industrial internet security technology, and discloses a method and system for evaluating industrial internet data security protection capabilities. The method includes acquiring network traffic logs and system response records; performing time-series correlation analysis and sequence causal relationship completion based on the logs and records to obtain a dynamic evolution sequence of attack behavior; constructing an attack path graph model and parsing the correlation structure based on the sequence to obtain an attack path correlation structure; identifying high-latency paths and calculating response time differences to obtain a set of high-latency paths; extracting time feature vectors and quantifying the similarity of protection effectiveness from this set to obtain a quantitative score for path protection effectiveness; combining the score and difference index to perform a comprehensive risk assessment of physical topology mapping and node cascade failure analysis to obtain the system's comprehensive protection weaknesses; and performing adaptive scenario reconstruction closed-loop verification based on the weaknesses. This method can achieve accurate evaluation and dynamic verification of system protection weaknesses in complex adversarial scenarios.

This invention discloses a multifunctional analyzer combining CL-LIBS-LA-ICP-MS, comprising a laser optical path module, an electronic excitation system, a spectral detection module, a sample chamber, and a mass spectrometry detection module. The laser optical path module includes a laser source, a beam adjustment system, a scanning galvanometer, and a coaxial microscopic observation system. The spectral detection module includes a light signal collection end, an echelle grating spectrometer, a gated camera, and a timing control module. Another aspect of this invention discloses an analytical method, comprising setting the environment to vacuum and performing CL imaging scanning; selecting a LIBS test area based on the CL imaging scan image and performing LIBS scanning; selecting a third test area based on the LIBS scan results, filling the sample chamber with carrier gas, and performing laser ablation mass spectrometry detection. This invention eliminates the positioning error caused by sample transfer between multiple instruments during combined techniques, provides more comprehensive information on the structure and composition of the sample, and further improves the detection efficiency of the entire method through two screening test ranges.

This application relates to a high-precision visual inspection system and method for product sides, belonging to the technical field of visual inspection. It includes a worktable, a light source, a vision camera, and reflectors. The worktable has an inspection area for placing the product. The light source illuminates the side of the product within the inspection area. The vision camera is positioned above the inspection area. Several reflectors are obliquely arranged on the worktable, each corresponding to a side of the product within the inspection area. The reflectors are located to the side of the corresponding side of the product. When the light source illuminates the side of the product, the light reflected from the side is reflected by the reflectors to the central area of ​​the vision camera. This application achieves high-precision inspection of all sides of a product under single-vision camera conditions, reducing equipment cost and size.

The application discloses a radar voice interaction control method and system based on natural language processing, relates to the technical field of voice recognition, and solves the technical problems that it is difficult to combine radar echo signals with hyperspectral image data to detect target states, it is difficult to realize voice interaction control by using natural language processing, it is difficult to reasonably determine the priority of control instructions based on an environment comprehensive coefficient and an emergency degree value, it is difficult to establish a conflict detection mechanism to ensure the feasibility of instructions, and it is difficult to execute instructions under the conditions of multi-target game and dynamic priority change and monitor and evaluate deviation values to establish an error reporting mechanism. The application realizes target state detection by fusing radar echo signals and hyperspectral image data, realizes voice interaction control by using natural language processing, and dynamically generates hierarchical control signals in combination with an environment comprehensive coefficient and an emergency degree value.

The invention discloses a dexterous hand force tactile sensor structure, which belongs to the technical field of tactile perception of robot dexterous hands, and comprises a first force arm, a second force arm, a contact slide rail and a fiber grating sensor, distances between hinge points of the first force arm and the second force arm and same-direction ends of the first force arm and the second force arm are equal; one side of the first force arm and one side of the second force arm are slidably connected with the contact sliding rail and correspondingly connected with the two ends of the elastic element. The fiber grating sensor is connected with the other sides of the first force arm and the second force arm; according to the invention, the fiber grating is used as a core sensitive element, and the two ends of the fiber grating sensor are synchronously triggered by matching the two force arms which are arranged in a crossed manner with the contact slide rail, so that the problems of large size, poor durability, easy interference, poor precision and the like of a traditional electrical sensor in dexterous hand application are solved.

The utility model relates to the technical field of single crystal silicon rod detection, and provides a gantry type ground rail device for single crystal silicon rod detection, which comprises a ground rail mechanism, a gantry mechanism and a silicon rod rotating table, the ground rail mechanism comprises a base, a sliding rail and a sliding platform. Sliding rails are arranged on the two sides of the base respectively. A rack is arranged on the sliding rail; a sliding platform is arranged on each sliding rail; a servo motor is arranged on the sliding platform; gears are arranged at the output ends of the servo motors, and the gears are meshed with the corresponding racks; the gantry mechanism comprises a mounting plate and two gantry stand columns. The gantry stand columns are arranged on the corresponding sliding platforms, and a mounting plate is connected between the two gantry stand columns. The mounting plate is used for arranging a visual acquisition system; and the silicon rod rotating table is arranged on the base. According to the utility model, the measurement in a full-length range can be realized, and the stability of the visual acquisition system during automatic image data acquisition is ensured.

The application discloses a weak pressure detection method and system, which comprises a piezoelectric pressure sensor, a piezoresistive pressure sensor, a piezoelectric pressure sensor charge amplification filter circuit, a piezoresistive pressure sensor full-bridge amplification filter circuit, an analog switch circuit, an ADC conversion circuit and a processor; the piezoelectric pressure sensor charge amplification filter circuit comprises a charge amplification circuit, a follower and an amplification filter circuit; the piezoresistive pressure sensor full-bridge amplification filter circuit comprises a sensor full-bridge circuit and a differential amplification filter circuit; the input end of the analog switch circuit is electrically connected with the output end of the differential amplification filter circuit and the output end of the amplification filter circuit respectively, and the output end of the analog switch circuit is electrically connected with the input end of the processor. The application can adapt to signal frequency, simultaneously cover static and dynamic pressure detection, and realize high-precision weak signal extraction in a strong noise background.

The application is suitable for the technical field of gear defect detection, and provides a defect detection method and a detection system for PEEK gear production, which comprises the following steps: S1, after the workpiece is completed injection molding production, multi-modal data acquisition is performed on the workpiece; S2, defect analysis is performed on the workpiece according to appearance data and internal data; S3, the workpiece is sorted, when the workpiece is marked as a qualified workpiece, when the workpiece is marked as an unqualified workpiece, a triple screening mechanism is triggered to judge whether the workpiece needs to be repaired; S4, defect data of all the unqualified workpieces in the production process of the batch is recorded, and defect distribution data of the batch production is counted based on the defect type; and S5, a multi-objective optimization function is called to obtain production process parameters of the next batch production according to the updated prediction model M. The application guarantees the quality of the workpiece and improves the material utilization rate and production efficiency under the premise of reducing the waste of PEEK material.

The application discloses a fault detection method and device based on graph structure difference and electronic equipment, and relates to the technical field of intelligent monitoring. The method comprises the following steps: acquiring an observation data vector of a physical system to be monitored at time t, a linear mapping matrix and an upper state matrix vector, the observation data vector being determined by collecting sensing data of the physical system to be monitored in real time, and the linear mapping matrix and the upper state matrix vector being constructed based on a basic structure model, operating parameters and predictive input of the physical system to be monitored; constructing an optimization problem objective function at time t based on the observation data vector, the linear mapping matrix and the upper state matrix vector at time t; obtaining a sparse difference vector at time t by solving the optimization problem objective function at time t; comparing the sparse difference vector at time t with a threshold value to obtain a fault detection result, and sending a control instruction to a system controller. The method can improve the accuracy of fault diagnosis.

The present application relates to a kind of tunnel fire detection method, device and medium, wherein the method comprises the following steps: obtaining historical tunnel sensor dataset and constructing tunnel fire image dataset;Three-stage neural network architecture including trigger network, risk assessment network and complete detection network is constructed, trigger network carries out all-weather abnormal monitoring to the whole tunnel;Risk assessment network is activated when potential risk is detected by trigger network;Complete detection network is activated when high risk is determined by risk assessment network;The three-stage neural network is trained using historical tunnel sensor dataset and tunnel fire image dataset, and the trained fire detection model is obtained;Real-time acquisition tunnel video and sensor data, input trained fire detection model, and obtain tunnel fire detection recognition achievement.Compared with prior art, the present application solves the problems of low tunnel fire detection accuracy, serious waste of computing resources, insufficient real-time performance and high false detection rate.

This invention relates to a universal contour detection device and assembly method for assisted robotic optical processing, belonging to the field of advanced optical manufacturing technology, and solves the technical problem of the lack of an in-situ high-precision detection device in the optical processing of large-aperture mirrors by robotic arms in the prior art. The contour detection device includes: a workpiece turntable and a swing-arm air-floating turntable; a workpiece table is provided on the upper surface of the workpiece turntable; the workpiece to be measured is placed on the workpiece table; the upper end of the swing-arm air-floating turntable is connected to the end effector of the robotic arm via a quick-change detection fixture; the lower end of the swing-arm air-floating turntable is connected to the arm via an arm fixture; a probe is provided at one end of the arm, which is located near the upper surface of the workpiece to be measured. In the contour detection device of this invention, the end effector of the robotic arm remains stationary during the measurement of the optical element's surface shape; compared to the measurement mode of a moving probe at the end effector, the accuracy and stability of the robotic arm in the stationary state are better.

The invention discloses a multi-light-intensity scanning measurement method for nano-particle tracking analysis. According to the method, scanning measurement is carried out on the same sample according to a plurality of preset laser power gears in sequence, and particle scattering signals and motion trail data under different light intensities are obtained; processing the data under each light intensity to generate a concentration distribution curve, and evaluating a light intensity measurement result to determine the adaptive measurement light intensity of each particle size peak; and finally, aiming at the components with different particle size spans, carrying out data merging by adopting a'long-distance peak direct splicing 'strategy and a'neighbor peak weighted smooth fusion' strategy respectively. According to the invention, the problem of deviation caused by weak small particle signals and easy saturation of large particles during single light intensity measurement of a wide-distribution sample is solved.

The utility model provides a portable formula can manual regulation's track detection dolly relates to track detection technical field, including connecting rod one, the both ends fixed mounting of connecting rod one has the car body. The utility model discloses a 6x6 capacitor sensor matrix is installed in the car body bottom, can more accurately detect the damage condition of track surface and inside, cooperate the image information that OpenMV camera gathers, control terminal comprehensive analysis, has improved the accuracy of track damage identification greatly, effectively solved the problem of low detection accuracy of existing track detection car, in addition, through adopting hand -operated lifting wheel, the staff can manually adjust the distance between car body and track according to track height, make the dolly can nimblely adapt to the track detection demand of different height, at the same time, the flexible rotation of the OpenMV camera driven by the steering wheel can realize multi -angle detection and obstacle avoidance, greatly enhanced the flexibility of track detection dolly work in different track environment.

The utility model discloses a kind of nonwoven fabric weld detection equipment, it is related to automatic detection technical field, including conveying system, detection system, rejecting mechanism, stacking mechanism and man-machine interactive system, characterized by, the conveying system includes air suction belt, conveying belt support and base, air suction belt is set on conveying belt support and is fixed by base, adjustable conveying belt is further equipped on conveying belt support, the detection system includes shadowless lamp box and visual detection device, shadowless lamp box is installed above conveying system, visual detection device is located below shadowless lamp box and is connected with control system by output pivot, the rejecting mechanism includes flap and defective product box. A kind of nonwoven fabric weld detection equipment provided by the utility model, by the combination of shadowless lamp box and visual detection device, high-precision detection to nonwoven fabric weld is realized, and the reliability of detection is significantly improved.

The application discloses a bimodal fusion intelligent cotton foreign fiber sorting system and method, and belongs to the field of foreign fiber sorting technology.The sorting system comprises a shell, an image acquisition module, an image processing module, a conveying module and a rejection module, and specifically comprises an LED light source, a polarization camera, an RGB camera, an industrial computer, a camera support, a cotton flow channel, a spray valve control board and a high-speed spray valve.Cotton flow enters the cotton flow channel through a cotton inlet pipeline, image data is transmitted into the industrial computer through the image acquisition module, a detection result is quickly obtained through algorithm processing of the image processing module, and the high-speed spray valve is driven by the spray valve control board according to the detection result to remove foreign fibers.The application can realize real-time detection and removal of foreign fibers in cotton, and greatly improves the detection speed and accuracy.

The application discloses a kind of low-dose CT image denoising and multi-dimensional auxiliary diagnosis system based on large model belongs to medical image intelligent processing and man-machine interaction technical field.The system fuses large language model and double space alignment denoising module, lightweight multilevel anomaly detection module, single Agent-oriented medical scene man-machine interaction architecture, and integrates three major subsystems such as front-end, background algorithm and database management and communication interface, realizes from low-dose CT image denoising, anomaly detection to intelligent interactive diagnosis end-to-end integrated processing.Through introducing LLM semantic injection, double space constraint denoising, cross-modal feature alignment and dynamic iterative optimization etc., effectively overcome the imbalance of noise suppression and detail preservation in traditional method, weak model generalization ability, diagnosis process fragmentation and interaction unfriendly etc., significantly improve the diagnosis efficiency and accuracy, reduce the clinical use threshold, suitable for low-dose CT intelligent auxiliary diagnosis scene of medical institutions at all levels.

The application discloses a dynamic power quality disturbance signal detection method, device and medium, and the method steps comprise the following steps: S01, acquiring a dynamic power quality disturbance signal to be detected; S02, dividing a signal frequency band, and performing time-frequency analysis on the dynamic power quality disturbance signal by using an improved variable resolution S transform method; the improved variable resolution S transform method is an S transform based on a Gaussian window, and a Gaussian window scale factor is used to optimize the Gaussian window function; S03, performing a synchronous squeezing rearrangement operation on the improved variable resolution S transform result, so that energy components scattered in adjacent frequency intervals are aggregated to real frequency axis positions, and a time-frequency matrix after synchronous squeezing rearrangement is obtained; and S04, detecting signal components of the time-frequency matrix after synchronous squeezing rearrangement. The application can reduce energy diffusion and realize high-precision detection of non-stationary multi-scale complex dynamic power quality disturbance signals.

This utility model provides a keyboard appearance inspection device, belonging to the field of keyboard manufacturing technology. It includes a support assembly comprising a housing, a support platform fixedly connected to the top of the housing, a support plate fixedly connected to the middle of the support platform, and a positioning mold seat slidably connected to the side wall of the support plate. The inspection assembly includes a column fixedly connected to the side wall of the support platform, a main support rod installed on the side wall of the column, a main extension rod fixedly connected to the end of the main support rod, a connector fixedly connected to the end of the main extension rod, and a vision sensor adapted to be installed in the middle of the connector. The advantages of this utility model are: through the combined use of the support assembly and the inspection assembly, along with an adjustable-angle vision sensor, high-precision inspection of the keyboard appearance is achieved. The entire inspection process can be completed with simple operation, effectively preventing interference from external dust and light. The equipment can adapt to the inspection needs of keyboards of different sizes and models, and has good scalability.

The invention provides a testing method, device, equipment, medium and system for a testing structure on a wafer, and relates to the technical field of semiconductor testing. The method comprises the following steps: acquiring a test structure coordinate file of a wafer to be tested; the test structure coordinate file comprises identification characters and identification positions of a plurality of test structures on the wafer to be tested, and the identification positions are positions of the identification characters on the corresponding test structures; according to the identification positions of the plurality of test structures, acquiring detection images of the plurality of test structures by using an image acquisition device; and testing the test structure according to the detection image of the test structure. According to the invention, a test automation process framework is established, high-precision detection of the test structure coordinates is realized while manual intervention is reduced and detection time consumption is reduced, the problems of needle kneeling, wafer scratching, test data abnormity and the like caused by coordinate deviation are avoided, and the wafer delivery yield is guaranteed.

This utility model relates to the field of tunnel lining crack detection technology, and discloses a portable laser scanning detector for high-pressure tunnel lining crack width. The detector includes a housing with a mounting groove on the top wall. A camera is fixedly mounted on the top of the housing via the mounting groove. A mounting frame is fixedly connected to the middle of the inner wall of the housing, and a connecting groove is provided on the top of the mounting frame. A scanning module is fixedly mounted on the top of the housing via the connecting groove. A laser emitting module is fixedly connected to the left side of the bottom wall of the mounting frame, and an image processor is fixedly connected to the right side of the bottom wall of the housing. In this utility model, the reflected light from a high-precision laser beam is captured by the camera, and the image processor then analyzes the crack width, thereby achieving high-precision detection of crack width in high-pressure tunnel lining. The integrated design improves portability and makes it suitable for the complex environment of high-pressure tunnels.

The utility model belongs to the technical field of auxiliary fixing tools, and provides a speed sensor auxiliary tool for a 27.5 KV vacuum circuit breaker test, which comprises an upper fixing piece, a right-angle positioning plate is fixedly connected to the top surface of the upper fixing piece, a strip-shaped connecting groove penetrates through the surface of the upper fixing piece, and a first fixing groove is formed in the side wall of the right-angle positioning plate; four groups of second fixing grooves are symmetrically formed in the surface of the lower fixing piece, and four groups of connecting holes are further formed in the surface of the lower fixing piece; according to the utility model, through the arrangement of the upper fixing member and the lower fixing member and the cooperative constraint of the two groups of fixing members, the axial offset of the transmission rod of the sensor is greatly reduced, the installation precision is greatly improved, and the high-precision detection of the dynamic parameters of the vacuum circuit breaker is realized through replacing magnetic adsorption with mechanical coupling and combining an adjustable long groove structure and a dynamic compensation mechanism.

The invention relates to an automatic driving system distribution external detection method based on class specific channel activation difference, and the method comprises the steps: extracting an input feature of a deep neural network model in front of a global average pooling layer, and obtaining a feature tensor; dynamically selecting a channel subset which is most relevant to and most contradictory to the prediction category according to the weight of the classification layer; calculating activation intensity indexes and space consistency indexes of positive and negative channels; fusing the indexes to form a detection score, and judging whether the sample is an out-of-distribution sample or not. The method has the beneficial effects that the high-precision detection of the automatic driving system is realized by quantifying the activation symmetry damage degree of the class-related channel and the class contradictory channel in the model, and the method does not need to modify the model training process or depend on auxiliary data, so that the calculation overhead is low.

The invention provides a dam micro crack detection and dynamic trend prediction method. According to the method, high-resolution images of the dam surface are shot through unmanned aerial vehicle cruising, and a two-dimensional data set is constructed; an improved YOLOvll small target detection model is adopted to extract spatial positions and scale parameters of the cracks, a crack time sequence matrix is established, and spatio-temporal evolution of the cracks is recorded; the time sequence matrix is input into a pre-training mask auto-encoder for masking and reconstruction, and the future evolution trend of the crack is predicted; and according to a prediction result, extracting length, width and area changes of the crack, calculating a risk index through a weighted risk scoring model, and finally outputting a risk level and a spatial distribution diagram of the crack. According to the method, crack identification and time sequence modeling are combined, an integrated solution is provided, the crack detection precision and stability are improved, the crack evolution trend prediction capability is enhanced, and technical support is provided for dam safety monitoring and management.

The present disclosure relates to the technical field of citrus detection in agricultural automation, and particularly relates to a citrus detection method based on a frequency domain aggregation attention mechanism and a multi-scale encoder. The method proposes an innovative detection framework for small target and occluded target detection problems, including a frequency aggregation attention network (FAN) and a multi-scale Transformer encoder. The frequency aggregation attention network decomposes the feature map through two-dimensional discrete wavelet transform to enhance the frequency domain features of small targets and occluded targets; the multi-scale Transformer encoder combines convolution feature pyramid operation and retains high-frequency detail information through a wavelet fusion module. In addition, an IoU-aware query selection and an optimized loss function are used to significantly improve detection accuracy. Through frequency domain feature enhancement and multi-scale feature fusion, the present disclosure realizes high-precision detection of citrus fruits, especially small targets and occluded targets, and is suitable for fruit grading, yield statistics and other scenes in the field of intelligent agriculture.

The application discloses an environmental noise source positioning and classification method based on Bayesian inference, and belongs to the technical field of environmental noise detection. The steps are as follows: a dynamic noise threshold is set, and whether the noise exceeds the threshold is detected through noise time-frequency domain joint detection; a spherical acoustic array is used for noise source positioning; noise source identification and classification are carried out based on a noise target classification model to obtain the probability of each noise category; and the positioning result and the classification result are fused based on Bayesian inference to obtain the final noise classification result. The application improves the accuracy of noise monitoring, realizes accurate noise source positioning, improves the reliability of noise classification, enhances the robustness and adaptability of the system, and has a wide application prospect.

The utility model relates to the technical field of workpiece detection, in particular to a tensile machine for workpiece detection, which comprises a detection table, side guide rods are fixedly connected to the left side and the right side of the top end of the detection table, an upper clamp body is fixedly connected to the top ends of the side guide rods, and a conical block is fixedly connected to the middle position of the bottom end of the upper clamp body. According to the tensile machine for workpiece detection, through the arrangement of the first hydraulic telescopic rod, the push block, the upper sliding plate, the lower sliding plate, the clamping opening, the limiting square block, the guide column, the spring and the adapter block, the tensile machine for workpiece detection can be convenient to carry out detection work before the tensile machine for workpiece detection is carried out, and when a workpiece to be detected needs to be vertically placed, the workpiece to be detected can be conveniently and rapidly placed. Under the connection limitation of the conical block and the side guide rail, the auxiliary deviation rectifying structure is used for performing auxiliary deviation rectifying on the to-be-detected workpiece needing to be vertically placed, and the problem that the to-be-detected workpiece is obliquely placed after being placed due to misoperation is avoided.

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 utility model provides a kind of sensor and electronic equipment, it is related to sensor field.Sensor includes: substrate, resistance sensing layer, capacitance sensing layer, pressure sensitive layer and contact layer.Resistance sensing layer is set on substrate.Capacitance sensing layer is set on the side of resistance sensing layer away from substrate, and capacitance sensing layer includes at least one hollow structure, and at least one hollow structure extends from the side of capacitance sensing layer close to resistance sensing layer to the side of capacitance sensing layer away from resistance sensing layer.Pressure sensitive layer is set on capacitance sensing layer, and is filled into at least one hollow structure, and pressure sensitive layer is contacted with the side of resistance sensing layer away from substrate by at least one hollow structure.Contact layer is set on pressure sensitive layer, and is configured to generate deformation under the action of external force, to transmit external force to pressure sensitive layer.

The application discloses a kind of pressure pipeline elbow defect detection methods, it is related to pipeline inspection detection technical field, it is based on annular transducer array waveguide excitation and reception and fuses deep learning technology, can adapt to the fine, efficient and intelligent development of complex structure area corrosion damage detection.The pressure pipeline elbow defect detection method comprises the following steps: step S1, measures pipeline curvature radius, outer diameter and wall thickness;Step S2, arrange sensor array and collect pipeline defect data;Step S3, calculate the dispersion data of pipeline waveguide;Step S4, iteration inversion pipeline real defect size.