91results about How to "Detection speed" patented technology

The utility model relates to the technical field of agricultural machinery transmission system detection, and discloses an agricultural machinery transmission system intelligent running-in table which comprises an installation platform, a main power assembly is arranged on the rear side of the upper end of the installation platform, and a running-in tool is arranged in front of the output end of the main power assembly. A left loading assembly and a right loading assembly are arranged on the left side and the right side of the running-in tool respectively, a transmission axle to be tested is arranged on the running-in tool to be supported, the main power assembly is in transmission connection with the power input end of the transmission axle, and the two output ends of the transmission axle are in transmission connection with the left loading assembly and the right loading assembly respectively. According to the utility model, through the automatic design of the main power assembly, the left loading assembly and the right loading assembly, the full-process automatic operation from axle installation, power input to loading test is realized, and the main power assembly is driven by the first driving motor, the first gear and the first rack plate to automatically complete the butt joint with the input end of the axle. And the complexity and the time cost of manual operation are greatly reduced.

The utility model relates to the technical field of motor detection, in particular to motor gear run-out detection equipment. Comprising a rack and a pair of conveying assemblies at the upper end, the upper end of each pair of conveying assemblies is provided with a detection station used for containing a motor to be detected, the two ends of each conveying assembly are provided with linear scanning lasers fixedly connected to the rack, the tail end of each conveying assembly is provided with a grabbing assembly used for clamping and discharging, and the motors are transplanted to the detection stations. A contact pin is arranged in the jig, a product is electrified to rotate after being placed, and rotation of the gear can be controlled through contact between the contact pin and the motor gear, so that preparation is made for subsequent detection. According to the motor gear detection device, the motor gears on the two detection stations can be detected at the same time or in sequence, the detection efficiency is remarkably improved, the to-be-detected motor can be rapidly and accurately conveyed to the detection stations through the design of the conveying assembly, and the waiting time is shortened.

The invention provides a directional ship detection method and system based on joint attention. The method comprises the following steps: acquiring image acquisition data; performing feature extraction by using a backbone network to obtain a multi-scale feature map, performing feature re-calibration on the multi-scale feature map, and outputting an enhanced target feature map; carrying out convolution operation on the enhanced target feature map by adopting self-adaptive geometric convolution to obtain ship direction characterization information; generating a candidate frame based on the ship direction representation information, calculating intersection-parallel-ratio statistical characteristics in combination with a ship real frame, and performing training sample adaptive distribution according to the intersection-parallel-ratio statistical characteristics; based on an Anchor-free detection framework, carrying out ship orientation detection by utilizing the training sample subjected to self-adaptive distribution to obtain a ship orientation detection result; through multi-scale feature re-calibration, adaptive geometric convolution and dynamic sample distribution, the ship direction and features in a maritime monitoring scene can be captured, and the detection precision and real-time performance are improved.

The application discloses a cotton bale detection method based on multi-modal data timestamp synchronization and GPU / CPU collaborative acceleration, collects multi-modal data, marks timestamps, and performs GPU accelerated distortion correction on cotton bale images; the multi-modal data is synchronized and integrated according to timestamps; a main program adopts Nodelet combined with C++ multi-threading technology to process the reception of multi-modal data and the publication of multi-modal sensor coordinate systems in parallel, the main program running optimizes the transmission efficiency of multi-modal data; a cotton bale detection model is constructed, the optimized multi-modal data are input for training, the cotton bale detection model after training is optimized using TensorRT, and cotton bale images are input for inference, cotton bale target recognition data are obtained and transmitted to a CPU for post-processing operation, and OpenMP is used to accelerate point cloud traversal in the main program to match the cotton bale target recognition data with laser radar point cloud data; the matched multi-modal data are subjected to point cloud feature and plane fitting calculation, and the rectangular frame, pose information and score of the cotton bale target are obtained.

This invention discloses a method for detecting corn kernel breakage rate by incorporating an attention mechanism. This method further improves the lightweight one-stage object detection network YOLOv4-tiny by introducing a coordinate attention mechanism into the feature pyramid network to enhance the model's ability to detect dense corn kernels. Furthermore, an online mosaic data augmentation method is used during the model training phase to improve the model's ability to detect smaller-scale broken kernels. The method disclosed in this invention is easier to deploy on embedded platforms due to its low parameter size, and it has a high response speed while maintaining accuracy. It can efficiently detect the degree of corn kernel breakage and thus obtain the corn kernel breakage rate in real time.

The invention discloses a novel power system false data injection attack detection method based on CPO-CNN-SE. The method comprises the following steps: preprocessing a measurement test of a novel power system; performing hyper-parameter optimization by using a crown porcupine optimization algorithm (CPO) to improve the precision of the CNN detection model; meanwhile, in consideration of synchronous increase of the FDIA detection speed, a compression excitation (SE) attention mechanism is introduced, a CNN-SE mixed learning model is formed, and the characterization efficiency of the CNN on FDIA spatial features is enhanced; and finally, carrying out binary classification on the FDIA feature data through a full connection layer, a sigmoid classifier and a binary cross entropy loss function. According to the invention, the FDIA detection precision is improved, and the synchronous improvement of the detection speed is realized.

The utility model provides a kind of mixing device of arterial blood collector, including rotating shaft and the mixing assembly being fixed in its outside, and the side plate of polygon is respectively arranged in the two sides of rotating shaft and multiple bearing plates are fixed on side plate, the detachable blood gas needle loading plate is equipped on the bearing plate, and multiple detachable blood gas needle mounting clips are equipped on the blood gas needle loading plate;The blood gas needle mounting clip is detachably set on the bearing plate.By blood gas needle mounting clip detachably set on blood gas needle loading plate, and blood gas needle loading plate itself also detachably install in the design of bearing plate, effectively solve the core pain point of poor versatility of traditional mixing device.

The invention discloses a joint sorting QR decomposition method and related device for multi-antenna detection, and belongs to the technical field of multi-input multi-output signal detection, and the method comprises the steps: initializing an orthogonal matrix and an upper triangular matrix; acquiring a channel matrix H; extracting candidate columns from residual columns in the channel matrix H based on the sum of residual energy and self energy joint weighting, updating an orthogonal matrix and an upper triangular matrix according to the candidate columns until all columns in the channel matrix H are traversed, and obtaining a final orthogonal matrix and a final upper triangular matrix; and taking the final orthogonal matrix and the upper triangular matrix as a joint sorting QR decomposition result for multi-antenna detection, the method and the related device can shear out the nodes with the super radius as early as possible, reduce access nodes, and improve the speed of multi-antenna detection while ensuring the detection performance.

The application relates to the field of workpiece defect detection, and discloses a workpiece end face defect detection method and system based on deep learning, which comprises the following steps: acquiring an end face image of a machined workpiece, performing image enhancement and region marking on the end face image to obtain an end face enhanced image and an end face marked region, querying abnormal points corresponding to the end face marked region, calculating an image offset of the workpiece end face image in a preset direction, querying an image difference frame corresponding to the workpiece end face image according to the image offset, extracting pixel values of the image difference frame, calculating an image difference value of the workpiece end face image, performing classification detection on the workpiece end face image by using a preset end face detection model to obtain a classification image, identifying a defect region in the classification image, extracting region features, and performing defect detection on the workpiece end face image to obtain a defect detection result of the machined workpiece. The application can improve the detection efficiency of workpiece end face defects.

The application discloses a kind of positioning method and related equipment based on image, method includes: shooting environment, obtain the mark image for the positioning image of pre-set, wherein the positioning image includes DM code from inside to outside, circular mark and several mark blocks;Based on the circular mark, the mark image is carried out ellipse detection, and ellipse position information is obtained;According to the ellipse position information, the mark three-dimensional coordinates corresponding to the DM code are extracted;And, according to the ellipse position information, the block coordinate information corresponding to the mark block in the mark image is determined;According to the block coordinate information, the mark two-dimensional coordinates corresponding to the positioning image are calculated;According to the mark two-dimensional coordinates and the mark three-dimensional coordinates, the positioning information corresponding to the mark image is calculated.The application can significantly improve the speed and accuracy of positioning.

This utility model discloses a visual inspection device for nonwoven fabrics, comprising a main frame and feet and rollers fixedly installed at the bottom of the main frame. A roller assembly is sequentially arranged above the main frame for tightening and unwinding the nonwoven fabric. A light source mechanism is fixedly installed above the roller assembly. A support frame is fixedly installed above the main frame. A set of camera lenses is respectively installed at the bottom of the main frame and the top of the support frame. The camera lenses are fixedly connected to a camera height adjustment module. A connecting frame is fixedly installed on the right side of the support frame, and a labeling machine assembly is fixedly installed on the connecting frame. This utility model discloses a visual inspection device for nonwoven fabrics with high-precision recognition: through a high-resolution camera, optical sensor, and AI algorithm, it can detect minute defects (such as holes, stains, and uneven fibers) that are difficult to detect with the naked eye, with an accuracy down to the micrometer level, eliminating human error and ensuring the consistency and reliability of the inspection results.

The present application provides a ginseng quality nondestructive evaluation method based on hyperspectral and X-ray technology, belongs to the field of spectral analysis technology, and comprises the following steps: collecting information of a complete ginseng sample by using hyperspectral and X-ray technology, and integrating complementary information from the two devices by a modeling method of ensemble learning. The present application provides a fast, nondestructive and accurate ginseng quality evaluation method, and solves the problems of low accuracy of experience identification analysis, complex and time-consuming pretreatment of wet chemical analysis method, and difficulty in adapting to batch rapid detection due to sample crushing treatment of near-infrared spectral analysis technology.

This invention discloses a broadband non-contact terahertz near-field trace substance detection device and method. The device includes a vector network analyzer, a terahertz signal transmitter, an extended hemispherical lens, a trace substance detection chip, and a terahertz signal receiver. The terahertz signal transmitter includes a first terahertz S-parameter detection module, a first lens, a second terahertz S-parameter detection module, a second lens, a first frequency selective surface, and a first reflector. The terahertz signal receiver includes a third terahertz S-parameter detection module, a third lens, a fourth terahertz S-parameter detection module, a fourth lens, a second frequency selective surface, and a second reflector. The device and method disclosed in this invention use quasi-optical technology to achieve non-contact connection between the trace substance detection chip and the terahertz S-parameter detection module. Simultaneously, quasi-optical band splicing technology enables detection over a broadband range, which can improve the detection speed of the sample and achieve broadband non-destructive non-contact detection of the sample.

The application discloses a flaw detection device and method based on light-weight agricultural transmission shaft production and relates to the technical field of transmission shaft production.The application comprises a rack, a push plate type elevator is arranged on one side of the rack, a detection mechanism is arranged in the middle of the rack and is used for detecting the flaw of the transmission shaft, the detection mechanism comprises a conveying assembly, the conveying assembly comprises two supporting plates which are slidably arranged in the middle of the top end of the rack, and the driving motor is arranged on the supporting plate; the driving motor is used for driving the transmission shaft to be lifted from the rotating roller through the clamping groove when the moving frame is lifted, the transmission shaft is then horizontally conveyed to a working position and then is lowered and placed, the step-by-step one-by-one transfer of the transmission shaft is realized, when the rotating shaft rotates and conveys, the eccentric wheel at the end of the rotating shaft synchronously drives the outer shell body provided with the air knife to vertically reciprocate, the air knife moves to the lowest point when the transmission shaft is transferred to the cleaning working position and is placed, and therefore, the transmission shaft can be effectively cleaned at the best time while being continuously conveyed.

The application relates to the technical field of cable detection, and discloses a multi-channel cable on-off and line sequence automatic detection method and system, which comprises the following steps: loading a corresponding standard connection mapping relationship according to a received detection mode instruction, and configuring a single-chip microcomputer to generate a serial mask signal and a synchronous timing control signal; the single-chip microcomputer sends the serial mask signal to a cascaded shift register group, and the shift register group converts the serial mask signal into multi-channel parallel excitation levels under the driving of the timing control signal and sequentially injects the multi-channel parallel excitation levels into the input end of a measured cable. By adopting the technical means that the single-chip microcomputer configures the serial mask signal and the cascaded shift register group converts the serial mask signal into the multi-channel parallel excitation levels, the detection speed of the multi-channel cable is improved, and through bit-by-bit logical comparison and voltage amplitude double-threshold determination between a measured connection matrix and a standard mapping matrix, the accuracy and efficiency of fault identification are improved.

The present application relates to a biomedical image copy detection method, belonging to the technical field of digital information security, which can solve the problem of low accuracy, great detection difficulty and low efficiency of the image copy detection method in the prior art when used for biomedical image copy detection. The method steps of the present application are: S1, input the path of the query image set and the path of the reference image set; S2, input the query image set and the reference image set into the self-supervised image copy detection model to generate image feature vectors; S3, use the faiss library to construct the index of the image feature vectors in the reference image set; S4, traverse and calculate the minimum Euclidean distance between the image feature vectors of the query image set and the image feature vectors in the reference image set according to the index of S3; S5, obtain the suspected copy image pair based on the minimum Euclidean distance obtained in step S4; S6, judge whether the biomedical image is a copy image according to each suspected copy image pair.

The invention relates to the technical field of software engineering, in particular to a code detection method and device, electronic equipment and a storage medium, and aims to improve code detection efficiency and role perceptivity. Comprising the steps of obtaining a to-be-detected code and structured data of the to-be-detected code; the structured data is used for describing the function of the to-be-detected code; based on the task splitting agent and a plurality of preset detection angles, performing task splitting on the changed sub-codes and the structured data in the to-be-detected codes to obtain a plurality of detection sub-tasks corresponding to different detection angles; for any detection angle, executing a detection sub-task corresponding to any detection angle through a detection intelligent agent corresponding to any detection angle to obtain a detection sub-result corresponding to any detection angle; and inputting the plurality of detection sub-results and the information of the target detection role into the security field large model to obtain a target detection result of the target detection role corresponding to the to-be-detected code.

The invention discloses a black vehicle-oriented real-time point cloud fusion detection method, system and device, and a medium. The method comprises the following steps: step 1, obtaining point cloud data through a laser radar; 2, scanning the point cloud data, marking the continuous point cloud blocks with the reflection intensity of 0 as unlicensed car identifiers, and storing the unlicensed car identifiers in point cloud attribute positions; step 3, performing dual-thread compensation, performing clustering operation on the point cloud data set with the unlicensed car identifier by using DBSCAN, and performing imaging processing on a clustering operation result by using Point Pill to obtain a three-dimensional image model; forcibly outputting an unlicensed vehicle detection frame image according to an image processing result or improving the confidence coefficient as an unlicensed vehicle compensation confidence coefficient, and preferentially adopting a model result; when the two conditions do not belong to the above two conditions, performing weighted fusion on the operation result; and step 4, fusing operation results in the step 3 into a complete three-dimensional frame image. Therefore, the problem of missing detection is solved, and the detection rate and detection efficiency are improved.

The utility model provides a kind of fast detection wing angle instrument, including pedestal, inclination detection mechanism, and the pedestal is provided with the positioning part for installing and positioning wing and the installation part for installing inclination detection mechanism;Inclination detection mechanism includes four distance detectors, four distance detectors are all installed on the installation part of pedestal;Four distance detectors are divided into two groups of relative arrangement, and detection zone is formed between two groups of distance detectors, and two distance detectors in the same group of distance detectors are distributed upside down.This application carries out ranging to wing by four distance detectors respectively, the distance between corresponding distance detector and wing can be obtained, and the coordinates of distance detector can be calculated by known distance detector, and the coordinates of detection point on the wing corresponding to the distance detector are fitted into oblique line, the included angle between oblique line and median line is the inclination of wing, so that whether the inclination of the wing piece is qualified can be quickly judged.

The application discloses an online action detection method based on a light-weight Transformer, and comprises the following steps: setting a detection model, wherein the detection model is based on a Transformer model; acquiring features of a video stream with a length of T; inputting the features of the video stream into the detection model; and outputting an action category of the last frame of the video stream through the detection model as a detection result. The online action detection method based on the light-weight Transformer disclosed by the application reduces the calculation amount while improving the accuracy.

The utility model discloses a multifunctional reinforcing steel bar detection device which comprises a base, an electronic weighing module is arranged in the base, two brackets extend out of the top of the electronic weighing module, the brackets are used for lifting reinforcing steel bars to be detected, a detection table is fixedly installed on the top of the base, and the brackets penetrate through a through groove formed in the middle of the detection table. The top of the detection bench is provided with a length detection module for measuring a to-be-detected steel bar. The multifunctional reinforcing steel bar detection device can simplify the measurement process and the data processing process of the reinforcing steel bar to be detected, reduces errors caused by measurement and calculation, improves the data accuracy of the weight deviation of the reinforcing steel bar, and accelerates the detection speed of the reinforcing steel bar.

This invention provides a magnetic detection device based on diamond NV centers and the Kerr effect. It achieves the sharing of light sources and optical paths between magnetic detection technologies based on the magneto-optical Kerr effect and those based on NV centers, combining the two technologies and greatly simplifying the device structure. This increases the intensity of the optical signal received by the detection module, reduces noise interference in the signal, and thus improves the accuracy of magnetic detection. It can simultaneously meet the requirements of rapid and high-resolution detection, and improve the overall detection speed while ensuring detection accuracy.

This application discloses a method for dispensing samples and reagents, comprising: controlling a first element to perform a sample dispensing action, dispensing a sample to be tested into a reaction vessel, the sample dispensing action including at least a sample input action and a sample output action; while controlling the first element to perform the sample dispensing action, controlling a second element to perform a reagent dispensing action, dispensing a detection reagent into the reaction vessel, the reagent dispensing action including at least a reagent input action and a reagent output action; wherein the sample output action and the reagent output action are executed asynchronously. This method achieves parallel dispensing of samples and reagents, shortens the time consumed in the sample / reagent dispensing stage during sample detection, and improves the operating efficiency and sample detection speed of automated sample dispensing equipment.

This utility model discloses a surface defect detection device for rubber roller production, comprising a feeding assembly, a rotary drive assembly, a discharging assembly, and a vision inspection assembly. The feeding assembly includes a feed plate for the rubber rollers to be inspected, a feed lifting ramp, and a lifting assembly for orderly conveying the rubber rollers to be inspected. The rotary drive assembly includes an active drive shaft for roller rotation, a passive drive shaft for roller rotation, a roller rotation drive motor, and a drive shaft mounting bracket to ensure stable rotation of the rubber rollers. The discharging assembly includes a discharge lifting ramp and a collection trough for collecting the inspected rubber rollers. The vision inspection assembly includes a translational drive rail and a surface defect detection camera to achieve omnidirectional scanning of surface defects on the rubber rollers. This equipment has a high degree of automation, accurate detection, effectively improves the quality control level of rubber roller production, and ensures the surface quality of the rubber rollers.

The application discloses a pedestrian fall detection method based on mixed precision quantization and a storage medium, relates to the technical field of computer vision, and solves the technical problem that the mixed quantization precision model used in the existing pedestrian fall detection is difficult to achieve the best balance in model volume, precision and processing speed. The method comprises the following steps: S1, encoding a pedestrian neural network and quantizing the pedestrian neural network into a basic neural network; S2, initializing the basic neural network to obtain K different individuals, and performing selection and crossover operations; S3, performing game mutation operations; and S4, repeating steps S2-S3 until the iteration number reaches a preset maximum iteration number or the iteration termination condition is met, and obtaining an optimal mixed precision quantized pedestrian neural network model. The genetic algorithm improved by the game theory algorithm can make the model after mixed precision quantization achieve the best balance in model volume, precision and processing speed.

The embodiment of the utility model relates to the technical field of test fixtures, and particularly discloses a test fixture, which comprises a substrate and a connector, and is characterized in that the substrate is provided with a plurality of test point positions; the connector is arranged on the substrate, the connector is electrically connected with the plurality of test point positions, and the connector is used for being matched with an interface of equipment to be detected in an inserted mode. Through the mode, the metal contact in the interface of the to-be-detected equipment can be guided to the test point position on the substrate through the connector which is in plug-in fit with the interface, so that the operation space of a user during detection is expanded, and the operation experience of the user during detection is improved.

The utility model relates to a detection technology for welding of a tube and a tube plate in the field of manufacturing of pressure vessel equipment, relates to a helium leak detection test device for a tube and a tube plate of a heat exchanger, and aims to overcome the defect of lack of a helium leak detection device which is simple and convenient to operate, compact in structure, reusable and low in cost. According to the technical scheme, a handle and a suction gun connector are fixed to the front face of a baffle, the suction gun connector is communicated with the baffle, the suction gun connector is used for being connected with a sniffing probe to detect helium leakage, and a sealing strip and a positioning mandrel are fixed to the back face of the baffle. The sealing strip is annular and fixed to the baffle along the outline of the sealing strip, the sealing strip is used for abutting against gaps between adjacent tube holes in a tube plate of a heat exchange tube so that the position, covered by the baffle, of the tube plate can be sealed, the positioning mandrel is used for being inserted into the tube holes in the tube plate of the heat exchange tube to position the baffle, and the whole device is easy to manufacture and operate. Large-range helium leakage detection of the tube plate can be realized and the efficiency is high.

The invention discloses a carbon electro-optic catalysis water ecological restoration device in the technical field of water ecological restoration, which comprises a support frame, a protective shell with a plurality of water filtering holes in the surface, and a protective cylinder which is mounted in the protective shell and provided with water permeable holes in the surface, a plurality of mounting openings are formed in the surface of the mounting frame, the surface of the mounting frame is hollowed out, and an opening is formed in the position, corresponding to the mounting frame, of the protective shell; in the process of testing the ratio of carbon electro-optical catalysis, the fastening frame and the mounting frame are used for pressing and fixing the carbon rod, other structures do not need to be disassembled additionally, unnecessary operation is reduced, the replacement efficiency is improved, and therefore the detection speed is increased, the contact and the connecting block are communicated when the carbon rod is pressed and fixed, and the detection efficiency is improved. The carbon rod can be thoroughly powered off in time when the fastening frame is turned over and opened, and the situation that power failure is not timely due to misoperation, and harm is caused to the safety of replacement personnel is avoided.

The application relates to a method for detecting illegal operation of a tool, an embedded terminal and a storage medium. The application uses a target detection algorithm to detect whether a scene image contains a human body and a tool; if yes, the scene image is input into a lightweight OpenPose-CA key point detection algorithm to perform real-time human body and tool key point detection, and the key point set of the human wrist and the tool in each scene image is output; each key point in the key point set in the continuous scene image is connected into a straight line, and the consistency of the hand and the tool action is determined according to whether the shapes and directions of the straight lines are similar, and then whether the human body holds the tool is determined based on the action consistency and the distance between the wrist and the tool key point; the Euclidean distance between the tool key point and the center coordinates of a dangerous area is calculated, and the relationship between the Euclidean distance and a preset threshold is analyzed to determine whether the operation is standard. The method, the embedded terminal and the storage medium provided by the application are lightweight under the condition of ensuring detection accuracy, and are suitable for industrial embedded scenes.

The technical scheme of the present application provides a method, system, electronic device and storage medium for detecting harmful URLs. The method comprises: obtaining URL data, wherein the URL data includes harmful URL data and normal URL data; creating word features according to the URL data, wherein the word features are used to summarize the features possessed by the URL data; creating a training set and a test set according to the URL data, and counting the word features of the URL data in the training set; constructing a decision tree according to the word features of the URL data in the training set and generating a random forest model; and identifying harmful URL data from the test set according to the random forest model. This technical scheme can improve the efficiency and accuracy of URL detection and reduce the consumption of computer computing resources.