43results about How to "Reduce missed detection" patented technology

This invention discloses a system and method for labeling automotive abnormal noise data, relating to the field of automotive NVH detection technology. The method includes: receiving raw signal data of automotive abnormal noise; performing time-frequency transformation on the raw signal to generate a time-frequency diagram; identifying key frequency ranges characterizing the abnormal noise features; then performing directional filtering to enhance the abnormal noise signal; identifying candidate time ranges for abnormal noise through an automatic detection algorithm; and outputting the final abnormal noise time range labels and key frequency ranges in a structured format after verification and correction. The system includes a data receiving module, a signal processing module, a display module, an intelligent labeling module, an audio playback module, a labeling output module, and an interaction module, achieving triple-assisted labeling through auditory, visual, and intelligent pre-selection methods. This solves the problems of low efficiency, low accuracy, and poor consistency in traditional manual listening methods, providing high-quality labeled data for deep learning classification of automotive abnormal noises.

This invention belongs to the field of power monitoring technology and discloses a brightness balancing and regional smoothing fusion algorithm for power monitoring images. The method includes: image denoising, using mean filtering and median filtering to smooth the image; image registration, performing optimal matching on two or more images obtained from different sensors, at different times, or from different angles; and image region fusion, smoothly fusing images with different angles and brightness contrasts. This method is applicable to panoramic video monitoring systems. Designed specifically for the complex lighting and high electromagnetic interference characteristics of power operation sites, this invention effectively eliminates on-site noise through adaptive preprocessing, and achieves a balance between global brightness uniformity and local detail preservation through layered brightness balancing, solving the problems of incomplete brightness balancing and detail loss in power scenarios encountered by general algorithms.

The application belongs to the technical field of application software development test, and discloses an application software development test system with real-time vulnerability detection, which comprises a code real-time collection module, a multi-dimensional vulnerability detection module, a vulnerability accurate positioning module, a vulnerability risk quantitative evaluation module, a dynamic repair guidance module, a data storage module, a visual interaction module and an iterative optimization module, and each module cooperates to form a whole-process closed-loop vulnerability detection and management and control system. The application software development test system with real-time vulnerability detection is adopted, real-time capture, accurate positioning, risk evaluation and dynamic repair suggestion output of the vulnerability are realized, and the software development test efficiency and application program security are improved.

This application relates to the field of image processing technology, and in particular to a machine vision-based method for detecting the filling quality of sound-absorbing materials in sound barriers. The method includes: acquiring a sequence of synchronized infrared and visible light video frames, performing pixel-level registration, and then stitching them together to form multi-channel input features; constructing a detection network containing an improved octave convolution module to decompose the multi-channel input features into three branches: high-frequency, mid-frequency, and low-frequency; generating an offset field and performing deformable convolution on the mid-frequency branch; averaging the variance of each channel in the feature map along the channel dimension, adding a minimum constant, and taking the square root as a temperature coefficient; performing cross-frequency fusion through a cross-attention mechanism; and extracting the low-frequency feature map as a spatial prior weight matrix when a defect region exists in the current frame, which is then fed back to the next frame after inter-frame motion compensation. This application can introduce mid-frequency transition band information and combine the differences in local spatial distribution of dual modalities to adjust the convolution sampling position, reducing boundary jitter and missed detections in video stream detection.

This utility model provides an adjustable AOI inspection machine, belonging to the field of AOI inspection technology. It includes a support and a workpiece to be inspected, as well as a drive assembly. The drive assembly includes a slide rail fixedly connected to the top end; a flexible assembly including a connecting slider slidably connected to the slide rail. Pressure flaps are fixedly connected to both ends of the connecting slider's outer side, and a vertical plate is fixedly connected to the outer side of each pressure flap. A horizontal plate is fixedly connected to the end of the vertical plate away from the pressure flaps. A rack is fixedly connected to the top end of the support, and a gear is movably connected to the top end of the support. This design achieves high-precision horizontal transport, flexible support, and anti-deformation protection for the workpiece to be inspected, while maintaining stability and precise positioning during high-speed movement. It effectively solves the problem that fixed lens positions are difficult to adapt to products of different specifications. Precise transport and stable support ensure clear and accurate images are obtained during inspection, reducing missed or false detections and improving inspection accuracy.

This invention provides a method for detecting rotating debris in coal flow based on physical fuzzy modeling and scene-customized attention. The method includes: acquiring a clear coal flow image and then labeling non-coal debris targets in the image; establishing a dataset; constructing a debris detection network; constructing a physics-driven motion fuzzy mapping model; using the motion fuzzy mapping model to dynamically blur the clear coal flow image, generating training samples simulating motion fuzziness phenomena in a conveyor belt; training and optimizing the debris detection network; inputting a real-time coal flow image into the optimized network to obtain candidate detection results for non-coal debris targets; post-processing the candidate detection results and outputting the final filtered detection results. This invention can improve the stability and accuracy of debris detection under complex conditions of high-speed coal flow, reduce the influence of motion fuzziness and background interference, and provide technical support for the safety monitoring and automatic sorting of coal mine conveying systems.

This application discloses a security protection method and related products. The method includes: identifying abnormal behavior in the data to be processed corresponding to a target vehicle based on a preset security rule base and a pre-trained anomaly recognition model to obtain a security recognition result; if the security recognition result indicates a first anomaly level, then performing local security protection on the target vehicle according to a local protection strategy; if the security recognition result indicates a second anomaly level, then obtaining the collaborative protection strategy sent by the cloud platform corresponding to the target vehicle, and performing collaborative security protection with other vehicles according to the collaborative protection strategy. This improves the security of the entire vehicle-to-everything (V2X) environment.

This application discloses a sample detection device and a sample analysis equipment. The sample detection device includes a carrier component, a carrier base, a light source component, and a detection component. The carrier component has a detection channel; the carrier base is at least partially disposed within the detection channel and is used to place the sample to be tested. The carrier base is used to move the sample to be tested relative to the carrier component along the scanning direction. The light source component and the detection component are disposed on the carrier component. The light source component generates detection light, and the detection component receives the detection light. The detection light forms an elliptical spot on the sample to be tested through a first optical path and is reflected to the detection component through a second optical path. The above-mentioned sample detection device can realize optical path detection of the sample to be tested. During optical path detection, it will not interfere with non-target samples. Moreover, the detection light irradiating the sample to be tested can form an elliptical spot. The formation of the elliptical spot allows more detection points to fall within the detection range of the detection component, which can reduce false detections and missed detections.

This utility model discloses a rail coating thickness measuring instrument, relating to the field of rail inspection technology. The instrument includes a mounting plate, a testing mechanism, and a positioning mechanism, with a rail body positioned below the mounting plate. The instrument moves along the rail body via casters on the mounting plate, eliminating the need for manual operation. This significantly reduces the physical strain and difficulty of prolonged hand-held operation and avoids positional shifts and data fluctuations caused by hand tremors, ensuring the stability and accuracy of coating thickness measurement data. It is particularly suitable for continuous testing of long-distance rails, minimizing interruptions. Simultaneously, guide wheels embedded in grooves on both sides of the rail body provide precise positioning for the thickness measuring instrument as it moves the mounting plate, preventing lateral shift during testing.

This invention discloses a bidirectional guided fusion method for image information, a target detection method, and a system. The fusion method includes: inputting the image information to be processed into a YOLO model to obtain a shallow feature image from the Backbone network and a deep feature image from the Neck network; decoupling the feature frequency bands of the shallow feature image and the upsampled deep feature image to obtain a shallow high-frequency feature map and a deep low-frequency feature map, respectively; analyzing the semantic information represented by the deep low-frequency feature map to guide the shallow high-frequency feature map to enhance details, resulting in a detail-enhanced image; evaluating the weights of each feature channel using the shallow high-frequency feature map to guide the deep low-frequency feature map to calibrate semantics, resulting in a calibrated image; and fusing the detail-enhanced image with the calibrated image. This invention solves the problems of detail loss and semantic ambiguity in existing target detection networks, especially for small-scale targets.

This invention relates to the field of cable defect identification technology, solving the technical problems of low accuracy in cable defect identification caused by gradient diffusion and feature degradation in existing deep networks, which lead to loss of edge details and difficulty in effectively extracting true weak thermal deformation features. Specifically, it relates to a method for identifying surface thermal deformation defects in extruded insulated low-voltage fire-resistant cables. The method acquires a visual image of the cable surface in the extrusion cooling state and a one-dimensional temporal physical signal, preprocesses the surface visual image to obtain a standard image, and uses a weighted gradient edge detection algorithm to construct templates in multiple directions to perform edge detection on the standard image. This invention reduces the probability of network parameter combinations getting trapped in local optima during model training, lowers false positive and false negative rates, improves the classification accuracy of cable surface thermal deformation defects, and meets the high-precision and high-robust defect detection requirements of extruded insulated low-voltage fire-resistant cables.

This disclosure provides a method, apparatus, electronic device, and storage medium for audio and video call quality detection, relating to the field of call technology. The method includes: before a call, detecting multiple first indicators of a terminal to obtain a first risk score; collecting call data during the call; during the call, detecting the terminal and the call data based on the first risk score to obtain a second risk score; after the call ends, determining a quality inspection intensity score based on the first risk score and the second risk score; and performing quality inspection on the call data based on the quality inspection intensity score to obtain a quality inspection result.

This application relates to the field of flexible printed circuit boards (FPCs), and more particularly to an FPC electrical testing fixture, which includes a worktable, a lower mold, an upper mold, and a spring-loaded probe assembly. The lower mold is disposed on the worktable, and the worktable is provided with a mounting bracket located above the lower mold. The upper mold is vertically slidably connected to the mounting bracket and has a plurality of test probes. The spring-loaded probe assembly includes probes and an elastic element. A plurality of probes are disposed and slidably connected to the upper mold in a vertical direction. The first elastic element forces the probes to slide downwards so that the lower end face of the probe is lower than the lower end face of the test pin. The positions of the plurality of probes correspond to the edge positions of the flexible printed circuit board mounted on the lower mold. This application has the effect of reducing the possibility of missed tests.

This invention discloses an intelligent inspection system for the appearance and dimensions of capacitors, belonging to the field of capacitor appearance quality inspection technology. It aims to solve the problems of low efficiency, inconsistent standards, limited functionality, and cumbersome workstation switching in existing manual inspection methods. The system includes an image acquisition module, an image processing and inspection module, a workstation control module, and an information storage and output module. The supporting hardware structure includes a chassis, a rotary motor, a pentagonal turntable, an extension block, a lifting cylinder, and a mechanical gripper. Through multi-station image acquisition and comprehensive image processing, it achieves full-dimensional inspection. The workstation control module, in conjunction with the hardware, completes automatic transfer and positioning, and the inspection data is uniformly stored and output. This invention achieves automated full-dimensional inspection, improves inspection efficiency and accuracy, ensures consistency in judgment, is suitable for mass production, and facilitates quality traceability and control.

This invention relates to the field of Building Information Modeling (BIM), and discloses a method and system for collision detection of complex electromechanical pipelines based on a feature-enhanced neural network. The method includes: processing the electromechanical pipeline model file using a multi-source BIM data fusion and geometric-semantic joint feature extraction method to obtain initial feature representations of pipeline components; performing multi-layer convolution on the initial feature representations using a dynamic heterogeneous graph neural network method to obtain enhanced feature representations of the pipeline components; performing two-stream interaction on multiple pipeline component pairs in a candidate collision pair set based on the enhanced feature representations to obtain a collision pair set; and continuously optimizing the pipeline avoidance path based on the collision pair set to obtain a collision-free BIM model. This invention achieves high-precision identification and intelligent avoidance of multiple types of collisions in complex electromechanical scenarios.

The application discloses a kind of power equipment defect identification and warning method and system based on deep learning.The method comprises: synchronously collecting and registering the visible light and infrared thermal imaging image on the surface of power equipment, constructs the instance segmentation network including light weight feature extraction network, multiscale feature fusion network and frequency domain mask prediction branch;Adopt the generative adversarial strategy to enhance the diversity of training sample;Based on graph neural network, analyze the association between defect and equipment topology, historical record, infer the cause-effect relationship of defect and risk level;Generate the interpretable warning information including heat map, natural language report and repair suggestion;Real-time detection and deep analysis are realized using end-edge-cloud collaborative architecture;Through closed-loop optimization mechanism, continuously improve system performance.The application realizes high-precision defect detection under multi-modal data fusion, has strong robustness and interpretability, significantly improves the intelligent level of power equipment operation and maintenance.

This invention discloses a linearized thickness detection device and method for automotive sound-absorbing cotton, relating to the field of sound-absorbing cotton processing quality inspection technology. The invention includes a transmission component, a displacement guide, a lateral movement mechanism, a micro servo motor, a rotating probe, an auxiliary drive roller, and a driven roller. Through the coordinated movement of the lateral movement mechanism and the rotating probe, the auxiliary drive roller and the driven roller straighten the sound-absorbing cotton. The detection module continuously collects thickness data, which is processed by the PCB motherboard and transmitted to an external terminal. This invention achieves full-range lateral coverage detection of automotive sound-absorbing cotton, reducing missed detections, avoiding detection errors caused by wrinkles or excessive stretching of the sound-absorbing cotton, preventing interference from sound-absorbing cotton lint to the detection module, and improving detection accuracy and efficiency. It is suitable for thickness quality control in the production process of automotive sound-absorbing cotton.

This invention relates to the field of biodetection technology, specifically to a primer set for identifying Fritillaria taibaiensis, a real-time quantitative PCR detection kit, and their applications. The primer set includes a first ARMS primer pair, a second ARMS primer pair, and a universal primer pair for the Fritillaria genus. The second ARMS primer introduces an artificial mismatched base near the 3' end, improving the specific recognition ability of the target site and reducing the risk of false negatives due to rare variations in the target region. Based on real-time quantitative PCR amplification using specific fluorescent probes, the relative quantitative analysis of Fritillaria taibaiensis DNA in the sample is achieved through the Ct value of the amplification curve. Furthermore, combined with amplification using universal primers for the Fritillaria genus and HRM analysis, the melting peak characteristics of the amplified product are used to determine whether other Fritillaria species are mixed in the sample, thereby achieving specific identification, relative quantitative analysis, and adulteration identification of Fritillaria taibaiensis, improving the accuracy and reliability of Fritillaria-type medicinal materials identification.

Embodiments of the present application provide an OFD document printing control method, an image forming device, an electronic device and a storage medium. The method comprises: obtaining an OFD document, analyzing a text page of the OFD document, when the OFD document contains a text object and / or an image object, performing sensitive word detection on the text object and / or the image object contained in the OFD document, when a sensitive word is detected in the text object and / or the image object contained in the OFD document, outputting a prompt picture; and in response to an image forming control instruction triggered in the prompt picture, performing a corresponding image forming control operation on the OFD document. Embodiments of the present application can detect sensitive words in multiple layers without manual detection, thereby ensuring detection efficiency and comprehensiveness.

The utility model belongs to appearance detection device technical field, concretely relates to a corn wafer cylinder appearance visual inspection equipment, including transportation subassembly, front detection mechanism, back detection mechanism, internal detection mechanism, controller and reject subassembly. Transportation subassembly includes conveyer one, falls and conveyer two, and conveyer one and conveyer two are all push plate type conveyer, and falls and includes connecting plate, a plurality of air cylinders and detection board, and the middle part of conveyer two is equipped with transportation track vacancy section, and reject subassembly sets up in transportation track vacancy section, and includes a plurality of air cylinders two and movable part, and the device compares with manual detection, has more accurate, more swift and efficient, more convenient and so on advantage, equipment operation is simple, improves process management, reduces the missed detection, prevents the inferior product to flow out, reduces manpower, maintains brand reputation.

This invention discloses a satellite fire detection method based on dynamic exponential features and deep learning. The method includes: acquiring multi-band spatiotemporal observation data from geostationary meteorological satellites; filtering candidate pixels from the full-disk satellite data using multiple threshold conditions; extracting spatiotemporal input features and channel input features of the candidate pixels based on the multi-band spatiotemporal observation data from the geostationary meteorological satellites; and inputting the spatiotemporal input features and channel input features of the candidate pixels into a pre-trained fire spatiotemporal network model to obtain the fire detection result. This invention effectively solves the problem of high false alarms and false negatives caused by cloud cover, high-temperature ground surfaces, and vegetation interference in traditional methods, overcomes the difficulties of weak fire signal extraction and spatial positioning in mixed pixel backgrounds, and significantly improves detection accuracy, stability, and computational efficiency. It can provide key technical support for forest fire monitoring and emergency decision-making.

The utility model relates to a railway wagon inspection trolley, including chassis and upper cover, the middle part of chassis is provided with two groups of wheel hub motor before and after symmetry, wheel hub motor is connected with chassis rotation, wheel hub motor bottom and track contact, be provided with four guide wheels on the chassis, the lower end of guide wheel is provided with mounting panel, guide wheel and mounting panel rotation is connected, four guide wheels are rectangular distribution, four guide wheels all with the outside surface of track is pasted together, the upper end of chassis is provided with controller, power module, picture acquisition module, communication module and position detection module, picture acquisition module is close to the upper cover setting, the upper cover is provided with the window in picture acquisition module, the periphery of window is provided with a plurality of LED lamp, the car body still is provided with photosensitive resistance, controller and wheel hub motor electric connection, the upper cover and chassis are detachable connection, the utility model moves along the track in the wagon bottom, replaces manual work and completes the wagon bottom detection.

This invention discloses a packaging inspection method and system based on high dynamic range 3D imaging, relating to the field of semiconductor packaging inspection technology. The method includes: acquiring multi-exposure images of the packaged device surface; pre-classifying the point cloud into metal pads, molding compounds, and pin regions based on the curvature coefficient of the saturation region and the dynamic range width of the linear region of the brightness response curve; calculating the normal vector dispersion index to extract complete point cloud layers for each material; constructing a weighted spatial transformation error function using this index as dynamic weights, and fusing multiple point clouds into a high-density complete point cloud; calculating a weighted fusion value of the local surface curvature change rate and depth gradient modulus, matching it with defect feature intervals to identify cold solder joints, warpage, and cracks, and outputting their locations; calculating a dynamic threshold based on the fusion value and the normal vector dispersion index, outputting a pass / fail conclusion, and generating an inspection report. This invention significantly improves the defect detection accuracy and reliability of complex surface packaging by adaptively adjusting parameters.

This invention provides a detection and tracking algorithm and application system for weakly textured multi-target targets using a monocular camera, belonging to the field of computer vision and video intelligent analysis technology. The method includes a detection stage and a tracking stage executed sequentially. In the detection stage, by analyzing candidate connected regions in the binarized image, a Gaussian mixture model is constructed based on the foreground pixel distribution for adhered or dense targets, and adaptive decomposition of single connected regions is performed. This invention introduces a adhered target separation method based on the Gaussian mixture model in the detection stage, performing pixel-level modeling of adhered or densely clustered target regions. Through multi-component Gaussian fitting of the foreground pixel coordinates, adaptive decomposition of single connected regions is achieved, effectively distinguishing multiple similar targets whose detection boxes merge due to spatial proximity or local occlusion, thereby reducing the false negative and false positive rates in dense scenes and providing more accurate and reliable initial detection results for subsequent multi-target tracking.

The application discloses a kind of tunnel lining crack detection method and system based on improved YOLO model, constructs the tunnel lining crack detection model based on improved YOLO (including but not limited to YOLOv8-YOLOv12 and its derivative architecture), including in the feature extraction module of main network Backbone, introduction expansion residual network DWR;Variable convolution and channel-space double attention mechanism are introduced in detection head network Head;Optimize bounding box regression loss function, and boundary box regression loss is calculated using Inner-CIoU loss function.The application realizes the high-precision, real-time detection of multi-scale cracks, especially fine cracks, under the premise of not significantly increasing the computing overhead, through the multi-level, collaborative improvement of network structure.This method is not only suitable for tunnel lining crack detection, but also can be widely used in the detection of other fine crack defects such as bridges, roads and building exterior walls.

This utility model discloses a non-destructive testing instrument for wind turbine blades, belonging to the technical field of wind turbine blade flaw detectors. Its key technical features include an assembly frame and a base. The assembly frame is threadedly connected to the bottom of the base, and a flaw detection mechanism is threadedly connected to the front side of the assembly frame. An auxiliary mechanism is threadedly connected to the inner wall of the flaw detection mechanism. The flaw detection mechanism includes a mounting ring, a mounting groove, several infrared thermal imagers, several eddy current probes, several ultrasonic probes, a mounting rod, a connecting frame, a motor, and a propeller. By setting up the flaw detection mechanism, non-destructive testing can be performed after the wind turbine blades are installed, avoiding the cumbersome process of disassembling and installing the blades in traditional flaw detection methods. Simultaneously, the flaw detector can be driven by the motor and propeller to fly near the blades and automatically complete the detection, improving flaw detection efficiency and reducing operational difficulty. Multiple detection methods cooperate and cross-verify each other, effectively improving the accuracy of the detection results.

The application discloses a transformer production quality online detection method and system, and the method comprises the following steps: clamping a transformer to be detected and reading a unique identifier, measuring the primary terminal contact resistance and the secondary terminal contact resistance, and re-measuring if the contact resistance is out of limit; applying a bipolar high-slope pulse between the primary and the secondary, synchronously sampling the voltage, the response current and the reference noise, and aligning the sampling time; setting two levels of gate windows with the pulse edges, coherently superimposing the response current in the inner window, and calculating the offset amount according to the reference noise to obtain the net response in the outer window; calculating the cross-correlation peak value, the gated energy and the frequency band energy ratio from the net response, and generating the first index in combination with the batch reference. The application realizes the synchronous online identification of insulation hidden troubles and connection hidden troubles under the production line condition, and forms a stable judgment and a full-flow tracing closed loop.

This application discloses a method, apparatus, and device for detecting defects in printed circuit boards based on an improved YOLO, relating to the field of circuit board defect detection technology. The method includes: inputting the image to be detected into a backbone network, where the C3K2-IMCA module extracts features through cross-scale information interaction and spatial-channel co-modeling, outputting multiple first feature maps at different scales; inputting the first feature maps into a neck network, where the CCFM-Neck performs information interaction and fusion of feature maps at different levels to obtain multi-scale fused features; and inputting the multi-scale fused features into a detection head, where the LDCD-Head performs feature processing through detail enhancement convolution to obtain the defect detection result. This invention achieves lightweight modeling while suppressing background interference and enhancing small target detection capabilities, resulting in high detection accuracy, good real-time performance, and suitability for deployment on edge devices.

The application provides a real-time positioning and mapping method, device and electronic equipment in a dynamic environment. The method comprises: obtaining an environment image and a preset map, and obtaining a key frame according to the environment image and the preset map; according to the key frame, a first mask map is calculated through a trained deep learning model; according to the first mask map, a second mask map is calculated through a dense optical flow algorithm; the dynamic probability of a map point of the preset map is updated according to the first mask map and the second mask map; a re-projection residual and a feature relative position residual are constructed according to the dynamic probability of the map point, and a camera pose is calculated according to the re-projection residual and the feature relative position residual; and a target map is constructed according to the camera pose. Through the method, device and electronic equipment provided by the application, the accuracy and robustness of real-time positioning and mapping can be improved.

The utility model relates to the technical field of instruction manual missing detection, and disclose a kind of instruction manual missing detection equipment, including fixed bolster, the top fixed mounting of fixed bolster has support frame, the bottom fixed mounting of one end of support frame has first air cylinder, the output of first air cylinder fixed mounting has mounting seat, the inside movable mounting of mounting seat has mounting plate, the bottom fixed mounting of mounting plate has photoelectric sensor.The utility model compared with traditional equipment, the cooperation between the positioning hole, positioning block, spring and pull rod, it is convenient to install photoelectric sensor, significantly improve the installation efficiency, so that photoelectric sensor can be quickly, accurately positioned and fixed, reduce installation time and labor cost;It also enhances the flexibility of equipment, it is convenient to adjust or replace the position of photoelectric sensor according to actual demand, improves the adaptability of equipment.