18 results about "Step detection" patented technology

The application discloses a kind of based on jigsaw puzzle's flat large-size printing plate detection method, it is related to the technical field of printed matter layout machine vision detection, the method first single-step detection image is spliced into complete product graph, using grid division and NCC template matching extract adjacent two graph high reliability point pair, and combined with K-means clustering, remove abnormal point pair, solve homography matrix, using homography matrix carries out accurate perspective transformation and image splicing, again carries out rotation scaling transformation and makes template graph and product graph alignment, and difference configuration parameter is set in detection area, using the dual comparison dimension detection logic of chromatic aberration and edge detection combination accurately determines defect position;The application can effectively eliminate the false matching caused by complex background and similar texture, solves the problem of splicing misalignment;Real defect is accurately locked by double-dimension detection, effectively suppresses false alarm, significantly improves the capture ability of low contrast small defect and geometric deformation defect, ensures the reliability of detection under complex environment.

This invention discloses a synchronous detection method for machine vision devices, relating to the field of synchronous detection technology, comprising the following steps: constructing a scene screen; setting the placement position of the machine vision device based on the scene screen; acquiring a real-time target image based on the scene screen and the machine vision device; acquiring a grayscale segmentation threshold based on the real-time target image; acquiring a real-time target region based on the grayscale segmentation threshold and the real-time target image; constructing a real-time reference value based on the real-time target region; determining whether the machine vision devices are synchronized based on the real-time reference value; if the machine vision devices are not synchronized, acquiring the time deviation between the two machine vision devices based on the real-time reference value; this invention addresses the problem that existing synchronous detection technologies fail to analyze whether synchronization is achieved based on image results, leading to low accuracy of synchronous detection results.

The application provides a decision tree recommendation method and system based on random sampling, which deduces the conduction path of faults among devices from the device physical topology association relationship in the device production detection scene, determines the sequential association order of each conduction node and the conduction trigger condition between nodes, groups and collects real detection data and virtual detection data according to the conduction node correspondence relationship to obtain a sampling pool, determines the decision tree branch splitting priority based on the upstream and downstream association relationship of the fault conduction path, obtains a decision tree, generates a step-by-step detection action sequence corresponding to the fault conduction path according to the reasoning path, corresponds each reasoning branch to a detection operation link to obtain a step-by-step detection action sequence, obtains an execution feedback result, updates the node splitting weight of the decision tree, adjusts the sample screening condition of the sampling pool, and obtains the sampling pool to optimize the decision tree. The application can realize the linkage adaptation of the decision tree structure and the data source, and continuously improve the accuracy of fault detection.

The application discloses a kind of explosion vibration source positioning method, system and computer program product based on machine learning classification and guided pulse detection, it is related to signal processing and target positioning technical field, solve the problem of insufficient robustness of existing detection method in complex environment.It includes the following steps: step S1, multi-channel signal is synchronously collected, and the multi-channel signal is pretreated;Step S2, pulse detection is carried out to the multi-channel signal after pretreatment, and TOA sequence is formed;Step S3, preliminary detection is carried out to TOA sequence, and after extracting features, the features are input into machine learning model for classification, and the output category is explosion, then enter positioning solution;Step S4, positioning solution is carried out, and the solution result is output.

This invention discloses a method for detecting escalator steps that integrates the YOLO algorithm and digital twin technology. First, sensor and video stream data are collected to construct a step dataset. Then, YOLOv8n is modified by introducing the CCA attention mechanism and reconstructing the EL-Head detection head. After pruning and INT8 quantization, a lightweight TJ-YOLOv8 model is obtained and trained. The model is deployed to the edge to achieve real-time step detection, constructing topological relationships and marking suspected missing steps, generating abnormal metadata with 3D coordinates. A digital twin of the escalator is constructed to achieve data injection, virtual-real synchronization, and sensor calibration. A decision signal is generated by fusing multi-source heterogeneous features, and a three-level filtering system is formed by combining gradient accumulation and historical backtracking to determine anomalies. This invention offers high detection accuracy and fast response, achieving closed-loop management of missing steps and improving escalator safety and intelligent operation and maintenance.

The application relates to the technical field of electric power operation and maintenance, and discloses a cable external damage detection method and system. The method comprises the following steps: collecting first vibration data of a cable through a first vibration sensor arranged on a first edge computing terminal; if the vibration amplitude of the first vibration data exceeds a preset amplitude threshold, a virtual reconstruction signal is generated; the virtual reconstruction signal is sent to a second edge computing terminal to trigger the second edge computing terminal to extract second vibration data of the cable; after the second vibration data is received, virtual reconstruction is performed based on the vibration data of the two, and respective corresponding reconstructed vibration data is obtained; preliminary detection is performed on the two, and a first cable external damage detection result is obtained; if the detection result is a valid event, the first reconstructed vibration data is input into a preset cable external damage detection model, and a second cable external damage detection result is output. The application improves the identification accuracy and response real-time performance of cable external damage, and guarantees the working efficiency and long-term stable operation of a cable external damage early warning system.

This invention relates to the field of gas detection technology, specifically to a method and system for simultaneous multi-parameter detection of compressed air quality, addressing the problems of sampling distortion, asynchronous detection, insufficient trace detection limits, delayed microbial detection, and severe cross-interference in existing technologies. The method comprises four steps: in-situ non-disruptive sampling, global dual-synchronous triggering, multi-parameter synchronous detection, and multi-parameter spatiotemporal coupling correction. The system is correspondingly equipped with an adaptive isodynamic coaxial laminar flow sampling unit, an optical frequency comb global synchronization unit, multiple detection units, and a data processing and control unit. This invention enables in-situ non-disruptive sampling of all compressed air mass parameters, simultaneous time-spectral dual-dimensional detection, and highly sensitive reagent-free online measurement, exhibiting excellent detection accuracy and long-term stability, meeting the online detection needs of high-end applications such as pharmaceuticals, semiconductors, and aerospace.

A correction circuit (600) for correcting one or more errors in a digitized current signal, wherein the digitized current signal is a digital representation of an analog current signal of a current flow through an energy storage element (602), wherein the correction circuit (600) is configured to correct an offset error between the digitized current signal and the analog current signal by: a) comparing the digitized current signal with the analog current signal to determine the offset error by: i. detecting a first time step when the digitized current signal crosses a first digital threshold; ii. detecting a second time step when the analog current signal crosses a first analog threshold; iii. calculating a first duration between the first time step and the second time step; iv. determining a first slope of at least one of the digitized current signal and the analog current signal; v.Multiplying the first duration by the first slope to determine the offset error; and b) correcting the digitized current signal using the determined offset error; and / or wherein the correction circuit (600) is configured to correct a relative slope error between the digitized current signal and the analog current signal by: a) comparing the digitized current signal with the analog current signal to determine the relative slope error by: i. detecting a first time step when the digitized current signal crosses a first digital threshold; ii. detecting a second time step when the analog current signal crosses a first analog threshold; iii. detecting a third time step when the digitized current signal crosses a second digital threshold; iv. detecting a fourth time step when the analog current signal crosses a second analog threshold; v.a) Calculate a first digital slope delay between the first time step and the third time step; b) Calculate a first analog slope delay between the second time step and the fourth time step; c) Divide the first analog slope delay by the first digital slope delay to calculate a first delay parameter, then subtract one from the first delay parameter to determine the relative slope error, and d) Correct the digitized current signal using the determined relative slope error.

This application discloses a method for correcting misjudgments in high-speed multi-type event detection based on LoRA, relating to the field of intelligent transportation technology. The method includes: acquiring real-time event information on the highway, identifying it using the YOLO algorithm, and outputting the original preliminary event detection results and environmental parameters; standardizing the preliminary detection results and extracting semantic and scene features of the event targets from the preliminary detection results to obtain standard preliminary detection results; performing secondary verification and misjudgment correction using a LoRA-optimized large model based on the standard preliminary detection results to obtain the event detection results; uploading the event detection results to the road segment central monitoring platform, and retaining misjudged, missed, and new scene samples for iterative optimization. This application aims to resolve the contradiction between the low reliability of event detection in complex highway environments and the inability to deploy high-precision large models at low cost and high efficiency under existing hardware conditions.

The embodiment of the application provides a kind of unmanned aerial vehicle signal synchronization detection method and device, method includes: by in first mode with high gain to signal blind search, signal strength is evaluated after identifying to broadcast pulse and switches to second gain, subsequently enters second mode;Signal is received using adjusted gain and is detected synchronously, further adjusts gain after detection success and enters third mode, realize the continuous tracking and stable reception of signal, wherein, synchronous detection process is carried out frequency domain correlation operation to the synchronization sequence in received signal and local reference sequence, by re-sampling reference sequence to actual signal sampling rate, and using the method that frequency domain multiplication is combined with time domain overlap addition, it is greatly reduced to calculation complexity, while ensuring the accurate positioning of synchronization peak, the application can improve the efficiency and accuracy of unmanned aerial vehicle signal detection and synchronization.

This invention discloses a method and system for processing abnormal data in virtual games, relating to the field of big data processing technology. The method involves receiving a sequence of interactive data frames uploaded by a terminal device and parsing it to obtain a set of input device sampling points and displacement coordinate vectors. Feature extraction is performed on the input device sampling point set to obtain a high-dimensional feature vector. This high-dimensional feature vector is mapped to a preset behavioral feature space, and the multidimensional statistical distance of the high-dimensional feature vector in the behavioral feature space is calculated to generate a first anomaly confidence coefficient. Spatial mapping data corresponding to the virtual scene is invoked. Discretized ray stepping detection is performed in the spatial mapping data based on the displacement coordinate vector to generate a second anomaly confidence coefficient. The first and second anomaly confidence coefficients are fused using a dynamic weighted algorithm to obtain a comprehensive anomaly score. Abnormal data is determined based on the comprehensive anomaly score, and a state rollback operation is performed on the virtual object.

This application relates to the field of industrial computer vision and discloses a closed-loop optimization method and system for AOI defect detection in smart factories. The method includes: dividing a high-resolution industrial image to be detected into multiple image blocks; performing initial defect detection on the images based on a dual-branch architecture in a high-resolution anomaly detection model; outputting preliminary detection results; filtering material images identified as having defects from the preliminary detection results and obtaining their actual defect information; aligning the actual defect information with intermediate detection data generated by the detection model during the detection process to generate a supervised training dataset; adjusting the core parameters of the detection model based on the supervised training dataset; updating and deploying the optimized detection model to the AOI detection equipment; and repeating steps S1 to S4 to form a closed-loop iterative process of detection-feedback-optimization. This solution achieves dynamic self-optimization of the AOI defect detection model and continuous improvement of detection performance.

This invention discloses a water hammer testing device and method for detecting leaks, belonging to the field of water hammer testing technology. The device comprises a closed loop consisting of a water supply system, a controllable modulated water hammer generator, a main test pipeline, a spatiotemporal synchronization detection unit, and an intelligent analysis and control unit. The controllable modulated water hammer generator employs multi-stage valve cores and servo drive closed-loop control. The spatiotemporal synchronization detection unit synchronously acquires signals through a pressure detection unit, an acoustic vibration detection unit, and a high-precision clock. The testing method relies on a spatiotemporal decoupling algorithm to separate the intrinsic water hammer signal from the leakage signal, and combines a "dual-group time difference-circumferential positioning" algorithm to achieve accurate leak point location and leakage estimation. This invention overcomes industry technical biases, achieving integrated detection of instantaneous dynamic leaks during water hammer impact, significantly improving the detection signal-to-noise ratio and positioning accuracy, and effectively solving the problems of traditional equipment's inability to detect instantaneous micro-leakage and high false positive / false negative rates.

The application discloses a kind of for wire feeding length detection tooling, detection method and wire feeding equipment, it is related to wire processing equipment technical field, it is applicable to high-precision scene such as cold header contact production.Defect that point contact is easy to slide, precision is low, poor adaptability of existing wheeled detection mechanism, tooling uses linear contact clamping follow-up structure, cooperates displacement scale and reader signal acquisition, length is accurately calculated by PLC controller and is linked with out-of-tolerance shutdown.Detection method is executed according to clamping, reset, detection, calculation, alarm / reset process, supports multi-line synchronous detection.Equipment integrates the tooling, realizes feeding and detection real-time linkage.The detection precision of the application reaches 0.001mm, the anti-sliding effect is excellent, and the adaptability is strong, which can improve production efficiency and product qualification rate, effectively reduce production cost, and is suitable for industrialization.

The application discloses a timing synchronization detection method and system in an OFDM system, and relates to the technical field of communication. The technical problem that the performance of synchronization detection is insufficient when the signal-to-noise ratio is low and it is difficult to reduce the influence of frequency offset is solved. The method comprises the following steps: locally storing a received complex sequence; delaying a scrambled short training field to obtain first redundancy information, second redundancy information and third redundancy information, and performing segmentation processing; calculating a timing metric function value Mn1 of a first time domain sampling complex point and a timing metric function value Mn2, and respectively judging whether the timing metric function value Mn1 and the timing metric function value Mn2 pass; calculating a timing metric function value Mn1 of a second time domain sampling complex point to a L-Ls time domain sampling complex point and a timing metric function value Mn2; and updating a first threshold cumulative value CountCn1 and a second threshold cumulative value CountCn2. The application improves the synchronization detection performance under a low signal-to-noise ratio condition, and solves the influence of frequency offset change on the detection performance.

This application proposes a training method for a line step detection model, a line step detection method, and related apparatus. The method extracts the target image of the human body and target foot mask data from an initial test image; based on the target foot mask data, a preset starting line, and the line step type, a starting line corresponding to the line step type is generated; the target image and the starting line are stitched together to obtain training sample images; based on the target foot mask data, the target image, and the starting line, the actual line step ratio corresponding to the training sample image is determined; using the training sample images and the actual line step ratios corresponding to the training sample images, the line step detection model is trained to predict the line step ratio. This scheme automatically generates training sample images and automatically determines the actual line step ratios corresponding to the training sample images, reducing the data preparation costs of training data collection and manual annotation, avoiding the subjectivity of manual annotation, and improving the accuracy of the line step detection model, thereby improving the accuracy of line step detection.