135 results about "Window detection" patented technology

The invention relates to the technical field of cooperative control, in particular to a multi-machine cooperative control method and system for a bridge cable hoisting device, and the method comprises the following steps: collecting tension change characteristics through a distributed sensor array, extracting indexes through a sliding window algorithm to generate a response time window, and generating a cooperative time window through time sequence overlapping and speed trend adjustment. Calculating a compensation value by combining inertial parameters and acceleration to generate a trigger window, detecting tension and displacement difference, inputting the tension and displacement difference into a dynamic threshold function for screening and fusion, outputting a synchronous trigger condition, and generating a synchronous control instruction by encoding a device number and a tension change rate after timestamp alignment. According to the method, multi-node tension synchronous acquisition and normalization processing, dynamic response generation through a sliding window, boundary matching action triggering adjustment through an overlapping algorithm, response lag correction through inertia compensation, tension and displacement difference real-time detection, dynamic threshold screening and triggering condition fusion and timestamp alignment packaging instruction consistency are carried out; and the cooperation precision and the system robustness are improved.

The invention discloses an out-of-focus identification and restoration method for a microscopic system. The method comprises the following steps: 1, preparing a microscopic out-of-focus image data set and carrying out degradation modeling; 2, constructing an out-of-focus parameter prediction network based on multi-label parameter reasoning and microscopic system priori knowledge and an image restoration network based on a generative adversarial network, performing independent training, and then performing merging training through a circulation system formed by mutual connection based on predicted point spread function convolution and deconvolution operation; 3, model fine tuning based on a specific system and a new data set; and 4, performing model testing, performing large-view image sliding window detection and collage fusion, and explicitly outputting defocus parameters of the system during image shooting. The method can be applied to out-of-focus fuzzy recognition and restoration of microscopic imaging of various systems, and is beneficial to the accuracy of functions such as particle counting and particle size statistics of the systems, thereby further promoting the application of the full-depth-of-view microscopic system in biomedical detection.

The invention discloses a GNSS (Global Navigation Satellite System) / INS (Inertial Navigation Satellite System) anti-deception navigation method based on ESKF (Enhanced Shift Keying Function) and dynamic window detection, which comprises the following steps of: 1, acquiring observation data of an INS and a GNSS, performing time synchronization and coordinate system unification on the observation data of the INS and the GNSS, and respectively eliminating a time error and a coordinate difference; 2, a dynamic window detection mechanism is designed, an error state dynamical model is constructed, the dynamic window detection mechanism is used for detecting whether GNSS cheating exists or not, and meanwhile the error state dynamical model can output stable navigation parameters; and 3, outputting a final high-precision navigation result according to the stable navigation parameters. According to the method, the problems of error accumulation and covariance distortion of nonlinear system model linearization are effectively solved, pollution of GNSS deception signals can be effectively inhibited, high-precision positioning and anti-deception capability are kept in complex environments (such as urban shielding and electromagnetic interference), and a navigation system with high precision and high reliability is formed.

The invention relates to an energy storage battery anomaly analysis method and system based on retrieval enhancement generation. The method comprises the following steps: acquiring real-time operation data of an energy storage battery, extracting a statistical feature vector, performing sliding window segmentation according to a division condition, and determining an abnormal window; constructing a knowledge database; taking abnormal window data at the abnormal window as input, searching corresponding energy storage battery abnormal data and contextual information from the knowledge database, and combining the energy storage battery abnormal data and the contextual information with the statistical feature vector of the abnormal window to obtain combined information; and inputting the combined information into a generation model, and generating a battery abnormity report corresponding to the energy storage battery through the generation model. Through the sliding window detection technology, the exceptions can be quickly screened, and the real-time performance and accuracy of exception analysis are greatly improved in cooperation with the reasoning ability of knowledge base retrieval and model generation.

The invention provides a brain-computer interface decoding method and system based on multi-modal signal fusion, and relates to the technical field of brain-computer interfaces. The method comprises the following steps: S1, acquiring a multi-mode signal, unifying a time reference and starting a sliding window detection intention; s2, de-prompting, sequential bias checking and permutation correction, artifact suppression and band-pass filtering are carried out; s3, channel and modal quality is calculated, and a reliability weight and a rejection list are generated and marked; s4, multi-scale coding is carried out, cross-modal alignment is realized through learnable time delay compensation, and a first fusion representation is obtained; s5, performing layering and cross attention fusion under reliability gating so as to align and reconstruct constraint to keep semantic consistency, and obtaining joint semantic representation; and S6, sequence-level decoding is carried out to output semantics / states / instructions. According to the method, bias and noise are suppressed, time delay difference and cross-main-body equipment change are resisted, and decoding accuracy, robustness and practicability are remarkably improved.

The invention provides a house external window detection method and device, a terminal and a storage medium, and the method comprises the steps: obtaining an external window thermal image generated by scanning an external window of a current house through thermal imaging equipment, and extracting corresponding temperature distribution information from the external window thermal image; acquiring an outer window image generated by shooting the outer window of the current house by a camera device, and identifying the outer window image to determine outer window structural features and outer window potential safety hazards; constructing an outer window three-dimensional model based on the outer window thermal image and the outer window image; and detecting and evaluating the outer window based on the outer window three-dimensional model, the temperature distribution information, the outer window structure characteristics and the outer window potential safety hazard to obtain a detection and evaluation result reflecting the outer window thermal performance and the outer window safety performance. Through combined detection of thermal imaging and machine vision, comprehensive evaluation of the thermal performance and the safety performance of the outer window is realized, automatic detection of the outer window of the house is realized, and the detection efficiency and the accuracy of a detection result are improved.

The invention discloses a video target tracking system and method combined with deep learning, and relates to the technical field of computer vision, and the method comprises the following steps: obtaining video frame sequence data of each monitoring device; performing segmentation processing on the time coding sequence of the video frame sequence data to obtain track fragments of corresponding monitoring equipment; and extracting a time coding subsequence of a track fragment pair formed by any two track fragments, and carrying out feature analysis on the time coding subsequence to obtain a multi-dimensional matching confidence score of each track fragment pair. According to the scheme, a shielding time window detection mechanism is introduced, shielding influences are actively recognized and quantified, the problem of time coding distortion caused by shielding in a multi-monitoring-device environment is solved, a similarity calculation result can be dynamically corrected, mismatching caused by local shielding is avoided, and the accuracy of time coding is improved by combining motion continuity constraint and a nonlinear fusion strategy. The track matching robustness in a complex shielding scene is effectively improved, and a high-confidence matching reference is provided for subsequent time axis unification.

The invention relates to an existing building information model reconstruction method based on image target detection and an unmanned aerial vehicle, and the method comprises the following steps: obtaining pictures, shot by the unmanned aerial vehicle, of four external vertical faces of a target building, and employing a deep learning target detection YOLO V9 model, obtaining a detection graph containing a window detection frame and a central point mark, window position information and window size information; determining the corresponding relation between the pixel length of the shooting and the actual length; performing edge detection processing on the detection image, and combining the corresponding relation to obtain boundary position information of the wall and actual coordinates of the window based on the wall surface; and performing parametric modeling of the building envelope based on the boundary position information of the wall, and simultaneously obtaining floor information of the building and the plane layout of each floor to complete reconstruction of the whole building information model. Compared with the prior art, the position and the size of the building envelope can be quickly, simply and conveniently recognized, modeling is further facilitated, a certain automation degree is achieved, and cost is low.

The invention provides a photon point cloud data under-forest terrain inversion method and system based on multistage window detection, and the method comprises the steps: obtaining under-forest ground photon points based on a multistage window terrain detection method; on the basis of the under-forest ground photon points, terrain elevation residual errors under the multi-level window size are obtained; shunting the terrain elevation residual error based on a preset residual error threshold value to obtain different types of deviation points; correcting the different types of deviation points, and fusing the ground photon points under the multi-level window size based on a correction result to obtain corrected ground photon points under the small window; and obtaining an under-forest terrain inversion result based on the corrected ground photon points under the small window. According to the under-forest terrain inversion method based on multistage window detection, residual noise resistance photons of under-forest terrains inversed under windows of different sizes and terrain errors of dense vegetation areas are fused, and a terrain result with rich terrain details and high precision is obtained.

The invention provides a popup window control detection method and device, equipment and a storage medium, and the method comprises the steps: obtaining a view tree corresponding to a current interface in an automatic task execution process; determining a pop-up window detection result according to the view tree, wherein the pop-up window detection result is used for indicating whether the current interface comprises a pop-up window control or not; and when the popup window detection result indicates that the current interface comprises the popup window control, closing the popup window control so as to continue to execute the automatic task. By implementing the method, the pop-up window can be detected and processed in time, and the problem that automatic task execution fails due to display of the pop-up window control is effectively solved.

The invention relates to a frequency mixing method and device for eddy current detection, electronic equipment and a storage medium, which are used for improving the detection efficiency of eddy current detection. The method comprises the following steps: acquiring manual calibration pipe data, wherein the manual calibration pipe data comprises eddy current signal data of a plurality of different channels; screening out a plurality of pieces of pipeline area signal data from all the eddy current signal data; performing signal analysis on the signal data of each pipeline region one by one, and extracting signal data of a candidate region of the support plate; identifying target support plate signal data from the support plate candidate region signal data by using a sliding window detection method; calculating a mixing factor according to the target support plate signal data; and performing frequency mixing processing on target test tube data by using the frequency mixing factor to obtain target frequency mixing signal data.

The invention provides a window display method, electronic equipment and a computer storage medium, the method is applied to the electronic equipment, and the method comprises the following steps: displaying a first window of a first application; detecting a first event, wherein the first event is used for triggering a preparation process of a second window of a second application; obtaining a first attribute change parameter of the first window and a second attribute change parameter of the second window; adjusting the first attribute change parameter according to the second attribute change parameter, and obtaining a third attribute change parameter of the first window; and displaying the animation process of the first window according to a third attribute change parameter, and displaying the animation process of the second window according to the second attribute change parameter. For example, the animation process of the second window is an approach process. According to the method and the device, the problems that attribute changes of the windows are mutually split and motion is not uniform in a multi-window attribute change scene can be solved, and the visual effect is effectively improved.

The invention relates to the technical field of data processing, and discloses a visual large-screen dynamic display method and system based on data driving, and the method comprises the steps: collecting business scene demand data, generating a display logic configuration instruction, and setting a display content type, a spatial layout and an interaction mode; the calling data interface is connected with a background storage system and obtains service data in real time through the data stream processing module; performing time sequence analysis, sliding window detection and association rule calculation on the data to obtain a freshness index, an abnormal fluctuation parameter and a coupling degree, and judging whether abnormal fusing is triggered or not; performing exception filtering and standardization on the processed data, mapping the processed data into a graph data structure, optimizing layout through the Fresnel's law, adjusting color matching through a color contrast algorithm, and generating a chart graph; and dynamically refreshing the interface by the rendering engine. According to the method, on-demand customization and dynamic adaptation are realized, and the influence of wrong data on the accuracy of a large screen is avoided.

1. The name of the design product: door and window detection equipment. 2. The use of the design product: a detection device for detecting the fatigue performance of window hardware hinges. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The utility model relates to the field of door and window detection, and discloses a door and window smog prevention detection sensor mounting structure, which comprises a smog machine and a connecting pipe, a handle is slidably mounted on the inner wall of the smog machine, two rollers are rotatably connected to the bottom end of the smog machine, and one end of the connecting pipe communicates with a shielding cloth. A plurality of supporting rods are fixedly installed on the inner wall of the shielding cloth and evenly distributed at the four corners of the shielding cloth, one end of each supporting rod is rotationally connected with a connecting base, the two rolling wheels are symmetrically distributed with the smoke sprayer as the axis, and one end of a connecting pipe communicates with one end of the smoke sprayer; the shielding cloth communicates with the smoke sprayer through the connecting pipe, the multiple supporting rods are installed on the inner wall of the shielding cloth and connected through the connecting base, so that the shielding cloth can be attached to the surface of the door and window conveniently, the size of the shielding cloth is adjusted through rotation of the supporting rods and the connecting base, and smoke generated by the smoke sprayer can be shielded conveniently.

The invention relates to a door-based sound insulation performance detection method and system, and relates to the field of door and window detection technologies, and the method comprises the steps: obtaining a detection influence index of a to-be-detected sound insulation sample; establishing a historical interval taking the current time point as a rear end point and the width as historical duration on the time axis, and acquiring historical influence indexes and historical sound insulation quantities of the sound insulation samples in the historical interval; performing comparison according to the detection influence index and the historical influence index to determine the sample similarity, defining the sound insulation samples with the sample similarity greater than the demand similarity as similar samples, and determining a reasonable sound insulation range according to the historical sound insulation amount of each similar sample; the detection device is controlled to work to obtain the detected sound insulation amount, and whether the detected sound insulation amount is within the reasonable sound insulation range or not is judged; if so, outputting a normal detection signal; and if not, outputting an abnormal detection signal. The sound insulation performance detection device has the effect of improving the sound insulation performance detection operation effect of the door.

The utility model discloses a detection device, which relates to the technical field of building door and window detection and comprises a driving assembly composed of a detection frame, a driving motor, a driving rod and a detection shifting fork. Through cooperative use of the driving assembly and the stress mechanism, the door and window can be circularly pushed and pulled, so that the durability of the door and window can be tested, meanwhile, the stress mechanism can detect the force required by the whole push-pull stroke of the door and window, so that the reaction is comprehensive, the force curve is accurate, the detection result is accurate and reliable, and the detection efficiency is improved. The problems that when an existing building door and window detection device detects the push-pull force, detection is achieved through manual pulling of a pull force scale, the detection mode cannot well reflect data such as a force curve needed when a door and window are pushed and pulled, and meanwhile the service life of the door and window cannot be detected are solved.

The invention discloses a distributed acoustic sensing road cavity detection method based on an active excitation source. The method is based on distributed acoustic sensing (DAS), and comprises the following steps of: firstly, acquiring a DAS signal sampling data sequence to be processed; preprocessing the data of each DAS channel; calculating a short-time zero-crossing rate to remove channels with abnormal data records; then, signal space-time positioning is carried out through sliding window detection, signal envelopes in a signal area are extracted, and space-time distribution information of signals is obtained; and finally, extracting spatial correlation features and energy distribution features of the signals, and realizing automatic detection of the road cavity based on feature judgment. According to the method, all-weather sensing and high-resolution precision characteristics of the DAS array are fully utilized, accurate estimation of road cavity detection is achieved with small calculation amount, large-range sensing can be achieved, and the method is suitable for real-time engineering application occasions.

This invention provides an obstacle avoidance method, system, electronic device, and storage medium for autonomous driving, belonging to the field of autonomous driving control technology. It includes: continuously performing dynamic window detection in front of the vehicle to obtain detection results; dividing the dynamic window into multiple detection areas based on vehicle driving parameters and a pre-set mapping relationship between vehicle driving parameters and detection areas; if the detection results contain obstacles, comparing the relative positional relationship between the obstacles and each detection area to obtain position comparison results; and determining the vehicle's obstacle avoidance control logic based on the position comparison results and a pre-set mapping relationship between the position comparison results and obstacle avoidance control logic for obstacle avoidance. This invention can effectively reduce the time and resource consumption of meaningless window creation, reduce the computational load on the central processing unit, improve the overall vehicle control performance such as control cycle, and increase the efficiency and experience of autonomous driving.

The application provides a door and window hardware motion simulation test system with adaptive passive following and universal adjustment function, which solves the problems of door and window detection motion constraint, and comprises a support frame, a non-powered horizontal guide rail movably installed on the support frame, and a freely-slidable sliding mounting seat installed on the non-powered horizontal guide rail; a swing driving motor for driving the non-powered horizontal guide rail to swing relative to the support frame is installed on the support frame, a rotary driving motor is carried on the sliding mounting seat, an output shaft of the rotary driving motor is connected with a handle operating clamp through a universal transmission assembly, and the universal transmission assembly allows an included angle between the axes of the rotary driving motor and the handle operating clamp while transmitting the rotary torque; when the opening and closing action of the door and window fan drives the handle to produce horizontal displacement, the sliding mounting seat passively slides on the non-powered horizontal guide rail following the displacement. The application has the advantages of good structural stability, strong compatibility and the like.

The present disclosure provides a method and system for analyzing the quality and source of DPF ash, and the scheme includes: S1: when a preset condition is met, obtaining the DPF ash content within the current window detection period; S2: calculating the ash content growth rate between the current window and the previous window detection period, and comparing it with the preset first threshold value to determine whether it exceeds the limit; S3: looping through steps S1 to S2, and counting the number of consecutive exceeding the limit. When the number of consecutive exceeding the limit is greater than the preset second threshold value, the loop is terminated and an ash content growth rate abnormality alarm is issued; S4: determining whether the value of the pressure sensor after the air filter element is higher than the preset third threshold value. If it is higher than the preset third threshold value, it is determined that the source of the ash content is an air filter element failure. If it is lower than the preset third threshold value, it is determined that the source of the ash content is an engine oil failure.

Various embodiments described herein relate to a method, apparatus, and a non-transitory machine-readable storage medium including one or more of the following: locating a 2D plane correlated with a 3D mesh representing a surface of a room; taking a virtual 2D picture of a 3D mesh along the 2D segment; within the virtual 2D picture, finding a hole; determining the virtual picture floor, and hole width; when the hole intersects the virtual picture floor and is at least as wide as a door width then classifying the hole as a door; else classifying the hole as a window.

This invention belongs to the field of image processing technology and discloses a method, device, equipment, and storage medium for judging the results of COVID-19 antigen detection. By calling a camera device to acquire the detection image based on the user's shooting command input on the user interface, image recognition is performed to complete the antigen detection result acquisition, thereby enabling rapid interpretation of the detection results. Simultaneously, the detection image undergoes a qualification verification process; only after passing the verification is the antigen card area further detected. An affine transformation is performed on the antigen card area to obtain a corrected scaled image before window detection. Finally, the detected window areas are classified. This avoids capturing unqualified images from affecting subsequent recognition results, reduces the probability of false detection, achieves a coarse-to-fine detection process, and improves the accuracy of interpretation.

The embodiment of the invention provides a pop-up window processing method and device and a storage medium. In the embodiment of the invention, based on a collaborative architecture of two AI models, pop-up window processing is divided into two stages of potential pop-up window area analysis and pop-up window feature recognition, a potential pop-up window area in a screen image is analyzed by using a first AI model, and a sub-image of the potential pop-up window area is cut out from the screen image; and performing multi-dimensional feature analysis and popup window feature identification based on the sub-images by using the second AI model, positioning position information of closing options according to the multi-dimensional feature analysis and the popup window feature identification, executing popup window closing operation based on the position information, cutting out the sub-images of potential popup window areas, converting global analysis into local analysis, reducing calculation overhead of irrelevant areas, and on the basis, improving the popup window closing efficiency. Model reasoning is used for analyzing the cut sub-images, the efficiency and accuracy of pop-up window detection and closing are effectively improved, then the probability that automatic testing is interrupted due to pop-up window interference is reduced, and the testing stability and continuity are improved.

The invention provides a car window weight reduction device and a car window detection control system. The car window weight reduction device comprises a motion guide device and a pressure reduction supporting structure. The two ends of the pressure reduction supporting structure are slidably connected to the movement guiding device, one end of the movement guiding device is fixed to the car window, the other end of the movement guiding device is fixed to the car body, and when the car window moves up and down, the pressure reduction supporting structure can slide leftwards and rightwards towards the two sides on the movement guiding device. Through the unique sliding connection mode of the pressure reduction supporting structure and the movement guiding device, when the car window moves up and down, the pressure reduction supporting structure can slide leftwards and rightwards towards the two sides on the movement guiding device, and the gravity borne by the car window can be effectively decomposed.

The present invention discloses an air pressure resistance test device for door and window quality detection, belonging to the technical field of door and window detection. It includes a test channel. On one side of the test channel, there is a clamping and adsorption assembly for clamping and limiting the door and window. Inside the test channel, there is a test fan that can slide, and an adjustment assembly is arranged at the bottom of the test fan. In the present invention, by setting the clamping and adsorption assembly, the staff drives the clamping plate to move to one side by adjusting the lead screw, so that the clamping plate gradually approaches the connection box side, and the detection door and window is fixed and limited by extrusion, ensuring the stability of the detection of the door and window under test and improving the stability of the detection data. By controlling the moving stroke of the sliding box, it can adapt to different specifications of building doors and windows, improving the applicability of the device. At the same time, through the vacuum adsorption of the adsorption disc, the rapid adsorption and positioning of the door and window under test can be realized, simplifying the installation and limiting process and improving the detection efficiency.

The invention provides a security detection method and device for network traffic data, and the method comprises the steps: extracting a plurality of preset network features of each traffic data packet in a target time period, and obtaining a plurality of pieces of evolution data; dividing the plurality of evolution data of the target time period into to-be-detected data of a plurality of windows by using a sliding window; processing the to-be-detected data of each window to obtain a matrix representation of the to-be-detected data; determining an approximation ratio test value distribution based on the matrix representation of the data to be detected; determining a threshold value based on the approximate ratio test value distribution and a preset false alarm probability; whether the to-be-detected data is larger than a threshold value or not is judged, and if yes, it is determined that the to-be-detected data is abnormal data; and processing the abnormal data by utilizing hash function calculation and bit operation, and judging whether the abnormal data is attack data or not according to a processing result. According to the invention, the detection efficiency and detection precision of the network traffic data are improved.

The utility model discloses a door and window thermal insulation detection device, which relates to the technical field of door and window detection equipment and comprises a bottom plate, a thermal insulation detection chamber is arranged in the middle of the top of the bottom plate, a refrigeration assembly is arranged on one side of the exterior of the thermal insulation detection chamber, and a heating assembly is arranged on the other side of the exterior of the thermal insulation detection chamber. A door and window adjusting assembly is arranged in the middle of the interior of the heat preservation detection chamber, ventilation plates are symmetrically arranged on the two sides of the door and window adjusting assembly, temperature adjusting assemblies are symmetrically arranged on the two sides of the interior of the heat preservation detection chamber, and a controller is arranged outside the heat preservation detection chamber and located on one side of the top of the bottom plate. The device can clamp and fix doors and windows, guarantees the stability of the doors and windows in the detection process, can adapt to doors and windows of different sizes through adjusting the distance between the two groups of door and window fixing plates, and improves the adaptability.

Disclosed is a method for detecting a line in an image or a video. The method includes smoothing the image, selecting an area in which a line is to be detected, determining a center pixel in the selected area, applying a window centered on the center pixel, detecting a sum of gradient angle differences of pixels surrounding the center pixel, classifying the center pixel determined as the line candidate into a ridge or a valley, and eliminating a non-maximum pixel.