555 results about "Location detection" patented technology

The invention discloses a power distribution network line fault positioning detection system, and relates to the technical field of power distribution network fault detection. The system comprises a mixed information acquisition layer, a fault feature extraction layer, an intelligent diagnosis layer and a fault positioning layer. The mixed signal acquisition layer comprises a high-frequency transient wave recording unit, a power frequency measurement unit, a wireless pulse sensor and a distributed optical fiber temperature measurement unit; the fault feature extraction layer comprises a time-frequency analysis module, a preprocessing module and a three-dimensional feature vector module; the intelligent diagnosis layer comprises a convolutional attention network, a space-time diagram neural network and a transfer learning module; the fault positioning layer comprises a particle swarm module and a fuzzy reasoning module. According to the invention, data information of the cable is acquired through the mixed information acquisition layer, a video analysis window function is dynamically matched with signal characteristics, a time domain graph scale, a frequency domain resonance component and a space field intensity gradient are constructed, fault diagnosis and positioning are carried out by using the intelligent diagnosis layer, and the fault positioning detection efficiency of the power distribution network is improved.

The invention relates to a ship berthing position detection method and system based on shore end laser radars, and the method comprises the steps: deploying a plurality of laser radars at a shore end, and collecting original point clouds in parallel through an asynchronous thread model; constructing a rigid transformation matrix based on the radar installation attitude parameters, and further generating fusion point cloud data under a unified world coordinate system; then extracting 3D geometric edge points in a preset range of the front edge of the wharf as near-shore point cloud data, and further calculating the minimum ship-shore distance; based on the ship bow direction and a preset segmentation threshold value, the coastal point cloud data are segmented into ship bow area point cloud and ship stern area point cloud in the x-axis direction, the coordinate mean value of the ship bow area point cloud and the ship stern area point cloud is calculated and compared with an expected position in a wharf operation system, and berthing accuracy is judged; and the drift distance is calculated in real time, the drift distance, the attitude angle and the change rate of the attitude angle are compared with corresponding preset threshold values respectively for graded early warning and drift alarm, and high-precision ship berthing position dynamic detection is achieved.

The invention provides a multi-source information fusion unmanned aerial vehicle marine target tracking method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining image data, and extracting the features of a target region; unmanned aerial vehicle attitude data, radar position detection data and AIS identification data are obtained, attitude disturbance correction is executed, and time axis alignment is performed on the data; calculating the visual feature matching offset of the adjacent frames, and comparing the visual feature matching offset with the radar azimuth change trend; constructing a candidate target spatial position set, and executing distance convergence screening and spatial overlapping constraint processing of a geometric projection range on the candidate target spatial position set; motion direction continuity comparison is executed, and target position data is generated; generating a track control instruction for controlling the flight direction and speed of the unmanned aerial vehicle according to the target position data, and adjusting the subsequent flight path of the unmanned aerial vehicle according to the track control instruction; according to the invention, autonomy and accuracy of unmanned aerial vehicle marine target tracking are improved.

An end effector of a surgical instrument may be equipped with a limited (e.g., minimal) number of electrical pads that provides useful tissue presence and positioning information using a limited number of signals communicated between the electrical pads and a controller located remotely from the end effector.

A method comprises registering, by an application executing at a computer system in an inventory system, a tag identifier received from a tag in an inventory environment with location data indicating a location of the tag based on an audio attribute of an audio signal received from the tag, initiating, by the application, a scan of the tag to obtain tag data from the tag and to receive the audio signals from the tag by transmitting a signal to the tag after registering the tag identifier with the location data of the tag, and triggering, by the application, activation of an audio emitting device of the tag to emit an alert signal indicating whether a reader device is in a read range of the tag.

The invention belongs to the field of train structure health monitoring, and discloses a bogie tube plate structure welding seam detection method and device, and the method comprises the steps: obtaining a Lamb wave signal of a to-be-detected tube plate structure welding seam region, and carrying out the preprocessing, and obtaining a preprocessed Lamb wave signal; on the basis of the preprocessed Lamb wave signal, the position of the weld crack defect of the to-be-detected tube plate structure is predicted through the RAPID tomography technology, and a weld crack defect positioning detection result is obtained; inputting the preprocessed Lamb wave signal sequence into a bogie tube plate structure welding seam detection model to obtain a welding seam crack defect quantitative detection result; outputting a welding seam crack defect positioning detection result and a quantitative detection result as welding seam detection results; according to the invention, the positioning and quantitative detection result of the welding seam damage of the bogie tube plate structure can be quickly and accurately obtained, the high-precision detection requirement of the welding seam of the bogie tube plate structure is met, and the safe operation of a rail transit vehicle is ensured.

The invention relates to the field of smart home, and particularly provides an air purification device, method and equipment, a storage medium and a product. The device comprises a position detection module, an animal attraction module and an air purification module; the position detection module is used for detecting the real-time position of the target animal; the animal attraction module is used for sending attraction information interested by a target animal, and the attraction information comprises at least one of sound information, light information and smell information; and the air purification module is used for purifying surrounding air according to the real-time position and the attraction information. By means of the device, the effect of improving the efficiency of the air purification process can be achieved.

The invention discloses a PCB welding spot defect positioning detection method and system based on deep learning, and the method comprises the steps: S1, collecting visible light data and thermal imaging data of a PCB, carrying out the preprocessing, and obtaining the preprocessed visible light data and thermal infrared data of the PCB; s2, according to the pre-processed visible light data and thermal infrared data of the PCB, feature extraction and feature alignment are carried out respectively, and a textural feature map and a temperature feature map after alignment are obtained; s3, carrying out feature calibration, and generating a fusion feature map; s4, calculating a positioning feature map and an optimized enhanced feature map, and finally outputting a welding spot defect detection frame set; s5, calculating a sub-pixel feature map, and outputting a defect distribution probability map; and S6, converting the defect distribution probability graph into a binary defect mask, and outputting a final defect detection result in combination with morphological closed operation. The method can solve the problem that a traditional PCB welding spot defect positioning method is insufficient in small defect recognition accuracy.

A cleaning apparatus includes: a robot cleaner including a motion driver, and a dust bin to store dirt; a station including a dirt container, a seating portion on which the robot cleaner is seated and including an inlet through which the dirt is introduced from the dust bin; and at least one processor to control operations of the robot cleaner and the station. The robot cleaner further includes a location detection sensor configured to obtain information about a location of the robot cleaner, the station further includes a pressure sensor configured to obtain information about a pressure inside the dirt collection duct, and the at least one processor is configured to control the motion driver to adjust the location of the robot cleaner to allow an opening of the dust bin to correspond to the inlet based on the information obtained by the location detection sensor and the pressure sensor.

The invention discloses a steel rail corrugation detection method and device based on computer vision, and relates to the technical field of rail transit, and the method comprises the steps: 1, periodically and automatically collecting a high-resolution steel rail surface image, and carrying out the preprocessing; 2, carrying out steel rail region detection on the preprocessed steel rail surface image, and extracting a steel rail sub-image; step 3, carrying out corrugation position detection on the steel rail sub-graph to obtain a corrugation area coordinate; and 4, mapping the coordinates of the corrugation area to a coordinate system of the steel rail surface image to obtain full-image corrugation positioning. According to the method, advanced image processing and deep learning algorithms are adopted, the steel rail corrugation characteristics can be effectively extracted from a complex background, high-precision disease recognition and positioning are achieved, compared with a traditional method, the method has higher detection sensitivity and lower false alarm rate, and the precision ratio and recall ratio of steel rail corrugation detection can be remarkably increased.

The embodiment of the invention provides a target detection method and device, a controller and automatic driving equipment, and the method comprises the steps: obtaining a multi-view image of a target region where the automatic driving equipment is located, and corresponding camera parameters, and the target region comprises a to-be-detected target object; performing feature extraction on the multi-view image, fusing camera parameters to obtain a three-dimensional feature image of the target area, performing rasterized semantic segmentation and offset prediction on the three-dimensional feature image to respectively obtain a grid mask image and offset information, and performing image segmentation on the grid mask image and the offset information; the grid mask image is used for indicating information of a target grid occupied by the target object in each grid of the three-dimensional feature image, and the offset information is used for indicating position offset information of the target object in the target grid; and determining the position information of the target object according to the offset information and the information of the target grid in the grid mask image. By adopting the scheme, the obtained position information error of the target object is smaller, and the position detection result of the target object is more accurate.

An object of the present disclosure is to make it possible to isolate whether an abnormality has occurred in any one of sections of an optical fiber and a device.The present disclosure provides an optical power feeding system including: a light source that outputs power feeding light to an optical fiber; a plurality of optical nodes connected in series to the optical fiber; and an optical tester that transmits test light from the light source side of the optical fiber toward the plurality of optical nodes and detects reflected light of the test light, in which each optical node includes: a photoelectric conversion element that converts the power feeding light into electricity; a power storage unit that stores electric power converted by the photoelectric conversion element; an optical switch that switches an output destination of the power feeding light propagated through the optical fiber between the photoelectric conversion element included in the optical node and another optical node connected to the optical fiber; a control unit that switches connection of the optical switch in accordance with a control signal superimposed on the power feeding light; and a test light cut filter that reflects, toward the optical tester, the test light output from the optical switch to the photoelectric conversion element.

Disclosed are systems and methods including computing-processes, which may include layers of machine-learning architectures, for assessing risk for calls directed to call center systems using carrier signaling metadata. A computer evaluates carrier signaling metadata to perform various new risk-scoring techniques to determine riskiness of calls and authenticate calls. When determining a risk score for an incoming call is received at a call center system, the computer may obtain certain metadata values from inbound metadata, prior call metadata, or from third-party telecommunications services and executes processes for determining the risk score for the call. The risk score operations include several scoring components, including appliance print scoring, carrier detection scoring, ANI location detection scoring, location similarity scoring, and JIP-ANI location similarity scoring, among others.

The invention discloses an optical fiber unmanned aerial vehicle and optical fiber dog cooperative control method and system, and the method comprises the steps: controlling an optical fiber unmanned aerial vehicle to fly to a target region, collecting a first environment parameter, and obtaining a first region image; calculating the safety coefficient of the current position of the optical fiber unmanned aerial vehicle, and when the safety coefficient is greater than a preset threshold, controlling the optical fiber dog to advance to the current position of the optical fiber unmanned aerial vehicle; sending a second environment parameter and a second area image collected by the optical fiber dog to the control terminal, and calculating the distance to the optical fiber unmanned aerial vehicle in real time according to the advancing speed of the optical fiber dog; when the distance reaches a preset distance value, controlling the optical fiber unmanned aerial vehicle to continuously fly and keeping the preset distance value with the optical fiber dog; establishing a three-dimensional environment model of the target area; and planning an optimal rescue path based on the three-dimensional environment model, and sending the optimal rescue path to the control terminal. According to the invention, the accuracy and comprehensiveness of dangerous position detection data are improved, and the efficiency of emergency rescue work is improved.

The invention discloses a part relative position detection method and system under three-axis movement and a medium, and relates to the technical field of position detection, and the method comprises the steps: carrying out the scanning of a target part, obtaining three-dimensional point cloud data, carrying out the region segmentation recognition, carrying out the clustering analysis, obtaining a point cloud cluster of a plurality of feature points, carrying out the global fitting, and determining a plurality of feature space coordinates; constructing a part local coordinate system, mapping the plurality of feature space coordinates to the part local coordinate system for position calculation, and obtaining a plurality of feature relative position relation diagrams; traversing a plurality of feature relative position relation graphs to perform deviation marking, obtaining a plurality of out-of-tolerance items, performing binding storage on the out-of-tolerance items and a target part, constructing a position detection anomaly database, performing position deviation training, and constructing a position deviation prediction channel to perform feedback optimization on a detection path. The technical problems that in the prior art, part relative position detection precision is insufficient, and efficiency is low are solved, and the technical effect of improving part relative position detection precision and detection efficiency is achieved.

The invention provides a constant false alarm target detection method and device for an airborne random pulse repetition interval radar system, and relates to the technical field of radar signal processing. The method comprises the following steps: estimating a target scene through a compressed sensing model according to an echo sampling result and an observation matrix to obtain an estimation result of the target scene; taking a constant detected false alarm rate as a target, and constructing test statistics according to an echo sampling result, the observation matrix and an estimation result; performing threshold calculation based on chi-square distribution according to a preset expected false alarm rate and the test statistics to obtain a detection threshold; based on the support set definition of the clutter region, calculating according to the information of the receiving platform to obtain the position of the clutter region; and based on the clutter region position, according to the test statistics and the detection threshold, performing target position detection on a region outside the clutter region to obtain a target position. The method is an efficient and accurate constant false alarm target detection method for an airborne random pulse repetition interval radar.

A method comprises registering, by an application, a tag identifier received from a tag in an inventory environment with location data indicating a location of the tag based on a visual attribute of the tag, initiating, by the application, a scan of the tag to obtain tag data from the tag and to capture an image depicting the tag by transmitting a signal to the tag after registering the tag identifier with the location data of the tag, and triggering, by the application, activation of a light emitting diode (LED) on the tag to indicate whether a reader device is in a read range of the tag, in which a visual feature of the LED indicates whether the reader device is in the read range of the tag, and wherein the signal is used to activate the LED on the tag.

The invention discloses a ground equipment oil leakage hidden danger identification method and system, and the method comprises the steps: collecting the ground surface reflected light brightness data of a ground region of target equipment through a satellite multispectral channel, recognizing a suspected oil leakage region according to the ground surface reflected light brightness data, and extracting the position coordinates and boundary range of the suspected oil leakage region; the unmanned aerial vehicle detects the organic matter concentration of the suspected oil leakage area one by one according to the inspection flight route, determines concentration distribution data, identifies an abnormal concentration standard-exceeding area according to the concentration distribution data, and generates an abnormal concentration distribution area map corresponding to the abnormal concentration standard-exceeding area; and comparing and matching the suspected oil leakage region with the concentration anomaly region map, determining a comprehensive matching degree score about the position overlapping degree and the boundary consistency, comprehensively evaluating the suspected oil leakage region and the concentration anomaly exceeding region, and determining an actual oil leakage region, thereby improving the recognition efficiency and reliability of the oil leakage hidden danger.

The invention discloses a valve recognition pose estimation method and system based on an FPPE network, and relates to the field of image recognition. The problems that an existing visual positioning and pose detection method for the valve is not high in pose recognition degree and too large in calculated amount are solved. The method comprises the following steps: collecting a multi-angle valve picture and valve point cloud data, and constructing a valve point cloud data set and template point cloud; the RT-DETR v2 target detection network is trained; an FPPE network is constructed and trained; according to the trained RT-DETR v2 network, carrying out target identification and plane target position detection on the valve image to obtain a central position coordinate of a valve area and an ROI boundary point pixel coordinate; points of all depths in the ROI space area are extracted to form a view cone point cloud; and inputting the view cone point cloud into the trained FPPE network to obtain a final valve pose estimation result. The method is applied to the technical field of object positioning.

The invention is applicable to the technical field of data mining, and provides a deep learning-based false data positioning and recovery system for a power system, which comprises a data acquisition and standard processing module, a position detection module and a data recovery module, the data acquisition and standard processing module is used for acquiring operation parameters of the electric power system and performing cleaning and normalization processing on the operation parameters to generate standardized operation parameters; the position detection module is used for inputting the standardized operation parameters into a preset spatial-temporal feature fusion detection model and outputting a predicted position index of the false data; and the data recovery module is used for generating recovery data according to the predicted position index and the TVAE-WGANGP recovery model. According to the method, the positioning sensitivity and the data reconstruction precision in a complex attack scene can be remarkably improved, and a reliable active defense technology is provided for security protection of a smart power grid.

The present invention is specifically a positioning auxiliary device for steel truss hoisting; the device is characterized by: an acoustic laser composite rangefinder transmitting device (1), a laser rangefinder receiving device (2), a three-dimensional scanner (3) and a computer (4); wherein the acoustic laser composite rangefinder transmitting device (1) is installed on the truss column foot, the laser rangefinder receiving device (2) is installed on the truss support, and the three-dimensional scanner (3) and the computer (4) are handheld. The present invention can control the relative position relationship between the truss and surrounding obstacles in real time during the hoisting process of a large truss, and realize real-time position detection of the truss and surrounding obstacles. Even if the truss column foot is in a blind spot, through the present invention and actual on-site operation, it can still prevent it from colliding or scraping with the surrounding obstacles, thereby ensuring the safety and stability of the hoisting process.

The invention provides an underground cable position detection method and system based on a ground penetrating radar, relates to the technical field of ground penetrating radar imaging, and provides a fast search method of an optimal migration speed combined with F-FK, which does not need to traverse all speed values in a scanning interval, and only needs to determine a small number of key search points based on a specific sequence. The search interval is dynamically reduced by comparing the information entropy values of the search points, the number of times of calculation of the imaging entropy values is greatly reduced, and the cable data processing efficiency is greatly improved; secondly, the algorithm does not need a fixed scanning interval, the search point determined through the golden section proportion can adaptively focus the optimal speed area, even if the cable penetrates through the concrete-wet soil mixed medium section, the speed sudden change point can be accurately captured, the problem that the real speed is missed at the fixed interval is avoided, and finally, the algorithm is high in convergence speed and high in accuracy. Compared with a traditional method, the processing time of GPR data of a long measuring line and a high-density sampled cable is greatly shortened, and the method can be applied to emergency troubleshooting.

The invention discloses a position detection system and method of a jet structure and an engine. The position detection system comprises an image acquisition assembly and a prism assembly. Wherein the image acquisition assembly is located in the spraying direction of the spraying structure and is fixed; and the prism assembly is fixed in the mounting cavity, is arranged corresponding to the spraying section of the spraying structure, and is at least used for projecting the spraying section onto the image acquisition surface of the image acquisition assembly. According to the invention, the prism assembly can be utilized to refract an image on the side surface of the jet structure to the horizontal direction, and then the image acquisition assembly is utilized to shoot so as to obtain two two-dimensional projection images in the vertical direction at the same time; and the angle deviation and the translation amount of the part are calculated through image analysis, and the three-dimensional space coordinates of the point to be measured are finally synthesized based on the reference coordinates, so that the injection point position of the oil nozzle is obtained outside the mounting cavity by using a camera and a controller.

A control method for a mobile device, and a related device. The method comprises: controlling a mobile device to move along a preset path; when the mobile device moves to a location at which a satellite positioning signal does not meet a preset condition, controlling the mobile device to continue moving along the preset path for first mileage or a first duration; after the mobile device continues moving along the preset path for the first mileage or the first duration, if it is detected that the satellite positioning signal does not meet the preset condition, controlling the mobile device to stop moving, collecting an environmental image in at least one direction by means of a camera, and identifying a target object by means of the environmental image, wherein the target object belongs to a preset object or sky region; and controlling the mobile device to move toward the target object, such that the mobile device detects at a location after movement that the satellite positioning signal meets the preset condition.

To provide a position measurement device, a position measurement method, and a position measurement program, in which position detection accuracy can be improved when a sensor measures an object in a non-contact mode from above the object.SOLUTION: A position measurement device 1, a position measurement method, and a position measurement program use a controller 10 into which data are inputted from a sensor 50 for measuring an object in a non-contact mode from above the object. The sensor 50 has a primary scanning direction in which measurement points are aligned with a prescribed spacing when measuring the object and a sub-scanning direction in which measurement points are aligned with a wider spacing than the spacing in the primary scanning direction. The controller 10 acquires data on target measurement points within a detection target part from among measurement points spreading across the horizontal plane of a maker which has a reference point on a straight line suspended vertically from the sensor 50. The controller also calculates the attitude of the sensor 50 toward the reference point on the basis of the spacing distances.SELECTED DRAWING: Figure 1

Conferencing systems and methods configured to generate true talker coordinates for use in camera tracking of talkers and objects in an environment and other room intelligence use cases are disclosed. The initial configuration and ongoing usage of conferencing systems can be improved by detecting and converting the locations of objects and talkers in an environment into a common coordinate system. The amount of time and effort by installers, integrators, and users, can be reduced leading to increased satisfaction with installation and usage of the conferencing system.

A radar device includes: a first receiver antenna outputting a first reception signal; a second receiver antenna outputting a second reception signal; a third receiver antenna outputting a third reception signal; a first receiver circuit processing the first reception signal; and a second receiver circuit selecting one of the second reception signal and the third reception signal and processing the selected signal. The first receiver antenna is placed apart from the second receiver antenna in a first direction and apart from the third receiver antenna in a second direction.

This application discloses a method, apparatus, device, and storage medium for object reconstruction, belonging to the field of 3D reconstruction technology. The method includes: when a terminal detects a target object, performing feature position detection on the target object to obtain feature information; if feature information is detected, scanning a local area around the target object to obtain first scan information; and establishing a 3D model of the target object based on the first scan information. After detecting the target object to be modeled, this application first determines whether the target object has feature information through feature position detection. If the target object has feature information, a 3D model of the target object is then established based on the first scan information. Therefore, the 3D model established in this embodiment closely matches the actual shape of the target object, has high accuracy, and achieves good object reconstruction results.

To provide a technology that optimizes the balance between positioning accuracy and power consumption in monitored devices, thereby efficiently acquiring highly accurate location information while improving battery life. [Solution] The monitored terminal includes a first positioning unit 11 that measures position with low power consumption, a second positioning unit 12 that measures position with high accuracy, a positioning switching unit 13 that controls the operation of the second positioning unit 12 according to the error in the position obtained by the first positioning unit 11, and a transmission unit 14 that transmits at least one of the acquired positions to the server.

According to examples, an apparatus may include a processor that may, responsive to a determination that a secondary display is connected to the apparatus, cause a primary display of the apparatus to display a window including an option to be selected to proceed with a location detection operation of the secondary display. The processor may also cause an icon to be displayed on the secondary display, track a movement of a cursor from the primary display to the icon displayed on the secondary display, and determine a position of the secondary display with respect to the primary display based on the tracked movement of the cursor. The processor may further store the determined position of the secondary display with respect to the primary display.