7 results about "Edge orientation" patented technology

Methods, systems, and devices for an antenna subsystem are described. An antenna subsystem may include multiple printed wiring boards and multiple antenna substrates mounted on multiple sides of the printed wiring boards. The antenna substrates may include one or more planar-oriented elements that emit or receive in a planar orientation and one or more edge-oriented elements that emit or receive in an edge orientation. The various antenna elements may be connected to one or more analog-to-digital converters that may convert signals received at the antenna elements to obtain digital component receive signals that may be processed by one or more signal processors according to a set of beam weights to obtain a signal of a radio frequency beam that may have a field of view greater than (180) degrees.

The application discloses a kind of based on digital twinning turnout switch machine monitoring and fault diagnosis system and method, belong to rail transit field, including based on edge orientation and edge edge federal union's cloud edge collaborative mode to the data of turnout switch machine is collected and is governed;Establish turnout switch machine twinborn model, including three-dimensional model, behavior model and diagnostic model, and will switch machine work twinborn data integration and fusion in three-dimensional model, realize three-dimensional visualization;Based on one-dimensional power signal twinborn data and two-dimensional GASF image parallel learning fault diagnosis method diagnoses whether turnout switch machine fails.This application uses the above-mentioned based on digital twinning turnout switch machine monitoring and fault diagnosis system and method, effectively improve the switch machine operation and maintenance efficiency, reduce the operation and maintenance cost of switch machine, can be more intuitive, efficient, intelligently realize switch machine health management.

The application relates to the field of artificial intelligence, and discloses a bus safety early warning method and system supporting road condition shadow removal, which comprises the following specific steps: acquiring an original image; inputting the original image into an HSI space and constructing a shadow identification index SI; obtaining a shadow preliminary detection image; obtaining a shadow image and a shadow preliminary removal image; performing intrinsic decomposition on the shadow preliminary detection image to obtain a color orientation template; constructing an edge contour verification image pair of the original image to obtain a structural skeleton as an edge orientation template; constructing a generative adversarial network; obtaining a detection result output by a discriminator based on the color orientation template and the edge orientation template; obtaining a road condition shadow removal image according to the detection result; and performing bus safety early warning according to the road condition shadow removal image. The application solves the problems that the existing bus safety early warning technology training depends on data, and the phenomena of fuzzy repair area, inconsistent chroma and boundary artifacts, and has the characteristics of high early warning accuracy.

This invention discloses an IoT fault diagnosis method and system based on dynamic causal graph learning. The method collects three types of heterogeneous data streams: network signaling, device telemetry, and platform logs, and performs type-aware standardization preprocessing to generate a standardized multimodal time-series matrix. It identifies subsets of changing variables and anomaly markers through sliding window statistical feature change detection. It performs local skeleton updates and edge orientation on the causal adjacency matrix using incremental mixed conditional independence testing, dynamically maintaining a causal directed acyclic graph. When an anomaly is detected, a candidate root cause set is constructed, and the average causal effect value of each candidate root cause is quantified using a do-intervention propagation algorithm based on a structural causal model. The root cause localization results are then sorted and output according to the average causal effect value. The system includes a multi-source heterogeneous data acquisition and preprocessing module, an anomaly detection and change subset identification module, a dynamic causal graph learning module, a counterfactual inference module, and a root cause report generation module.

The invention relates to the technical field of blind person perception assistance, in particular to a blind person image perception assistance system and method based on electric tactile sensation. The system comprises an image acquisition and basic processing module, a key object identification and mask generation module, an edge and gray information processing module, an edge-guided dynamic scanning module, a multi-mode electric tactile coding and output module and a user feedback adjustment module. The method comprises the following steps: acquiring an image, identifying a key object, extracting edge and gray information, dividing grids based on an edge trend, performing dynamic scanning, and finally mapping stimulation information to a hand and brain bimodal electric tactile array for output. According to the method, hand accurate contour touch and brain overall imaging stimulation are fused, a closed-loop adjustment mechanism based on key object recognition and user feedback is introduced, the problems that a traditional method is inaccurate in image structure perception and low in information transmission efficiency are effectively solved, and the perception efficiency and recognition accuracy of the blind to image information are remarkably improved.

The invention discloses a digital twinning-based turnout switch machine monitoring and fault diagnosis system and method, and belongs to the field of rail transit, and the method comprises the steps: carrying out the collection and treatment of the data of a turnout switch machine based on an edge guiding and edge-edge federation combined cloud edge cooperation mode; establishing a turnout switch machine twinborn model which comprises a three-dimensional model, a behavior model and a diagnosis model, and integrating and fusing switch machine twinborn data into the three-dimensional model to realize three-dimensional visualization; the fault diagnosis method based on one-dimensional power signal twinborn data and two-dimensional GASF image parallel learning is used for diagnosing whether the turnout switch machine breaks down or not. According to the turnout point switch monitoring and fault diagnosis system and method based on digital twinning, the operation and maintenance efficiency of the point switch is effectively improved, the operation and maintenance cost of the point switch is reduced, and health management of the point switch can be achieved more visually, efficiently and intelligently.

The application relates to the technical field of image processing, in particular to an image reconstruction method based on edge orientation constraint. A non-convex regularization term is constructed based on edge information of an image block, an L1-TV model is combined to construct an image reconstruction model, and a mature optimization algorithm is used for solving. The model uses dynamic edge detection to locate a key structure area of an image, and correspondingly protects wavelet coefficients, so as to reduce the shrinkage deviation of large coefficients, and thus edge and texture information can be more accurately reserved.