4 results about "Surface recovery" patented technology

The application discloses a kind of based on AI Lingnan historical building mural protection restoration method, comprising: step 110, obtaining the mural image data to be repaired, and the data is preprocessed;Step 120, the preprocessed data is input into mural restoration model;Step 130, the mural restoration model is based on the preprocessed data input to generate virtual reinforcement layer for mural hollow area, using physical engine simulates stress distribution under the action of gravity, obtains the image after structure repair;Step 140, the image after structure repair is based on style migration reconstruction missing pattern, obtains surface recovery image;Step 150, based on visual fusion to the surface recovery image color recovery, obtains the image after repair;Step 160, the image after repair is compared with original image and historical data, check whether the image after repair meets requirements.The application solves the problem of excessive dependence on expert knowledge reserves and experience, realizes the disease site of quick and accurate determination.

This invention provides a method and system for measuring atmospheric data using integrated optical sensing, comprising: real-time acquisition of surface pressure distribution and surface recovery temperature using a FADS subsystem, and inversion of Mach number, static pressure, and attack angle parameters; periodic laser emission using a MOADS subsystem, and analysis of atmospheric parameters such as air velocity, attack angle, and density through backscattering spectroscopy; independent Kalman filters running on the FADS and MOADS subsystems, performing local optimal estimations using aerodynamic equations and observation equations; employing a federated Kalman filtering algorithm, dynamically adjusting the weights based on the residual covariance matrix of the two subsystems, and jointly solving the pressure, temperature data, and optical signals based on the adjusted weights, outputting Mach number, attack angle, total / static pressure, total / static temperature, and atmospheric density. The technical solution of this invention addresses the technical problems of high cost and limited environmental adaptability associated with using FADS or MOADS systems alone in existing technologies.

The application discloses a multi-source data fusion furniture AR preview space replacement matching system, which comprises a collection association module, a region division module, a depth splitting and supporting surface recovery module, a model matching module and an occlusion synthesis module. The system collects a current frame RGB image, an aligned original depth map and a camera pose, and associates scene points to a world coordinate system; performs semantic segmentation on the image and divides a furniture region to be replaced, a reserved object region and a background structure region; splits the depth map according to this, fits a ground plane and a wall plane, and generates a recovered ground region and a recovered wall region; then places and matches a virtual furniture three-dimensional model with the recovered region, performs pixel-by-pixel occlusion judgment based on a reserved depth map, and synthesizes and outputs an AR preview picture after furniture replacement.

The present invention relates to an automated turf repair and condition-management system configured to detect, fill, and monitor divots and surface irregularities on turf areas such as golf courses and athletic fields. The system includes an air-assisted dispensing array that precisely delivers a dry repair material through multiple controllable nozzles, and a liquid-mist subsystem that applies water, binder, or growth solution post-nozzle to create a wetted, stabilized fill. A control system measures divot geometry, computes fill volume, and regulates airflow, mist, and nozzle activation in real time. The system can be integrated with a host vehicle or autonomous platform, and may operate in coordination with aerial drones for GPS-based mapping, repair scheduling, and regrowth monitoring. This integrated approach enables data-driven, repeatable, and biologically responsive turf restoration with improved accuracy, reduced labor, and accelerated surface recovery compared to prior mechanical or manual repair methods.