4results about How to "Comprehensive inspection" patented technology

The invention is suitable for the technical field of unmanned aerial vehicle routing inspection, and provides a water conservancy and hydropower building construction self-adaptive routing inspection unmanned aerial vehicle path planning method and system, and the method comprises the following steps: building a dynamic four-dimensional environment model based on an airborne multi-source sensor of an unmanned aerial vehicle and construction plan data; based on the dynamic four-dimensional environment model, a preset key inspection point and a path fitting algorithm, generating a three-dimensional space path matched with the surface form of the terrain building; when the unmanned aerial vehicle executes an inspection task, sensing environment change in real time, and when an unforeseen obstacle is recognized or dynamic update sent by a construction BIM management system is received, performing local path re-planning based on a composite cost function; according to the invention, the environment information and the construction plan data acquired by the airborne multi-source sensor of the unmanned aerial vehicle can be fused in real time, and the dynamic change of the construction environment is accurately reflected. And local path re-planning is carried out based on the composite cost function, so that the unmanned aerial vehicle can avoid obstacles in time, and smooth completion of an inspection task is ensured.

This invention discloses a method, equipment, and storage medium for selecting favorable areas of low-permeability carbonate gas reservoirs based on intuitionistic fuzzy multi-attribute boundary approximation region comparison (MABAC). Specifically, it includes the following steps: S1, screening key indicators of carbonate gas reservoirs for favorable area selection; S2, determining attribute weights based on the Brown-Warshall Method (BWM); S3, establishing a favorable area selection model for low-permeability carbonate gas reservoirs using the intuitionistic fuzzy multi-attribute boundary approximation region comparison method (MABAC); S4, calculating conditional probabilities, and then ranking the decision objectives included in the positive, boundary, and negative domains to obtain the favorable area selection results. This invention can simultaneously consider the influence of multiple factors on different schemes and grasp the priority relationship between factors.

This utility model discloses a touch screen bonding bubble inspection device, including a base plate. An electric push rod is fixedly installed in the center of the top of the base plate. Support frames located on both sides of the electric push rod are fixedly installed on the top of the base plate. A fixed bracket located behind the support frames is fixedly installed on the top of the base plate. An LED light source is movably mounted on the top of the fixed bracket. A placement platform is fixedly installed on the top of the support frames. A placement groove is formed on the top of the placement platform. A telescopic cylinder is fixedly installed through the bottom of the placement groove. A lifting plate located between the two support frames is fixedly installed at the movable end of the top of the electric push rod. A telescopic rod is fixedly installed on the top of the lifting plate. The air pressure inside the telescopic cylinder decreases, and the screen is fixed in the placement groove under negative pressure, ensuring that the screen is fixed without obstructing it, thus allowing for more comprehensive inspection.

This invention relates to a method for fine-grained route planning in power distribution networks based on insulator detection. The method includes: constructing and training an insulator detection model based on an improved YOLOv7 model, then deploying the model on a drone; performing fine-grained route planning: cleaning the power distribution network point cloud data and tower inspection tables; then planning coarse waypoints and routes based on the usable data obtained from the data cleaning; continuously capturing images and detecting insulators using the insulator detection model during the drone's inspection flight along the preset route; when an insulator is detected, adjusting the drone's position in real time and using that position as a new waypoint for fine-grained route planning; after the flight mission ends, using the captured insulator images as new samples for training the model; and simultaneously using the newly generated fine-grained waypoints and routes as coarse waypoints and routes for the next flight mission. This method can be used for fully autonomous drone inspection operations.