UAV Weight Distribution Measurement Using Load Cell Grids
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Solution Overview
Problem
Current maintenance protocols for vehicle fleets, especially for unmanned aerial vehicles (UAVs), rely on manual inspection which is time-consuming and error-prone, and existing automated systems fail to capture comprehensive physical metrics such as weight distribution, center of mass, and moments of inertia, limiting their effectiveness in ensuring stable flight operations.
Innovation Solution
Implementing a system with physical metrics acquisition (PMA) devices like load cell grids and configurable scales that measure weight distribution and moments of inertia, coupled with a central controller that processes this data to provide analytics for total weight, center of mass, and moments of inertia, enabling stable flight and efficient power management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to collect vehicle data, then inspection accuracy can be maintained, but inspection time increases significantly and error rates increase
Solution Approach 1:
The patent replaces manual mechanical inspection with automated vision systems including cameras, depth sensors, and image processing algorithms. The system automatically captures images of vehicles, processes them through computer vision algorithms, and extracts maintenance data without human intervention, thereby reducing inspection time while maintaining accuracy through automated defect detection.
Solution Approach 2:
The system enables vehicles to be self-inspected through automated capture of vehicle images and automatic processing of maintenance data. The vision system and processing unit work autonomously to identify defects, determine maintenance needs, and generate reports without requiring manual inspection, allowing the inspection process to serve itself through automation.
2Loss of time
If automated error code systems are used to collect vehicle data, then inspection time is reduced, but the system cannot capture all types of useful physical data about the vehicle
Solution Approach 1:
The patent implements a multi-functional vision system that performs multiple measurement tasks simultaneously using the same hardware infrastructure. The system captures vehicle images, measures physical dimensions, detects defects, and determines maintenance needs all through a single automated inspection process, making the system universal in its capability to collect diverse vehicle data types without requiring separate specialized equipment for each measurement type.
3Reliability
If comprehensive physical metrics measurement systems are implemented, then flight stability and power management improve, but system complexity and cost increase
Solution Approach 1:
The patent segments the measurement system into distinct functional modules: image capture devices (cameras, depth sensors), processing units for different types of analysis (dimensional measurement, defect detection), and output systems for different data types. This modular segmentation allows the complex measurement system to be broken down into manageable components that can be independently optimized, maintained, and scaled based on specific operational requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system allows for automated, accurate, and efficient collection of physical metrics for multiple UAVs, improving flight stability and power management by providing precise data for control systems, thus enhancing operational efficiency and reducing maintenance time.
Implementation Method 1
The PMA device may include a grid of load cells or a configurable scale and may be used to determine a distribution of weight of the UAV at three or more points associated with the UAV.
Implementation Method 2
one or more scales may be moveably positioned over a surface. A UAV may be placed on the surface, lifted and measured by the one or more scales
Implementation Method 3
The inertia device may include one or more motors that may cause rotation of the inertia device and/or the UAV, and one or more accelerometers that may determine one or more attributes of rotations of the UAV
Data Source
AI summary
A weight distribution associated with an unmanned aerial vehicle (UAV) may be determined prior to dispatch of the UAV and/or after the UAV returns from operation (e.g., a flight). In some embodiments, one or more UAVs may be placed on or proximate to a physical metrics acquisition (PMA) device. The PMA device may include a configurable scale and may be used to determine a distribution of weight of the UAV at three or more points associated with the UAV. The distribution of weight may be used generate analytics, which may include a total weight of a vehicle, a center of mass of the vehicle (in two or more dimensions), power requirements of the UAV for a given flight task (e.g., how much battery power the UAV requires, etc.), and/or other analytics. In various embodiments, the PMA device may perform moment of inertia tests for the UAV.