Asset Inspection Data Acquisition Planning for Complete UAV Capture
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Solution Overview
Problem
Existing data acquisition methods using UAVs for physical asset inspection, such as cell towers and roofs, often result in incomplete or inaccurate data due to human oversight and the inability to consistently capture all relevant aspects, especially in challenging conditions, leading to inefficient and potentially dangerous manual inspections.
Innovation Solution
A method that integrates sensor data acquisition with existing database information to determine the necessity of additional data collection, using automated data processing and machine learning to generate inspection plans and ensure comprehensive data capture, thereby reducing human error and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual inspection methods are used for physical assets, then human judgment and flexibility can be applied, but data completeness and accuracy deteriorate due to human oversight and inconsistency
Solution Approach 1:
The patent replaces manual inspection with an automated system comprising a UAV, sensor array, and processing unit. The UAV flies along a planned trajectory capturing sensor data, which is then processed to generate 3D reconstructions and measurements. This substitution eliminates human oversight and inconsistency while maintaining operational flexibility through automated decision-making algorithms.
Solution Approach 2:
The system performs self-inspection by autonomously navigating to the physical asset, capturing necessary sensor data, processing the information, and generating inspection reports without requiring continuous human intervention. The automated processing unit analyzes the captured data and determines whether additional data collection is needed, enabling the system to serve itself in completing the inspection task.
2Measurement precision
If comprehensive data collection is performed to ensure accuracy, then measurement precision improves, but data processing time and complexity increase
Solution Approach 1:
The system performs preliminary actions by first capturing sensor data and generating an initial 3D reconstruction before determining whether additional data collection is needed. The processing unit analyzes the completeness and quality of the initial reconstruction, allowing the system to avoid unnecessary comprehensive data collection while ensuring sufficient measurement accuracy for the inspection objectives.
Solution Approach 2:
The system implements feedback by continuously analyzing the quality and completeness of captured sensor data during the inspection process. The processing unit evaluates whether the current data suffices for accurate measurements or if additional data collection is required, adjusting the inspection plan dynamically to balance measurement precision with processing efficiency.
3Productivity
If automated data acquisition systems are deployed, then productivity and consistency improve, but system complexity and initial setup requirements increase
Solution Approach 1:
The patent employs a multi-functional system where the UAV serves multiple purposes: navigation, sensor data acquisition, and platform for carrying various sensor types. The processing unit handles multiple tasks including 3D reconstruction, measurement extraction, quality assessment, and decision-making regarding additional data collection. This universality improves productivity while managing complexity through integrated design.
Solution Approach 2:
The system segments the inspection process into distinct modules: UAV navigation, sensor data acquisition, 3D reconstruction, measurement extraction, and quality assessment. Each module performs a specific function, allowing the system to achieve high productivity through automated workflows while managing complexity through modular architecture that can be configured based on inspection requirements.
Data Source
AI summary
Various examples are provided for data acquisition, processing, and output generation for use in analysis of a physical asset or a collection of physical assets of interest. In one example, a method includes providing a user information goal including user information for acquisition, processing, or output of data associated with a physical asset or collection of physical assets; and evaluating existing database information to determine whether all or part of the first user information goal can be substantially completed by retrieval and processing of an information set obtainable from existing database information. If the user information goal cannot substantially be completed using the information set, then a data acquisition plan configured to acquire data needed to substantially complete first user information goal can be generated. If the user information goal can be substantially completed using the information set, then the formation set can be processed to provide an output.