UAV Ground Radar Mapping for Faster Underground Pipe Inspection
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Solution Overview
Problem
Current methods for inspecting underground pipe networks are labor-intensive, costly, and time-consuming, with human inspectors required to analyze data from CCTV systems and mobile robots, limiting the speed and efficiency of pipe inspection and maintenance.
Innovation Solution
The use of an unmanned aerial vehicle (UAV) equipped with sensors such as ground penetrating radar and terahertz units to collect and analyze data for identifying underground pipe features, allowing for rapid identification and characterization of pipe assets, including leaks and material composition, and providing displayable data for targeted inspections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection by human inspectors is used, then inspection accuracy can be maintained, but inspection time and cost increase significantly
Solution Approach 1:
The system enables automated inspection where the UAV collects sensor data, the processor analyzes the data to identify pipe features, and the system automatically generates inspection reports without requiring manual human intervention for data collection and analysis, thereby reducing inspection time while maintaining accuracy through systematic automated processing
Solution Approach 2:
The patent replaces manual mechanical inspection processes with an automated electronic system comprising a UAV equipped with sensors, a processor for data analysis, and automated feature identification algorithms, substituting human inspectors with an integrated automated inspection system that reduces time loss while maintaining measurement precision
2Productivity
If automated sensor data collection is used, then inspection speed increases, but system complexity increases
Solution Approach 1:
The UAV-based inspection system is designed to perform multiple functions including data collection, data analysis, feature identification, and report generation within a single integrated platform, allowing the system to achieve high inspection speed while managing complexity through multi-functional integration rather than requiring separate systems for each task
Solution Approach 2:
The processor acts as an intermediary component that bridges the sensor data collection and feature identification processes, automatically analyzing raw sensor data to identify pipe features and reducing the complexity burden on the overall system by handling data processing tasks centrally rather than requiring complex coordination between multiple independent components
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
Enables quick analysis of larger pipe network sections, reducing the time and cost of inspections by automating the detection of underground features and prioritizing areas for further investigation, thereby improving the efficiency of pipe maintenance and asset management.
Implementation Method 1
obtaining sensor data from a ground penetrating radar (GPR) unit
Data Source
AI summary
One aspect provides a method, including: obtaining sensor data from a ground penetrating radar (GPR) unit; analyzing, using a processor, the sensor data to detect a first object and a second object, the second object being associated with the first object based on location; identifying, with the processor, an underground pipe feature based on the analyzing; associating a position of the underground pipe feature with a location in a pipe network; selecting a subset of the pipe network including a pipe segment associated with the position of the underground pipe feature; and providing the subset of the pipe network as displayable data to a display device. Other aspects are described and claimed.