Remote Facility Change Detection Using LiDAR and Multispectral Imagery
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Solution Overview
Problem
Traditional facility inspection methods fail to timely monitor changes across multiple elements using a single set of observations, miss spatial and spectral changes, leading to inaccurate evaluation of equipment conditions and potential failures.
Innovation Solution
A system utilizing processors and memory to analyze collected data, generate three-dimensional models from spatial and multispectral image data, and detect changes by comparing new data to previous models, with alerts generated when changes exceed predetermined thresholds, employing autonomous vehicles and LiDAR systems for data collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual inspection methods are used, then inspection coverage is limited to individually visited facilities, but timely monitoring of multiple elements across multiple facilities is not achieved
Solution Approach 1:
The system uses a single set of multispectral and thermal imagery observations to simultaneously monitor multiple facility elements (power transformers, switchgear, conductors, insulators, etc.) across multiple facilities, enabling one inspection campaign to serve multiple inspection objectives rather than requiring separate inspections for each element type
Solution Approach 2:
The patent replaces manual mechanical inspection processes with automated remote sensing systems that capture multispectral and thermal data, eliminating the need for physical inspector presence at each facility and enabling simultaneous monitoring of multiple elements through data processing algorithms
2Measurement precision
If traditional inspection methods focus on single data types, then inspection simplicity is maintained, but spatial and spectral changes are not detected
Solution Approach 1:
The system merges multiple data types (multispectral imagery, thermal imagery, and LiDAR point cloud data) into a unified inspection framework, combining spatial, spectral, and thermal information to detect a broader range of equipment conditions that would be invisible to single-data-type inspections
Solution Approach 2:
The patent adds spectral and thermal dimensions to traditional visual inspection by incorporating multispectral and thermal imagery, transforming the inspection from purely spatial (2D/3D visual) to include spectral reflectance and temperature measurements, enabling detection of equipment issues before they manifest visually
3Reliability
If periodic on-site inspection is used, then equipment condition assessment is performed, but missed equipment failures occur due to insufficient monitoring frequency
Solution Approach 1:
The system enables continuous monitoring of facility elements by processing sequential imagery and thermal data over time, maintaining constant surveillance of equipment conditions rather than intermittent checks, allowing trends to be tracked and anomalies to be detected between traditional inspection intervals
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 timely and accurate detection of spatial and spectral changes in facility components, reducing missed equipment failures and maintenance issues through automated and remote change detection.
Implementation Method 1
The spatial image data includes image-derived point cloud data generated by one or more autonomous vehicles in proximity to the facility. In this example, the autonomous vehicles may include ground and/or airborne light imaging direction and ranging (LiDAR) systems.
Implementation Method 2
receiving multispectral and thermal image data in the previously collected data, the multispectral and thermal image data describing a color, spectral reflectance, and temperature range for each of the elements from one or more multispectral and thermal cameras
Implementation Method 3
receiving multispectral and thermal image data in the previously collected data, the multispectral and thermal image data describing a color, spectral reflectance, and temperature range for each of the elements
Data Source
AI summary
Various embodiments are directed to facilitating imagery and point-cloud based facility modeling and remote change detection. A computing device may receive collected data for a facility. The collected data may include spatial image data obtained from light detection imaging and ranging systems (LiDAR), multispectral data, and thermal data. The computing device may then analyze, based on software models generated for previously collected data for the facility, the collected data to determine changes in the previously collected data. The computing device may then update the models upon determining changes in the previously collected data. Finally, the computing device may generate an alert based on the updated models when any changes in the previously collected data are above a predetermined threshold corresponding to a current security or operational condition associated with the facility.