Augmented Reality Buried Asset Detection System
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Solution Overview
Problem
Conventional electromagnetic locate devices (ELDs) for buried asset detection are time-consuming, require extensive training, and are limited by the geometry and distance between antennas, leading to inaccurate identification and marking of buried assets, especially in complex environments with signal interference and depth limitations.
Innovation Solution
A system combining an electromagnetic locate device with an augmented reality system, using a single electromagnetic sensor set and inertial sensors to create a virtual array of sensors, which calculates and visualizes the electromagnetic field, providing a 3D model and graphic representation of buried assets on a display, overlaying the asset's position and type onto real-world video.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional electromagnetic locate devices are used with multiple antennas arranged at various geometries, then the ability to detect buried assets is improved, but the device complexity and difficulty of operation increase due to the need for proper geometric alignment and interpretation of multiple antenna signals
Solution Approach 1:
The patent combines multiple antenna signals and their geometric relationships into a single integrated processing system that automatically calculates asset position. Instead of requiring separate interpretation of multiple antenna readings, the system merges all antenna data streams and processes them together to directly determine buried asset location, eliminating the complexity of manual geometric alignment and interpretation.
Solution Approach 2:
The patent replaces the mechanical/physical alignment process with computational methods. Instead of requiring technicians to manually align antennas with specific geometries to the target, the system uses signal processing and mathematical calculations to automatically determine the correct geometric relationships and compute asset position, substituting physical alignment procedures with computational analysis.
2Measurement precision
If field technicians perform manual interpretation of ELD data to deduce buried conductor location, then the detection capability is maintained, but the time required and training needed increase significantly
Solution Approach 1:
The patent implements a self-service system where the ELD automatically performs the interpretation and deduction functions that previously required trained technicians. The device processes its own raw electromagnetic signals, automatically calculates vector field values, determines asset positions, and generates location information without human intervention, making the system self-sufficient and eliminating the need for extensive operator training.
Solution Approach 2:
The patent substitutes manual interpretation processes with automated computational algorithms. Instead of technicians manually analyzing ELD readings and deducing conductor locations, the system uses computer-based signal processing and mathematical models to automatically interpret the electromagnetic data and determine asset positions, replacing human cognitive processes with computational methods.
3Reliability
If conventional ELDs are used in complex environments with multiple buried assets, then the basic detection function is maintained, but signal interference and field distortion cause incorrect identification and marking
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors electromagnetic signals from multiple antennas, compares the observed field patterns with expected patterns, and adjusts its calculations to account for interference and distortion. The system uses feedback from the actual measured signals to refine its asset location calculations and compensate for environmental disturbances, improving reliability in complex environments.
Solution Approach 2:
The patent introduces computational algorithms and signal processing techniques as intermediaries between the raw electromagnetic signals and the final asset location determination. These intermediary processing steps filter out interference, correct for field distortion, and isolate the signals from individual assets, acting as a buffer that protects the final interpretation from the harmful effects of signal interference and environmental distortion.
4Measurement precision
If the distance between antennas in the ELD is limited by the device design, then the device portability is maintained, but the depth at which buried assets can be detected is limited
Solution Approach 1:
The patent transitions from relying solely on physical antenna separation distance to using computational dimensions for signal analysis. By processing signals from multiple antennas in the time and frequency domains and using mathematical calculations to extend the effective sensing volume, the system achieves deeper detection capability without physically increasing the antenna separation distance, effectively adding computational dimensions to overcome the physical size constraint.
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 approach enhances the accuracy, efficiency, and safety of buried asset detection by providing a precise and automated method for interpreting electromagnetic fields, reducing human error and increasing the depth at which assets can be detected.
Implementation Method 1
The ELD typically contains multiple ferrite or air cored antennae, arranged at various geometries to the target pipe or cable, that detect the low-level signals radiating from the target conductor
Data Source
AI summary
A system for calculating and visualizing a position of buried assets during a buried asset locate procedure in a target area includes an electromagnetic locate device (ELD) including electromagnetic antennas configured for sensing an electromagnetic (EM) field emanating from a buried asset at a target area, and an augmented reality system comprising a camera, a display, inertial sensors for measuring motion and distance moved, and processors configured for reading camera and sensor data, calculating motion and distance moved, generating a 3D model representing the target area, generating a 3D vector field representing the EM field emanating from the buried asset, calculating a position and type of the buried asset based on the 3D vector field and the 3D model, creating an object in the 3D model that represents the buried asset, and rendering video of the target area and the position and type of the buried asset.