Planar LIDAR Sensor for Confined Asset Model Reconstruction
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Solution Overview
Problem
Existing asset model reconstruction systems lack small, remotely controlled, ruggedized sensors suitable for accessing hard-to-reach inspection environments within pressure vessels and storage tanks, which are often too large to pass through small openings and pose risks to human inspectors.
Innovation Solution
A system comprising a 2-dimensional planar LIDAR sensor coupled to a rotating actuator and a navigable device, such as a pole or mobile robot, that collects point cloud data and inertial data to generate a 3-dimensional surface model of the asset's interior, allowing for remote inspection and model generation without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional LIDAR sensors are used for asset model reconstruction, then measurement precision is improved, but device complexity increases and the sensors cannot access confined spaces
Solution Approach 1:
The system segments the LIDAR scanning function into multiple passes from different positions. Instead of using one complex large sensor, multiple smaller sensors or the same sensor moved to different locations perform sequential scanning, with each scan capturing a portion of the asset interior that is then integrated into a complete model.
Solution Approach 2:
A pole or rod acts as an intermediary carrier that holds the compact LIDAR sensor and allows it to be positioned in confined spaces. The pole extends through small openings and enables the sensor to reach areas that would be inaccessible to larger inspection equipment, while the sensor itself remains small enough to pass through restricted openings.
2Adaptability or versatility
If human inspectors manually create models, then adaptability is improved, but loss of time increases and safety risks arise
Solution Approach 1:
The system performs self-service by automatically capturing LIDAR data, processing the point clouds, and generating the 3D model without human intervention. The automated pipeline eliminates manual model creation steps while maintaining adaptability through software-based processing that can handle various asset types.
Solution Approach 2:
The manual mechanical process of model creation by human inspectors is replaced with an automated electronic system. LIDAR sensors electronically capture geometric data, and computer algorithms automatically process this data into 3D models, substituting human manual work with automated computational processes.
3Measurement precision
If multiple LIDAR scans from different positions are integrated, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs universal coordinate transformation algorithms that can integrate LIDAR scans from any position and orientation into a unified coordinate system. This multi-functional approach allows the same processing pipeline to handle scans from multiple perspectives, making the integration process systematic rather than complex.
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
The system enables rapid generation of high-quality 3-dimensional surface models of assets with confined spaces, reducing inspection time and eliminating the need for model creation expertise, while ensuring safety by avoiding human access to hazardous areas.
Implementation Method 1
LIDAR sensors utilize lasers to emit many beams of light within a space. The beams of light that are emitted into the space then collide with objects and/or surfaces within the space and are reflected. LIDAR sensors then measure the time that it takes for the reflected light to return to a receiver within the sensor.
Implementation Method 2
The beams of light that are emitted into the space then collide with objects and/or surfaces within the space and are reflected.
Data Source
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AI summary
In one aspect a system for asset model reconstruction is provided. The system includes a data collection assembly including a rotator, a LIDAR sensor coupled to the rotator and arranged to acquire LIDAR point cloud data of an asset, an inertial measurement unit (IMU) arranged to collect inertial data of the data collection assembly and a computing system communicatively coupled to the data collection assembly and including at least one data processor and a memory storing instructions which, when executed by the at least one processor, cause the at least one processor to perform operations including receiving rotational data from the rotator, receiving inertial data from the IMU, receiving LIDAR point cloud data from the LIDAR sensor and generating a surface model of the asset.