Automated Wear Measurement Using 3D Point Cloud Alignment
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Solution Overview
Problem
Conventional wear measurement systems for machine components are time-consuming and inaccurate, requiring manual selection of scale features and reference points, which are challenging due to lighting and dirt issues, and result in incorrect predictions for component life, leading to premature or delayed replacement.
Innovation Solution
A device with processors that receive images, generate three-dimensional point clouds, align them with a model point cloud, and project mask regions to automatically determine reference points and calculate wear, reducing manual intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement techniques are used to detect wear on machine components, then the measurement process can be performed with simple equipment, but the measurement is time-consuming and inaccurate
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated image processing system that captures images of machine components and uses computer vision algorithms to automatically detect and measure wear, eliminating the need for physical contact measurements and significantly reducing inspection time while improving accuracy
Solution Approach 2:
The system enables the machine component inspection process to be self-performing by automatically capturing images, processing them through algorithms, and generating wear assessment reports without requiring operator intervention for measurement tasks, allowing the system to inspect itself or other components autonomously
2Measurement precision
If automated image processing is implemented to select scale features and reference points, then measurement accuracy improves, but the system complexity increases due to challenges with lighting and dirt detection
Solution Approach 1:
The patent introduces an intermediary image processing layer that captures images under controlled lighting conditions and uses algorithmic mediation to identify scale features and reference points, bridging the gap between simple imaging and accurate measurement by processing intermediate image data to extract meaningful geometric information
Solution Approach 2:
The system changes imaging parameters such as lighting conditions, image resolution, and processing thresholds to optimize the detection of scale features and reference points, adjusting these parameters dynamically to compensate for environmental factors like dirt and varying light levels
3Adaptability or versatility
If manual selection of scale features is required, then the system can handle various lighting and dirt conditions, but the measurement process becomes time-consuming and operator-dependent
Solution Approach 1:
The patent replaces manual operator selection of scale features with automated image processing algorithms that can rapidly analyze images and identify appropriate features, eliminating the bottleneck of manual inspection while maintaining adaptability to different environmental conditions through algorithmic robustness
Data Source
AI summary
A device for measuring wear is disclosed. The device may receive images associated with a component, and may receive a three-dimensional (3D) model of the component. The device may generate an image point cloud based on the images, and may generate a model point cloud based on the 3D model of the component. The device may perform a first alignment of the image point cloud and the model point cloud to generate first-aligned point clouds, and may perform a second alignment of the first-aligned point clouds to generate second-aligned point clouds. The device may generate 3D mask regions based on the second-aligned point clouds, and may project the 3D mask regions on the images. The device may process the 3D mask regions, projected on the images, to determine reference points in the images, and may determine an amount of wear associated with the component based on the reference points.