X-ray CT Inspection of Carbon Bicycle Parts for Internal Defect Detection
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Solution Overview
Problem
The challenge lies in detecting abnormal portions such as pores or cracks in carbon composite bicycle parts without disassembling them, as these defects can lead to stability issues and accidents, and current inspection methods are time-consuming and costly.
Innovation Solution
A non-destructive inspection apparatus that uses X-ray technology to generate gray scale images, measure changes in gray value, and detect abnormal areas by emitting X-rays with specific voltage and current settings, and employs neural networks to classify and determine the type of abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional inspection methods are used to detect abnormal portions in carbon composite parts, then detection accuracy may be maintained, but inspection time and cost increase significantly
Solution Approach 1:
The patent replaces manual disassembly and visual inspection with automated X-ray computed tomography (CT) scanning. The X-ray CT system automatically captures three-dimensional images of the carbon composite part's internal structure, eliminating the need for time-consuming disassembly while maintaining high detection accuracy for pores and cracks
Solution Approach 2:
The patent creates a digital three-dimensional copy (virtual model) of the part's internal structure through X-ray CT scanning. This digital replica allows for automated analysis and detection of abnormalities without physically manipulating or disassembling the actual part, significantly reducing inspection time while preserving detection precision
2Weight of moving object
If the carbon composite material is made thinner to reduce weight, then bicycle weight decreases, but the part becomes more susceptible to damage and cracks
Solution Approach 1:
The patent performs preliminary quality verification through X-ray CT scanning before the part is put into service. By detecting pores, cracks, and other defects in the internal structure before the part is installed on the bicycle, the system prevents potential failures, thereby maintaining reliability even as wall thickness decreases for weight reduction
Solution Approach 2:
The patent introduces an intermediary inspection process (X-ray CT scanning) between manufacturing and final assembly. This intermediary step identifies and flags defective parts before they reach the user, allowing thin-walled parts to be used confidently for weight reduction while reliability is maintained through pre-screening
3Measurement precision
If expert inspection is used to identify abnormal portions, then detection accuracy is maintained, but the process requires considerable time and specialized knowledge
Solution Approach 1:
The patent implements automated image processing algorithms that independently analyze the X-ray CT data to detect pores, cracks, and other abnormalities. The system performs self-diagnosis without requiring expert human intervention, maintaining high detection accuracy while eliminating the need for specialized knowledge and reducing inspection complexity
Solution Approach 2:
The patent replaces the human expert's analytical function with automated computer-based image processing. The system uses algorithms to automatically identify and classify defects in the three-dimensional images, substituting human expertise with computational analysis that maintains accuracy while simplifying the overall inspection process
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 accurate detection of abnormal areas without disassembling the bicycle, improving inspection efficiency and allowing for certification of second-hand bicycles, thereby ensuring user safety and establishing a healthy trading culture.
Implementation Method 1
obtain information on a transmission amount of an X-ray by emitting the X-ray to a part of a bicycle
Data Source
AI summary
A non-destructive inspection apparatus is provided. The non-destructive inspection apparatus includes at least one memory configured to store commands for performing predetermined operations, and at least one processor operatively coupled to the at least one memory and configured to execute the commands. The at least one processor is configured to obtain information on a transmission amount of an X-ray by emitting the X-ray to a part of a bicycle, generate a gray scale image based on the information on the transmission, measure an amount of change in a gray value from one end to the other end of the part of the bicycle represented in the gray scale image along an extending direction of the part, and detect an area in which the amount of change in the gray value is equal to or greater than a threshold, as an abnormal area.