Ultrasonic Inspection of Fiber-Reinforced Molded Article Strength
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Solution Overview
Problem
There is a need for low-cost and high-precision inspection methods to evaluate the mechanical properties of fiber-reinforced molded article regions without direct measurement, as existing visual inspection methods lack objective evaluation standards and are prone to misclassification.
Innovation Solution
A machine learning-based approach using a mechanical property inference model generated through supervised or unsupervised deep learning, which infers mechanical properties from nondestructive inspection information such as ultrasonic images, allowing for accurate classification of molded article regions as defective or non-defective.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If visual inspection is used to evaluate molded article regions, then inspection cost is reduced, but measurement precision and evaluation objectivity deteriorate
Solution Approach 1:
The patent replaces human visual inspection with an automated inspection device that uses ultrasonic waves to detect internal defects. The device objectively measures mechanical properties by analyzing ultrasonic wave propagation characteristics, eliminating the subjectivity and inconsistency of visual inspection while maintaining cost-effectiveness through automation.
Solution Approach 2:
The patent introduces ultrasonic waves as an intermediary medium to indirectly assess mechanical properties. Instead of directly measuring mechanical properties or relying on visual appearance, the system uses ultrasonic wave propagation characteristics as a mediator to infer internal structural quality and mechanical property states, providing objective evaluation data.
2Reliability
If nondestructive inspection is performed to detect internal defects, then product quality is improved, but device complexity increases
Solution Approach 1:
The patent designs the inspection device to perform multiple functions: detecting internal defects, evaluating mechanical properties, and classifying product quality levels. By integrating these functions into a single system that uses ultrasonic wave propagation characteristics, the device achieves comprehensive quality assessment without requiring multiple separate complex systems.
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 instant and accurate inference of mechanical properties, reducing waste and production costs while maintaining high quality by avoiding misclassification in visual inspection.
Implementation Method 1
ultrasonic waves are emitted from the ultrasonic wave transmitter, pass through the object to be inspected, and then received by the opposite receiver, and a propagation time of the ultrasonic waves is measured
Data Source
AI summary
An inspection device includes a storage unit for storing a mechanical property inference model generated by machine learning based on mechanical property information and nondestructive inspection information of a fiber-reinforced first molded article region for which the mechanical property information and the nondestructive inspection information are known, the mechanical property inference model being configured to be input nondestructive inspection information of a second molded article region which is reinforced with reinforcing fibers for predicting unknown mechanical property information of the second molded article region. The inspection device acquires the nondestructive inspection information of the second molded article region; inputs the nondestructive inspection information to the mechanical property inference model; acquire the mechanical property information of the second molded article region predicted by the mechanical property inference model; and outputs the mechanical property information of the second molded article region.