Composite Resin Shear Strength Prediction Using IR and Ultrasound
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Solution Overview
Problem
Existing methods for measuring interfacial shear strength of composite resin materials containing fibrous materials are time-consuming and inefficient, particularly when predicting the mechanical properties of large numbers of samples.
Innovation Solution
A prediction device and system that acquires and analyzes first and second measurement information using different measurement devices, such as infrared spectrometers and ultrasonic or terahertz wave spectrometers, to predict interfacial shear strength through machine learning with a trained discriminator, allowing non-destructive assessment of composite resin materials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If destructive testing methods are used to measure interfacial shear strength, then measurement accuracy is improved, but sample destruction occurs and time consumption increases
Solution Approach 1:
The patent replaces destructive mechanical testing with non-destructive measurement devices that use electromagnetic waves (infrared spectrometer, terahertz wave spectrometer) or ultrasonic waves to measure material properties. This substitution enables prediction of interfacial shear strength without physical destruction of samples, significantly reducing measurement time while maintaining accuracy through multiple measurement parameters
Solution Approach 2:
The patent introduces measurement devices as intermediaries that indirectly assess interfacial shear strength by measuring material properties (such as absorption coefficients, ultrasonic wave characteristics) rather than directly applying destructive mechanical loads. The prediction device acts as another intermediary that processes these measurements to predict the target property, enabling non-destructive evaluation
2Measurement precision
If multiple measurement parameters are used to predict interfacial shear strength, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent employs measurement devices with multi-functionality that can measure multiple material properties (absorption coefficient, ultrasonic wave characteristics, etc.) simultaneously or sequentially. This allows the system to acquire multiple measurement parameters needed for accurate prediction without requiring separate specialized devices for each parameter, thereby managing device complexity while improving prediction accuracy
Solution Approach 2:
The patent uses multiple types of measurement devices (infrared spectrometer, terahertz wave spectrometer, ultrasonic measurement device) that each create different types of measurement data 'copies' of the material properties. By combining these complementary copies, the system achieves comprehensive characterization and accurate prediction of interfacial shear strength without over-relying on a single complex measurement system
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 and efficient prediction of interfacial shear strength without the need for destructive testing, improving prediction accuracy and reducing the time required for assessing multiple samples.
Implementation Method 1
the first measurement device is an infrared spectrometer
Implementation Method 2
the second measurement device is an ultrasonic measurement device
Implementation Method 3
the second measurement device is a terahertz wave spectrometer
Data Source
AI summary
A prediction device includes an acquirer that acquires first measurement information and second measurement information obtained by measuring a material property of a composite resin material containing a fibrous material, and a predictor that predicts interfacial shear strength of the composite resin material based on the acquired first measurement information and the acquired second measurement information.