Microtexture Region Detection in Alloys Using Acoustic Frequency Shifts
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Solution Overview
Problem
Traditional inspection methods for determining microstructural characteristics in metal alloys, such as titanium alloys, often require destructive testing and extensive surface preparation, which can damage the components and are inefficient.
Innovation Solution
A non-destructive inspection system and method for determining the acoustic and electromagnetic properties of titanium alloys, which can detect and analyze the acoustic and electromagnetic properties of titanium alloys, which can detect microstructural characteristics without damaging the components and require minimal surface preparation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inspection methods are used to determine microstructural characteristics, then measurement precision is improved, but the components are damaged and surface preparation is required
Solution Approach 1:
The patent replaces mechanical inspection methods (such as metallographic sampling and microscopy) with acoustic emission detection. Acoustic sensors detect sound waves generated by acoustic streaming in the liquid, which carries information about microstructural characteristics without physical contact or damage to the component surface.
Solution Approach 2:
The patent introduces liquid as an intermediary medium between the component and the sensor. The liquid transmits acoustic information from the component's microstructure to the sensor through acoustic streaming, enabling non-contact detection without requiring direct sensor contact or surface preparation.
2Measurement precision
If traditional inspection methods are used to determine microstructural characteristics, then measurement precision is improved, but inspection efficiency is reduced due to extensive surface preparation
Solution Approach 1:
The patent replaces time-consuming mechanical surface preparation and sampling procedures with rapid acoustic emission detection. The acoustic sensors can detect microstructural characteristics in real-time without requiring physical access to or manipulation of the component surface.
Solution Approach 2:
The component itself generates the detection signal through acoustic streaming in the liquid, eliminating the need for external mechanical processing. The microstructure naturally produces acoustic emissions that can be captured and analyzed directly.
3Object-affected harmful factors
If acoustic emission detection is used to detect microstructural characteristics, then component damage is avoided, but detection capability for microtexture regions is insufficient
Solution Approach 1:
The patent utilizes acoustic vibrations and sound waves generated by acoustic streaming to detect microstructural characteristics. The liquid undergoes acoustic streaming motion that interacts with the component's microstructure, generating detectable sound signals that reveal microtexture region information.
Solution Approach 2:
The patent transitions from surface-level inspection to volumetric detection by using liquid penetration and acoustic streaming throughout the material volume. This enables detection of microstructural characteristics in the bulk material rather than limited to surface regions.
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 effectively identifies microstructural characteristics like grain size, orientation, and texture regions in titanium and nickel alloys, enabling non-destructive evaluation of peened and machined surfaces, thereby improving component performance and reducing maintenance costs.
Implementation Method 1
the liquid undergoes acoustic streaming motion, which generates acoustic emissions
Data Source
AI summary
Provided herein are inspection systems and methods for detecting MTR present within a subsurface volume of a specimen. The approaches use acoustic transducers and, optionally, near-surface sensors to introduce inspecting energy into the specimen. Signal data representative of the inspecting energy is analyzed to detect MTRs. In some approaches, a shift in a frequency distribution of the signal data is determined. In other approaches, a distribution of values for a given characteristic of the signal data, such as amplitude or frequency, is computed and a quantified description of the distribution is computed. Response scores and/or intensity maps can be generated for the specimen based on the analysis of the signal data. MTR scores indicative of MTR in the specimen can be correlated to the response score and/or intensity map. The specimen can then be dispositioned based on the response scores and/or intensity map and their correlation with the MTR scores.