Ultrasonic Modeling for Composite Irregularity Inspection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current nondestructive evaluation methods for composite structures, such as pulse-echo ultrasound and X-ray radiography, are inadequate in fully characterizing the severity and depth of irregularities like wrinkles in composite materials, being time-consuming and limited in their ability to detect defects accurately.
Innovation Solution
A computer-implemented method using a simulated inspection to generate a waveform data set associated with irregularity parameters, identifying a desired evaluation setting based on image quality thresholds, and employing a finite element analysis to iteratively refine the evaluation settings for precise characterization of composite structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pulse-echo ultrasound or X-ray radiography is used to inspect composite structures, then detection of irregularities is achieved, but the severity and depth characterization of irregularities is insufficient and the inspection process is time-consuming
Solution Approach 1:
The patent applies preliminary action by pre-generating a database of simulated ultrasonic signals corresponding to various known irregularities (wrinkles, delaminations, voids) with different severity levels and depths. This pre-computed reference database eliminates the need for time-consuming real-time analysis during actual inspection, allowing direct comparison and immediate characterization of detected irregularities.
Solution Approach 2:
The patent creates virtual copies of actual irregularities through finite element analysis simulations. These simulated ultrasonic signals serve as reference templates that replicate the acoustic response of various defect types, enabling accurate comparison and characterization without requiring physical test specimens or repeated measurements.
2Loss of information
If traditional ultrasonic inspection methods are used, then irregularities are detected, but the ability to fully characterize severity and depth is limited
Solution Approach 1:
The patent introduces a simulated signal database as an intermediary between the ultrasonic inspection system and the irregularity characterization process. This reference database acts as a mediator that translates raw ultrasonic signals into detailed irregularity parameters (severity, depth, type) by comparing measured signals against the pre-computed simulated signals, thereby completing the information without adding physical complexity to the inspection hardware.
Solution Approach 2:
The patent adds an informational dimension by incorporating multiple simulation parameters (irregularity type, severity level, depth, orientation) into the reference database. This multi-dimensional approach allows comprehensive characterization of irregularities by matching measured signals against simulations across multiple parameters simultaneously, extracting complete information from single measurements.
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
This approach allows for accurate and efficient characterization of irregularities in composite structures, enabling effective inspection and identification of defects within composite materials, improving the precision and speed of nondestructive evaluation processes.
Implementation Method 1
The system utilizes an ultrasound measurement system
Implementation Method 2
The expected result is generated from a model such as a wave propagation model
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
A first simulated inspection is conducted to provide a first waveform data set associated with the at least one irregularity (270, 450) parameter. The first simulated inspection is conducted using a first evaluation setting. A first image (572) is produced based on the first waveform set, and it is determined whether a quality of the first image (572) satisfies a predetermined threshold.