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At least 37 records · Page 2

Evolutionary Design of a Robotic Material Defect Detection System

During the post-flight inspection of SSME engines, several inaccessible regions must be disassembled to inspect for defects such as cracks, scratches, gouges, etc. An improvement to the inspection process would be the design and development of very small robots capable of penetrating these inaccessible regions and detecting the defects. The goal of this research was to utilize an evolutionary design approach for the robotic detection of these types of defects. A simulation and visualization tool was developed prior to receiving the hardware as a development test bed. A small, commercial off-the-shelf (COTS) robot was selected from several candidates as the proof of concept robot. The basic approach to detect the defects was to utilize Cadmium Sulfide (CdS) sensors to detect changes in contrast of an illuminated surface. A neural network, optimally designed utilizing a genetic algorithm, was employed to detect the presence of the defects (cracks). By utilization of the COTS robot and US sensors, the research successfully demonstrated that an evolutionarily designed neural network can detect the presence of surface defects.

Ballard, Gary

Lamb wave defect detection and evaluation using a fully non-contact laser system

Traditional Lamb wave structural health monitoring (SHM)/nondestructive evaluation (NDE) system employs contact type transducers such as PZT, ultrasonic transducers, and optical fibers. In application, transducer attachment and maintenance can be time and labor consuming. In addition, the use of couplant and adhesives can introduce additional materials on structures, and the interface coupling is often not well understood. To overcome these limitations, we proposed a fully non-contact NDE system by employing pulsed laser (PL) for Lamb wave actuation and scanning laser Doppler vibrometer (SLDV) for Lamb wave sensing. The proposed system is implemented on aluminum plates. The PL Lamb wave excitation is calibrated, and the optimal parameters are obtained. Lamb wave modes are then characterized through 1D wavefield analysis. With the calibrated and characterized system, defect detection and evaluation are achieved on aluminum plates with simulated defects (surfaced-bonded quartz rod, and machine milled crack) through 1D and 2D inspection in both time-space and frequency-wavenumber domains.

Ma, Zhaoyun

Product Defect Detection System: SYSM- 5620 Final Project

Retail sales is a growing market estimated to up to seven percent year over year. With this growing market there is also a trend in growing rate of retail returns, estimated just last year at $\$$850 billion. Retail stores must ensure that products available for purchase remain safe, undamaged, and acceptable to customers throughout their time in the store. This job exists regardless of the specific solution used because stores are always responsible for preventing damaged or defective products from reaching customers and when they fail to this is categorized under operation inefficiencies which accounts for an estimated $\$$12 billion in returns. When defective items remain on the sales floor, stores may experience increased returns, reduced customer satisfaction, loss of customer trust, and potential safety concerns depending on the product type. As a result, the core job to be done is to identify defective products quickly, remove them from the sales floor before they are purchased, and preserve useful information about the defect so that the store can improve its handling, stocking, and supplier coordination over time. The need for a more reliable process is especially important in high volume retail environments where employees manage large numbers of products across many aisles, shelves, and storage areas. In these settings, manual inspection alone can be inconsistent and difficult to sustain at the individual item level. At the same time, broader retail trends continue to emphasize operational efficiency, product visibility, and improved customer experience, creating an opportunity for more automated and data driven defect detection methods.

42 ENGINEERING

Method and System for Multi-Path Active Defect Detection, Localization and Characterization with Ultrasonic Guided Waves

A method and system of detecting, localizing, and characterizing a defect at one or more spatial points of interest on a structure. The method may include collecting first data in a first state using one or more transducers on the structure, collecting second data in a second state subsequent to the first state, computing a scattered impulse response based on the collected first data and the collected second data, comparing the scattered impulse response with an estimated scattered impulse response corresponding to the case when damage is present at one or more spatial points of interest on the structure, and combining the generated comparison results to detect, localize, and characterize a defect at the one or more spatial points of interest on the structure.

Hall, James Stroman

Thermographic imaging for high-temperature composite materials: A defect detection study

The ability of a thermographic imaging technique for detecting flat-bottom hole defects of various diameters and depths was evaluated in four composite systems (two types of ceramic matrix composites, one metal matrix composite, and one polymer matrix composite) of interest as high-temperature structural materials. The holes ranged from 1 to 13 mm in diameter and 0.1 to 2.5 mm in depth in samples approximately 2-3 mm thick. The thermographic imaging system utilized a scanning mirror optical system and infrared (IR) focusing lens in conjunction with a mercury cadmium telluride infrared detector element to obtain high resolution infrared images. High intensity flash lamps located on the same side as the infrared camera were used to heat the samples. After heating, up to 30 images were sequentially acquired at 70-150 msec intervals. Limits of detectability based on depth and diameter of the flat-bottom holes were defined for each composite material. Ultrasonic and radiographic images of the samples were obtained and compared with the thermographic images.

Roth, Don J.

Various Types of Defects Detection in Flat and Curved Laminated Composite Plates using Nonintrusive Lamb Wave System

Composite materials are widely used in aerospace industries due to their light weight, strength, and various other desired properties. However, they are susceptible to various defects occurring during the manufacturing process or in service. Typical defects include porosity, wrinkles, and delamination. Nondestructive means of detection of the defects at any stage are of great importance to ensure quality and safety of composite structures. A nonintrusive removeable Lamb wave system and accompanied methodology that is not material-dependent is presented in this paper to detect various types of typical defects in laminated composite plates, flat or curved. Through multidimensional data acquisition and processing, abnormality in waves caused by defects is captured and presented in inspection images. The methodologies are demonstrated in 2 cases: flat plate with wrinkles, and curved plate with delamination. Overall the results show that Lamb waves using the piezoelectric transducer and laser vibrometer system can be used for various types of defects inspection in flat or curved composite plates.

composite structures

Detecting Defective Solder Bonds

Method is noncontact and nondestructive. Technique detects solder bonds in solar array of other large circuit board, using thermal-imaging camera. Board placed between heat lamp and camera. Poor joints indiated by "cold" spots on the infrared image.

Paulson, R.

Defect Detection and Prevention

As NASA continues to impement its Faster, Better, Cheaper philosophy, new approaches for implementing Mission Assurance activities are being developed.

faster

Application of Hilbert-Huang Transform for Improved Defect Detection in Terahertz NDE of Shuttle Tiles

Terahertz NDE is being examined as a method to inspect the adhesive bond-line of Space Shuttle tiles for defects. Terahertz signals are generated and detected, using optical excitation of biased semiconductors with femtosecond laser pulses. Shuttle tile samples were manufactured with defects that included repair regions unbond regions, and other conditions that occur in Shuttle structures. These samples were inspected with a commercial terahertz NDE system that scanned a tile and generated a data set of RF signals. The signals were post processed to generate C-scan type images that are typically seen in ultrasonic NDE. To improve defect visualization the Hilbert-Huang Transform, a transform that decomposes a signal into oscillating components called intrinsic mode functions, was applied to test signals identified as being in and out of the defect regions and then on a complete data set. As expected with this transform, the results showed that the decomposed low-order modes correspond to signal noise while the high-order modes correspond to low frequency oscillations in the signal and mid-order modes correspond to local signal oscillations. The local oscillations compare well with various reflection interfaces and the defect locations in the original signal.

Anastasi, Robert F.

In Situ Thermal Inspection of Automated Fiber Placement Operations for Tow and Ply Defect Detection

The advent of Automated Fiber Placement (AFP) systems have aided the rapid manufacturing of composite aerospace structures. One of the challenges that AFP systems pose is the uniformity of the deposited prepreg tape layers, which complicates detection of laps, gaps, overlaps and twists. The current detection method used in industry involves halting fabrication and performing a time consuming, visual inspection of each tape layer. Typical AFP systems use a quartz lamp to heat the base layer to make the surface tacky as it deposits another tape layer. The innovation proposed in this paper is to use the preheated base layer as a through-transmission heat source for inspecting the newly added tape layer in situ using a thermographic camera mounted on to the AFP hardware. Such a system would not only increase manufacturing throughput by reducing inspection times, but it would also aid in process development for new structural designs or material systems by providing data on as-built parts. To this end, a small thermal camera was mounted onto an AFP robotic research platform at NASA, and thermal data was collected during typical and experimental layup operations. The data was post processed to reveal defects such as tow overlap/gap, wrinkling, and peel-up. Defects that would have been impossible to detect visually were also discovered in the data, such as poor/loss of adhesion between plies and the effects of vacuum debulking. This paper will cover the results of our experiments, and the plans for future versions of this inspection system.

Juarez, Peter D.

Effective Defect Detection Using Instance Segmentation for NDI

Ultrasonic testing is a common Non-Destructive Inspection (NDI) method used in aerospace manufacturing. However, the complexity and size of the ultrasonic scans make it challenging to identify defects through visual inspection or machine learning models. Using computer vision techniques to identify defects from ultrasonic scans is an evolving research area. In this study, we used instance segmentation to identify the presence of defects in the ultrasonic scan images of composite panels that are representative of real components manufactured in aerospace. We used two models based on Mask- RCNN (Detectron 2) and YOLO 11 respectively. Additionally, we implemented a simple statistical pre-processing technique that reduces the burden of requiring custom-tailored pre-processing techniques. Our study demonstrates the feasibility and effectiveness of using instance segmentation in the NDI pipeline by significantly reducing data pre-processing time, inspection time, and overall costs.

computer vision techniques

Autogeneous Friction Stir Weld Lack-of-Penetration Defect Detection and Sizing Using Directional Conductivity Measurements with MWM Eddy Current Sensor

Al 2195-T8 plate specimens containing Friction Stir Welds (FSW), provided by Lockheed Martin, were inspected using directional conductivity measurements with the MWM sensor. Sensitivity to lack-of-penetration (LOP) defect size has been demonstrated. The feature used to determine defect size was the normalized longitudinal component of the MWM conductivity measurements. This directional conductivity component was insensitive to the presence of a discrete crack. This permitted correlation of MWM conductivity measurements with the LOP defect size as changes in conductivity were apparently associated with metallurgical features within the first 0.020 in. of the LOP defect zone. Transverse directional conductivity measurements also provided an indication of the presence of discrete cracks. Continued efforts are focussed on inspection of a larger set of welded panels and further refinement of LOP characterization tools.

Goldfine, Neil

Pulse Phase Thermography for Defect Detection and Visualization

Pulse Phase Thermography (PPT) has been reported as a novel powerful technique of the thermal NDE. It employs application of the Discrete Fourier Transform (DFT) to thermal images obtained following flash heating of the front surface of a specimen. The computed phasegrams are excellent for defect visualization in a wide range of materials. This is in part due to their low sensitivity to uneven heating. This work is an attempt to analyze advantages and limitations of PPT. Results of application of the DFT to simulated temperature decays are presented. The temperature evolution on a surface has been simulated based on an analytical solution of the one-dimensional heat diffusion problem. A more sophisticated study has been done for different sizes of defects using numerical solution of the three-dimensional mathematical model. Capabilities of PPT for in-depth scanning and for monitoring of the material loss are discussed. The recommendations for the practical application of the PPT are presented. Experimental results obtained following these recommendations are reported.

Marinetti, Sergio

Defect Detection Model Development for Large Scale Thermoplastic Printing

Large-format additive manufacturing (LFAM) offers several advantages, including high throughput, cost-effective pellet-fed extrusion, and the capability to produce large-scale structures. The main pain points of LFAM include start and stops during the printing process, warpage, long layer times that lead to bead freezing, and bead separation due to shrinkage. These issues can lead to overfill, underfill and buildup of material in different sections of a print. This can lead to hidden defects embedded within the printed layers, or even ultimate failure of the printed structure. This ensures these defects can only be identified through nondestructive testing (NDT) inspection methods after printing, which can be timely and costly. Aligned Vision work specializes in 2D projectors with visual inspection systems and machine learning. Traditionally system is used for composite layup and layup inspections. In this work we used the LFAM system at Oak Ridge National Laboratory to create defect rich samples. The Aligned Vision inspection system then performed in-situ monitoring of the print process after each part was printed. This in-situ vision inspection system was used to develop a layer-by-layer inspection model that looks for overfill, underfill, and the buildup of defects using only a camera-based vision system. This leads to the assurance of high-quality production components.

36 MATERIALS SCIENCE