Nondestructive Evaluation (NDE): Auralization of Ultrasonic Signals for the Detection of Corrosion

1997 ◽  
Author(s):  
Amos E. Holt ◽  
Glenn M. Light
Keyword(s):  
Nondestructive Evaluation ◽  
High Spatial Resolution ◽  
Signal Amplitude ◽  
Visual Interpretation ◽  
Ultrasonic Signals ◽  
Thin Walls ◽  
Southwest Research Institute ◽  
Wing Structure ◽  
To Receive ◽  
Hidden Corrosion

During nondestructive evaluation (NDE), an instrument is used to receive inspection signals and display them for visual interpretation. Southwest Research Institute (SwRI) has developed technology that allows NDE signals generated from conventional ultrasonic instrumentation to be completely converted into audible (aural) signals to enhance reliability of evaluation through the use of two senses (ears and eyes) to improve inspection reliability. For example, detection of hidden corrosion on aircraft structures using conventional ultrasonic testing (UT) techniques is difficult because of thin walls and corrosion topography. These characteristics require use of high-frequency, high-spatial-resolution transducers to attempt to detect backwall signal amplitude. It is difficult to visually discriminate backwall signals of thin wing structure from the normal ringdown of the transducer. Using aural UT, a trained inspector can listen to sounds generated by aural UT equipment and detect the presence of hidden corrosion with higher reliability than using conventional UT.

Using Aural (Audible) Information Generated Directly From Conventional NDE Technology Signals to Aid the Inspector in Defect Detection and Discrimination

1996 ◽  
Vol 118 (1) ◽  
pp. 74-77
Author(s):  
A. E. Holt ◽  
G. M. Light ◽  
K. D. Polk ◽  
W. T. Clayton
Keyword(s):  
Nondestructive Evaluation ◽  
Defect Detection ◽  
Visual Interpretation ◽  
Ultrasonic Nde ◽  
To Receive

During nondestructive evaluation (NDE) of a material, an NDE instrument typically is used to receive the inspection signals and display them for visual interpretation. Work has been underway to convert these signals to a range of aural (audible) signals with the intent to enhance the accuracy of evaluation through the use of two senses (ears and eyes) instead of one. This paper describes auralization of ultrasonic NDE testing signals to improve characterization and evaluation of materials.

scholarly journals A Comparison of Methods for Determining Forest Composition from High-Spatial-Resolution Remotely Sensed Imagery

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1290
Author(s):  
Benjamin T. Fraser ◽  
Russell G. Congalton
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Remotely Sensed ◽  
Local Scale ◽  
Google Earth ◽  
Forest Composition ◽  
Visual Interpretation ◽  
Individual Tree ◽  
Remotely Sensed Imagery ◽  
Composition Classes

Remotely sensed imagery has been used to support forest ecology and management for decades. In modern times, the propagation of high-spatial-resolution image analysis techniques and automated workflows have further strengthened this synergy, leading to the inquiry into more complex, local-scale, ecosystem characteristics. To appropriately inform decisions in forestry ecology and management, the most reliable and efficient methods should be adopted. For this reason, our research compares visual interpretation to digital (automated) processing for forest plot composition and individual tree identification. During this investigation, we qualitatively and quantitatively evaluated the process of classifying species groups within complex, mixed-species forests in New England. This analysis included a comparison of three high-resolution remotely sensed imagery sources: Google Earth, National Agriculture Imagery Program (NAIP) imagery, and unmanned aerial system (UAS) imagery. We discovered that, although the level of detail afforded by the UAS imagery spatial resolution (3.02 cm average pixel size) improved the visual interpretation results (7.87–9.59%), the highest thematic accuracy was still only 54.44% for the generalized composition groups. Our qualitative analysis of the uncertainty for visually interpreting different composition classes revealed the persistence of mislabeled hardwood compositions (including an early successional class) and an inability to consistently differentiate between ‘pure’ and ‘mixed’ stands. The results of digitally classifying the same forest compositions produced a higher level of accuracy for both detecting individual trees (93.9%) and labeling them (59.62–70.48%) using machine learning algorithms including classification and regression trees, random forest, and support vector machines. These results indicate that digital, automated, classification produced an increase in overall accuracy of 16.04% over visual interpretation for generalized forest composition classes. Other studies, which incorporate multitemporal, multispectral, or data fusion approaches provide evidence for further widening this gap. Further refinement of the methods for individual tree detection, delineation, and classification should be developed for structurally and compositionally complex forests to supplement the critical deficiency in local-scale forest information around the world.

Application of Joint-Time Frequency Analysis Methods for Nondestructive Evaluation

1999 ◽  
Author(s):  
Ki-Woo Nam ◽  
Kun-Chan Lee ◽  
Jeong-Hwan Oh
Keyword(s):  
Crack Propagation ◽  
Nondestructive Evaluation ◽  
Frequency Analysis ◽  
Cyclic Fatigue ◽  
Frequency Characteristics ◽  
Time Frequency Analysis ◽  
Ultrasonic Signals ◽  
Time Frequency ◽  
Analysis Methods ◽  
Ae Signals

Abstract Application of signal processing techniques to nondestructive evaluation (NDE) in general and acoustic emission (AE) studies in particular has become a standard tool in determining the frequency characteristics of the signals and relating these characteristics to the integrity of the structure under consideration. Recent studies have shown that the frequency characteristics of ultrasonic signals from evolving damage during cyclic (fatigue) and dynamic loads change with time; in other words, the signals are nonstationary, and that these changes can be related to the nature of the damage taking place during loading. A joint time-frequency analysis such as Short Time Fourier Transform (STFT) and Wigner-Ville distribution (WVD), can in principle be used to determine the time dependent frequency characteristics of nonstationary signals in presence of background noise. In this study these techniques are applied to analyze AE signals from fatigue crack propagation in 5083 aluminum alloys and ultrasonic signals in degraded austenitic 316 stainless steels, to study the evolution of damage in these materials. It is demonstrated that the nonstationary characteristics of both AE and ultrasonic signals could be analyzed effectively by these methods. STFT was found to be more effective in analyzing AE signals, and WVD was more effective for analyzing the attenuation and frequency characteristics of degraded materials through ultrasonics. It is indicated that the time-frequency analysis methods should also be useful in evaluating crack propagation and final fracture process resulting from various damages and defects in structural members.

Dual-energy wave subtraction imaging for evaluation of barely visible impact damage with an ultrasonic propagation imaging system

2017 ◽  
Vol 29 (17) ◽  
pp. 3411-3425 ◽  
Author(s):  
Yunshil Choi ◽  
Jung-Ryul Lee
Keyword(s):  
Laser Beam ◽  
Nondestructive Evaluation ◽  
Composite Structures ◽  
Imaging System ◽  
Impact Damage ◽  
Dual Energy ◽  
Ultrasonic Waves ◽  
Excitation Energies ◽  
Ultrasonic Signals ◽  
Ultrasonic Propagation

Barely visible impact damage from low-velocity impacts have been studied as critical design factors of composite structures. In this article, a dual-energy wave subtraction algorithm using an ultrasonic propagation imaging system is proposed to evaluate barely visible impact damage as a strategy of fast in situ nondestructive evaluation or structural health monitoring (SHM). The ultrasonic propagation imaging system is a type of nondestructive evaluation or SHM system and is based on scanning laser-induced guided ultrasound and fixed sensors. The amplitude of ultrasonic signals generated by the ultrasonic propagation imaging system increases with the increasing energy of the laser beam. Two ultrasonic signals generated by different excitation energies of the laser beam can be equalized by multiplying a constant factor to one of them. Therefore, the residuals after subtraction of two signals may be close to zero. However, the two different energy induced signals in the damaged area will be nonzero due to the change in material conditions regarding the laser ultrasonic generation mechanism. The dual-energy wave subtraction algorithm eliminates most of the incident ultrasonic waves and amplifies anomalous waves. A composite wing skin including two barely visible impact damages as well as a composite sandwich panel, including a single barely visible impact damage, were inspected to validate the proposed algorithm.

scholarly journals Damage Assessment of a Salt Dome in Jizan, Southwestern Saudi Arabia, Using High Spatial Resolution Remote Sensing Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Habes Ghrefat ◽  
Ahmed Hakami ◽  
Elkhedr Ibrahim ◽  
Saad Mogren ◽  
Saleh Qaysi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Saudi Arabia ◽  
Spatial Resolution ◽  
Damage Assessment ◽  
High Spatial Resolution ◽  
Remote Sensing Data ◽  
Salt Dome ◽  
Visual Interpretation ◽  
Sensing Data ◽  
Residential Neighborhood

The salt dome in Jizan, southwestern Saudi Arabia, has caused several problems related to underground dissolution, particularly in the old part of the city. Examples of these problems include surface collapse, building failure, fracturing, tilting, and road cracking. Analysis of the salt dome using X-ray diffraction (XRD) revealed the dominance of gypsum, anhydrite, and halite. This study evaluates the damage assessment using multitemporal high spatial resolution data of the GeoEye-1, and QuickBird-2 sensors. Change detection technique, textural analysis, and visual interpretation were applied to these data. Analysis of the data recorded before and after a particular damage event revealed that three neighborhoods located above the Jizan salt dome—Al-Ashaima, Shamiya, and Aljabal—were affected to the greatest extent. The entire residential neighborhood of Al-Ashaima was evacuated, and the buildings located in it were demolished. Several buildings in the Shamiya and Aljabal neighborhoods were also demolished. Therefore, high spatial remote sensing data are effective in assessing building damage and for anticipating future damage, thus benefiting decision making for the affected cities.

Nondestructive Evaluation in Materials Using Time-Frequency Analysis Methods

2005 ◽  
Vol 297-300 ◽  
pp. 2090-2095 ◽  
Author(s):  
Ki Woo Nam ◽  
Seok Hwan Ahn ◽  
Jin Wook Kim
Keyword(s):  
Nondestructive Evaluation ◽  
Frequency Analysis ◽  
Frequency Characteristics ◽  
Structural Members ◽  
Time Frequency Analysis ◽  
Ultrasonic Signals ◽  
Time Frequency ◽  
Analysis Methods ◽  
Standard Tool ◽  
Processing Techniques

Application of signal processing techniques to nondestructive evaluation (NDE) in general has become a standard tool in determining the frequency characteristics of the signals and relating these characteristics to the integrity of the structure under consideration. The joint time-frequency analysis techniques are applied to analyze ultrasonic signals in degraded austenite stainless 316 steel, to study the evaluation of damage in this material. It is demonstrated that the nonstationary characteristics of ultrasonic signals could be analyzed effectively by these methods. WVD was found to be more effective for analyzing the attenuation and frequency characteristics of degraded materials through ultrasonic. It is indicated that the time-frequency analysis methods should also be useful in evaluating various damages and defects in structural members.

Cardiac Vector Estimation in Fetal Magnetocardiography Using Realistic Approximations of the Volume Conductor

2012 ◽  
Author(s):  
Rong Tao ◽  
Elena-Anda Popescu ◽  
William B. Drake ◽  
David Jackson ◽  
Mihai Popescu
Keyword(s):  
Magnetic Field ◽  
Fetal Heart ◽  
Signal Amplitude ◽  
Signal Quality ◽  
Fetal Magnetocardiography ◽  
Vector Estimation ◽  
Fetal Electrocardiography ◽  
Cardiac Vector ◽  
To Receive ◽  
The Magnetic Field

Fetal magnetocardiography (fMCG) records the magnetic field generated by the electrical activity associated with the fetal cardiac muscle contraction and has emerged as an attractive tool for monitoring the fetal heart in-utero. The magnetic sensor array is placed above the maternal abdomen to receive the extremely weak magnetic signal of the fetal heart from 20 weeks of gestation onward. fMCG outperforms fetal electrocardiography (fECG) in its notably superior signal quality, as the magnetic field is considerably less affected by tissues with low electrical conductivity surrounding the fetal heart [1], which can drastically diminish the fECG signal amplitude.

scholarly journals Design of Partial Discharge Test Environment for Oil-Filled Submarine Cable Terminals and Ultrasonic Monitoring

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4774
Author(s):  
Yulong Wang ◽  
Xiaohong Zhang ◽  
Lili Li ◽  
Jinyang Du ◽  
Junguo Gao
Keyword(s):  
Partial Discharge ◽  
Maximum Amplitude ◽  
Signal Amplitude ◽  
Ultrasonic Signal ◽  
Signal Spectrum ◽  
Test Environment ◽  
Ultrasonic Signals ◽  
Amplitude Coefficient ◽  
Marine Cable ◽  
Submarine Cables

Based on the principle of operating an oil-filled-cable operation and the explanation of the oil-filling process provided in the cable operation and maintenance manual of submarine cables, this study investigated oil-pressure variation caused by gas generated as a result of cable faults. First, a set of oil-filled cables and their terminal oil-filled simulation system were designed in the laboratory, and a typical oil-filled-cable fault model was established according to the common faults of oil-filled cables observed in practice. Thereafter, ultrasonic signals of partial discharge (PD) under different fault models were obtained via validation experiments, which were performed by using oil-filled-cable simulation equipment. Subsequently, the ultrasonic signal mechanism was analyzed; these signals were generated via electric, thermal, and acoustic expansion and contraction, along with electric, mechanical, and acoustic electrostriction. Finally, upon processing the 400 experimental data groups, four practical parameters—maximum amplitude of the ultrasonic signal spectrum, Dmax, maximum frequency of the ultrasonic signals, fmax, average ultrasonic signal energy, Dav, and the ultrasonic signal amplitude coefficient, M—were designed to characterize the ultrasonic signals. These parameters can be used for subsequent pattern recognition. Thus, in this study, the terminal PD of an oil-filled marine cable was monitored.

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