Evaluation of Mechanical Fatigue Damage Accumulation in Metal Matrix Composites Using Ultrasonic Surface Waves

This study demonstrates that an in situ nondestructive, ultrasonic surface wave technique can successfully detect the onset and extent of matrix cracking fatigue damage in a titanium metal matrix composite (MMC). A quasi-isotropic [0/±45/90]s SCS-6/Timetal®21S MMC material was used for room temperature fatigue tests and the resultant matrix cracking damage was ultrasonically monitored in situ as a function of cycle count. Damage accumulation in the material was successfully correlated with decreases in ultrasonic pitch catch amplitude and verified through the use of immersion ultrasonic C-scans and metallographic techniques. Damage initiation and progression was tracked through the use of complementary nondestructive and destructive techniques. The in situ surface wave data show that the higher the fatigue stress level, the more quickly damage occurs; conversely, the lower the stress level, the slower the damage initiation. The in situ surface wave technique proved to be more sensitive to the accumulating damage than standard load-displacement modulus measurements. The surface wave technique also indicated a change in material properties after only one fatigue cycle. The data acquired show that a better understanding of damage initiation and accumulation can be gained using the in situ surface wave technique in comparison to current load-displacement modulus measurements

Urban and rural differences in needs, service use and satisfaction among caregivers of autistic children in Morocco

Education and Child Studie

Socio-demographic disparities in receipt of clinical health care services during the COVID-19 pandemic for Canadian children with disability

Background: Little is known about the experience of receiving in-person and virtual clinical health care services during the COVID-19 pandemic for Canadian children with developmental disabilities and delays facing multiple layers of vulnerability (e.g., low income, low educational attainment families). We examined the relationship between socio-demographic factors and the receipt of these services (physical and mental health services) during COVID-19 for Canadian children with these conditions. Methods: Data collected in Canada for the Global Report on Developmental Delays, Disorders and Disabilities were used. The survey: (1) was developed and disseminated in collaboration with caregivers of children with disabilities, (2) included topics such as response to the pandemic and receipt of services and supports, and (3) documented the experiences of a non-random convenience sample of caregivers of children (any age) with these conditions during and prior to the pandemic. We used four logistic regression models to assess the association between socio-demographic factors and receipt of services. Results: Being a single parent, having low educational attainment (high school or less), having low income (making less than $40,000 per year), working less than full time (working part-time, working reduced hours due to COVID, retired, stay home parent or student), as well as male gender and older age of the child with disability were factors associated with decreased likelihood of receiving services. Conclusion: Our findings point to the need for tailoring services for families of children with disabilities, particularly low socioeconomic status families, to ensure continuity of care during public health emergencies

Wavelet Cycle Spinning Denoising of NDE Ultrasonic Signals Using a Random Selection of Shifts

Wavelets are a powerful tool for signal and image denoising. Most of the denoising applications in different fields were based on the thresholding of the discrete wavelet transform (DWT) coefficients. Nevertheless, DWT transform is not a time or shift invariant transform and results depend on the selected shift. Improvements on the denoising performance can be obtained using the stationary wavelet transform (SWT) (also called shift-invariant or undecimated wavelet transform). Denoising using SWT has previously shown a robust and usually better performance than denoising using DWT but with a higher computational cost. In this paper, wavelet shrinkage schemes are applied for reducing noise in synthetic and experimental non-destructive evaluation ultrasonic A-scans, using DWT and a cycle-spinning implementation of SWT. A new denoising procedure, which we call random partial cycle spinning (RPCS), is presented. It is based on a cycle-spinning over a limited number of shifts that are selected in a random way. Wavelet denoising based on DWT, SWT and RPCS have been applied to the same sets of ultrasonic A-scans and their performances in terms of SNR are compared. In all cases three well known threshold selection rules (Universal, Minimax and Sure), with decomposition level dependent selection, have been used. It is shown that the new procedure provides a good robust denoising performance, without the DWT fluctuating performance, and close to SWT but with a much lower computational cost.This work was partially supported by Spanish MCI Project DPI2011-22438San Emeterio Prieto, JL.; Rodríguez-Hernández, MA. (2015). Wavelet Cycle Spinning Denoising of NDE Ultrasonic Signals Using a Random Selection of Shifts. Journal of Nondestructive Evaluation. 34(1):1-8. https://doi.org/10.1007/s10921-014-0270-8S18341Galloway, R.L., McDermott, B.A., Thurstone, F.L.: A frequency diversity process for speckle reduction in real-time ultrasonic images. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 35, 45–49 (1988)Newhouse, V.L., Bilgutay, N.M., Saniie, J., Furgason, E.S.: Flaw-to-grain echo enhancement by split spectrum processing. Ultrasonics 20, 59–68 (1982)Karpur, P., Canelones, O.J.: Split spectrum processing: a new filtering approach for improved signal-to-noise ratio enhancement of ultrasonic signals. Ultrasonics 30, 351–357 (1992)Donoho, D.L., Johnstone, I.M.: Ideal spatial adaptation by wavelet shrinkage. Biometrika 81, 425–455 (1994)Donoho, D.L., Johnstone, I.M., Kerkyacharian, G., Picard, D.: Wavelet shrinkage: asymptotia? J. R Stat. Soc. Ser. B 57, 301–369 (1995)Donoho, D.L., Johnstone, I.M.: Adapting to unknown smoothness via wavelet shrinkage. J. Am. Stat. Assoc. 90, 1200–1224 (1995)Johnstone, I.M., Silverman, B.W.: Wavelet threshold estimators for data with correlated noise. J. R Stat. Soc. 59, 319–351 (1997)Jansen, M.: Noise Reduction by Wavelet Thresholding. Lecture Notes in Statistics 161. Springer, New York (2001). doi: 10.1007/978-1-4613-0145-5Nason, G.P., Silverman, B.W.:The stationary wavelet transform and some statistical applications. In: Antoniadis, A., Oppenheim, G. (eds.) Wavelets and Statistics. Lecture Notes in Statistics, Vol. 103, pp 281–299. Springer, New York (1995)Lang, M., Guo, H., Odegard, J.E., Burrus, C.S.: Noise reduction using an undecimated discrete wavelet transform. IEEE Signal Proc. Lett. 3, 10–12 (1996)Coifman, R.R., Donoho, D.L.: Translation-invariant de-noising. In: Antoniadis, A., Oppenheim, G. (eds.) Wavelets and Statistics. Lecture Notes in Statistics, vol. 103, pp 125–150, Springer, New York (1995) .Abbate, A., Koay, J., Frankel, J., Schroeder, S.C., Das, P.: Signal detection and noise suppression using a wavelet transform signal processor: application to ultrasonic flaw detection. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 44, 14–26 (1997)Lázaro, J.C., San Emeterio, J.L., Ramos, A., Fernandez, J.L.: Influence of thresholding procedures in ultrasonic grain noise reduction using wavelets. Ultrasonics 40, 263–267 (2002)Matz, V., Smid, R., Starman, S., Kreidl, M.: Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing. Ultrasonics 49, 752–759 (2009)Kubinyi, M., Kreibich, O., Neuzil, J., Smid, R.: EMAT noise suppression using information fusion in stationary wavelet packets. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 58, 1027–1036 (2011)Shi, G.M., Chen, X.Y., Song, X.X., Qui, F., Ding, A.L.: Signal matching wavelet for ultrasonic flaw detection in high background noise. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 58, 776–787 (2011)Song, S.P., Que, P.W.: Wavelet based noise suppression technique and its application to ultrasonic flaw detection. Ultrasonics 44, 188–193 (2006)Rodriguez, M.A., San Emeterio, J.L., Lázaro, J.C., Ramos, A.: Ultrasonic flaw detection in NDE of highly scattering materials using wavelet and Wigner-Ville transform processing. Ultrasonics 42, 847–851 (2004)Zhang, G.M., Zhang, S.Y., Wang, Y.W.: Application of adaptive time-frequency decomposition in ultrasonic NDE of highly-scattering materials. Ultrasonics 38, 961–964 (2000)Drai, R., Khelil, M., Benchaala, A.: Time frequency and wavelet transform applied to selected problems in ultrasonics NDE. NDT & E Int. 35, 567–572 (2002)Pardo, E., San Emeterio, J.L.: Noise reduction in ultrasonic NDT using undecimated wavelet transforms. Ultrasonics 44, e1063–e1067 (2006)Kechida, A., Drai, R., Guessoum, A.: Texture analysis for flaw detection in ultrasonic images. J. Nondestruct. Eval. 31, 108–116 (2012). doi: 10.1007/s10921-011-0126-4Rucka, M., Wilde, K.: Experimental study on ultrasonic monitoring of splitting failure in reinforced concrete. J. Nondestruct. Eval. 32, 372–383 (2013). doi: 10.1007/s10921-013-0191-yHosseini, S.M.H., Duczek, S., Gabbert, U.: Damage localization in plates using mode conversion characteristics of ultrasonic guided waves. J. Nondestruct. Eval. 33, 152–165 (2014). doi: 10.1007/s10921-013-0211-yMohammed, M.S., Ki-Seong, K.: Shift-invariant wavelet packet for signal de-noising in ultrasonic testing. Insight 54, 366–370 (2012)San Emeterio, J.L., Rodriguez-Hernandez, M.A.: Wavelet denoising of ultrasonic A-scans by random partial cycle spinning. In: Proceedings of the 2012 IEEE International Ultrasonics Symposium. pp 455–458.Mallat, S.G.: A theory of multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11, 674–693 (1989)Shensa, M.J.: The discrete wavelet transform: wedding the à trous and Mallat algorithms. IEEE Trans. Signal Process. 40, 2464–2482 (1992). doi: 10.1109/78.157290Beylkin, G., Coifman, R., Rokhlin, V.: Fast wavelet transforms and numerical algorithms. Commun. Pure Appl. Math. 44, 141–183 (1991)Daubechies, I.: Ten Lectures on Wavelets. SIAM, Philadelphia (1992)Romijn, R.L., Thijssen, J.M., Vanbeuningen, G.W.J.: Estimation of scatterer size from backscattered ultrasound: a simulation study. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 36, 593–606 (1989)Gustafsson, M.G., Stepinski, T.: Studies of split spectrum processing, optimal detection, and maximum likehood amplitude estimation using a simple clutter model. Ultrasonics 35, 31–53 (1997

Information management technology of cable harness virtual assembly planning for cross assembly

Firstly, based on the analysis of the information that needed to be managed in cable harness virtual assembly planning process, the storage structure based on assembly task and cable harness routing task was put forward, which can record the cable harness virtual assembly planning history. Secondly, post-processing of outcome information was described in three aspects: generation of BOM, producing initialization assembly planning documentation, recording assembly animation. Finally, the above techniques and methods were validated in self-developed virtual assembly prototype software system named VAPP through instances.link_to_subscribed_fulltex

A Framework for Research in Transition: Identifying Important Areas and Intersections for Future Study

The role of research in transition education has been prominent and influential. Yet too many young people with disabilities are still not experiencing outcomes aligned with their personal aspirations and priorities. Moreover, individuals with disabilities continue to experience barriers to employment, educational, economic, and other challenges well into adulthood. Moving forward as a field will require continued investment in strong scholarship and careful consideration of new areas of inquiry. In this article, we present a framework for transition research designed to identify key issues and intersections in which future inquiry should be directed. We present research needs in six different areas to illustrate these possibilities. We also highlight some of the complexities and considerations associated with conducting this research