Di Maio, D.

Harvey, P. S.

English

University of Twente Research Information

Special Issue on Computer Vision and Scanning LaserVibrometry MethodsD. Di Maio1 & P.S. Harvey Jr.2# The Society for Experimental Mechanics, Inc 2021In recent decades, the use of optical measurement tech-niques for experimental testing has rapidly been gainingpopularity for dynamic measurements. The aim of thisspecial issue of Experimental Techniques is to assemblea collection of papers that present recent work on opticalmeasurement techniques, focusing on computer vision andscanning laser Doppler vibrometry (SLDV) methods andtheir applications. This collection of papers highlights ad-vancements in the areas of computer vision, laservibrometry, digital image correlation (DIC), photogram-metry, and other optical techniques, along with applica-tions of these techniques for dynamic measurements,structural dynamics, and structural health monitoring.During IMAC-XXXVIII held in Houston, TX onFebruary 10–13, 2020, researchers and practitioners fromaround the world comprising the SEM Technical Divisionon Computer Vision and Laser Vibrometry (previously theSLDV Application & Methods FG and Optical Methods &Computer Vision for Structural Dynamics FG of SEM)identified the need for this special issue. After undergoingan external peer review, twelve technical papers were ac-cepted for this special issue, covering a wealth of topicsconcerning computer vision and SLDV methods.Moreover, this special issue gives an international perspec-tive on these topics, with authors from six different coun-tries, including Belgium, China, Netherlands, Poland, UKand USA. The technical papers fall into two broad catego-ries—(1) computer vision and (2) scanning laser Dopplervibrometry—with some overlaps existing among subsets ofpapers, which are briefly described herein.Computer VisionEight articles on computer vision are presented in this issue ofExperimental Techniques. The first three are focused on dig-ital image correlation, the next two on motion magnification,and the last three on single camera approaches.DICBeberniss and Ehrhardt (1) investigate the presence of lightrefraction distortions in 3D DIC displacement measurementsof a panel specimen during Mach 2 wind tunnel tests. Theirstudy addresses distortions from the optical access windowand high-speed flow density gradients, with shock foot distor-tion posing the greatest challenge but ultimately being deemedacceptably small. Recommendations for DIC optical setupsare proposed to mitigate light refraction distortions.Hu et al. (2) combine 3DDIC and Bayesian operational mod-al analysis (BOMA) for high-temperature modal analysis of atitanium plate. The plate was prepared with a laser engravedspeckle pattern, and a low-cost heating technique combiningelectromagnetic induction and radiant heating was used. Theexperimentally measured natural frequencies exhibited a non-monotonic dependence on the temperature, which is hypothe-sized to be attributed to a non-uniform temperature field andgeometric imperfections and is a topic of ongoing investigation.Witt and Rohe (3) present a framework for performingexperimental modal analysis (EMA) using DIC, coveringsome best practices in the test planning, setup, execution,and post-processing phases. Challenges in DIC-based EMAare identified (e.g., noise floor of the optical data acquisitionsystem and the relatively long data processing time), and rec-ommendations for overcoming these challenges are proposedto promote and improve the use of DIC in EMA.Motion MagnificationEitner et al. (4) utilize phased-based motion magnification(PMM) to reduce the signal-to-noise ratio in the output-only* D. Di Maiod.dimaio@utwente.nl1 Mechanical Engineering, University of Twente,Enschede, Netherlands2 School of Civil Engineering and Environmental Science, Universityof Oklahoma, Norman, OK, USAhttps://doi.org/10.1007/s40799-021-00480-2Published online: 18 May 2021Experimental Techniques (2021) 45:237–239modal identification of a polycarbonate’s out-of-plane dis-placement. The technique showed nearly fourfold increase inmodal assurance criteria (MAC) values when compared to afinite element model. Recommendations for the selection ofthe magnification factor and frequency band are given basedon a coherence function.Rohe and Reu (5) introduce a phase-based processing tech-nique for extracting modal parameters directly from the phasequantities. By treating the phase data directly as deformations,closely spaced peaks can be separated and qualitative analysescan be performed on the scaled modal quantities.Parallelization of the computation combined with optimizeddata storage is shown to greatly decrease the computationaltime required.Single CameraRohe et al. (6) introduce a novel technique to extract 3D mo-tions from a single camera. The technique uses a finite elementmodel expansion to recover the out-of-plane displacementsthat have traditionally been inaccessible with a single camera.Both synthetic and experimental sets of 2D images were usedto validate the method, which shows promise for future appli-cations with radiographic images.SoleimaniBabakamali et al. (7) proposed leveraging trafficcameras to extract modal information of the supporting trafficsignal mast arm. By using a single traffic camera and a pixel-based photogrammetric technique, modal frequencies anddamping ratios could be accurately predicted usingcovariance-driven stochastic subspace identification.Possible extensions of this proof-of-concept study are de-scribed, motivating future research in this area.Chi et al. (8) propose and validate the use of image com-pression in infrared thermography (IRT). Compressed imageswere shown to preserve meaningful features during two ex-perimental tests. The gains in storage space saved from imagecompression outweigh the accuracy lost in the determinationof feature size, which holds promise for future research onmore complicate structures.Scanning Laser VibrometryFour articles on scanning laser vibrometry are presented in thisedition of Experimental Techniques. The first one is under thecategory of interferometry techniques, while the other threeare about using laser vibrometry in application of experimen-tal model validation and damage detection. A brief account ofthe papers is given herein.Styk and Dziubecka-Bala (9) propose a new investigationabout the classical time-averaging interferometry technique,which is widely used for MEMS/MOEMS dynamic behaviorinvestigations. It provides useful information on resonantvibration frequencies and mode shapes in the form of Besselfringe images. The paper numerically investigates the possi-bility of reducing Bessel images argument (phase) evaluationerror by different phase shifting strategies.Sever and Maguire (10) propose a new approach to themodel validation by exploiting dynamic strain measurements.The paper shows how a 3D SLDV system can derive modalstrains from a turbine and compressor blades. The strain fieldsare then used for performing Modal Assurance Criterion(MAC) correlations, which are typically done by modal dis-placement vectors. The research demonstrates the augmentedaccuracy of performing the correlation by modal strain fields.Tavares et al. (11) propose a novel integration of SLDVmeasurements and Artificial Intelligence for Non-DestructiveEvaluation (NDE). The paper proposes an algorithm for iden-tifying the defects based on the Local Defect Resonance(LDR) concept, which looks to the high frequency vibrationsto get a localized resonant activation of the defect. ArtificialIntelligence (AI) techniques were implemented with the aimof creating an automatic procedure based on features extrac-tion for damage detection.Di Maio et al. (12) propose a novel algorithm which pro-cesses the spectral sidebands of an amplitude modulated timesignal into a damage indicator. The continuous scanning LDVenables the measurement of one deflection shape by a singleamplitude modulated time history. The RASTAR algorithmperforms an intelligent calculation of the spectral sidebands toderive a deflection shape change between a pristine and dam-aged test article.References1. Beberniss, TJ, Ehrhardt, DA (2021) Visible light refraction effectson high-speed stereo digital image correlation measurement of athin panel in Mach 2 flow. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00408-22. Hu YJ, Huang ZS, Zhu WD, Li HL (2021) A full-field non-contactthermal modal testing technique under ambient excitation. ExpTech 45(3). https://doi.org/10.1007/s40799-021-00441-93. Witt BL, Rohe DP (2021) Digital image correlation as an experi-mental modal analysis capability. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00420-64. Eitner M,MustaM, Vanstone L, Sirohi J, Clemens N (2021)Modalparameter estimation of a compliant panel using phase-based mo-tion magnification and stereoscopic digital image correlation. ExpTech 45(3). https://doi.org/10.1007/s40799-020-00393-65. Rohe D, Reu P (2021) Experimental modal analysis using phasequantities from phase-based motion processing and motion magni-fication. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00392-76. Rohe D, Witt B, Schoenherr T (2021) Predicting 3D motions fromsingle-camera optical test data. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00391-87. SoleimaniBabakamali MH, Moghadam A, Sarlo R, Hebdon MH,Harvey Jr. PS (2021) Mast arm monitoring via traffic camera238 Exp Tech (2021) 45:237–239footage: a pixel-based modal analysis approach. Exp Tech 45(3).https://doi.org/10.1007/s40799-020-00422-48. Chi X, Zhang Y, DiMaio D, Lieven NAJ (2021) Viability of imagecompression in vibrothermography. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00395-49. Styk A, Dziubecka-Bala H (2021) Phase shift strategies in phaseshifting time averaging interferometry. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00427-z10. Sever I, Maguire M (2021) Correlation of full-field dynamic strainmeasurements with reverse engineered finite element model predic-tions. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00410-811. Tavares A, Di Lorenzo E, Peeters B, Coppotelli G, SilvestreN (2021) Damage detection in lightweight structures using artificialintelligence techniques. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00421-512. Di Maio D, Bruinsma S, Tinga T (2021) Diagnostics based oncontinuous scanning LDV measurements and RASTAR analysismethod. Exp Tech 45(3). https://doi.org/10.1007/s40799-020-00406-4Publisher’s Note Springer Nature remains neutral with regard to jurisdic-tional claims in published maps and institutional affiliations.239Exp Tech (2021) 45:237–239

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