Modal Analysis of a Cantilever Beam Using an Inexpensive Smartphone Camera: Motion Magnification Technique
This paper aims to prove the accuracy of an inexpensive smartphone camera as a non-contact vibration sensor to recover the vibration modes of a vibrating structure such as a cantilever beam. A video of a vibrating beam is filmed using a smartphone camera and then processed by the motion magnification technique. Based on this method, the first two natural frequencies and their associated mode shapes are estimated experimentally and compared to the analytical ones. Results show a relative error of less than 4% between the experimental and analytical approaches for the first two natural frequencies of the beam. Also, for the first two-mode shapes, a Modal Assurance Criterion (MAC) value of above 0.9 between the two approaches is obtained. This slight error between the different techniques ensures the viability of a cheap smartphone camera as a non-contact vibration sensor, particularly for structures vibrating at relatively low natural frequencies.
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[2] D. Mandal, D. Wadadar, and S. Banerjee, “Performance evaluation of damage detection algorithms for identification of debond in stiffened metallic plates using a scanning laser vibrometer,” Journal of Vibration and Control, vol. 24, no. 12, pp. 2464–2482, 2018.
[3] K. Saravanan, A. Sekhar, “Crack detection in a rotor by operational deflection shape and kurtosis using laser vibrometer measurements,” Journal of Vibration and Control, vol. 19, no. 8, pp. 1227–1239, 2013.
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[7] P. Poozesh, A. Sarrafi, Z. Mao, P. Avitabile, C. Niezrecki, “Feasibility of extracting operating shapes using phase-based motion magnification technique and stereo-photogrammetry,” Journal of Sound and Vibration, vol. 407, pp. 350–366, 2017.
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[10] A. Sarrafi, Z. Mao, C. Niezrecki, P. Poozesh, “Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification,” Journal of Sound and Vibration, vol. 421, pp. 300–318, 2018.
[11] A. Davis, M. Rubinstein, N. Wadhwa, G. Mysore, F. Durand, W. Freeman, “The visual microphone: passive recovery of sound from video,” ACM T Graphic 2014; vol. 33(4): 10 pages.
[12] G. Balakrishnan, F. Durand, J. Guttag, “Detecting pulse from head motions in video,” in 2013 Proc. of the IEEE on Computer Vision and Pattern Recognition Conf., pp. 3430–3437.
[13] Tracker. https://physlets.org/tracker/ (accessed 01.12.18).
[14] D. Ewins, “Modal testing: theory, practice, and application (2nd Ed),” Research Studies Press, Baldock, Hertfordshire, England, 2000; Philadelphia, PA.
[15] D. J. Inman. Engineering vibration. 3rd edition, 2007.
[16] N. Wadhwa, M. Rubinstein, F. Durand, WT. Freeman, “Phase-based video motion processing,” ACM Trans. Graph., vol. 32, no. 4, 2013.
[17] D. Fleet, A. Jepson, “Computation of component image velocity from local phase information”. International Journal of Computer Vision, vol. 5, no. 1, pp. 77–104, 1990.
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[1] T. Kranjc, J. Slavič, and M. Boltežar, “A comparison of strain and classic experimental modal analysis,” Journal of Vibration and Control, vol. 22, no. 2, pp. 371–381, 2014.
[2] D. Mandal, D. Wadadar, and S. Banerjee, “Performance evaluation of damage detection algorithms for identification of debond in stiffened metallic plates using a scanning laser vibrometer,” Journal of Vibration and Control, vol. 24, no. 12, pp. 2464–2482, 2018.
[3] K. Saravanan, A. Sekhar, “Crack detection in a rotor by operational deflection shape and kurtosis using laser vibrometer measurements,” Journal of Vibration and Control, vol. 19, no. 8, pp. 1227–1239, 2013.
[4] J. Chen, N. Wadhwa, Y. Cha Y., F. Durand, W. Freeman, O. Buyukozturk. “Structural Modal Identification Through High Speed Camera Video: Motion Magnification,” in 2014 Proc. of the Society for Experimental Mechanics Series Conf., pp. 191–197.
[5] D. Feng, M. Feng, “Identification of structural stiffness and excitation forces in time domain using noncontact vision-based displacement measurement,” Journal of Sound and Vibration, vol. 406, pp. 15-28, 2017.
[6] J. Chen, N. Wadhwa, Y. Cha, F. Durand, W. Freeman, O. Buyukozturk, “Modal identification of simple structures with high-speed video using motion magnification,” Journal of Sound and Vibration, vol. 345, pp: 58–71, 2015.
[7] P. Poozesh, A. Sarrafi, Z. Mao, P. Avitabile, C. Niezrecki, “Feasibility of extracting operating shapes using phase-based motion magnification technique and stereo-photogrammetry,” Journal of Sound and Vibration, vol. 407, pp. 350–366, 2017.
[8] Video magnification. http://people.csail.mit.edu/mrub/vidmag/ (accessed 01.12.18).
[9] A. Davis, K. Bouman, J. Chen, M. Rubinstein, F. Durand, W. Freeman, “Visual vibrometry: Estimating material properties from small motion in video,” in 2015 Proc. of the IEEE on Computer Vision and Pattern Recognition Conf., pp. 5335–5343.
[10] A. Sarrafi, Z. Mao, C. Niezrecki, P. Poozesh, “Vibration-based damage detection in wind turbine blades using Phase-based Motion Estimation and motion magnification,” Journal of Sound and Vibration, vol. 421, pp. 300–318, 2018.
[11] A. Davis, M. Rubinstein, N. Wadhwa, G. Mysore, F. Durand, W. Freeman, “The visual microphone: passive recovery of sound from video,” ACM T Graphic 2014; vol. 33(4): 10 pages.
[12] G. Balakrishnan, F. Durand, J. Guttag, “Detecting pulse from head motions in video,” in 2013 Proc. of the IEEE on Computer Vision and Pattern Recognition Conf., pp. 3430–3437.
[13] Tracker. https://physlets.org/tracker/ (accessed 01.12.18).
[14] D. Ewins, “Modal testing: theory, practice, and application (2nd Ed),” Research Studies Press, Baldock, Hertfordshire, England, 2000; Philadelphia, PA.
[15] D. J. Inman. Engineering vibration. 3rd edition, 2007.
[16] N. Wadhwa, M. Rubinstein, F. Durand, WT. Freeman, “Phase-based video motion processing,” ACM Trans. Graph., vol. 32, no. 4, 2013.
[17] D. Fleet, A. Jepson, “Computation of component image velocity from local phase information”. International Journal of Computer Vision, vol. 5, no. 1, pp. 77–104, 1990.
[18] T. Gautama, M. Hulle, “A phase-based approach to the estimation of the optical flow field using spatial filtering,” IEEE Trans Neural Network, vol. 13, no. 5, pp. 1127–1136, 2002.
[19] W. Freeman, E. Adelson, “The design and use of steerable filters,” IEEE Trans Pattern Anal Mach Intell., vol. 13, no. 9, pp. 891–906, 1991.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:80207", author = "Hasan Hassoun and Jaafar Hallal and Denis Duhamel and Mohammad Hammoud and Ali Hage Diab", title = "Modal Analysis of a Cantilever Beam Using an Inexpensive Smartphone Camera: Motion Magnification Technique", abstract = "This paper aims to prove the accuracy of an inexpensive smartphone camera as a non-contact vibration sensor to recover the vibration modes of a vibrating structure such as a cantilever beam. A video of a vibrating beam is filmed using a smartphone camera and then processed by the motion magnification technique. Based on this method, the first two natural frequencies and their associated mode shapes are estimated experimentally and compared to the analytical ones. Results show a relative error of less than 4% between the experimental and analytical approaches for the first two natural frequencies of the beam. Also, for the first two-mode shapes, a Modal Assurance Criterion (MAC) value of above 0.9 between the two approaches is obtained. This slight error between the different techniques ensures the viability of a cheap smartphone camera as a non-contact vibration sensor, particularly for structures vibrating at relatively low natural frequencies.
", keywords = "Modal Analysis, motion magnification, smartphone camera, structural vibration, vibration modes.", volume = "15", number = "1", pages = "52-5", }
