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Design of an Ultrasonic Concentrator for Vibro-Tactile Sensors Using Electro-Mechanical Analogy

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Abstract

Vibro-tactile sensors have been utilized to measure the mechanical properties of soft materials based on the shift of resonant frequency. However, their low signal to noise ratio (SNR) has impeded them from critical applications where accurate measurements are required. One of the ways to improve the SNR is to add an ultrasonic concentrator as a mechanical filter to the vibro-tactile sensor. In order to maximize the SNR, the concentrator should be optimally designed; however, systematic design approach of the concentrator has rarely been considered so far. In this paper, a hybrid design approach employing both analytical analysis and numerical simulation is presented. For analytical analysis, impedance analogy was used to facilitate the designing process, and the numerical simulation using FEA was conducted to carry out the parametric refinement of the design. The performance of the final design was verified by mechanical and electrical characteristics tests. Tests results indicate that the longitudinal resonance mode of the sensor was significantly enhanced and the increase in its mechanical quality factor was achieved by the ultrasonic concentrator. The tactile sensing experiments on the silicone rubber samples showed the high potential of the vibro-tactile sensor in estimating the elastic moduli of soft materials in the range of 5–100 kPa, which is not readily available with conventional testing methods.

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Abbreviations

\(F_{i}\) :

Force

\(u\) :

Velocity

\(M\) :

Mass

\(C_{m}\) :

Damping

\(K_{m}\) :

Stiffness

\(x\) :

Longitudinal dimension

\(l\) :

Length of the structure

\(D\) :

Diameter

\(\upalpha\) :

Measure of the cone opening

\(\xi \left( x \right)\) :

Longitudinal displacement distribution

\(S\left( x \right)\) :

Shape function in the longitudinal direction

\(k\) :

Wave number

\(K\) :

Generalized wave number

\(\omega\) :

Angular velocity

\(c\) :

Sound speed

\(\rho\) :

Density

\(U\) :

Equivalent voltage

\(i\) :

Equivalent current

\(R\) :

Resistance in equivalent circuit

\(C\) :

Capacitance in equivalent circuit

\(L\) :

Inductance in equivalent circuit

\(Z\) :

Electrical impedance

\(\varPhi\) :

Phase angle

SNR:

Signal to noise ratio

FEA:

Finite element analysis

SIMP:

Solid isotropic material with penalization

ESO:

Evolutionary structural optimization

References

  1. Tiwana, M. I., Redmond, S. J., & Lovell, N. H. (2012). A review of tactile sensing technologies with applications in biomedical engineering. Sensors and Actuators, A: Physical, 179, 17–31.

    Article  Google Scholar 

  2. Sadeghi-Goughari, M., Mojra, A., & Sadeghi, S. (2016). Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network. Journal of Physics. D: Applied Physics, 49(7), 075404. https://doi.org/10.1088/0022-3727/49/7/075404.

    Article  Google Scholar 

  3. Sangpradit, K., Liu, H., Dasgupta, P., Althoefer, K., & Seneviratne, L. D. (2011). Finite-element modeling of soft tissue rolling indentation. IEEE Transactions on Biomedical Engineering, 58(12 PART 1), 3319–3327.

    Article  Google Scholar 

  4. Vidic, A., Then, D., & Ziegler, C. (2003). A new cantilever system for gas and liquid sensing. Ultramicroscopy, 97(1–4), 407–416.

    Article  Google Scholar 

  5. Omata, S., & Terunuma, Y. (1992). New tactile sensor like the human hand and its applications. Sensors and Actuators, A: Physical, 35(1), 9–15.

    Article  Google Scholar 

  6. Lindahl, O. A., & Omata, S. (1995). Impression technique for the assessment of oedema: Comparison with a new tactile sensor that measures physical properties of tissue. Medical & Biological Engineering & Computing, 33(1), 27–32.

    Article  Google Scholar 

  7. Lindahl, O. A., Omata, S., & Ängquist, K.-A. (1998). A tactile sensor for detection of physical properties of human skin in vivo. Journal of Medical Engineering & Technology, 22(4), 147–153.

    Article  Google Scholar 

  8. Jalkanen, V., Andersson, B. M., Bergh, A., Ljungberg, B., & Lindahl, O. A. (2006). Prostate tissue stiffness as measured with a resonance sensor system: A study on silicone and human prostate tissue in vitro. Medical & Biological Engineering & Computing, 44(7), 593.

    Article  Google Scholar 

  9. Jalkanen, V., Andersson, B. M., Bergh, A., Ljungberg, B., & Lindahl, O. A. (2013). Indentation loading response of a resonance sensor—Discriminating prostate cancer and normal tissue. Journal of Medical Engineering & Technology, 37(7), 416–423.

    Article  Google Scholar 

  10. Nyberg, M., Jalkanen, V., Ramser, K., Ljungberg, B., Bergh, A., & Lindahl, O. A. (2015). Dual-modality probe intended for prostate cancer detection combining Raman spectroscopy and tactile resonance technology—discrimination of normal human prostate tissues ex vivo. Journal of Medical Engineering & Technology, 39(3), 198–207.

    Article  Google Scholar 

  11. Åstrand, A. P., Andersson, B. M., Jalkanen, V., Ljungberg, B., Bergh, A., & Lindahl, O. A. (2017). Prostate cancer detection with a tactile resonance sensor—measurement considerations and clinical setup. Sensors (Switzerland), 17(11), 2453. https://www.ncbi.nlm.nih.gov/pubmed/29072592.

  12. Jalkanen, V., Andersson, B. M., Bergh, A., Ljungberg, B., & Lindahl, O. A. (2008). Explanatory models for a tactile resonance sensor system—Elastic and density-related variations of prostate tissue in vitro. Physiological Measurement, 29(7), 729–745.

    Article  Google Scholar 

  13. Murayama, Y., & Lindahl, O. A. (2017). Sensitivity improvements of a resonance-based tactile sensor. Journal of Medical Engineering & Technology, 41(2), 131–140.

    Article  Google Scholar 

  14. Aminzahed, I., Zhang, Y., & Jabbari, M. (2016). Energy harvesting from a five-story building and investigation of frequency effect on output power. International Journal on Interactive Design and Manufacturing, 10(3), 301–308.

    Article  Google Scholar 

  15. Rani, M. R., & Rudramoorthy, R. (2013). Computational modeling and experimental studies of the dynamic performance of ultrasonic horn profiles used in plastic welding. Ultrasonics, 53(3), 763–772.

    Article  Google Scholar 

  16. Mason, W. P. (1948). Electromechanical transducers and wave filters (pp. 80–83). New York: D. Van Nostrand Co.

    Google Scholar 

  17. Gardonio, P., & Brennan, M. J. (2004). Mobility and impedance methods in structural dynamics. In Advanced applications in acoustics, noise and vibration (Chap. 9). Spon Press. https://books.google.ca/books?hl=en&lr=&id=ZUtZDwAAQBAJ&oi=fnd&pg=PA389&dq=Mobility+and+impedance+methods+in+structural+dynamics+(Vol.+9)+in+Advanced+Applications+in+Acoustics&ots=K6UNQdZ-iL&sig=YOCeDcYagTRbvqm72gW3vPhUXH0#v=onepage&q&f=false.

  18. Melke, J. (1988). Noise and vibration from underground railway lines: Proposals for a prediction procedure. Journal of Sound and Vibration, 120(2), 391–406.

    Article  Google Scholar 

  19. Wang, K., & Nguyen, C. T. C. (1999). High-order medium frequency micromechanical electronic filters. Journal of Microelectromechanical Systems, 8, 534–556.

    Article  Google Scholar 

  20. Prokic, M. (2004). Piezoelectric transducers modeling. In Piezoelectric transducers modeling and characterization (Chap. 1, pp. 2–26). MP Interconsulting. https://books.google.ca/books/about/Piezoelectric_Transducers_Modeling_and_C.html?id=0ENvGwAACAAJ&redir_esc=y.

  21. Schaschke, C. (2014). A dictionary of chemical engineering (p. 384). Oxford: Oxford University Press.

    Google Scholar 

  22. Tortorelli, D. A., & Zixian, W. (1993). A systematic approach to shape sensitivity analysis. International Journal of Solids and Structures, 30(9), 1181–1212.

    Article  MathSciNet  MATH  Google Scholar 

  23. Arora, J. S. (2007). Introduction to optimization. In Optimization of structural and mechanical systems (Chap. 1). World Scientific. https://www.worldscientific.com/worldscibooks/10.1142/6214.

  24. Allaire, G., Jouve, F., & Toader, A.-M. (2004). Structural optimization using sensitivity analysis and a level-set method. Journal of Computational Physics, 194(1), 363–393.

    Article  MathSciNet  MATH  Google Scholar 

  25. Ning, J., Nguyen, V., Huang, Y., Hartwig, K. T., & Liang, S. Y. (2018). Inverse determination of Johnson–Cook model constants of ultra-fine-grained titanium based on chip formation model and iterative gradient search. The International Journal of Advanced Manufacturing Technology, 99, 1131–1140.

    Article  Google Scholar 

  26. Keshavarzzadeh, V., Meidani, H., & Tortorelli, D. A. (2016). Gradient based design optimization under uncertainty via stochastic expansion methods. Computer Methods in Applied Mechanics and Engineering, 306, 47–76.

    Article  MathSciNet  Google Scholar 

  27. Sjølund, J. H., & Lund, E. (2018). Structural gradient based sizing optimization of wind turbine blades with fixed outer geometry. Composite Structures, 203, 725–739.

    Article  Google Scholar 

  28. Bendsøe, M. P., & Kikuchi, N. (1988). Generating optimal topologies in structural design using a homogenization method. Computer Methods in Applied Mechanics and Engineering, 71(2), 197–224.

    Article  MathSciNet  MATH  Google Scholar 

  29. Deaton, J. D., & Grandhi, R. V. (2014). A survey of structural and multidisciplinary continuum topology optimization: Post 2000. Structural and Multidisciplinary Optimization., 49(1), 1–38.

    Article  MathSciNet  Google Scholar 

  30. Liu, J., & Ma, Y. (2016). A survey of manufacturing oriented topology optimization methods. Advances in Engineering Software, 100, 161–175.

    Article  Google Scholar 

  31. Langelaar, M. (2016). Topology optimization of 3D self-supporting structures for additive manufacturing. Additive Manufacturing, 12, 60–70.

    Article  Google Scholar 

  32. Zheng, J., Luo, Z., Li, H., & Jiang, C. (2018). Robust topology optimization for cellular composites with hybrid uncertainties. Journal for Numerical Methods in Engineering, 115, 695–713.

    Article  MathSciNet  Google Scholar 

  33. Wang, D. A., Chuang, W. Y., Hsu, K., & Pham, H. T. (2011). Design of a Bézier-profile horn for high displacement amplification. Ultrasonics, 51(2), 148–156.

    Article  Google Scholar 

  34. Qian, Y. J., Han, S. W., & Kwon, H. J. (2016). Development of ultrasonic surface treatment device. Applied Mechanics and Materials, 835, 620–625.

    Article  Google Scholar 

  35. Lin, S. (2004). Theories and designs of the ultrasonic transducers (pp. 98–111). Beijing: Science Press. [in Chinese].

    Google Scholar 

  36. Sherrit, S., & Mukherjee, B. K. (2007). Characterization of piezoelectric materials for transducers. arXiv:0711.2657.

  37. Lin, Z. (1987). Theories and designs of the ultrasonic horn (pp. 108–126). Beijing: Science Press. [in Chinese].

    Google Scholar 

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Acknowledgement

The work was supported by Natural Sciences and Engineering Research Council of Canada (NSERC).

Funding

Funding was provided by Discovery Grant, Natural Sciences and Engineering Research Council of Canada (RGPIN-2015-04118).

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Correspondence to Yanjun Qian.

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Qian, Y., Han, SW. & Kwon, HJ. Design of an Ultrasonic Concentrator for Vibro-Tactile Sensors Using Electro-Mechanical Analogy. Int. J. Precis. Eng. Manuf. 20, 1787–1800 (2019). https://doi.org/10.1007/s12541-019-00190-1

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