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MSM 2018: Methods and Techniques of Signal Processing in Physical Measurements pp 351–359Cite as

Frequency Components of Signals Producing the Upper Bound of Absolute Error Generated by the Charge Output Accelerometers

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 548))

Abstract

The paper presents an assessment of frequency components by the time-frequency representation of signals with one constrain producing the upper bound of the absolute error generated by charge output accelerometers. The constraint concerns the amplitude resulting from the measuring range of an accelerometer. This assessment was carried out by using a wavelet analysis implemented in MATLAB. Mathematical basis regarding both modeling charge output accelerometers and determining the absolute error were presented. Shapes of signals producing the upper bound of error and results of analysis for selected parameters of the accelerometer model are also presented and discussed.

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References

  1. Layer, E., Gawedzki, W.: Dynamics of Measurement Systems: Investigation and Estimation. Polish Scientific Publisher, Warsaw (1991)

    MATH  Google Scholar 

  2. Rutland, N.K.: The principle of matching: practical conditions for systems with inputs restricted in magnitude and rate of change. IEEE Trans. Autom. Control 39, 550–553 (1994)

    Article  Google Scholar 

  3. Hessling, J.P.: A novel method of estimating dynamic measurement error. Meas. Sci. Technol. 17, 2740–2750 (2006)

    Article  Google Scholar 

  4. Layer, E., Gawedzki, W.: Time-frequency properties of signals maximizing the dynamic errors. SAMS 11, 73–77 (1993)

    MATH  Google Scholar 

  5. Tomczyk, K., Layer, E.: Energy density for signals maximizing the integral-square error. Measurement 90, 224–232 (2016)

    Article  Google Scholar 

  6. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA (1989)

    MATH  Google Scholar 

  7. Booker, L.B., Goldberg, D.E., Holland, J.H.: Classifier systems and genetic algorithms. Artif. Intell. 40, 235–282 (1989)

    Article  Google Scholar 

  8. Tomczyk, K.: Application of Genetic Algorithm to Measurement System Calibration Intended for Dynamic Measurement. Metrology and Measurement Systems, vol. XIII, pp. 93–103 (2006)

    Google Scholar 

  9. Mallat, S.A.: Tour of Signal Processing. Academic Press, New York (1998)

    MATH  Google Scholar 

  10. Huang, M.C.: Wave parameters and functions in wavelet analysis. Ocean Eng. 31, 111–125 (2005)

    Article  Google Scholar 

  11. Xiangcheng, M., Haibao, R., Zisheng, O., Wei, W., Keping, M.: The Use of the Mexican Hat and the Morlet Wavelets for Detection of Ecological Patterns. Plant Ecology, vol. 179, pp. 1–19. Springer (2005)

    Google Scholar 

  12. Bialasiewicz, J.T.: Wavelet-based approach to evaluation of signal integrity. IEEE Trans. Ind. Electron. 60, 4590–4598 (2013)

    Article  Google Scholar 

  13. Tomczyk, K.: Problems in modelling of charge output accelerometers. Metrol. Meas. Syst. 23(4), 645–659 (2016)

    Article  Google Scholar 

  14. Jyh-Cheng, Y., Ching-Bin, L.: System modeling and robust design of microaccelerometer using piezoelectric thin film. In: Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems. Taiwan, pp. 99–104 (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155, Krakow, Poland

    Krzysztof Tomczyk & Marek Sieja

Authors
  1. Krzysztof Tomczyk
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  2. Marek Sieja
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Corresponding author

Correspondence to Krzysztof Tomczyk .

Editor information

Editors and Affiliations

  1. Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, Rzeszów, Poland

    Robert Hanus

  2. Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, Rzeszów, Poland

    Damian Mazur

  3. Faculty of Electrical Engineering,Electrical Machines and Drive Systems, Helmut Schmidt University ,University of the Federal Armed Forces Hamburg,, Hamburg, Hamburg, Germany

    Christian Kreischer

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Tomczyk, K., Sieja, M. (2019). Frequency Components of Signals Producing the Upper Bound of Absolute Error Generated by the Charge Output Accelerometers. In: Hanus, R., Mazur, D., Kreischer, C. (eds) Methods and Techniques of Signal Processing in Physical Measurements. MSM 2018. Lecture Notes in Electrical Engineering, vol 548. Springer, Cham. https://doi.org/10.1007/978-3-030-11187-8_29

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  • DOI: https://doi.org/10.1007/978-3-030-11187-8_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11186-1

  • Online ISBN: 978-3-030-11187-8

  • eBook Packages: EngineeringEngineering (R0)

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