Problems in Modelling Charge Output Accelerometers

• Autorzy: Tomczyk K.

Identyfikatory

DOI

10.1515/mms-2016-0045

• Języki publikacji: EN

Abstrakty

EN

The paper presents major issues associated with the problem of modelling change output accelerometers. The presented solutions are based on the weighted least squares (WLS) method using transformation of the complex frequency response of the sensors. The main assumptions of the WLS method and a mathematical model of charge output accelerometers are presented in first two sections of this paper. In the next sections applying the WLS method to estimation of the accelerometer model parameters is discussed and the associated uncertainties are determined. Finally, the results of modelling a PCB357B73 charge output accelerometer are analysed in the last section of this paper. All calculations were executed using the MathCad software program. The main stages of these calculations are presented in Appendices A−E.

Słowa kluczowe

EN

weighted least square method; charge output accelerometer; mathematical modelling; parameter estimation

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2016
• Tom: Vol. 23, nr 4
• Strony: 645--659
• Opis fizyczny: Bibliogr. 21 poz., rys., tab., wykr., wzory

Twórcy

autor

Tomczyk K.

• Cracow University of Technology, Faculty of Electrical and Computer Engineering, Warszawska 24, 31-155 Kraków, Poland

Bibliografia

• [1] Yu, J.Ch., Lan, Ch.B. (1999). System Modeling and Robust Design of Microaccelerometer using Piezoelectric Thin Film. Proc. of the IEEE Int. Conf. on MFI for Intell. Syst., 99-104.
• [2] Levy, E.C. (1959). Complex-Curve Fitting. IEEE T. Automat. Contr., AC-4, 37-44.
• [3] Sanathanan, C.K., Koerner, J. (1963). Transfer Function Synthesis as a Ratio of Two Complex Polynomials. IEEE T. Automat. Contr., AC-9, 56-58.
• [4] Strobel, H. (1966). On a New Method of Determining the Transfer Function by Simultaneous Evaluation of the Real and Imaginary Parts of the Measured Frequency Response, 3-rd IFAC Symposium. London.
• [5] Gyurki, J. (1970). Some Questions of Identification on the basis of Frequency Response. Acta Tech. Hung., 68, 145-160.
• [6] Payne, P.A. (1970). An Improved Technique for Transfer Function Synthesis from Frequence Response Data. IEEE T. Automat. Contr., 14, 480-483.
• [7] t’Mannetje, J.J. (1973). Transfer-Function Identification using a Complex Curve-Fitting Technique. J. Mech. Eng. Sci., 15, 339-345.
• [8] Stahl, H. (1984). Transfer Function Synthesis using Frequency Response Data. Int. J. Control, 39, 541-550.
• [9] Whitfield, A.H. (1987). Asymptotic Behavior of Transfer Function Synthesis Methods. Int. J. Control, 1083-1092.
• [10] Glob, G.H., Van Loan, C.F. (1980). An Analysis of the Total Least Squares Problem. SIAM J. Numer. Anal., 17, 883-893.
• [11] Pintelon, R., Schoukens, J. (2001). System Identification: A Frequency Domain Approach. IEEE Press, Piscataway, New York.
• [12] JCGM 101 (2008). Evaluation of Measurement Data - Supplement 1 to the Guide to the Expression of Uncertainty in Measurement - Propagation of Distributions using a Monte Carlo Method.
• [13] Soysal, A.O., Semlyen, A. (1993). Practical Transfer Function Estimation and its Application to Wide Frequency Range Representation of Transformers. IEEE T. Power Deliver., 8, 1627-1637.
• [14] Janiszowski, K.B. (2014). Approximation of a Linear Dynamic Process Model using the Frequency Approach and a Nonquadratic Measure of the Model Error. Int. J. Appl. Math. Comput. Sci., 24, 99-109.
• [15] Link, A., Tabner, A., Wabinski, W., Bruns, T., Elster, C. (2007). Modelling Accelerometers for Transient Signals using Calibration Measurement upon Sinusoidal Excitation. Measurement, 40, 928-935.
• [16] Tomczyk, K., Sieja, M. (2006). Acceleration transducers calibration based on maximum dynamic error. Technical Trans., 3E, 37-49.
• [17] Layer, E., Tomczyk, K. (2010). Measurements. Modelling and Simulation of Dynamic Systems. Springer- Verlag, Berlin Heidelberg.
• [18] Tomczyk, K., Layer, E. (2015). Accelerometer Errors in Measurements of Dynamic Signals. Measurement, 60, 292-298.
• [19] JCGM 100 (2008). Evaluation of measurement data - Guide to the Expression of Uncertainty in Measurement.
• [20] Magain, P., Courbin, F., Sohy, S. (1988). Deconvolution with Correct Sampling. The Astrophys. J., 494, 472-477.
• [21] Morawski, R., Szczecinski, L., Barwicz, A. (1995). Deconvolution algorithms for instrumental applications: A comparative study. Journal of Chemometr., 9(1), 3-20.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).