Polynomial Identification of Strain Gauge Thermal Output...

  • Igor Vujović
  • Ivica Kuzmanić
  • Zlatan Kulenović
Keywords: strain gauges, deformation, neural network, identification, thermal output

Abstract

Strain gauges are used in different areas, especially in thedesign and development of new technical constructions andmode/testing. Also, strain gauges are inc01porated in the functionalpart of many instruments and devices. They are mostlyused as sensors in transducers designed to measure such mechanicalquantities as forces, moments, pressures, accelerations,etc. They have an important role in shipbuilding and marinetransport in general. In this paper we have suggested andshown an approach to the identification of strain gauge thermaloutput curve on the example of a product available at themarket. Neural network simulated in MatLab has been applied.The neural network has been adapted to simulate a realsystem with 1 o-9 order of magnitude error_ As it is well known,strain gauges measure deformations of 1 o-o order of magnitude.It is obvious that the network eJTOr cannot influence the measurementresults because of its being smaller by three orders ofmagnitude.

References

(1] *, Strain Gauge Measurement -A Tutorial, National

Instruments, Application Note 078, 1998.

(2] K. Schulze, Experimentelle MejJtechnik in Maschinen

und Stahlbau, VE Verlang Technik, Berlin, 1988.

(3] I. Alfirevic, Nauka o cvrstoCi, Tehnicka knjiga, Zagreb,

(4] J. W. Dally, Experimental stress analysis, McGrow-Hill,

Singapure, 1987.

*,Strain Gauge Transducers,

http://www.measurementsgroup.com

(6] *,PCB Technical Support- Introduction to Piezoelectric

Pressure Sensors, http://www.pcb.com/tech_press.html

*,PCB Technical Support- Introduction to Piezoelectric

Force Sensors, http://www.pcb.com/tech_press.html

*, Strain Gauge Thermal Output and Gauge Factor

Variation with Temperature,

http://www.measurementsgroup.com/guide/tn/tn504/

d.htm

A. P. Roskilly, E. Mesbahi, Marine System Modeling

Using Artificial Neural Networks: an Introduction to the

The01y and Practice, TranslmarE, vol. 108, part 3, pp

-201, 1996.

(10] M. Norgaard, Neural Network Based Control System

Design Toolkit, Technical report 00-E-892, Technical

University of Denmark, 2000.

(11] L. Ljung, System Identification - Theory for the User,

Prentice-Hall, 1987.

(12] M. Norgaard, Neural Network Based System Identification

Toolbox, Technical report 00-E-891, Technical University

of Denmark, 2000.

(13] MathWorks, http://www.mathworks.com

(14] I. Vujovic, S. Beros, I. Kuzma nic, Neural Networks and

Wavelets in Ships and Autopilots Modeling and Identification,

SORT A 2000, Rijeka, Croatia, pp 149-156.

How to Cite
1.
Vujović I, Kuzmanić I, Kulenović Z. Polynomial Identification of Strain Gauge Thermal Output. PROMET [Internet]. 1 [cited 2020Feb.27];14(6):277-84. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/1028
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