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TECHNICAL PAPERS

Robust Optimal Positioning of Strain Gages on Blades

[+] Author and Article Information
Marc P. Mignolet

Department of Mechanical and Aerospace Engineering, Arizona State University, Tempe, AZ 85287-6106e-mail: marc.mignolet@asu.edu

Byeong-Keun Choi

Gyeongsang National University, School of Mechanical and Aerospace Engineering, The Institute of Marine Industry, Tongyoung, Kyongnam 650-160, Koreae-mail: bg_choi@nongae.gsnu.ac.kr

J. Turbomach 125(1), 155-164 (Jan 23, 2003) (10 pages) doi:10.1115/1.1509076 History: Received March 04, 2002; Online January 23, 2003
Copyright © 2003 by ASME
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References

Yang,  M.-T., and Griffin,  J. H., 1998, “Theory and Methodology of Optimally Measuring Vibratory Strains in Closely Spaced Modes,” ASME J. Eng. Gas Turbines Power, 120(4), pp. 801–807.
Sensmeier, M. D., and Nichol, K. L., 1998, “Optimum Placement of Sensors for Vibration Measurements on Turbine Engine Blades,” Proc. 39th AIAA/ASME/ASCE/AHS/ASC Structures. Structural Dynamics, and Materials Conference, Long Beach, CA, April 20–23, AIAA Pap., 98-1849.
Sensmeier, M. D., and Nichol, K. L, 2000, “Improved Vibration Monitoring Through Optimization of Sensor Placements,” presented at the International Gas Turbine & Aeroengine Congress and Exposition, Munich, Germany, May 8–11, ASME Paper 2000-GT-612.
Gen, M., and Cheng, R., 1997, Genetic Algorithms & Engineering Design, Wiley-Interscience, New York, NY
Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization & Machine Learning, Addision Wesley, New York, NY.
Choi, B.-K., Lentz, J., Rivas-Guerra, A. J., and Mignolet, M. P., “Optimization of Intentional Mistuning Patterns for the Reduction of the Forced Response Effects of Unintentional Mistuning,” 2001-GT-0293 ASME J. Eng. Gas Turbines Power, to be published.
Petrov, E. P., Vitali, R., and Haftka, R., 2000, “Optimization of Mistuned Bladed Discs Using Gradient-Based Response Surface Approximations,” Proc. 41st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference and Exhibit, Atlanta, GA, Apr., Paper AIAA-2000-1522.

Figures

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Convergence plot of the genetic algorithm—maximum, mean, and minimum value of the smallest modal SNR as a function of the generation number
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Evolution of the modal signal-to-noise ratios as a function of the number of strain gages, standard deviation of mispositioning=0.06 in.;Pf=0
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Optimum strain gage locations for 1(Δ), 2 (+), 3 (•), and 4 (X) strain gages, standard deviation of mispositioning =0.06 in.; Pf=0
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Signal-to-noise ratios for three gages as a function of the mode number for different probabilities of failure
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Minimum modal signal-to-noise ratios corresponding to the optimum solutions for three gages as functions of the probability of gage failure. The top level corresponds to all three gages intact (SNR raised by 200 for display purposes only), the second level represents the signal-to-noise ratios when one gage has failed (SNR raised by 100), the bottom level corresponds to a single remaining gage. The mean and standard deviations are taken by groups of three only.
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Blade finite element modeling, surrounding nodes and mispositioning definition
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Strain gage and mispositioning parameters
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Graphical description of the single-point crossover technique
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Modal strain distributions for the first five modes of the fan blade; pressure side
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Evolution of the peak modal signal-to-noise ratios as a function of the standard deviation of mispositioning
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Distribution of signal-to-noise ratio on the pressure side of the blade for the third mode and for a standard deviation of mispositioning in location only of (a) 0.03 in, and (b) 0.06 in.

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