Robust Optimal Positioning of Strain Gages on Blades
Author:
Mignolet Marc P.1, Choi Byeong-Keun2
Affiliation:
1. Department of Mechanical and Aerospace Engineering, Arizona State University, Tempe, AZ 85287-6106 2. Gyeongsang National University, School of Mechanical and Aerospace Engineering, The Institute of Marine Industry, Tongyoung, Kyongnam 650-160, Korea
Abstract
This paper focuses on the formulation and validation of an automatic strategy for the selection of the locations and directions of strain gages to capture at best the modal response of a blade in a series of modes. These locations and directions are selected to render the strain measurements as robust as possible with respect to random mispositioning of the gages and gage failures. The approach relies on the evaluation of the signal-to-noise ratios of the gage measurements from finite element strain data and includes the effects of gage size. A genetic algorithm is used to find the strain gage locations-directions that lead to the largest possible value of the smallest modal strain signal-to-noise ratio, in the absence of gage failure, or of its expected value when gage failure is possible. A fan blade is used to exemplify the applicability of the proposed methodology and to demonstrate the effects of the essential parameters of the problem, i.e., the mispositioning level, the probability of gage failure, and the number of gages.
Publisher
ASME International
Subject
Mechanical Engineering
Reference7 articles.
1. 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. 2. 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. 3. 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. 4. Gen, M., and Cheng, R., 1997, Genetic Algorithms & Engineering Design, Wiley-Interscience, New York, NY 5. Goldberg, D. E., 1989, Genetic Algorithms in Search, Optimization & Machine Learning, Addision Wesley, New York, NY.
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Dynamic Strain Reconstruction of Rotating Blades Based on Tip Timing and Response Transmissibility;Journal of Engineering for Gas Turbines and Power;2022-05-20 2. Experimental investigation on forced response of mistuned bladed disc rotor in an aero-engine;Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering;2015-04-15 3. Load Recovery in Components Based on Dynamic Strain Measurements;Journal of Vibration and Acoustics;2013-06-18 4. Blade Stress Estimation During Multiple Vibratory Modes;54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference;2013-04-05 5. Vibration measurement of a cantilever beam using root embedded piezoceramic sensor;Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science;2008-02-01
|
|