Efficient temperature compensation strategies for guided wave structural health monitoring |
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| Authors: | Anthony J. Croxford Jochen Moll Paul D. Wilcox Jennifer E. Michaels |
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| Affiliation: | 1. University of Bristol, Mechanical Engineering, Queens Building, University Walk, Bristol, Avon BS8 1TR, United Kingdom;2. University of Siegen, 9-11 Paul Bonatz Str., Siegen, S7076, Germany;3. Van Leer Electrical Engineering Building, 777 Atlantic Drive NW, Atlanta, GA, 30332-0250, USA;1. Air Force Institute of Technology, 6 Ks. Boleslawa Street, 01-494 Warsaw, Poland;2. Institute of Fundamentals of Machinery Design, Silesian University of Technology, 18A Konarskiego Street, 44-100 Gliwice, Poland;1. State Key Lab. of Power System, Dept. of Electrical Engineering, Tsinghua University, Beijing 100084, China;2. School of Engineering and Computing Sciences, Durham University, DH1 3LE Durham, United Kingdom;1. Research Center of Structural Health Monitoring and Prognosis, State Key Lab of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China;2. Department of Mechanical Engineering, Hong Kong Polytechnic University, Kowloon, Hong Kong;1. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109-2125, USA;2. Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin, 150090, China;3. Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin, 150090, China;1. University of Michigan-Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University, Shanghai 200240, China;2. Department of Mechanical Engineering, University of South Carolina, 29208, USA |
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| Abstract: | The application of temperature compensation strategies is important when using a guided wave structural health monitoring system. It has been shown by different authors that the influence of changing environmental and operational conditions, especially temperature, limits performance. This paper quantitatively describes two different methods to compensate for the temperature effect, namely optimal baseline selection (OBS) and baseline signal stretch (BSS). The effect of temperature separation between baseline time-traces in OBS and the parameters used in the BSS method are investigated. A combined strategy that uses both OBS and BSS is considered. Theoretical results are compared, using data from two independent long-term experiments, which use predominantly A0 mode and S0 mode data respectively. These confirm that the performance of OBS and BSS quantitatively agrees with predictions and also demonstrate that the combination of OBS and BSS is a robust practical solution to temperature compensation. |
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