Extraction and processing of real time strain of embedded FBG sensors using a fixed filter FBG circuit and an artificial neural network
•Method to interrogate FBG sensors using the fixed wavelength FBG filters.•FBG filter system to capture data from an embedded FBG sensor in the time domain.•FBG data processing using area integration accounting for the distorted spectra.•Estimation of strain using distorted FBG sensor response spect...
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| Published in: | Measurement : journal of the International Measurement Confederation Vol. 46; no. 10; pp. 4045 - 4051 |
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01-12-2013
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| Abstract | •Method to interrogate FBG sensors using the fixed wavelength FBG filters.•FBG filter system to capture data from an embedded FBG sensor in the time domain.•FBG data processing using area integration accounting for the distorted spectra.•Estimation of strain using distorted FBG sensor response spectra using ANN.•It was found that the error levels were less than 0.3% in predictions using ANN.
Fibre Bragg Grating (FBG) sensors have been used in the development of structural health monitoring (SHM) and damage detection systems for advanced composite structures over several decades. Unfortunately, to date only a handful of appropriate configurations and algorithm sare available for using in SHM systems have been developed. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in predictions. The developed SMH system using this technology has been submitted to US patent office and will be available for use of aerospace applications in due course. |
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| AbstractList | Fibre Bragg Grating (FBG) sensors have been used in the development of structural health monitoring (SHM) and damage detection systems for advanced composite structures over several decades. Unfortunately, to date only a handful of appropriate configurations and algorithm sare available for using in SHM systems have been developed. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in predictions. The developed SMH system using this technology has been submitted to US patent office and will be available for use of aerospace applications in due course. •Method to interrogate FBG sensors using the fixed wavelength FBG filters.•FBG filter system to capture data from an embedded FBG sensor in the time domain.•FBG data processing using area integration accounting for the distorted spectra.•Estimation of strain using distorted FBG sensor response spectra using ANN.•It was found that the error levels were less than 0.3% in predictions using ANN. Fibre Bragg Grating (FBG) sensors have been used in the development of structural health monitoring (SHM) and damage detection systems for advanced composite structures over several decades. Unfortunately, to date only a handful of appropriate configurations and algorithm sare available for using in SHM systems have been developed. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in predictions. The developed SMH system using this technology has been submitted to US patent office and will be available for use of aerospace applications in due course. |
| Author | Epaarachchi, Jayantha Kahandawa, Gayan C. Lau, K.T. Canning, John Wang, Hao |
| Author_xml | – sequence: 1 givenname: Gayan C. surname: Kahandawa fullname: Kahandawa, Gayan C. email: gayan@usq.edu.au organization: Centre of Excellence in Engineered Fibre Composites, University of Southern Queensland, Toowoomba QLD 4350, Australia – sequence: 2 givenname: Jayantha surname: Epaarachchi fullname: Epaarachchi, Jayantha organization: Centre of Excellence in Engineered Fibre Composites, University of Southern Queensland, Toowoomba QLD 4350, Australia – sequence: 3 givenname: Hao surname: Wang fullname: Wang, Hao organization: Centre of Excellence in Engineered Fibre Composites, University of Southern Queensland, Toowoomba QLD 4350, Australia – sequence: 4 givenname: John surname: Canning fullname: Canning, John organization: Interdisciplinary Photonic Laboratories, School of Chemistry, University of Sydney, Sydney NSW 2000, Australia – sequence: 5 givenname: K.T. surname: Lau fullname: Lau, K.T. organization: The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong |
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| Cites_doi | 10.1016/0266-3538(90)90077-I 10.1016/0266-3538(95)00132-8 10.1016/S0266-3538(96)00142-X 10.1177/1045389X06074085 10.1016/j.sna.2007.02.012 10.1016/S0266-3538(99)00038-X 10.1177/002199838702100904 10.1088/0957-0233/17/5/S17 10.1016/j.sna.2007.05.009 10.1016/j.probengmech.2005.07.002 10.1109/JSEN.2008.926523 10.1016/j.compstruct.2009.11.023 10.1016/j.optlaseng.2004.02.003 10.1016/j.compositesa.2007.07.009 10.1016/S1359-835X(02)00036-2 10.1117/12.786945 10.1088/0964-1726/11/6/314 10.1016/S0266-3538(01)00204-4 10.1016/j.compscitech.2004.05.010 |
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| Snippet | •Method to interrogate FBG sensors using the fixed wavelength FBG filters.•FBG filter system to capture data from an embedded FBG sensor in the time... Fibre Bragg Grating (FBG) sensors have been used in the development of structural health monitoring (SHM) and damage detection systems for advanced composite... |
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| StartPage | 4045 |
| SubjectTerms | Algorithms Artificial neural networks Composite structures Extraction FBG sensors Health monitoring (engineering) Offices Real time Sensors Strain Structural health monitoring |
| Title | Extraction and processing of real time strain of embedded FBG sensors using a fixed filter FBG circuit and an artificial neural network |
| URI | https://dx.doi.org/10.1016/j.measurement.2013.07.029 https://search.proquest.com/docview/1530990524 |
| Volume | 46 |
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