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PARAFAC Decomposition for Ultrasonic Wave Sensing of Fiber Bragg Grating Sensors: Procedure and Evaluation.

Zheng R, Nakano K, Ohashi R, Okabe Y, Shimazaki M, Nakamura H, Wu Q - Sensors (Basel) (2015)

Bottom Line: Ultrasonic wave-sensing technology has been applied for the health monitoring of composite structures, using normal fiber Bragg grating (FBG) sensors with a high-speed wavelength interrogation system of arrayed waveguide grating (AWG) filters; however, researchers are required to average thousands of repeated measurements to distinguish significant signals.To resolve this bottleneck problem, this study established a signal-processing strategy that improves the signal-to-noise ratio for the one-time measured signal of ultrasonic waves, by application of parallel factor analysis (PARAFAC) technology that produces unique multiway decomposition without additional orthogonal or independent constraints.An experimental study has revealed that the final result is consistent with the conventional 1024-data averaging signal, and relative error evaluation has indicated that the signal-to-noise ratio of ultrasonic waves can be significantly improved.

View Article: PubMed Central - PubMed

Affiliation: Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan. topzrc@iis.u-tokyo.ac.jp.

ABSTRACT
Ultrasonic wave-sensing technology has been applied for the health monitoring of composite structures, using normal fiber Bragg grating (FBG) sensors with a high-speed wavelength interrogation system of arrayed waveguide grating (AWG) filters; however, researchers are required to average thousands of repeated measurements to distinguish significant signals. To resolve this bottleneck problem, this study established a signal-processing strategy that improves the signal-to-noise ratio for the one-time measured signal of ultrasonic waves, by application of parallel factor analysis (PARAFAC) technology that produces unique multiway decomposition without additional orthogonal or independent constraints. Through bandpass processing of the AWG filter and complex wavelet transforms, ultrasonic wave signals are preprocessed as time, phase, and frequency profiles, and then decomposed into a series of conceptual three-way atoms by PARAFAC. While an ultrasonic wave results in a Bragg wavelength shift, antiphase fluctuations can be observed at two adjacent AWG ports. Thereby, concentrating on antiphase features among the three-way atoms, a fitting atom can be chosen and then restored to three-way profiles as a final result. An experimental study has revealed that the final result is consistent with the conventional 1024-data averaging signal, and relative error evaluation has indicated that the signal-to-noise ratio of ultrasonic waves can be significantly improved.

No MeSH data available.


Related in: MedlinePlus

Wavelet transforms for the analysis period of 75 µs at AWG ports A1, A2, B1, and B2: (a) one-time measured signal (left); (b) one-time restored signal (middle); (c) 1024-time averaged signal (right).
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sensors-15-16388-f018: Wavelet transforms for the analysis period of 75 µs at AWG ports A1, A2, B1, and B2: (a) one-time measured signal (left); (b) one-time restored signal (middle); (c) 1024-time averaged signal (right).

Mentions: For the different analysis periods, the results of the relative measuring error Errm and relative analysis error Errp are presented in Figure 17, when the maximum input amplitude is 58 µε and the input frequency is 200 kHz. Furthermore, for an analysis period of 75 µs, the frequency distribution of the wavelet transforms at AWG ports A1, A2, B1, and B2 are presented in Figure 18, for the one-time measured signal (left), one-time restored signal (middle), and 1024-time averaged signal (right). Likewise, for the analysis periods of 105, 135, and 165 µs, the results of the wavelet transforms are presented in Figure 19, Figure 20 and Figure 21, respectively.


PARAFAC Decomposition for Ultrasonic Wave Sensing of Fiber Bragg Grating Sensors: Procedure and Evaluation.

Zheng R, Nakano K, Ohashi R, Okabe Y, Shimazaki M, Nakamura H, Wu Q - Sensors (Basel) (2015)

Wavelet transforms for the analysis period of 75 µs at AWG ports A1, A2, B1, and B2: (a) one-time measured signal (left); (b) one-time restored signal (middle); (c) 1024-time averaged signal (right).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4541884&req=5

sensors-15-16388-f018: Wavelet transforms for the analysis period of 75 µs at AWG ports A1, A2, B1, and B2: (a) one-time measured signal (left); (b) one-time restored signal (middle); (c) 1024-time averaged signal (right).
Mentions: For the different analysis periods, the results of the relative measuring error Errm and relative analysis error Errp are presented in Figure 17, when the maximum input amplitude is 58 µε and the input frequency is 200 kHz. Furthermore, for an analysis period of 75 µs, the frequency distribution of the wavelet transforms at AWG ports A1, A2, B1, and B2 are presented in Figure 18, for the one-time measured signal (left), one-time restored signal (middle), and 1024-time averaged signal (right). Likewise, for the analysis periods of 105, 135, and 165 µs, the results of the wavelet transforms are presented in Figure 19, Figure 20 and Figure 21, respectively.

Bottom Line: Ultrasonic wave-sensing technology has been applied for the health monitoring of composite structures, using normal fiber Bragg grating (FBG) sensors with a high-speed wavelength interrogation system of arrayed waveguide grating (AWG) filters; however, researchers are required to average thousands of repeated measurements to distinguish significant signals.To resolve this bottleneck problem, this study established a signal-processing strategy that improves the signal-to-noise ratio for the one-time measured signal of ultrasonic waves, by application of parallel factor analysis (PARAFAC) technology that produces unique multiway decomposition without additional orthogonal or independent constraints.An experimental study has revealed that the final result is consistent with the conventional 1024-data averaging signal, and relative error evaluation has indicated that the signal-to-noise ratio of ultrasonic waves can be significantly improved.

View Article: PubMed Central - PubMed

Affiliation: Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan. topzrc@iis.u-tokyo.ac.jp.

ABSTRACT
Ultrasonic wave-sensing technology has been applied for the health monitoring of composite structures, using normal fiber Bragg grating (FBG) sensors with a high-speed wavelength interrogation system of arrayed waveguide grating (AWG) filters; however, researchers are required to average thousands of repeated measurements to distinguish significant signals. To resolve this bottleneck problem, this study established a signal-processing strategy that improves the signal-to-noise ratio for the one-time measured signal of ultrasonic waves, by application of parallel factor analysis (PARAFAC) technology that produces unique multiway decomposition without additional orthogonal or independent constraints. Through bandpass processing of the AWG filter and complex wavelet transforms, ultrasonic wave signals are preprocessed as time, phase, and frequency profiles, and then decomposed into a series of conceptual three-way atoms by PARAFAC. While an ultrasonic wave results in a Bragg wavelength shift, antiphase fluctuations can be observed at two adjacent AWG ports. Thereby, concentrating on antiphase features among the three-way atoms, a fitting atom can be chosen and then restored to three-way profiles as a final result. An experimental study has revealed that the final result is consistent with the conventional 1024-data averaging signal, and relative error evaluation has indicated that the signal-to-noise ratio of ultrasonic waves can be significantly improved.

No MeSH data available.


Related in: MedlinePlus