Peak Detection Algorithm for Fiber Bragg grating Sensors.

Martelli, Cícero; Mezzadri, Felipe; Janzen, Frederic Conrad

doi:10.1364/laop.2012.lm2a.8

Cited by 1 publication

(4 citation statements)

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“…The peak ambiguity is greatly eliminated by the filtering process, as shown in Figure 9 b. It should be noted that the received curve is not parabolic nor Gaussian as many studies have pre-assumed [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ]. We believe this special curve shape comes from the slow response of the power detector and can further vary while different receivers are applied.…”

Section: Methodsmentioning

confidence: 99%

“…Two points should be noted. First, a second order polynomial approximation is directly applied without considering the theoretical shape of the FBG spectrum, as was done in [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ]. Hence, the proposed scheme can work under more general conditions.…”

Section: Theory and Principlesmentioning

confidence: 99%

“…The increasing number of calculation data points results in higher system complexity and energy consumption. On the other hand, conventional curve fitting methods also take extra time to capture the whole spectrum data, and additional windowing operations are necessary to select the spectrum portions to be fitted [ 16 , 18 ]. It can also be noticed that similar N-point peak estimator processing is studied in [ 16 , 17 ], merely as a simplified curve fitting alternative.…”

Section: Theory and Principlesmentioning

confidence: 99%

“…Additionally, windowing operations and knowledge of multiple spectrum data points are also required, which increase the memory and time expense. It is also worth mentioning that the windowing method, based on the maximum value selection used in [ 16 ], neglects the potential side lobe effects from the FBG spectra, as illustrated in [ 18 ]. Through our proposed scheme, within each continuously connected data point set above the threshold level, it is guaranteed that only one peak will be estimated.…”

Section: Theory and Principlesmentioning

confidence: 99%

See 3 more Smart Citations

Accurate Peak Detection for Optical Sensing with Reduced Sampling Rate and Calculation Complexity

Sung

Chen

Liaw

et al. 2021

Sensors

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Fiber Bragg gratings (FBGs) are widely applied in optical sensing systems due to their advantages including being simple to use, high sensitivity, and having great potential for integration into optical communication systems. A common method used for FBG sensing systems is wavelength interrogation. The performance of interrogation based sensing systems is significantly determined by the accuracy of the wavelength peak detection processing. Direct maximum value readout (DMVR) is the simplest peak detection method. However, the detection accuracy of DMVR is sensitive to noise and the sampling resolution. Many modified peak detection methods, such as filtering and curve fitting schemes, have been studied in recent decades. Though these methods are less sensitive to noise and have better sensing accuracy at lower sampling resolutions, they also confer increased processing complexity. As massive sensors may be deployed for applications such as the Internet of things (IoT) and artificial intelligence (AI), lower levels of processing complexity are required. In this paper, an efficient scheme applying a three-point peak detection estimator is proposed and studied, which shows a performance that is close to the curve fitting methods along with reduced complexity. A proof-of-concept experiment for temperature sensing is performed. 34% accuracy improvement compared to the DMVR is demonstrated.

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