BCG signal processing based on advanced LMS filter for optical fiber monitor

2020 ◽  
Author(s):  
Yifan Liu ◽  
Wei Xu ◽  
Changyuan Yu
Keyword(s):  
Signal Processing ◽  
Optical Fiber ◽  
Lms Filter

Signal Processing in Optical Fiber Sensor Networks

2018 ◽  
Author(s):  
Lianshan Yan ◽  
Zonglei Li ◽  
Haijun He ◽  
Yin Zhou ◽  
Xinpu Zhang
Keyword(s):  
Signal Processing ◽  
Sensor Networks ◽  
Optical Fiber ◽  
Optical Fiber Sensor ◽  
Fiber Sensor

Microbend optical fiber tapped delay line for gigahertz signal processing

1982 ◽  
Vol 41 (2) ◽  
pp. 139-141 ◽  
Author(s):  
K. P. Jackson ◽  
J. E. Bowers ◽  
S. A. Newton ◽  
C. C. Cutler
Keyword(s):  
Signal Processing ◽  
Optical Fiber ◽  
Delay Line

Optical-Fiber Sensors for the Detection of Acoustic Emission

MRS Bulletin ◽  
2002 ◽  
Vol 27 (5) ◽  
pp. 396-399 ◽  
Author(s):  
William B. Spillman ◽  
Richard O. Claus
Keyword(s):  
Signal Processing ◽  
Acoustic Emission ◽  
Optical Fiber ◽  
Material Properties ◽  
High Speed ◽  
Optical Fiber Sensors ◽  
Piezoelectric Transducers ◽  
Fiber Sensors ◽  
Critical Materials ◽  
Signal Processing Methods

AbstractAcoustic emission (AE) is used as a means to anticipate the mechanical failure of critical materials and structures by detecting the release of energy caused by material rearrangement at the microlevel. Optical-fiber sensors have potential advantages over conventional tuned piezoelectric transducers and signal-processing methods for the detection of such types of ultrasonic acoustic wave events. A number of fiber Bragg grating techniques are presented, which in particular offer the potential to provide the high-speed signal processing and ability to multiplex numbers of AE sensors necessary to detect, quantify, and locate AE sources and thereby determine material properties and damage.

Signal Processing of Fluorescent Optical Fiber Temperature Measurement Based on Hilbert-Huang Transform

2014 ◽  
Vol 1052 ◽  
pp. 447-453
Author(s):  
Ya Juan Yang ◽  
Zhi Yong Wang ◽  
Xiao Ping Yang ◽  
Yong Xin Shao
Keyword(s):  
Signal Processing ◽  
Optical Fiber ◽  
Temperature Measurement ◽  
Electromagnetic Interference ◽  
Signal To Noise Ratio ◽  
Extreme Environment ◽  
Intrinsic Mode Functions ◽  
Hilbert Huang Transform ◽  
Noise Characteristics ◽  
Novel Approach

The technology of fluorescent optical fiber temperature measurement has been used in many fields to accurately measure the variations of temperature, especially in some extreme environment, such as strong electromagnetic interference under, high voltage conditions. Wavelet analysis is the most frequent method used for signal processing in this technology. This method has excellent local characteristics and its precise of processing is high, whereas its result relies heavily on the selection of the wavelet basis, and has certain limitation. In this paper, a novel approach for fluorescent signal processing based on Hilbert-Huang transform is presented. A given signal is decomposed into a collection of intrinsic mode functions (IMF) by empirical mode decomposition, then Hilbert spectral analysis is performed for each of the IMF. According to the difference of signal and noise characteristics, HHT can generate adaptive modal functions and remove the noise from signal effectively, so that the signal to noise ratio can be improved. The result of experiment shows that HHT features convenient usage, fast processing and high resolution in time and frequency domains.

Application of Plastic Optical Fiber Fatigue Sensor in Real-Time Monitoring of Fatigue Cracks in Steel Structures

2020 ◽  
Vol 15 (7) ◽  
pp. 864-869
Author(s):  
Ying Liu
Keyword(s):  
Signal Processing ◽  
Optical Fiber ◽  
Real Time ◽  
Fatigue Cracks ◽  
Steel Structures ◽  
Luminous Flux ◽  
Plastic Optical Fiber ◽  
Signal Processing Algorithm ◽  
New Type ◽  
Fatigue Sensor

Plastic optical fiber (POF) is a new type of sensing material. Compared with traditional quartz optical fiber, it has the advantages of good tenacity, low cost, easy processing, and high sensitivity. A new type of POF-Fatigue sensor (nPOF-Fs) is designed by using POF, which is based on the changes the luminous flux. The change in the relative displacement of the two ends of the fiber is obtained through the change in the luminous flux in the POF, which is later converted into an electrical signal by the photoelectric conversion device. By collecting and analyzing the signals, accurate measurement of the dynamic response of the workpiece is achieved. Combined with the signal processing algorithm that can detect and monitor the crack expansion of steel structures under cyclic loading based on the RMS envelope and Hilbert transform filters, the fatigue crack can be monitored in real-time. The results obtained by nPOF-Fs are fundamentally coincide with the results acquired by the COD sensor. In view of the higher cost of monitoring with the COD sensor, the use of a POF sensor combined with a signal processing algorithm in monitoring the occurrence and expansion of fatigue cracks has great potential in the field of structural monitoring.

Optical Fiber Sensor Signal Processing by Use of Optoelectronic Neural System

1997 ◽  
Author(s):  
A. W. Domański ◽  
M. Karpierz ◽  
M. Sierakowski ◽  
T. R. Woliński
Keyword(s):  
Signal Processing ◽  
Optical Fiber ◽  
Optical Fiber Sensor ◽  
Neural System ◽  
Fiber Sensor ◽  
Sensor Signal
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