Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms
Low-coherent fiber-optic sensors combined with neural network algorithms were designed to carry out a load-sensitizing spherical bearing. Four sensing fibers were wound around the outside of the pot support of the spherical bearing uniformly deployed from upper to bottom. The upper three were config...
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Online Access: | https://www.mdpi.com/1424-8220/21/1/37 |
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doaj-3d442ded156745f9ba2961a9fef3c9af2020-12-24T00:06:03ZengMDPI AGSensors1424-82202021-12-0121373710.3390/s21010037Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network AlgorithmsJingjing Guo0Tiesuo Geng1Huaizhi Yan2Lize Du3Zhe Zhang4Changsen Sun5School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, ChinaBridge and Tunnel Research and Development Center, Dalian University of Technology, Dalian 116024, ChinaSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, ChinaSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, ChinaBridge and Tunnel Research and Development Center, Dalian University of Technology, Dalian 116024, ChinaSchool of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian 116024, ChinaLow-coherent fiber-optic sensors combined with neural network algorithms were designed to carry out a load-sensitizing spherical bearing. Four sensing fibers were wound around the outside of the pot support of the spherical bearing uniformly deployed from upper to bottom. The upper three were configured in a distributed way to respond to the applied load as a function of the three strain sensors. The bottom one was employed as a temperature compensation sensor. A loading experiment was implemented to test the performance of the designed system. The results showed that there was a hysteresis in all the three sensors between loading and unloading process. The neural network algorithm is proposed to set up a function of the three sensors, treated as a set of input vectors to establish the input-output relationship between the applied loads and the constructed input vectors, in order to overcome the hysteresis existing in each sensor. An accuracy of 6% for load sensing was approached after temperature compensation.https://www.mdpi.com/1424-8220/21/1/37bridge bearingfiber-optic sensorload-sensitizingneutral network algorithm |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jingjing Guo Tiesuo Geng Huaizhi Yan Lize Du Zhe Zhang Changsen Sun |
spellingShingle |
Jingjing Guo Tiesuo Geng Huaizhi Yan Lize Du Zhe Zhang Changsen Sun Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms Sensors bridge bearing fiber-optic sensor load-sensitizing neutral network algorithm |
author_facet |
Jingjing Guo Tiesuo Geng Huaizhi Yan Lize Du Zhe Zhang Changsen Sun |
author_sort |
Jingjing Guo |
title |
Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms |
title_short |
Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms |
title_full |
Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms |
title_fullStr |
Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms |
title_full_unstemmed |
Implementation of A Load Sensitizing Bridge Spherical Bearing Based on Low-Coherent Fiber-Optic Sensors Combined with Neural Network Algorithms |
title_sort |
implementation of a load sensitizing bridge spherical bearing based on low-coherent fiber-optic sensors combined with neural network algorithms |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-12-01 |
description |
Low-coherent fiber-optic sensors combined with neural network algorithms were designed to carry out a load-sensitizing spherical bearing. Four sensing fibers were wound around the outside of the pot support of the spherical bearing uniformly deployed from upper to bottom. The upper three were configured in a distributed way to respond to the applied load as a function of the three strain sensors. The bottom one was employed as a temperature compensation sensor. A loading experiment was implemented to test the performance of the designed system. The results showed that there was a hysteresis in all the three sensors between loading and unloading process. The neural network algorithm is proposed to set up a function of the three sensors, treated as a set of input vectors to establish the input-output relationship between the applied loads and the constructed input vectors, in order to overcome the hysteresis existing in each sensor. An accuracy of 6% for load sensing was approached after temperature compensation. |
topic |
bridge bearing fiber-optic sensor load-sensitizing neutral network algorithm |
url |
https://www.mdpi.com/1424-8220/21/1/37 |
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