A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural Network
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School of Aerospace Engineering, Beijing Institute of Technology, Zhongguancun South Street 5, Beijing 100081, China
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Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, Beijing 100081, China
3
Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration, Ministry of Industry and Information Technology, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Sensors 2017, 17(12), 2888; https://doi.org/10.3390/s17122888
Received: 14 October 2017
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Revised: 4 December 2017
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Accepted: 8 December 2017
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Published: 12 December 2017
(This article belongs to the Section Intelligent Sensors)
Measurement of dynamic responses plays an important role in structural health monitoring, damage detection and other fields of research. However, in aerospace engineering, the physical sensors are limited in the operational conditions of spacecraft, due to the severe environment in outer space. This paper proposes a virtual sensor model with partial vibration measurements using a convolutional neural network. The transmissibility function is employed as prior knowledge. A four-layer neural network with two convolutional layers, one fully connected layer, and an output layer is proposed as the predicting model. Numerical examples of two different structural dynamic systems demonstrate the performance of the proposed approach. The excellence of the novel technique is further indicated using a simply supported beam experiment comparing to a modal-model-based virtual sensor, which uses modal parameters, such as mode shapes, for estimating the responses of the faulty sensors. The results show that the presented data-driven response virtual sensor technique can predict structural response with high accuracy.
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Keywords:
virtual sensor; convolutional neural network; partial vibration measurements; response transmissibility
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MDPI and ACS Style
Sun, S.-B.; He, Y.-Y.; Zhou, S.-D.; Yue, Z.-J. A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural Network. Sensors 2017, 17, 2888. https://doi.org/10.3390/s17122888
AMA Style
Sun S-B, He Y-Y, Zhou S-D, Yue Z-J. A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural Network. Sensors. 2017; 17(12):2888. https://doi.org/10.3390/s17122888
Chicago/Turabian StyleSun, Shan-Bin, Yuan-Yuan He, Si-Da Zhou, and Zhen-Jiang Yue. 2017. "A Data-Driven Response Virtual Sensor Technique with Partial Vibration Measurements Using Convolutional Neural Network" Sensors 17, no. 12: 2888. https://doi.org/10.3390/s17122888
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