International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 13, No. 1, 8 Feb. 2021
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Fluid Temperature Detection Based on its Sound with a Deep Learning Approach
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Author(s)
Arshia Foroozan Yazdani
1,*
Ali Bozorgi Mehr
1
Iman Showkatyan
1
Amin Hashemi
1
Mohsen Kakavand
2
Index Terms
Fluid temperature, data spectrogram, V.G.G.16 (Visual Geometry Group), C.N.N (Convolutional Neural Network)., the environmental sounds, sound classification, physical-computational research, Deep learning
Abstract
The present study, the main idea of which was based on one of the questions of I.P.T.2018 competition, aimed to develop a high-precision relationship between the fluid temperature and the sound produced when colliding with different surfaces, by creating a data collection tool. In fact, this paper was provided based on a traditional phenomenological project using the well-known deep neural networks, in order to achieve an acceptable accuracy in this project. In order to improve the quality of the paper, the data were analyzed in two ways:
I. Using the images of data spectrogram and the known V.G.G.16 network.
II. Applying the data audio signal and a convolutional neural network (C.N.N.).
Finally, both methods have obtained an acceptable precision above 85%.
Cite This Paper
Arshia Foroozan Yazdani, Ali Bozorgi Mehr, Iman Showkatyan, Amin Hashemi, Mohsen Kakavand, " Fluid Temperature Detection Based on its Sound with a Deep Learning Approach", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.13, No.1, pp. 28-39, 2021. DOI: 10.5815/ijigsp.2021.01.03
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