Fluid Temperature Detection Based on its Soundwith a Deep Learning Approach
Arshia Foroozan Yazdani, Ali Bozorgi Mehr, Iman Showkatyan, Amin Hashemi, Mohsen Kakavand · International Journal of Image Graphics and Signal Processing · 2021
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%.