Abstract——Fluid, both gas and liquid, is a widely used
substance which can be used in pneumatic and hydraulic
system. However, the pneumatic system with compressed air
system integrated has a flaw that leakage air during power
transmission cost a lot of loss both resources and performance.
Leak detection is one of the main solution to plug the flaw. In
this research, we use acoustic signal to detect the leakage by
using it as an input for model. Artificial Neural Network (ANN)
is used in our model to achieve deep learning property via
Tensorflow. Acoustic signal is recorded in different situation
and is used as a model input. So, our model can be trained with
leak data and predict the leakage in pneumatic system. We
evaluate model using test data and shows the leakage
prediction in probability distribution.
Index Terms—Artificial neural network, leak detection,
Tensorflow.
The authors are with King Mongkut’s University of Technology North
Bangkok/Production Engineering, Bangkok, Thailand (e-mail:
naparat.pai@gmail.com, ramil.k@eng.kmutnb.ac.th).
Cite: Naparat Pairin and Ramil Kesvarakul, "Leak Detection on Air reservoir via Acoustic Models with TensorFlow Based," International Journal of Machine Learning and Computing vol. 10, no. 4, pp. 594-598, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).