Submersible Pump Vortex Detection Using Image Processing Technique and Neuro-Fuzzy

Yıl 2020, Cilt: 8 Sayı: 4, 163 - 172, 31.12.2020

Akif Durdu , Nuri Orhan , Seyit Alperen Celtek , Muhammet Fatih Aslan , Kadir Sabancı

https://doi.org/10.18100/ijamec.804049

Öz

The vortex means the mass of air or water that spins around very fast that often faced in the agriculture irrigation systems used the pump. The undesired effects like loss of hydraulic performance, erosion, vibration and noise may occur because of the vortex in pump systems. It is important to detect and prevent vortex for the economic life and efficiency of the agriculture pump. The image processing and neuro-fuzzy based novel model is proposed for the detection of a vortex in the deep well pump used in the agriculture system with this paper. The used images and data -submergence, flow rate, the diameter of the pipe, power consumption, pressure values and noise values- is acquired from an experimental pump. The proposed approach consists of three steps; Neuro-Fuzzy Learning, Image Processing and Neuro-Fuzzy Testing. In the first step, the eighty-two data have employed for the training process of the Neuro-Fuzzy. Then, the images derived from a camera placed near the experimental pump are used to detect vortex in the image processing step. Finally, the relevant data to vortex cases have employed for the testing process of the Neuro-Fuzzy. The result of this study demonstrates that image processing and neuro-fuzzy based design can be successfully used to detect vortex formation. This paper has provided novel contributions in the vortex detection issue such as find out vortex cases by using image processing and Neuro-Fuzzy. The image processing method has shed light on the studies to be done in the classification of vortexes and the measurement of their strength.

Anahtar Kelimeler

Image Processing Technique, Adaptive Neural Fuzzy Network, Vortex Detection, Submergence

Destekleyen Kurum

TUBITAK

Proje Numarası

213O140

Teşekkür

This study was supported by The Scientific and Technical Research Council of Turkey (TUBITAK, Project No:213O140). We would like to thank Prof. Dr. Sedat ÇALIŞIR who contributed to this work.

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