An Intelligent Flow Measurement Technique Using Neural Network

Authors(1) :-Shilpashree Nadagoudar

A variable area type flow meter called rotameter, a measuring instrument in which position of the flow is indicated by the stainless steel float which is present in rotameter. In the process industries the readings will be required in control room hence the float is converted into voltage. For non-contact flow measurement a hall effect sensor is kept on the rotameter which acts as secondary sensor. To convert float into voltage the hall effect sensor sense the magnetic field created by the magnet kept on the float, as water flow through the rotameter the float increases and the magnet varies its position and the hall sensor sense the change in magnetic field created by the magnet. The hall voltage varies with different parameters which affect the hall voltage measurement. As temperature is very slow process and water flow is very fast process both are considered for our work as temperature varies non linearly with voltage. The hall sensor output is amplified by instrumentation amplifier and that is given as input to the ANN. For neural network 70% readings has to be used for training and 30% readings should be used for testing process. Error is given back to the input so back propagation algorithm is used. By weight adjustment ANN gives the required output with iterations so we will get the accurate output.

Authors and Affiliations

Shilpashree Nadagoudar
Department of EIE, Dayananda Sagar College of Engineering, Bengaluru, Karnataka, India

ANN, Hall Effect Sensor, Rotameter.

  1. Sinha, D. Banerjee, N. Mandal, R. Sarkar, and S. C. Bera, “Design and implementation of real- time flow measurement system using Hall probe sensor and PC Based SCADA,” IEEE Sensors J., vol. 15, no. 10, pp. 5592–5600, Oct. 2015.
  2. Sinha and N.Mandal, “Optimization of modified
  3. rotameter using Hall probe sensor with respect to liquid density and Its calibration using artificial neural network,” Int. J. Smart Sens. Intell. Syst., vol. 9, no. 4, pp. 2204–2218, Dec. 2016.
  4. Mandal, B. Kumar, R. Sarkar, and S. C. Bera, “Design of an flow transmitter using an improved inductance bridge network and rotameter as sensor,” IEEE Trans. Instrum. Meas., vol. 63, no. 12, pp. 3127–3136, Dec. 2014.
  5. Mandal, B. Kumar, G. Rajita, and B. Mondal, “A modified design of a flow transmitter using rotameter as a primary sensor and LVDT as a transducer,” in Proc. Int. Conf. Control Instrum. Energy Commun., Kolkata, India, 2014, pp. 194–198.
  6. Sunita Sinha and Nirupama Mandal,” Design and Analysis of an Intelligent Flow Transmitter Using Artificial Neural Network” IEEE Transactions, VOL. 1, NO. 3, June 2017.
  10. Chengli Zhang, Yun Zeng, “New Flow Equation for Rotameter”, National Natural Science Foundation of China (No. 51179079), 2012.
  11. Lalnunthari and H.H. Thanga, “Dependence of Hall Effect flow sensor frequency on the attached inlet and outlet pipe size”, in IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia), 2017.
  12. Zhao, L. Peng, T. Takahashi, T. Hayashi, K. Shimizu, and T. Yamamoto, “ANN based data integration for multi-path ultrasonic ?ow meter,” IEEE Sensors Journal.,vol.14, no. 2, pp. 362–370, Feb. 2014.
  13. Shi, L. Cai, Z. Liang, and Z. Hou, “Nonlinear calibration of pH Sensor based on the Back –Propagation neural network,” in Proc. Int. Conf. IEEE Netw. Sens. Control, Anya, China, 2008, pp. 1300–1304.
  14. Sinha, N. Mandal, and S. C. Bera, “Calibration of electrode polarization impedance type ?ow meter using neural network,” in Proc. IEEE Conf. Control, Instrumentation., Energy Communes., Kolkata, India, 2016, pp. 64–67.
  15. -X. Wang, Z.-Hao, and T.-H. Zhang, “Research of ultrasonic ?ow measurement and temperature compensation system based on Neural Network ,” in Proc.Int.Conf. Artif. Intell. Comput. Intell., Sanya, China, 2010, pp. 268–271.

Publication Details

Published in : Volume 4 | Issue 6 | May-June 2018
Date of Publication : 2018-05-08
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 631-633
Manuscript Number : CSEIT1846118
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shilpashree Nadagoudar, "An Intelligent Flow Measurement Technique Using Neural Network", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 6, pp.631-633, May-June-2018.
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