Optimization of Modified Rotameter Using Hall Probe Sensor with Respect to Liquid Density and its Calibration Using Artificial Neural Network
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References
- E.O. Doeblin, Measurement system and design, 4th ed. New York: Mc Graw – Hill, 1990.
- P.Bentley, principles of measurement systems, 3rd ed. Singapore: Longman Singapore publishers Ltd. 1995.
- K. Gurney, An introduction to neural networks, UCL Press, 1997.10.4324/9780203451519
- B.G. Liptak, Process measurement and analysis, 3rd ed. Oxford, U K: Butterworth heinman, 1999.
- B. Yegnanarayana, Artificial neural networks, 11th ed. PHI, 2005.
- K. Suzuki, “Artificial neural networks- industrial and control engineering applications”, INTECH open access publisher, 2011.10.5772/2041
- H. Kang, Q.Yang, C.Butler, and Fi Benati, “Optimization of sensor locations for measurement of flue gas flow in industrial ducts and stacks using neural networks”, IEEE Trans. on Instrum. and Meas., vol. 49, no.2, pp. 288-233, April 2000.10.1109/19.843054
- T.T. Yeh, P.I. Espina and A.Stephen Osella, “An intelligent ultrasonic flow meter for improved flow measurement and flow calibration facility”, IEEE Instrum. and Meas. Conf., pp. 1741-1746, May 2001.
- C. Renotte, A. Vande Wouwer, Ph. Bogaertst and M. Remy, “Neural network applications in non-linear modelling of (bio)chemical processes”, Measurement + Control, vol. 34, pp.197-201, Sept. 2001.10.1177/002029400103400702
- S.G. Etemad, J. Thibault, and S.H. Hashemabadi, “Calculation of the Pitot tube correction factor for Newtonian and Non-Newtonian fluids,” ISA Trans., vol. 42, no.4, pp. 505-512, Oct. 2003.10.1016/S0019-0578(07)60001-9
- R. A. Hooshmand and M. Joorabian, “Design and optimization of electromagnetic flowmeter for conductive liquids and its calibration based on neural networks,”IEE Proc.on Science, Measurement and Technology, vol. 153, no. 4, pp.139-146, July 2006.10.1049/ip-smt:20050042
- Lei Shi, Li Cai, Zize Liang,and Zengguang Hou, “Nonlinear Calibration of pH Sensor Based on the Back–Propagation Neural Network,” IEEE Conference on Networking, Sensing and Control, pp. 1300-1304, 2008.
- T. Povey and P. F. Beard, “A novel experimental technique for accurate mass flow rate measurement”, Elsevier, Flow Meas. and Instrum. vol. 19, no. 5, pp. 251-259, Oct. 2008.10.1016/j.flowmeasinst.2007.11.005
- V.N. Petoussis, P. D. Dimitropoulos, and G. Stamoulis, “A novel Hall effect sensor using elaborate offset cancellation method,” Sensors and Transducers J., vol. 100, no. 1, pp. 85-91, Jan. 2009.
- Bo-Kai Xia and Ying-chun Bo, “A soft sensor for water content-in-oil based on GA-RBF neural network” Measurement + Control, vol. 43/6, pp. 179-182, July 2010.10.1177/002029401004300604
- V.N. Petoussis, P. D. Dimitropoulos, and G. Stamoulis, “General development of a new Hall effect sensor,” Sensors Transducers J., vol. 127, no. 4, pp. 36-44, Apr. 2011.
- A. A. Aldair and W.J. Wang, “Design an intelligent controller for full vehicle nonlinearActive suspension systems”, International journal on smart sensing and intelligentsystems, vol. 4, no. 2, pp. 224- 243, June 2011.10.21307/ijssis-2017-437
- R.I. Rodriguez and Yi Jia, “A wireless inductive–capacitive (L-C) Sensor for rotating component temperature monitoring”, International journal on smart sensing and intelligent systems, vol. 2, no. 2, pp. 325-337, June 2011.10.21307/ijssis-2017-442
- Nasrin Afsarimanesh and Pathan Zaher Ahmed, “LabVIEW based characterization and optimization of thermal sensors”, International journal on smart sensing and intelligent systems, vol. 4, no. 4, pp.726-739, Dec. 2011.10.21307/ijssis-2017-466
- K. Chakraborty, N. Mandal, and R. Sarkar, “Design of an electronic flow transmitter using LVDT & hall sensor,” Int. J. Electron. Commun. Technol., vol. 4, no. 1, pp. 180182, 2013.
- Jianmingliu, “Neural networks method applied to the property study of steelconcreteComposite columns under axial compression”, International journal on smart sensing andIntelligent systems, vol. 6, no. 2, pp. - 548-566, April 2013.10.21307/ijssis-2017-554
- Huichao Zhao, Lihui Peng, Tsuyoshi Takahashi, Takuya Hayashi, Kazuyoshi Shimizu, and Toshihiro Yamamoto, “ANN based Data Integration for Multi-path Ultrasonic Flowmeter,” IEEE Sensors journal,vol.14, no.2, pp. 362-370, Feb. 2014.10.1109/JSEN.2013.2282466
- Harvey T Dearden, “Uncertainty in Flow Totals,” Measurement and Control, vol. 47. no. 5, pp. 158-160, June 2014.10.1177/0020294014534207
- Zhang Haining and Ren Yonghui, “Frequency processing and Temperature– pressurecompensation of the vortex flow meter based on two phase”, International journal onsmart sensing and intelligent systems, vol. 7, no. 3, pp. 1326-1346, Sept. 2014.
- N. 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. on Instrum. Meas., vol. 63, no. 12, pp. 3127-3136, Dec. 2014.
- Xing Haihua, Yu Xianchuan, Hu Dan and Dai Sha, “Sensitivity analysis of hierarchicalhybrid fuzzy- neural network”, International journal on smart sensing and intelligentsystems, vol. 8, no. 3, pp. 1837-1854, Sept. 2015.
- S. 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 Journal, vol. 15, no. 10, pp. 5592-5600, Oct. 201510.1109/JSEN.2015.2442651
- Shaojiang Dong, XiangyangXu, Juan Liu and Zhengyuan Gao, “Rotating Machine Fault Diagnosis Based on Locality Preserving Projection and Back Propagation Neural Network–Support Vector Machine Model” Measurement and Control, vol. 48(7), pp. 211–216, 2015.10.1177/0020294015595995
DOI: https://doi.org/10.21307/ijssis-2017-960 | Journal eISSN: 1178-5608
Language: English
Page range: 2204 - 2218
Submitted on: Oct 3, 2016
Accepted on: Nov 12, 2016
Published on: Dec 1, 2016
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
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© 2016 Sunita Sinha, Nirupama Mandal, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.