Open Access Open Access  Restricted Access Subscription or Fee Access

Analysis of the Use of Digital Ultrasonic Based on Fuzzy Inference System to Get More Precise Water Discharge Measurement Results


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/iremos.v16i6.24023

Abstract


Water discharge measurement commonly used in Indonesia is based on a wheeled meter system. The management of water discharge to each house is regulated by the Regional Water Company (RDWC). However, the wheel meter system not only detects liquids, but also air. Therefore, if the air passes, the meter also rotates. This research aims to measure water discharge in RDWC in Indonesia by using ultrasonic. The use of ultrasonic is complemented by the use of Fuzzy Inference System (FIS). The initial stage of this research is to install an ultrasonic sensor device. This sensor is equipped with a display screen and data transmission system. Therefore, RDWC officers and customers can easily monitor water. In addition to using microcontroller media, artificial intelligence technology is also used to make input and output data more precise. The main water measurement is done with the Ultrasonic Echosounder method. This research compares three water measurement systems, namely manual wheel, ultrasonic-based only, and ultrasonic-based with FIS. The comparison is done by measuring the water discharge every minute for nine minutes, and then the difference is indicated by the error value in the form of a percentage. The speed or flow of water is measured before the discharge measurement. The results have showed a considerable difference between the manual and ultrasonic methods of 6.08%. In contrast, a minor error (3.74%) has been observed in the comparison between ultrasonic-FIS and manual methods. In addition, the results of this study also illustrate the difference between the ultrasonic-FIS and FIS-only methods. Overall, these findings provide additional information regarding the applicability of ultrasonic-FIS and non-FIS methods compared to manual methods for water discharge measurement in Indonesia.
Copyright © 2023 Praise Worthy Prize - All rights reserved.

Keywords


Ultrasonic; Fuzzy Inference System; Water Debit; Water Flow

Full Text:

PDF


References


D. Nugraha, "Study of Water Loss Due to Pipe Leakage in Pdam Distribution Line of Magelang City (Case Study: Armada Estate and Ministry of Health Housing, North Kramat, North Magelang Sub-district)," J. Presipitasi, vol. 7, no. 2, pp. 71-76-76, 2010.
https://doi.org/10.14710/presipitasi.v7i2.71-76

R. Dwi Yoga Maidiyanto, Ambroso Marthins Nuno, Yostan A. J Soinbala, "Technical Leakage Analysis as an Effort to Improve the Efficiency of Clean Water Services in Malang City" J. Widya Tek., vol. 21, no. 2, p. 9 hal, 2013.

A. Suharjono, L. N. Rahayu, and R. Afwah, "Application of Flow Water Sensor to Measure Customer Water Usage Digitally and Automatic Data Transmission at PDAM Semarang City", Tek. Elektro, Politek. negeri Semarang, vol. Vol.13, no. 1, pp. 7-12, 2015.

J. Senthil Kumar, A. Kamaraj, C. Kalyana Sundaram, G. Shobana, and G. Kirubakaran, "A comprehensive review on accuracy in ultrasonic flow measurement using reconfigurable systems and deep learning approaches," AIP Adv., vol. 10, no. 10, 2020.
https://doi.org/10.1063/5.0022154

Zen, H., Kusuma, I., Widjiati, E., Development of Low-Cost Wave Measurement Model Using Ultrasonic Sensor JSN-SR04T for Supporting Seakeeping Test in the Maneuvering and Engineering Ocean Basin (MOB), (2023) International Review on Modelling and Simulations (IREMOS), 16 (2), pp. 35-42.
https://doi.org/10.15866/iremos.v16i2.23490

C. H. Lee, H. K. Jeon, and Y. S. Hong, "An implementation of ultrasonic water meter using dToF measurement," Cogent Eng., vol. 4, no. 1, 2017.
https://doi.org/10.1080/23311916.2017.1371577

A. Suryana and M. A. S. Yudono, "Ultrasonic Sensor for Measurement of Water Flow Rate in Horizontal Pipes Using Segment Area", Fidelity, vol. 5, no. 1, pp. 60-68, Jan. 2023.
https://doi.org/10.52005/fidelity.v5i1.143

A. Suryana, Paikun, and M. Ali Setyo Yudono, "Fluid Volume Detector on a Horizontal Tube Using an Ultrasonic-based Water Level Sensor," Fidel. J. Tek. Elektro, vol. 4, no. 1, pp. 6-9, 2022.
https://doi.org/10.52005/fidelity.v4i1.80

A. Mustika and B. Rosa, "Use of Ultrasonic Sensor as Water Level Detection in River" Pros. Ind. Res. Work. Natl. Semin., vol. 2, no. November 2017, pp. 143-147, 2011.

Y. Abe, "Special section on recent development of electro-mechanical devices," IEICE Trans. Electron., vol. E102C, no. 9, p. 627, 2019.
https://doi.org/10.1587/transele.2019EMF0001

R. Chen, W. Zhai, and Y. Qi, "Mechanism and technique of friction control by applying electric voltage. (II) Effects of applied voltage on friction," Mocaxue Xuebao/Tribology, vol. 16, no. 3, pp. 235-238, 1996.

E. D. Arisandi, "Ease of Programming Arduino Microcontroller on Flying Vehicle Application" Setrum Sist. Kendali-Tenaga-elektronika-telekomunikasi-komputer, vol. 3, no. 2, p. 114, 2016.
https://doi.org/10.36055/setrum.v3i2.507

P. Y. Bate, A. Sartika Wiguna, and D. Aditya Nugraha, Automatic Drying System Using Arduino Uno R3 with Fuzzy Method Approach, "KURAWAL Journal of Technology, Information and Industry," vol. 3, pp. 81-92, 2020.
https://doi.org/10.33479/kurawal.v3i1.306

Shilpashree Nadagoudar, Satheesh kumar J. "Intelligent flow meter development using neural network", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Vol.6, Issue 2, pp.363-368, APRIL 2018.

B. Solioz and P. Mudry, "A Low-Cost Water Flow Meter on the Edge using Machine Learning", Proceedings of FTAL 2021, 28-29 October, 2021, Lugano, Switzerland-CEUR Workshop 2021.

A. Hussein and J. Agbinya, "Water Flow forecasting using Artificial Intelligence techniques and Markov chain model : The Blue Nile Scenario," Australian Journal of Basic and Applied Sciences, vol. 13, no. 12, pp. 10-18, 2019.doi: 10.22587/ajbas.2019.13.12.3
https://doi.org/10.22587/ajbas.2019.13.12.3

Thiam Wan, Hon Chung Lau, Wai Lam Loh. Machine Learning Applied to Ultrasonic Flow Meters for measuring Dilute, Turbulent Water-Bentonite Suspension Flow. TechRxiv. September 11, 2020.
https://doi.org/10.22541/au.159986871.18984293

O. Glovatskii, S. Usmanov, R. Ergashev, B. Hamdamov, and A. Gazaryan, "Hydrometric flow measurement in water management," E3S Web Conf., vol. 365, pp. 1-12, 2023.
https://doi.org/10.1051/e3sconf/202336503016

D. W. Meals and T. Tech, "Surface Water Flow Measurement for Water Quality Monitoring Projects Introduction," Environ. Sci., vol. 3, pp. 1-16, 2008.

J. Jamaaluddin, I. Robandi, I. Anshory, and A. Fudholi, "Very Short-Term Load Forecasting Of Peak Load Time Using Fuzzy Type-2 And Fast Bang Fast Crunch (Bbbc) Algorithm," ARPN J. Eng. Appl. Sci., vol. 15, no. 7, pp. 854-861, 2020.

J. Jamaaluddin et al., "Very Sort Term Load Forecasting Using Interval Type - 2 Fuzzy Inference System (IT- 2 FIS) (Case Study: Java Bali Electrical System)," in IOP Conference Series: Materials Science and Engineering, 2018, vol. 384, no. 1.
https://doi.org/10.1088/1757-899X/384/1/012078

T. J. Ross, Fuzzy Logic With Engineering Applications, Third. Mexico: A John Wiley and Sons, Ltd., Publication, 2010.

Chekenbah, H., Maataoui, Y., Boutfarjoute, O., El Abderrahmani, A., Lasri, R., Improved Fuzzy MPPT to Solve Partial Shading Conditions Problem in a Photovoltaic System, (2022) International Review on Modelling and Simulations (IREMOS), 15 (4), pp. 226-235.
https://doi.org/10.15866/iremos.v15i4.21728

O. Castillo and P. Melin, "A review on interval type-2 fuzzy logic applications in intelligent control," Inf. Sci. (Ny)., 2014.
https://doi.org/10.1016/j.ins.2014.04.015

M. Fastlarbegian, W. Melek, and J. Mendel, "On the robustness of type-1 and interval type-2 fuzzy logic systems in modeling," Inf. Sci. (Ny)., 2011.
https://doi.org/10.1016/j.ins.2010.11.003

Gouveia, E., Moisés Costa, P., Santos, V., Pereira, A., Constrained Fuzzy Power Flow Applied to Transmission Congestion, (2022) International Review on Modelling and Simulations (IREMOS), 15 (5), pp. 293-302.
https://doi.org/10.15866/iremos.v15i5.21632

O. Castillo, "Interval type-2 fuzzy logic for hybrid intelligent control," Studies in Fuzziness and Soft Computing. 2013.
https://doi.org/10.1007/978-3-642-24663-0

M. Tsukada and H. Matsutani, "An Overflow/Underflow-Free Fixed-Point Bit-Width Optimization Method for OS-ELM Digital Circuit," IEICE Trans. Fundam. Electron. Commun. Comput. Sci., vol. 105, no. 3, pp. 437-447, 2022.
https://doi.org/10.1587/transfun.2021VLP0017

M. Almaraashi, R. John, A. Hopgood, and S. Ahmadi, "Learning of interval and general type-2 fuzzy logic systems using simulated annealing: Theory and practice," Inf. Sci. (Ny)., 2016.
https://doi.org/10.1016/j.ins.2016.03.047

S. Hassan, A. Khosravi, J. Jaafar, and M. A. Khanesar, "A systematic design of interval type-2 fuzzy logic system using extreme learning machine for electricity load demand forecasting," Int. J. Electr. Power Energy Syst., 2016.
https://doi.org/10.1016/j.ijepes.2016.03.001

B. S. Khehra, A. P. S. Pharwaha, and M. Kaushal, "Fuzzy 2-partition entropy threshold selection based on Fast Bang-Fast Crunch Optimization algorithm," Egyptian Informatics Journal, 2014.
https://doi.org/10.1016/j.eij.2015.02.004

K. Crockett, M. Garratt, A. Latham, E. Colyer and S. Goltz, "Risk and Trust Perceptions of the Public of Artifical Intelligence Applications," 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1-8.
https://doi.org/10.1109/IJCNN48605.2020.9207654

K. Crockett, M. Garratt, A. Latham, E. Colyer and S. Goltz, "Risk and Trust Perceptions of the Public of Artifical Intelligence Applications," 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1-8.
https://doi.org/10.1109/IJCNN48605.2020.9207654

J. M. Mendel, "General type-2 fuzzy logic systems made simple: A tutorial," IEEE Trans. Fuzzy Syst., 2014.
https://doi.org/10.1109/TFUZZ.2013.2286414

C. I. Gonzalez, J. R. Castro, O. Mendoza, P. Melin, and O. Castillo, "Optimization by cuckoo search of interval type-2 fuzzy logic systems for edge detection," Stud. Fuzziness Soft Comput., 2016.
https://doi.org/10.1007/978-3-319-32229-2_11

D. Wu and J. M. Mendel, "Designing practical interval type-2 fuzzy logic systems made simple," 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Beijing, China, 2014, pp. 800-807.
https://doi.org/10.1109/FUZZ-IEEE.2014.6891534

M. Nur R., I. resha A., and R. Dian A., "Application of HC-SR04 Ultrasonic Sensor to Detect the Distance of Railway Passengers in the New Normal Era," National Conference PKM Center Sebelas Mare University, vol. 1. pp. 236-240, 2020. [Online].
Available: https://jurnal.uns.ac.id/pkmcenter/article/view/51362

S. Idris, "Design of Water Speed Measurement Tool in Pipes with Raspberry P-Based Doppler Effect Method," Thesis, Faculty of Engineering, Mataram University, 2017.


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize