نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی فارغ التصیل رشته مهندسی منابع آب، گروه مهندسی آب، دانشکئه کشاورزی، گروه مهندسی آب

2 گروه مهندسی آب- دانشگاه باهنر کرمان

3 دانشیار گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه شهید باهنر کرما

10.22103/nrswe.2022.19227.1001

چکیده

عامل اصلی انتقال آب در شبکه‏های توزیع آب، اختلاف هد فشاری بین دو نقطه بوده و در صورت افزایش فشار بیش از حد استاندارد، پدیده نامطلوب نشت رخ می‏دهد. نشت در سیستم آبی از لحاظ اقتصادی، اجتماعی و تأثیرات زیست محیطی مهم می‏باشد. اهداف تحقیق حاضر شامل تشخیص نقاط هدررفت آب در شبکه توزیع آبرسانی با استفاده از مدل EPANET و روش نروفازی، و مقایسه این دو روش و ارائه روش بهتر جهت تشخیص نقاط هدررفت آب می‏باشد. در این تحقیق به منظور ردیابی نشت در شبکه‏ توزیع آب شهر محی‏آباد استان کرمان، روشی مبتنی بر مدل‏سازی هیدرولیکی و حل معکوس معادلات جریان، جهت پیش‏بینی محل و میزان نشت موجود در شبکه توزیع آب با استفاده از نرم‏افزار EPANET و روش نروفازی، با داشتن مقادیر اندازه‏گیری شده فشار در تعدادی از گره‏های شبکه، معرفی شد. نتایج حاکی از آن است که در بهترین معماری انتخاب شده از بین کلیه شبکه‏های آزمایش شده، ضرایب نشت حاصل از پیش‏بینی نروفازی نسبت به مقادیر مدل‏سازی شده EPANET مناسب‏ترین گزینه برای مدل‏سازی بوده و دارای ضریب همبستگی 984/0 و میانگین خطای پیش‏بینی MSE، برابر صفر با ریشه میانگین مربعات خطا (RMSE)، 0024/0 لیتر بر ثانیه نشان‏دهنده دقت پیش‏بینی مطلوب و قابلیت اطمینان بسیار زیاد شبکه آموزش دیده‏است. روش پیشنهادی با حداقل برداشت اطلاعات هیدرولیکی از نوع فشارها، قابلیت خوبی در پیش‏بینی محل نشت در شبکه را دارا بوده و همچنین استفاده از روش نروفازی، ساده و کم‏هزینه بوده علاوه بر آن از دقت مناسبی برخوردار است.

کلیدواژه‌ها

عنوان مقاله [English]

Leakage in the Water Supply Network using EPANET Software and Neurofuzzy Method

نویسندگان [English]

  • Fatemeh Ghishinzadeh 1
  • Nasrin Sayari 2
  • Majid Rahimpour 3

1 Dept. of Irrigation(Water Engineering Group) Faculty of Agriculture Shahid Bahonar Univ. of Kerman Kerman IRAN

2 Nasrin Sayari (Ph.D)Assistant Professor Dept. of Irrigation(Water Engineering Group) Faculty of Agriculture Shahid Bahonar Univ. of Kerman Kerman IRAN

3 Professor Dept. of Irrigation(Water Engineering Group) Faculty of Agriculture Shahid Bahonar Univ. of Kerman Kerman IRAN

چکیده [English]

Water supply networks as a hydraulic system of water transmission and distribution have always been of interest to researchers. The main cause of water transfer in water distribution networks is the pressure head difference between the two points and in case of increasing the standard pressure, the undesirable phenomenon of leakage occurs. Leakage in the irrigation system is economically, socially and environmentally significant. Therefore, leak detection as one of the duties of water and sewage companies in the country has always been a concern. Objectives of the present research includes the detection of water loss points in the water distribution network using the EPANET model and the neurofuzzy method, and compares the two methods and provides a better method for detecting water loss points. In this study, in order to detect leakage in the water distribution network of Mohyabad city of Kerman province, a method based on hydraulic modeling and inverse solution of flow equations to predict the location and amount of leakage in the distribution network Water was introduced using EPANET software and neurofuzzy method with measured values of pressure in a number of network nodes. The results indicate that in the best selected architecture among all tested networks, leakage coefficients resulting from neurofuzzy prediction compared to EPANET modeled values are the most suitable option for modeling and have a coefficient. The correlation between 0.984 and the mean MSE forecast error, equal to zero with the root mean square error (RMSE), 0.0024 (l/s) indicates the optimal forecast accuracy and high reliability of the trained network. The proposed method with a minimum of hydraulic information from pressures, has a good ability to predict the location of leaks in the network and also the use of neurophase method is simple and low cost, in addition, has good accuracy.

کلیدواژه‌ها [English]

  • Pressure difference
  • Water distribution network
  • Mohyabad
  • Hydraulic modeling
  • Water loss
  1. 1.Ahmadfouad Z., Eddy H. S., Badronnisa Y., and Syazwani, I. 2019. Water leak detection method in water distribution network. Earth and Environmental Science, 357, 115-123. https://www.researchgate.net/publication/337499893.2019.11.25

    1. Azadfar M. S., Barani G.A., and Hesami Kermani M. 2019. Pressure optimization in urban water distribution network with the aim of minimizing leakage. the second national conference on modern studies of civil engineering, architecture, urban planning and environment in the 21st century. Shahid Bahonar University of Kerman. (In Persian). https://civilica.com/doc/943776
    2. Das S., Mukherjee B., and Mazumdar A. 2018. Comparison of outcomes through EPANET and LOOP softwares using a gravity flow water supply network at East Medinipur in West Bengal. Indian Chemical Society, 95: 313- 324. https://www.researchgate.net/publication/318014301. 2013.06.17
    3. Ghazizadeh M. R., and Shahroozi Sh. 2018. The effect of using indoor water tanks on reducing leakage of distribution networks in operation. Journal of Water and Sewerage, 29:119-112. (In Persian). http://www.wwjournal.ir/article_60168.html
    4. Jafari asl J., Sami Kashkoli B., and Bahrami M. 2017. Optimal pressure control with the target of minimizing leakage in water distribution networks. Journal of Water and Sustainable Development, 2: 56-49. (In Persian). https://www.sciencedirect.com/science/article/pii/S1110016817302363
    5. Majidikhalilabadi N., Mollazadeh M., Akbarpour A., and Khorashadizadeh S. 2017. Leak detection in water distribution systemusing non-linear kalman fil ter. Journal Optimization Civil Engineering, 8(2): 169-180. (In Persian). https://www.magiran.com/paper/1739420
    6. Mohammadi H., Qayini Hesarovieh M., and Fadaei Kermani A. 2019. Leakage reduction and pressure control by pressure relief valves in water distribution network. 15th National Conference on Irrigation and Evaporation Reduction, Kerman. (In Persian). https://civilica.com/doc/954794/
    7. Mokhtarichaharbari A. 2010. Leak modeling in urban water distribution networks and water transmission lines(M.Sc. Thesis), Department of Water Engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Iran. (In Persian). https://virascience.com/
    8. Momenzadeh R., Azarm R., and Aghamajidi, R. 2018. Demand allocation pattern for consumption points in domestic water distribution networks: A case study of Ilam Campus. Biochemical Technology Society, 2: 67- 72. (In Persian). http://www.waterjournal.ir/article_74208.html
    9. Musakhani A., and Akbari A. 2020. Evaluation and calculation of average area pressure and day-night factor and their application in the analysis of water distribution networks. Scientific Journal of Water Science and Engineering, 36(4): 33-38. (In Persian). http://www.jwwse.ir/article_112811.html
    10. Santhi c., Arnold J.G., Williams J.R., Dugas W.A., Srinivasan R., and Hauck L. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources. Assoc, 37: 1169- 1188. https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1752-1688.2001.tb03630
    11. Taebi A. (1999). Relationship between pressure and leakage rate in water distribution network. Second Iranian Hydraulic Conference, 255-252. (In Persian). http://www.wwjournal.ir/data/wwj/coversheet/
    12. Tavakoli R., Golkar R.H., and Tavoosi M. 2015. Pressure management to reduce leaks in water supply networks. Indian Journal of Fundamental and Applied Life Sciences, 5(s4): 795-802. (In Persian). http://www.waterjournal.ir/index.php/news/article_120716.html
    13. Whitmore A.P. 1991. A method for assessing goodness of computer simulation of soil processes. Journal Soil Science, 42(3): 289- 299. https://repository.rothamsted.ac.uk/item/86783/
    14. Xuan H., Yongming H., Bin Y., Zhiqiang G., and Jinzhen F. 2020. Novel leakage detection and water loss management of urban water supply network using multiscale neural networks, Journal of Cleaner Production (278). https://doi.org/10.1016/j.jclepro.2020.123611
    15. Zandi R., Yazdi j., and shahsavandi M. 2022. Leak detection in water distribution networks by considering the hourly changes of node needs using the harmonic search algorithm, Journal of Civil teacher, 21(4): 205- 217. http://mcej-modares.ac.ir/artical-16-44976-fa.html