تئوری شناسایی محدوده‌ی نشت در نواحی مجزای مجازی شبکه‌های توزیع آب با استفاده از شبکه‌ی عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی منابع آب، دانشکده مهندسی عمران، آب و محیط زیست، دانشگاه شهید بهشتی، تهران، ایران

2 دانشیار - دانشکده عمران، آب و محیط زیست، دانشگاه شهید بهشتی تهران

3 استادیار، گروه مهندسی منابع آب، دانشکده مهندسی عمران، آب و محیط زیست، دانشگاه شهید بهشتی، تهران، ایران

چکیده

 
یکی از مزیت­های طراحی شبکه­های توزیع آب به صورت نواحی مجزا، شناسایی نشت موجود در هر ناحیه با کنترل جریان ورودی و خروجی می­باشد که البته این کار نیازمند مجزاسازی و نصب دبی­سنج بین لوله­های رابط هر ناحیه است. با توجه به اینکه اکثر شبکه­های موجود به صورت سنتی و غیرمجزا گسترش یافته­اند، تبدیل آنها به نواحی مجزا نیازمند هزینه­های زیاد و حتی گاهی غیراجرایی است. در مقاله حاضر برای شناسایی نشت بین نواحی، ایده­ی نظری نواحی مجزای مجازی ارائه شده است. نوآوری این مقاله، امکان تبدیل شبکه­ها به نواحی مجزا با استفاده از ترکیب تئوری گراف و شبکه عصبی مصنوعی برای یافتن نشت بدون استفاده از دبی­سنج می­باشد. روش پیشنهادی علاوه بر کاهش هزینه­های لازم برای دبی­سنجی، باعث افزایش سرعت در شناسایی محدوده­های نشت می­شود. علاوه بر این، نیازی نیست تعداد گره­های نشت، قبل از شروع عملیات نشت­یابی مشخص باشد. روش پیشنهادی برای شبکه­ی توزیع آب شهر Balerma در اسپانیا با 443 گره و 454 لوله برای دو، سه و چهار نشت همزمان مورد بررسی قرار گرفت. نتایج مقاله حاضر نشان می­دهد که نظریه­ی پیشنهادی در روش ارائه شده، قادر به شناسایی نشت در هر ناحیه می­باشد و با این روش می­توان تعداد نواحی مجزای بهینه برای هر شبکه را تعیین کرد. در تمامی مثال­ها،­ ناحیه­ی نشت به درستی پیش­بینی شد و حداکثر خطای تعیین مقدار نشت حدود 5/6 درصد بود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Theoretical identification of leakage areas in virtual district metered areas of water distribution networks using the artificial neural network

نویسندگان [English]

  • Mohammad Reza Shekofteh 1
  • Mohammadreza Jalili Ghazizadeh 2
  • Jafar Yazdi 3
1 Department of Water Resources Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran
2 Associate Professor, Faculty of Civil, Water, and Environmental Engineering, Shahid Beheshti University
3 Department of Water Resources Engineering, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran
چکیده [English]

One of the advantages of designing water distribution networks (WDNs) as a district metered areas (DMAs) is to identify the leakage in each area by controlling the input and output flow, which of course requires the separating areas and installation of flowmeters between the interconnect pipes of areas. Considering that the most existing WDNs have been expanded traditionally and not as DMA, turning them into DMAs would require huge costs and might not be even practical in some networks. In this paper, a theoretical idea of virtual DMA is presented to identify the leakage in each areas. The innovation of this paper is the ability to transform networks into DMAs using a combination of the graph theory and artificial neural network to find leaks without using a flowmeter. The proposed method, in addition to reducing costs for the flowmeters, also increases the speed of detection of leakage areas. In addition, there is no need to specify the number of leakage nodes before the leak operation begins. The proposed method has been applied for the Balerma WDN in Spain with 443 nodes and 454 pipes for two, three and four simultaneous leaks. The results of this paper show that the proposed theory in this method is able to detect leakage in each area, and this method can determine the number of optimal virtual DMA for each network. In all examples, the leakage area was correctly predicted and the maximum leakage error was about 6.5%.

کلیدواژه‌ها [English]

  • Leakage
  • Graph theory
  • Virtual District Metered Areas
  • Water Distribution Network
  • Artificial Neural Network
Attari M and Faghfour Maghrebi M (2018) New method for leakage detection by using artificial   neural networks. Journal of Water and Wastewater (parallel title ); Ab va Fazilab 29(1):14-26 (In Persian)
 
Candelieri A, Conti D, and Archetti F (2014) A graph based analysis of leak localization in urban water networks. Procedia Engineering 70:228-237
 
Darsana P and Varija K (2018) Leakage detection studies for water supply systems- A review. Water Resources Management 141-150
 
Di Nardo A and Di Natale M (2011) A heuristic design support methodology based on graph theory for district metering of water supply networks. Engineering Optimization 43(2):193-211
 
Fanner P, Davis S, Hoogerwerf T, Liemberger R, Sturm R, and Thornton J (2008) Leakage management technologies. Water Environment Research Foundation
 
Farley M and Trow S (2003) Losses in water distribution networks. IWA publishing
 
Geem ZW (2009) Particle-swarm harmony search for water network design. Engineering Optimization 41(4):297-311
 
Gomes R, Marques AS, and Sousa J (2012.a) Decision support system to divide a large network into suitable District Metered Areas. Water Science and Technology 65(9):1667-1675
 
Hamilton S and McKenzie R (2014) Water management and water loss. IWA Publishing
 
Herrera M, Canu S, Karatzoglou A, Pérez-García R, and Izquierdo J (2010) An approach to water supply clusters by semi-supervised learning. International Environmental Modelling and Software Society (iEMSs), International Congress on Environmental Modelling and Software
 
Jung D and Kim J H (2018) Using mechanical reliability in multiobjective optimal meter placement for pipe burst detection. Journal of Water Resources Planning and Management 144(7):04018031
 
Newman ME and Girvan M (2004) Finding and evaluating community structure in networks. Physical Review 69(2):026113
 
Puust R, Kapelan Z, Savic D, and Koppel T (2010) A review of methods for leakage management in pipe networks. Urban Water Journal 7(1):25-45
 
Qi S, Gao J, Wu W, Qiao Y, Tu M, and Wang J (2014) Research on an optimized leakage locating model in water distribution system. Procedia Engineering 89:1569-1576
 
Reca J and Martínez J (2006) Genetic algorithms for the design of looped irrigation water distribution networks. Water Resources Research 42(5)
 
Reca J, Martínez J, Gil C, and Baños R (2008) Application of several meta-heuristic techniques to the optimization of real looped water distribution networks. Water Resources Management 22(10):1367-1379
 
Report (2018) Report from office of Basic Water Resources Studies, 2018, website:http://wrs.wrm.ir/m3/gozaresh.asp (In Persian)
 
Rossman LA (2000) EPANET 2: Users Manual.
 
Shekofteh MR and Jalili Ghazizadeh MR (2019) The optimized implementation of the District Metered Areas in the water distribution networks using graph theory. Journal of Water and Wastewater (parallel title ); Ab va Fazilab (In Persian)
 
Shekofteh MR, Jalili Ghazizadeh MR, and Yazdi J (2018) Finding the leakage zones in district metered areas (DMAs) of water distribution networks. Isfahan University of Technology, Isfahan, Iran (In Persian)
 
Soldevila A, Fernandez-Canti RM, Blesa J, Tornil-Sin S, and Puig V (2017) Leak localization in water distribution networks using Bayesian classifiers. Journal of Process Control 55:1-9
 
Tzatchkov VG, Alcocer-Yamanaka VH, and Bourguett Ortíz V (2008) Graph theory based algorithms for water distribution network sectorization projects. Eighth Annual Water Distribution Systems Analysis Symposium (WDSA) pp. 1-15
 
Wachla D, Przystalka P, and Moczulski W (2015) A method of leakage location in water distribution networks using artificial neuro-fuzzy system. IFAC-PapersOnLine 48(21):1216-1223
 
Wu ZY and Sage P (2008) Water loss detection via genetic algorithm optimization-based model calibration. Eighth Annual Water Distribution Systems Analysis Symposium (WDSA) pp. 1-11