Scopus
🔓 Açık Erişim YÖKSİS DOI Eşleşti
SJR Q2
Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions
Journal of Tekirdag Agricultural Faculty · Mart 2024
YÖKSİS Kayıtları
Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions
Tekirdağ Ziraat Fakültesi Dergisi · 2024 ESCI
Öğr. Gör. HASAN KIRILMAZ →
Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions
Tekirdağ Ziraat Fakültesi Dergisi · 2024 TR DİZİN
Öğr. Gör. MEHMET KURT →
Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions
Tekirdağ Ziraat Fakültesi Dergisi · 2024 ESCI
Doç. Dr. NURİ ORHAN →
Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions
Tekirdağ Ziraat Fakültesi Dergisi · 2024 ESCI
Öğr. Gör. MEHMET KURT →
YÖKSİS Kayıtları — ISSN Eşleşmesi
Yağlı Tohum Üretim Potansiyelinin Coğrafi Bilgi Sistemleri Kullanılarak Belirlenmesi: Balıkesir İli Örneği
2025 ISSN: 1302-7050 ESCI
Prof. Dr. TANZER ERYILMAZ →
Evaluation of Structural Conditions of Dairy Cattle Barns in Konya and Aydin Provinces
2025 ISSN: 1302-7050 TR DİZİN
Dr. Öğr. Üyesi ONUR ERZURUM →
Alternatif Ürün Projesi Kapsamında Tütün ve Bazı Ürünler Arasında Karlılık Karşılaştırmaları
2009 ISSN: 1302-7050 TR DİZİN
Doç. Dr. HASAN ARISOY →
AB ve Türkiye de Tarım Sektörüne Yapılan Direkt Ödemelerin Karşılaştırılması
2011 ISSN: 1302-7050 TR DİZİN
Doç. Dr. HASAN ARISOY →
Sille (Konya) Yerleşiminin Sürdürülebilirliği için Ekolojik Tasarım Önerileri
2011 ISSN: 1302-7050 TR DİZİN
Prof. Dr. FİLİZ ÇELİK →
The Effect of Clove and Cinnamon on Some Physicochemical Properties of Sucuk Producedby Different Animal Fat Types.
2017 ISSN: 1302-7050 Tarım ve Gıda
Prof. Dr. MUSTAFA KARAKAYA →
Effects of Four Different Crops Harvest Processes on Soils Compaction
2017 ISSN: 1302-7050 TR DİZİN
Öğr. Gör. HAMZA NEGİŞ →
Effects of Four Different Crops Harvest Processes on Soils Compaction
2017 ISSN: 1302-7050 TR DİZİN
Doç. Dr. İLKNUR GÜMÜŞ →
Tüketicilerin Helal Gıda Ürünlerine Yönelik Ödeme İstekliliklerinin Belirlenmesi
2020 ISSN: 1302-7050 ESCI
Prof. Dr. ZEKİ BAYRAMOĞLU →
Determination of Yield and Quality of Different Snap Bean Varieties Under Deficit Irrigation
2020 ISSN: 1302-7050 TR DİZİN
Dr. Öğr. Üyesi SİNAN SÜHERİ →
Comparatıve Investment Analysıs of Agrıcultural Irrıgatıon Systems
2021 ISSN: 1302-7050 Emerging Science Citation Index
Öğr. Gör. SÜHEYLA AĞIZAN →
COMPARATIVE INVESTMENT ANALYSIS OF AGRICULTURAL IRRIGATION SYSTEMS
2021 ISSN: 1302-7050 ESCI
Prof. Dr. ZEKİ BAYRAMOĞLU →
POTASYUM VE ÇİNKOLU GÜBRELEMENİN ENGİNARDA VERİM VE VERİM UNSURLARINA ETKİLERİ
2020 ISSN: 1302-7050 Alan endeksleri
Prof. Dr. MEHMET ZENGİN →
Artan Dozlarda Bakır Sülfat ve Azot Uygulamalarının Ekmeklik Buğdayda Verim ile Kök ve Kök Boğazı Çürüklüğü Hastalığına Etkileri
2020 ISSN: 1302-7050 Alan endeksleri
Prof. Dr. MEHMET ZENGİN →
Bazı Türkiye Yerli Irk Koyunlarında Entansif Besi Süresince Vücut Ölçülerinin Değişimi
2010 ISSN: 1302-7050 TR DİZİN
Doç. Dr. ÖZCAN ŞAHİN →
Detection of Vortex Cavitation With The Method Adaptive Neural Fuzzy Networks in the Deep Well Pumps
2021 ISSN: 1302-7050 TR DİZİN
Doç. Dr. NURİ ORHAN →
Beyşehir Gölü Milli Parkında Seyahat Maliyetini Etkileyen Faktörlerin Analizi
2022 ISSN: 1302-7050 ESCI
Prof. Dr. ZUHAL KARAKAYACI →
Anadolu Merinosu Koyunlarında Meme Tipleri ile Meme Özellikleri Süt Verimi ve Bileşenleri Arasındaki İlişkiler
2013 ISSN: 1302-7050 TUBİTAK]ULAKBİM, CABI, DOAJ, EBSCO, FAO!AGRISDatabase
, INDEXCOPERNICUS,
Prof. Dr. İBRAHİM AYTEKİN →
The Effects of Different Sulfur Forms and Biochar Applications on The Development of Radish (Raphanus sativus) in Calcareous Soils
2022 ISSN: 1302-7050 ESCI
Prof. Dr. AYŞEN AKAY →
Tarım İşletmelerinde İşgücü Etkinliğinin Artırılmasında Sermayenin Önemi
2022 ISSN: 1302-7050 ESCI
Prof. Dr. ZUHAL KARAKAYACI →
Makale Bilgileri
ISSN13027050
Yayın TarihiMart 2024
Cilt / Sayfa21 · 533-546
Scopus ID2-s2.0-85191361018
Erişim🔓 Açık Erişim
Özet
Cavitation, a physical phenomenon that detrimentally affects pump performance and reduces pump life, can cause wear on pump elements. Various engineering methods have been developed to identify the initiation and full development of the cavitation process. One such method is the determination of the net positive suction head (NPSH) through a 3% decrease in total head (Hm) at a constant flow rate. In radial pumps, commonly used in agricultural irrigation and industry, cavitation conditions result in a sudden drop in the Hm-Q curve, making it challenging to detect the 3% Hm value drop. This study differs from others in the literature by modelling NPSH, noise, and vibration levels using three machine learning models, specifically artificial neural networks (ANN), support vector machines (SVM), and decision tree regression (DTR). The best-performing model predicts NPSH, noise, and vibration levels corresponding to a 3% decrease in Hm level. The present study determined the NPSH values of a horizontal shaft centrifugal pump at different flow rates and constant operating speed, and the vibration and noise levels were measured for these NPSH values. For each of the NPSH, noise, and vibration levels, ANN, SVM and DTR models were created. The performances of these models were evaluated using criteria such as root mean squared error (RMSE), Mean Absolute Error (MAE) and mean absolute percentage error (MAPE). In addition, Taylor and error box diagrams were created. The ANN model and DTR yielded high accuracy predictions for NPSH values (R<sup>2</sup> = 0.86 and R<sup>2</sup> = 0.8, respectively). The ANN model provided the best prediction performance for noise and vibration levels. By entering the level of 3% drop in the Hm value of the pump as external data input to the ANN model, NPSH3, noise, and vibration levels were determined. The ANN models can be effectively employed to determine NPSH3, noise, and vibration levels, particularly in radial flow pumps, where detecting 3% reductions in manometric height value is challenging.
Yazarlar (4)
1
Nuri Orhan
ORCID: 0000-0002-9987-1695
2
Kurt Mehmet
ORCID: 0000-0002-9566-6627
3
Kirilmaz Hasan
ORCID: 0000-0002-0263-6200
4
Ertuğrul Murat
ORCID: 0000-0001-9582-1546
Anahtar Kelimeler
Centrifugal pumps
Machine learning
Net positive suction head (NPSH)
Noise
Vibration
Kurumlar
Bozok Üniversitesi
Yozgat Turkey
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Journal of Tekirdag Agricultural Faculty
Q2
SJR Skoru0,283
H-Index9
YayıncıNamik Kemal University - Agricultural Faculty
ÜlkeTurkey
Agricultural and Biological Sciences (miscellaneous) (Q2)
Pollution (Q3)
Metrikler
2
Atıf
4
Yazar
5
Anahtar Kelime