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العنوان
Diagnosis of rotary machines faults using artificial intelligence /
الناشر
Mostafa Hussien Metwally Ahmed ,
المؤلف
Mostafa Hussien Metwally Ahmed
هيئة الاعداد
باحث / Mostafa Hussien Metwally Ahmed
مشرف / Galal Ali Hassaan
مشرف / M. A. Moustafa Hassan
مناقش / Abdel Monem A. Seif
مناقش / Moustafa Hany Arafa
تاريخ النشر
2020
عدد الصفحات
107 P. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة الصناعية والتصنيع
الناشر
Mostafa Hussien Metwally Ahmed ,
تاريخ الإجازة
11/10/2020
مكان الإجازة
جامعة القاهرة - كلية الهندسة - Mechanical Design and Production Engineering
الفهرس
Only 14 pages are availabe for public view

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from 127

Abstract

This thesis employs three methods for diagnosing the bearing faults based on Fast Fourier Transform (FFT), Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models.The obtained data was classified into four main conditions: Healthy, Outer Faulty, Inner Faulty, and Ball Faulty. The four conditions were imported to ANN and ANFIS models. The input data was preprocessed before entering to ANN and ANFIS models by using three techniques: the normalized data in range (0-1), the time domain features, and finally the Auto Regressive (AR) model.The accomplished outcomes of ANN and ANFIS models in case of AR model give high accuracy results in classification issue