Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network
المؤلفون المشاركون
Şimşir, Mehmet
Bayır, Raif
Uyaroğlu, Yılmaz
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-12-27
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure.
Such systems driven by hub motors (in wheel motors) encounter previously defined and undefined faults under operation.
It may inevitably lead to the interruption of the electromechanical system operation; hence, economic losses take place at certain times.
Therefore, in order to maintain system operation sustainability, the motor should be precisely monitored and the faults are diagnosed considering various significant motor parameters.
In this study, the artificial feedforward backpropagation neural network approach is proposed to real-time monitor and diagnose the faults of the hub motor by measuring seven main system parameters.
So as to construct a necessary model, we trained the model, using a data set consisting of 4160 samples where each has 7 parameters, by the MATLAB environment until the best model is obtained.
The results are encouraging and meaningful for the specific motor and the developed model may be applicable to other types of hub motors.
The prosperous model of the whole system was embedded into Arduino Due microcontroller card and the mobile real-time monitoring and fault diagnosis system prototype for hub motor was designed and manufactured.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Şimşir, Mehmet& Bayır, Raif& Uyaroğlu, Yılmaz. 2015. Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099745
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Şimşir, Mehmet…[et al.]. Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-13.
https://search.emarefa.net/detail/BIM-1099745
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Şimşir, Mehmet& Bayır, Raif& Uyaroğlu, Yılmaz. Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network. Computational Intelligence and Neuroscience. 2015. Vol. 2016, no. 2016, pp.1-13.
https://search.emarefa.net/detail/BIM-1099745
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1099745
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر