Vehicle Remote Health Monitoring and Prognostic Maintenance System
المؤلفون المشاركون
Saleem, Muhammad Qaiser
Shafi, Uferah
Safi, Asad
Shahid, Ahmad Raza
Ziauddin, Sheikh
المصدر
Journal of Advanced Transportation
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-01-18
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
In many industries inclusive of automotive vehicle industry, predictive maintenance has become more important.
It is hard to diagnose failure in advance in the vehicle industry because of the limited availability of sensors and some of the designing exertions.
However with the great development in automotive industry, it looks feasible today to analyze sensor’s data along with machine learning techniques for failure prediction.
In this article, an approach is presented for fault prediction of four main subsystems of vehicle, fuel system, ignition system, exhaust system, and cooling system.
Sensor is collected when vehicle is on the move, both in faulty condition (when any failure in specific system has occurred) and in normal condition.
The data is transmitted to the server which analyzes the data.
Interesting patterns are learned using four classifiers, Decision Tree, Support Vector Machine, K Nearest Neighbor, and Random Forest.
These patterns are later used to detect future failures in other vehicles which show the similar behavior.
The approach is produced with the end goal of expanding vehicle up-time and was demonstrated on 70 vehicles of Toyota Corolla type.
Accuracy comparison of all classifiers is performed on the basis of Receiver Operating Characteristics (ROC) curves.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Shafi, Uferah& Safi, Asad& Shahid, Ahmad Raza& Ziauddin, Sheikh& Saleem, Muhammad Qaiser. 2018. Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1181707
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Shafi, Uferah…[et al.]. Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1181707
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Shafi, Uferah& Safi, Asad& Shahid, Ahmad Raza& Ziauddin, Sheikh& Saleem, Muhammad Qaiser. Vehicle Remote Health Monitoring and Prognostic Maintenance System. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1181707
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1181707
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