Machine Learning for Predictive Maintenance: Support Vector Machines and Different Kernel Functions

Küçük Resim Yok

Tarih

2022

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Pleiades Publishing Inc

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Predictive maintenance relies on machine learning techniques to learn from historical data and also uses live data to analyse failure patterns. Different from conservative maintenance procedures that generally lead to resource wastage, predictive maintenance can offer optimum resource utilisation and allow predict failures before they occur. Machine learning techniques are essential for automated predictive maintenance; therefore, in this paper the use and effectiveness of support vector machines for predictive maintenance is analysed. As the results show, support vector machines achieve the best performance when linear kernel function is used.

Açıklama

Anahtar Kelimeler

Predictive Maintenance, Support Vector Machines, Kernel Functions, Confusion Matrix, Accuracy

Kaynak

Journal Of Machinery Manufacture And Reliability

WoS Q Değeri

N/A

Scopus Q Değeri

Q3

Cilt

51

Sayı

5

Künye