Sökning: onr:"swepub:oai:DiVA.org:ltu-4076" >
Application of mult...
Application of multi regressive linear model and neural network for wear prediction of grinding mill liners
-
- Ahmadzadeh, Farzaneh (författare)
- Luleå tekniska universitet,Drift, underhåll och akustik,Luleå University of Technology, Sweden
-
- Lundberg, Jan (författare)
- Luleå tekniska universitet,Drift, underhåll och akustik,Luleå University of Technology, Sweden
-
(creator_code:org_t)
- 2013
- 2013
- Engelska.
-
Ingår i: International Journal of Advanced Computer Sciences and Applications. - 2158-107X .- 2156-5570. ; 4:5, s. 53-58
- Relaterad länk:
-
http://thesai.org/Pu...
-
visa fler...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
https://urn.kb.se/re...
-
visa färre...
Abstract
Ämnesord
Stäng
- The liner of an ore grinding mill is a critical component in the grinding process, necessary for both high metal recovery and shell protection. From an economic point of view, it is important to keep mill liners in operation as long as possible, minimising the downtime for maintenance or repair. Therefore, predicting their wear is crucial. This paper tests different methods of predicting wear in the context of remaining height and remaining life of the liners. The key concern is to make decisions on replacement and maintenance without stopping the mill for extra inspection as this leads to financial savings. The paper applies linear multiple regression and artificial neural networks (ANN) techniques to determine the most suitable methodology for predicting wear. The advantages of the ANN model over the traditional approach of multiple regression analysis include its high accuracy.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Annan samhällsbyggnadsteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Other Civil Engineering (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Annan teknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Other Engineering and Technologies (hsv//eng)
Nyckelord
- Drift och underhållsteknik
- Operation and Maintenance
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas