شماره ركورد كنفرانس :
3254
عنوان مقاله :
Intelligent Prognostics and Diagnostics of pumps using condition monitoring methods to improve reliability
Author/Authors :
Erfan َAhadi Iran University of science and Technology, Tehran , Mostafa Larki Iran University of science and Technology, Tehran , Hamidreza Javidrad Iran University of science and Technology, Tehran , Mohammad Riahi university of Science and Technology, Tehran
كليدواژه :
Artificial Intelligence , Predictive Maintenance , Condition Monitoring , Centrifugal Pumps , Prognostics and Health Management
عنوان كنفرانس :
پنجمين كنفرلنس بين المللي قابليت اطمينان و ايمني
چكيده لاتين :
Predictive maintenance aims to reduce costs of maintenance, improve safety, reliability and efficiency and prevent catastrophic and costly failures by early fault diagnosis and prediction of future status of machines by using condition monitoring methods. Pumps are the most used mechanical equipment after motors and annually huge amount of money is spent for their maintenance. In this paper, techniques for intelligent fault diagnosis and Prognosis of pumps using condition monitoring data and Artificial Intelligence methods such as Artificial Neural Networks, Support Vector Machines and Genetic Algorithm are reviewed. Our findings show advantages, disadvantages, limitations, research gaps and future trend of research.
