Open AccessA predicting method for the health state of the rolling bearing
Author(s) -
Hongyan Jiang,
Dianjun Fang
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1063/1/012005
Subject(s) - bearing (navigation) , fault (geology) , vibration , state (computer science) , control theory (sociology) , engineering , statistics , computer science , reliability engineering , structural engineering , mathematics , algorithm , artificial intelligence , physics , acoustics , control (management) , seismology , geology
As an important component of rotating machinery, the health of rolling bearings is related to the normal operation of the whole machinery. A Period-Sequential Index (PSI) method was used for forecasting the three working states of the rolling bearing: health, fault, or failure. A sample from the vibration signals of the bearing, running only 2538 min because of a fault of its inner race, were tested by using the PSI algorithm. The results show that, this proposed PSI algorithm showed satisfactory forecasting quality in predicting whether the bearing is working in a healthy state or not. And, the value of the mean absolute percentage error at a fault state or a failure state was higher than that at a health state.