Title :
The selection of time domain characteristic parameters of rotating machinery fault diagnosis
Author :
Chang, Ji-bin ; Li, Tai-fu ; Li, Peng Fei
Author_Institution :
Chongqing Univ. of Sci. & Technol., Chongqing, China
Abstract :
In order to choose the rotating machinery fault diagnosis characteristics accurately, in this paper, a kind of choice method of fault diagnosis characteristics was put forward based on the time domain statistical analysis. Through analysis the probability distribution of the time domain dimensionless characteristic parameters, choose the parameters witch is obviously different from others and used as rotating machinery´s fault diagnosis characteristic parameters. Through MATLAB simulation, we can draw a conclusion from the results that this method can improve the efficiency and accuracy of fault diagnosis effectively.
Keywords :
backpropagation; fault diagnosis; machinery; mathematics computing; mechanical engineering computing; neural nets; statistical distributions; time-domain analysis; MATLAB simulation; backpropagation neural network; probability distribution; rotating machinery fault diagnosis; time domain dimensionless characteristic parameters; time domain statistical analysis; Appraisal; Business; Costs; Fault diagnosis; Knowledge management; Machinery; Production; Raw materials; Supply chain management; Supply chains; Characteristics Parameters; Fault Diagnosis; Rotating Machinery; Selection; Time Domain;
Conference_Titel :
Logistics Systems and Intelligent Management, 2010 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-7331-1
DOI :
10.1109/ICLSIM.2010.5461346