Title :
Fault diagnosis for hydraulic gauge system based on data fusion
Author :
Huo Zehua ; Dong Min
Author_Institution :
Coll. of Eng. Technol., Northeast Forestry Univ., Ha´erbin, China
Abstract :
Data fusion method is applied in the diagnosing the faults of the hydraulic screw down system of rolling mill, where the difficulties lie in the difficulties of lacking enough theoretical basis and getting the degree of fault measure. In full consideration of the working status and environment of rolling mill, the dynamic time-domain analysis and ARX model were used in analyzing the fault signal data of the rolling mill. By introducing a reasonable measure as the foundation for the application of data fusion theory, using the above two fault diagnosis methods and the subjective experience, faults diagnosis are carried out by data fusion method. The results overcome the limitation and the instability caused by single diagnosis method. The diagnostic results are more reliable. Finally, the effectiveness and accuracy of the method are validated by examples.
Keywords :
fault diagnosis; gauges; hydraulic systems; mechanical engineering computing; rolling mills; sensor fusion; time-domain analysis; ARX model; data fusion method; data fusion theory; dynamic time-domain analysis; fault diagnosis methods; fault signal data; hydraulic gauge system; hydraulic screw down system; rolling mill; Data integration; Fault diagnosis; Market research; Mathematical model; Servomotors; Time-domain analysis; Uncertainty; data fusion; fault diagnosis; hydraulic gauge system; signal processing;
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location :
Qingdao
Print_ISBN :
978-1-4799-7016-2
DOI :
10.1109/CCDC.2015.7162394