Title :
Vibration faults diagnosis for centrifugal ventilator based on DDAGSVM
Author_Institution :
Dept. of Energy & Power Eng., Shenyang Inst. of Eng., Shenyang, China
Abstract :
Multi-class algorithm based on Support Vector Machines, which is also called as Decision Directed Acyclic Graph method, is used for ventilator faults diagnosis in order to diagnose the vibration faults of centrifugal ventilator and improve ventilator run security and economical efficiency. Results indicate that the method is a novel means to ventilator faults diagnosis, which can not only diagnose common vibration faults accurately but also it has some features which are faster diagnosis rate and higher accuracy.
Keywords :
fault diagnosis; support vector machines; vibration measurement; DDAGSVM; centrifugal ventilator; decision directed acyclic graph method; multiclass algorithm; support vector machines; vibration faults diagnosis; Databases; Fault diagnosis; Mathematical model; Support vector machines; Temperature measurement; Training; Vibrations; Centrifugal Ventilator; Faults Diagnosis; Support Vector Machines;
Conference_Titel :
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2465-6
DOI :
10.1109/MSNA.2012.6324577