36 citations · 56 across the 5 of their papers we have counts for
5 papers
Vibrational quality classification of metallic turbine blades under measurement uncertainty
Liangliang Cheng, Vahid Yaghoubi, Wim V. Paepegem +1
Non-destructive testing on metallic turbine blades is a challenging task due to their complex geometry. Vibrational test-ing such as Process Compensated Resonance Testing (PCRT) ha…
CNN-DST: ensemble deep learning based on Dempster-Shafer theory for vibration-based fault recognition
Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem +1
Nowadays, using vibration data in conjunction with pattern recognition methods is one of the most common fault detection strategies for structures. However, their performances depe…
Vibration-Based Condition Monitoring By Ensemble Deep Learning
Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem +1
Vibration-based techniques are among the most common condition monitoring approaches. With the advancement of computers, these approaches have also been improved such that recently…
A novel multi-classifier information fusion based on Dempster-Shafer theory: application to vibration-based fault detection
Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem +1
Achieving a high prediction rate is a crucial task in fault detection. Although various classification procedures are available, none of them can give high accuracy in all applicat…
An ensemble classifier for vibration-based quality monitoring
Vahid Yaghoubi, Liangliang Cheng, Wim Van Paepegem +1
Vibration-based quality monitoring of manufactured components often employs pattern recognition methods. Albeit developing several classification methods, they usually provide high…