Browsing School of Engineering and Sustainable Development by Author "Yang, Yingjie"
Now showing items 1-5 of 5
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Canonical variate residuals-based contribution map for slowly evolving faults
Li, Xiaochuan; Yang, Xiaoyu; Yang, Yingjie; Bennett, Ian; Collop, Andy; Mba, David (Article)The superior performance of canonical variate analysis (CVA) for fault detection has been demonstrated by a number of researchers using simulated and real industrial data. However, applications of CVA to fault identification ... -
Condition monitoring of rotating machines under time-varying conditions based on adaptive canonical variate analysis
Li, Xiaochuan; Yang, Yingjie; Bennett, Ian; Mba, David (Article)Condition monitoring signals obtained from rotating machines often demonstrate a highly non-stationary and transient nature due to internal natural deterioration characteristics of their constituent components and external ... -
An intelligent diagnostic and prognostic framework for large-scale rotating machinery in the presence of scarce failure data
Li, Xiaochuan; Yang, Xiaoyu; Yang, Yingjie; Bennett, Ian; Mba, David (Article)In this work, a novel diagnostic and prognostic framework is proposed to detect faults and predict remaining service life of large-scale rotating machinery in the presence of scarce failure data. In the proposed framework, ... -
A Novel Diagnostic and Prognostic Framework for Incipient Fault Detection and Remaining Service Life Prediction with Application to Industrial Rotating Machines
Li, Xiaochuan; Yang, Xiaoyu; Yang, Yingjie; Ian, Bennett; Mba, David (Article)Data-driven machine health monitoring systems (MHMS) have been widely investigated and applied in the field of machine diagnostics and prognostics with the aim of realizing predictive maintenance. It involves using data ... -
A novel multi-information fusion grey model and its application in wear trend prediction of wind turbines
Yang, Xiaoyu; Fang, Zhigeng; Yang, Yingjie; Mba, David; Li, Xiaochuan (Article)The small and fluctuating samples of lubricating oil data render the wear trend prediction a challenging task in operation and maintenance management of wind turbine gearboxes. To deal with this problem, this paper puts ...