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Flight Simulation Training Devices: Application, Classification, and Research
Jelena Vidakovic,Mihailo Lazarevic,Vladimir Kvrgic,Ivana Vasovic Maksimovic,Aleksandar Rakic 한국항공우주학회 2021 International Journal of Aeronautical and Space Sc Vol.22 No.4
Safe and efficient training using flight simulation training devices (FSTD) is one of the fundamental components of training in the commercial, military, and general aviation. When compared with the live training, the most significant benefits of ground trainers include improved safety and the reduced cost of a pilot training process. Flight simulation is a multidisciplinary subject that relies on several research disciplines which have a tendency to be investigated separately and in parallel with each other. This paper presents a comprehensive overview of the research within the FSTD domain with a motivation to highlight contributions from separate research topics from a general aspect, which is necessary as FSTD is a complex man–machine system. Application areas of FSTD usage are addressed, and the terminology used in the literature is discussed. Identification, classification, and overview of major research fields in the FSTD domain are presented. Specific characteristics of FSTD for fighter aircraft are discussed separately.
Condition monitoring of a steam turbine generator using wavelet spectrum based control chart
Bae, Suk Joo,Mun, Byeong Min,Chang, Woojin,Vidakovic, Brani Elsevier 2019 Reliability engineering & system safety Vol.184 No.-
<P><B>Abstract</B></P> <P>Condition-based maintenance (CBM) is designed to take maintenance actions only when there is an imminent evidence of failure for a monitoring system. The parameters indicating health status of the system are continuously monitored in CBM. This article proposes a condition monitoring scheme based on energy profiles generated from wavelet spectrum analysis. The energy of time series is represented by a wavelet spectrum in scale representations of signals. After deriving wavelet spectrums using a discrete wavelet transform at pre-specified windows, we aim to monitor the system based on multivariate <I>T</I> <SUP>2</SUP> chart for the parameters in the linear energy profiles. The monitoring scheme is applied to temperature signals measured from a steam turbine generator. The proposed <I>T</I> <SUP>2</SUP> chart based on the energy profiles shows a potential in early detecting the abnormality of a monitoring system which is not clearly detectable in original time scales.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Propose a condition monitoring scheme based on energy profiles generated from wavelet spectrum analysis. </LI> <LI> Monitor the system based on multivariate <I>T</I> <SUP>2</SUP> chart for the parameters in the linear energy profiles. </LI> <LI> The proposed approach is applied to temperature signals measured from a steam turbine generator. </LI> </UL> </P>