Designing Machine Learning Model for Predictive Maintenance of Railway Vehicle

Platform health management for aircraft maintenance – a review

“…Weber and Schütte 133 Big data and cognitive computing AI is the study of attempting to teach robots to utilise language, develop abstractions and concepts, and solve issues that are currently reserved for humans (p. 3). 145 DL System level Fault diagnosis Hermawan et al 146 CNN, LSTM System level RUL Putra et al 73 ML Vehicle level RUL Markridis et al 72 ML Vehicle level Fault diagnosis Chen et al 147 DCNN, NB Vehicle level Fault diagnosis Ezhilirasu and Jennions 74 ML Vehicle level Fault diagnosis intelligence (AI), the selection of AI techniques should be based on the desired outcomes. It is crucial to think about the intended results and select the AI techniques that are most likely to achieve them in order to successfully apply AI in maintenance.…”

“…The focus of IVHM was at the LRU level until it gravitated towards the subsystems/systems level. 71 There has been a shift towards the vehicle level, 72,73 where the advantage over component level diagnostics is evident. Ezhilarasu and Jennions 74 tackled health management at the vehicle level, using digital twins and a reasoning layer, to detect faults, their origin as well as their interaction effects.…”

“…83 In this way, from Figure 3, the health of components will be propagated to the subsystem level, the system level, and then to the platform. Health results reflect the health state of components and are typically referred to as health index as it was used in Kamtsiuris 12 for developing a health index framework, Khan et al 79 for health index behaviour based on vehicle level reasoning, and Yin et al 103 for constructing a health index for aircraft ECS. The potential to apply AI in a platform solution can be seen in how it has, for example, through the application of Physics-Informed Neural Networks (PINNs); which belong to a group of neural networks that, in both their design and training, take into account physical principles and limitations, been applied in areas like modelling cumulative damage (fatigue crack) in airplanes 104 and machine degradation assessment.…”

Predictive-Adaptive Maintenance Applied for Optimizing the Performance of Industrial Electrical Systems and Equipment

“…Spectral analysis is equivalent to transforming information from amplitude-time terms into amplitude-frequency terms, but in a more compact manner. It should be noted that graphically, this is represented in decibels (dB) as a function of the frequency spectrum [24,25].…”

“…This signal is then transmitted to the spectrum analyzer. In an ideal scenario, the current waveform is a pure sine wave, but this waveform contains numerous harmonics [6,25]. The frequency range of interest in the spectral analysis of currents is typically between 0-5 kHz.…”