Remaining useful life (RUL) prediction, known as 'prognostics', has long been recognized as
one of the key technologies in prognostics and health management (PHM) to maintain the …

Predictive maintenance for power electronic converters has emerged as a critical area of
research and development. With the rapid advancements in deep-learning techniques, new …

Reliable and accurate aeroengine remaining useful life (RUL) prediction plays a key role in
the aeroengine prognostics and health management (PHM) system. However, due to the …

Physics-informed machine learning (PIML) has been emerging as a promising tool for
applications with domain knowledge and physical models. To uncover its potentials in …

For Prognostics and Health Management (PHM) of Lithium-ion (Li-ion) batteries, many
models have been established to characterize their degradation process. The existing …

Health index (HI) can help equipment maintenance personnel better understand the health
status of equipment. However, how to construct a HI generation model with robust predictive …

Recently, monitoring machine health with artificial intelligence (AI) models becomes more
efficient using either vibration or audio signals. However, the vibration signals of machines …

Remaining useful life (RUL) prediction is crucial in improving the reliability of insulated gate
bipolar transistors (IGBTs) and has attracted widespread attention all over the world. Owing …

Modular multilevel converter (MMC) applied in high-voltage direct current (HVdc) field
consists of numerous submodules (SMs) and supports bidirectional power transfer, leading …

This article proposes a self-data-driven method for remaining useful life prediction of PV
arrays based on self-condition monitoring data considering the uncertainty and volatility …