Rotating machinery plays a vital role in the industrial sector, and ensuring its health status is
crucial for operational efficiency and safety. The construction of accurate health indicators …

As industrial cyber-physical systems (ICPS) play an increasingly pivotal role in the new
industrial paradigm, their sustainability has become the current research focus. Remaining …

The full-life data of machine is complex and abundant, requiring specialized and deep
predictive models for accurate forecasts. However, achieving high prediction accuracy often …

To accurately predict the remaining useful life (RUL) of rotating machinery while
continuously providing the task data, a novel continuous RUL prediction methodology was …

Although the maritime industry has the potential to lead smart maintenance methodologies,
current maintenance routines within the sector focus on either reactive or preventive …

Data-driven methods based on deep learning have achieved satisfactory results in the field
of health prognosis. However, the current network modeling still stays in the real number …

Gears, as indispensable components of machinery, demand accurate prediction of their
Remaining Useful Life (RUL). To enhance the utilization of ordered information within time …

Accurate and science-based prediction of bearing performance degradation has been a
principal concern and a critical challenge issue in the sector of Prognostics and Health …

Accurately and effectively predicting the Remaining Useful Life (RUL) of bearings in extreme
environments is crucial for efficient operations and maintenance. To improve the …

Accurately predicting remaining useful life (RUL) can help to make maintenance plans in
advance. Recently, machinery labelled end-to-end RUL prediction based on data-driven …