This manuscript provides a detailed synopsis of the contemporary advancements in the
nascent area of real-time structural damage detection for vibrating systems. The paper …

Extracting weak fault features under noise interference is crucial for the fault diagnosis of
rolling bearings at an early stage. In this paper, a new method based on improved ensemble …

The diagnosis of early-stage defects of rolling element bearings (REBs) using vibration
signals is a very difficult task since bearing fault signals are usually weak and masked by …

The number of research papers dealing with vibration-based condition monitoring has been
exponentially growing in recent decades. As a consequence, one may identify some trends …

Most of the existing time series methods of feature extraction involve complex algorithm and
the extracted features are affected by sample size and noise. In this paper, a simple time …

Ball bearings remain one of the most crucial components in industrial machines and due to
their critical role, it is of great importance to monitor their conditions under operation …

Valid and dependable water demand prediction is a major element of the effective and
sustainable expansion of municipal water infrastructures. This study provides a novel …

This paper presents a condition monitoring approach for point machine prognostics to
increase the reliability, availability, and safety in railway transportation industry. The …

Fault diagnosis of rotating machinery is difficult under the strong noisy environment.
Although singular value decomposition (SVD) can remove noise from vibration signals, the …

This study proposes a methodology for rolling element bearings fault diagnosis which gives
a complete and highly accurate identification of the faults present. It has two main stages …