Fault diagnosis is an important means to ensure the safe and reliable operation of
mechanical equipment. In machinery fault diagnosis, collecting and mining the potential fault …

The predictive maintenance of electrical machines is a critical issue for companies, as it can
greatly reduce maintenance costs, increase efficiency, and minimize downtime. In this …

Since loosening of the bolt connection reduce the stability and working accuracy of industrial
robot joint, developing and applying new detection methods to provide effective and reliable …

Abstract Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized
by difficulties in social communication and repetitive and stereotyped behaviors. According …

The instantaneous frequency (IF)-based post-processing methods, synchrosqueezing and
synchroextracting, can accurately characterize the time-varying frequency and amplitude of …

This study examines the impact of the mother wavelet, sensor selection, and machine
learning (ML) models for smart fault diagnosis of rotating machines via discrete wavelet …

In the real world, most signals encountered are nonstationary. It is essential to extract a time–
frequency (TF) characteristics in such signals for the accurate description. Two parameters …

Time–frequency analysis methods can be used to characterize the time-varying
characteristics of a signal. The postprocessing algorithm further enhances this ability. The …

The flexible thin-wall bearing, characterized by different kinematic attributes and fault
characteristic frequency in comparison to rolling bearings, introduces a great challenge in …

The fractional Fourier transform can transform the signal or function into any intermediate
domain between time and frequency domains called fractional Fourier domain, in which the …