With the continuous improvement in human awareness of environmental protection, energy
savings, and emission reduction, as well as the vigorous development of precision …

Noise in the data is one of the main cause of model performance drop. Denoising is
therefore a critical step in most data pipelines. In this paper we propose to fuse the learning …

A framework aimed to improve the bearing-fault diagnosis accuracy using a hybrid feature-
selection method based on Wrapper-WPT is proposed in this paper. In the first step, the …

Acoustic detection technology is a new method for early monitoring of wood-boring pests,
and the effective denoising methods are the premise of acoustic detection in forests. This …

In order to improve the accuracy of engine valve clearance fault diagnosis, in this study, a
fault identification algorithm based on wavelet packet decomposition and an artificial neural …

In-pipe inspection is an important means to ensure the safety of oil pipelines. External
positioning technology of the internal detector is a vital component of the pipeline detection …

The performance of sparse decomposition is directly determined by the similarity between
impact atoms and the actual fault impact waveform. The shift-invariant K-singular value …

Real-time and accurate fault diagnosis for permanent magnet synchronous motor (PMSM) is
crucial because interturn short fault (ISF) can disrupt its normal operation. This paper …

To solve the problem of difficulty in fault feature extraction for rolling bearings under strong
noise conditions, a K-value calculation method of variational mode decomposition (VMD) …

A three-band infrared flame sensor is designed and experimentally investigated for the
analysis of infrared signals from three radiation sources (Flame, man and ambient). The …