Background The development of fast, efficient, accurate, and reliable techniques and
methods for food authenticity identification is crucial for food quality assurance. Traditional …

Generative adversarial networks (GANs) have recently attracted attention owing to their
impressive ability in generating high-quality and novel synthetic datasets such as signals …

The detection of faulty bearings is an essential step in guaranteeing the safe and efficient
operation of rotating machinery. Bearings, which also transmit the loads and pressures …

Sparsity-based fault diagnosis methods have achieved great success. However, fault
classification is still challenging because of neglected potential knowledge. This paper …

Rotating machinery (eg rolling bearings and gearboxes) is usually operated in high-risk and
vulnerable environments such as time-varying loads and poor lubrication. Timely …

Multi-instance learning (MIL) is a generalized form of supervised learning that attempts to
extract useful information from sets of instances, known as bags. In practice, besides positive …

The key components of the rotating machinery, such as gears and bearings, are prone to
damage owing to long-term complex and harsh working situations. This study investigates …

Modern businesses use machines extensively, which are essential for running factories. The
machinery must be carefully monitored as it will suffer enormous losses if it suddenly breaks …

This article investigates the fault characteristic frequency extraction from the noisy vibration
signal for bearing fault diagnosis. Although sparse representation (SR) approaches are …

In this paper, a method for orthogonal tensor recovery based on non-convex regularization
and rank estimation (OTRN-RE) is proposed, which aims to accurately recover the low-rank …