We propose a new fault diagnosis model for rolling bearings based on a hybrid kernel
support vector machine (SVM) and Bayesian optimization (BO). The model uses discrete …

Concerning the problems of harrowing extraction and poor classification accuracy of fault
features in rolling bearing vibration signals, a fault feature selection and classification …

In this paper we present the Physics-Aware Deep-NMF (PAD-NMF) algorithm and we apply
it to hit detection in mechanical systems from audio mixtures. The algorithm accurately …

On top of the condition-based maintenance (CBM) practice for rotating machinery, the robust
estimation of remaining useful life (RUL) for rolling-element bearings (REB) is of particular …

Cyclic spectral coherence (CSCoh) is an effective tool to reveal the cyclostationarity of the
fault-induced components (FICs). Integrating CSCoh over the domain of the spectral …

Condition monitoring and fault diagnosis are topics of growing interest for improving the
reliability of modern industrial systems. As critical structural components, anti-friction …

Bearings are pivotal components of rotating machines where any defects could propagate
and trigger systematic failures. Once faults are detected, accurately predicting remaining …

Industry 5.0 advocates for a sustainable industry, particularly in terms of energy. One of the
most fundamental elements of comprehension is knowing when the systems are operated …

Data-driven fault diagnosis, identifying abnormality causes using collected industrial data, is
one of the challenging tasks for intelligent industry safety management. It is worth noting that …

The cross-domain diagnosis of tie rod bolt loosening is essential for guaranteeing the
healthy operation of rod-fastening rotor (RFR) systems. The unsupervised domain …