Sophie Sieg-Zieba

TL;DR: A model of rotating machine signals is introduced which sheds light on the various components to be expected in the squared envelope spectrum, and a critical comparison is made of three sophisticated methods, namely, the improved synchronous average, the cepstrum prewhitening, and the generalized synchronousaverage, used for suppressing the deterministic part.

TL;DR: In this article, an angle-time approach was proposed to analyze bearing fault vibrations and explore its angle ⧹ time cyclostationary property, which preserves the cyclic evolution of the signal while maintaining a temporal description of the system dynamics.

TL;DR: In this article, a generalized synchronous average (GSA) was proposed to extract the deterministic part of a cyclo-non-stationary vibration signal, i.e. the analog of the periodic part of cyclostationary signals.

TL;DR: In this article, a new technique of diagnosing data for broken rotor bars in induction motors derived from two of the three stator currents, the Beirut diagnostic procedure (BDP) is presented.

TL;DR: A systemic and pertinent state-of-art review on WT planetary gearbox condition monitoring techniques on the topics of fundamental analysis, signal processing, feature extraction, and fault detection is provided.

TL;DR: In this paper, a reweighted singular value decomposition (RSVD) strategy is proposed for signal denoising and weak feature enhancement in a two-stage gearbox as well as train bearings.

TL;DR: A broad outlook on rotor fault monitoring techniques for the researchers and engineers can be found in this paper, where the authors review and summarize the recent researches and developments performed in condition monitoring of the induction machine with the purpose of rotor faults detection.

TL;DR: Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping to bearing fault classification is proposed as a robust, parameter free method for race fault detection.

TL;DR: In this paper, a matching synchrosqueezing transform (MSST) was proposed to improve the readability of the TF representation of nonstationary signals composed of multiple components with slow varying instantaneous frequency (IF).