130 citations · 270 across the 11 of their papers we have counts for
11 papers
A method for signal components identification in acoustic signal with non-Gaussian background noise using clustering of data in time-frequency domain
A Drewnicka, A Michalak, R Zimroz +3
This paper presents a novel method for fault detection in vibration/acoustic signals contaminated with non-Gaussian noise, specifically addressing the challenge of random impulsive…
Robust correlation measures for informative frequency band selection in heavy-tailed vibration signal
Justyna Hebda-Sobkowicz, Radosław Zimroz, Anil Kumar +1
Vibration signals are commonly used to detect local damage in rotating machinery. However, raw signals are often noisy, particularly in crusher machines, where the technological pr…
Identification of fault frequency variation in the envelope spectrum in the vibration-based local damage detection in possible changing load/speed conditions
Daniel Kuzio, Radosław Zimroz, Agnieszka Wyłomańska
The problem of local damage diagnosis (based on the detection of impulsive and periodic signals) is discussed. Both features should be checked, as fault frequency must be linked to…
Modified Greenwood statistic and its application for statistical testing
Katarzyna Skowronek, Marek Arendarczyk, Radosław Zimroz +1
In this paper, we explore the modified Greenwood statistic, which, in contrast to the classical Greenwood statistic, is properly defined for random samples from any distribution. T…
An Adaptive feature mode decomposition based on a novel health indicator for bearing fault diagnosis
Sumika Chauhan, Govind Vashishtha, Rajesh Kumar +2
The vibration analysis of the bearing is very crucial because of its non-stationary nature and low signal-to-noise ratio. Therefore, a novel scheme for detecting bearing defects is…
Bearing damage detection with orthogonal and non-negative low-rank feature extraction
Mateusz Gabor, Rafal Zdunek, Agnieszka Wylomanska +1
Local damage of bearings can be detected as a weak cyclic and impulsive component in a highly noisy measured signal. A key problem is how to extract the signal of interest (SOI) fr…
Non-negative tensor factorization for vibration-based local damage detection
Mateusz Gabor, Rafal Zdunek, Radoslaw Zimroz +2
In this study, a novel non-negative tensor factorization (NTF)-based method for vibration-based local damage detection in rolling element bearings is proposed. As the diagnostic si…
Non-negative matrix underapproximation as optimal frequency band selector
Mateusz Gabor, Rafal Zdunek, Radoslaw Zimroz +1
Time-frequency representation (TFR) is often used for non-stationary signal analysis. The most intuitive and interpretable TFR is the spectrogram. Recently, a concept of non-negati…
Assessment of background noise properties in time and time-frequency domains in the context of vibration-based local damage detection in real environment
Katarzyna Skowronek, Tomasz Barszcz, Jerome Antoni +2
Any measurement in condition monitoring applications is associated with disturbing noise. Till now, most of the diagnostic procedures have assumed the Gaussian distribution for the…
Non-parametric Ensemble Empirical Mode Decomposition for extracting weak features to identify bearing defects
Anil Kumar, Yaakoub Berrouche, Radosław Zimroz +5
A non-parametric complementary ensemble empirical mode decomposition (NPCEEMD) is proposed for identifying bearing defects using weak features. NPCEEMD is non-parametric because, u…
Identification and validation of periodic autoregressive model with additive noise: finite-variance case
Wojciech Żuławiński, Aleksandra Grzesiek, Radosław Zimroz +1
In this paper, we address the problem of modeling data with periodic autoregressive (PAR) time series and additive noise. In most cases, the data are processed assuming a noise-fre…