Estimating Faults Modes in Ball Bearing Machinery using a Sparse Reconstruction Framework*. Juhlin, M., Swärd, J., Pesavento, M., & Jakobsson, A. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 2330-2334, Sep., 2018. doi abstract bibtex In this work, we present a computationally efficient algorithm for estimating fault modes in ball bearing systems. The presented method generalizes and improves upon earlier developed sparse reconstruction techniques, allowing for detecting multiple fault modes. The measured signal is corrupted with additive and multiplicative noise, yielding a signal that is highly erratic. Fortunately, the damaged ball bearings give rise to strong periodical structures which may be exploited when forming the proposed detector. Numerical simulations illustrate the preferred performance of the proposed method.
@InProceedings{8552950,
author = {M. Juhlin and J. Swärd and M. Pesavento and A. Jakobsson},
booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
title = {Estimating Faults Modes in Ball Bearing Machinery using a Sparse Reconstruction Framework*},
year = {2018},
pages = {2330-2334},
abstract = {In this work, we present a computationally efficient algorithm for estimating fault modes in ball bearing systems. The presented method generalizes and improves upon earlier developed sparse reconstruction techniques, allowing for detecting multiple fault modes. The measured signal is corrupted with additive and multiplicative noise, yielding a signal that is highly erratic. Fortunately, the damaged ball bearings give rise to strong periodical structures which may be exploited when forming the proposed detector. Numerical simulations illustrate the preferred performance of the proposed method.},
keywords = {ball bearings;compressed sensing;fault diagnosis;signal reconstruction;sparse reconstruction techniques;multiple fault modes;ball bearing systems;sparse reconstruction framework;ball bearing machinery;strong periodical structures;damaged ball bearings;multiplicative noise;additive noise;Harmonic analysis;Ball bearings;Frequency modulation;Signal processing algorithms;Europe;Ball bearing systems;sparse reconstruction;convex optimization;ADMM},
doi = {10.23919/EUSIPCO.2018.8552950},
issn = {2076-1465},
month = {Sep.},
}
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