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Candy JV, Franco SN, Ruggiero EL, et al. Anomaly detection for a vibrating structure: A subspace identification/tracking approach. J Acoust Soc Am. 2017;142(2):680doi: 10.1121/1.4996142.
Candy, J. V., Franco, S. N., Ruggiero, E. L., Emmons, M. C., Lopez, I. M., & Stoops, L. M. (2017). Anomaly detection for a vibrating structure: A subspace identification/tracking approach. The Journal of the Acoustical Society of America, 142(2), 680. https://doi.org/10.1121/1.4996142
Candy, J V, et al. "Anomaly detection for a vibrating structure: A subspace identification/tracking approach." The Journal of the Acoustical Society of America vol. 142,2 (2017): 680. doi: https://doi.org/10.1121/1.4996142
Candy JV, Franco SN, Ruggiero EL, Emmons MC, Lopez IM, Stoops LM. Anomaly detection for a vibrating structure: A subspace identification/tracking approach. J Acoust Soc Am. 2017 Aug;142(2):680. doi: 10.1121/1.4996142. PMID: 28863574.
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J Acoust Soc Am. 2017 Aug;142(2):680. doi: 10.1121/1.4996142.

Anomaly detection for a vibrating structure: A subspace identification/tracking approach.

The Journal of the Acoustical Society of America

J V Candy, S N Franco, E L Ruggiero, M C Emmons, I M Lopez, L M Stoops

Affiliations

  1. Lawrence Livermore National Laboratory, P.O. Box 808, L-151, Livermore, California 94551, USA.

PMID: 28863574 DOI: 10.1121/1.4996142

Abstract

Mechanical devices operating in noisy environments lead to low signal-to-noise ratios creating a challenging signal processing problem to monitor the vibrational signature of the device in real-time. To detect/classify a particular type of device from noisy vibration data, it is necessary to identify signatures that make it unique. Resonant (modal) frequencies emitted offer a signature characterizing its operation. The monitoring of structural modes to determine the condition of a device under investigation is essential, especially if it is a critical entity of an operational system. The development of a model-based scheme capable of the on-line tracking of structural modal frequencies by applying both system identification methods to extract a modal model and state estimation methods to track their evolution is discussed along with the development of an on-line monitor capable of detecting anomalies in real-time. An application of this approach to an unknown structural device is discussed illustrating the approach and evaluating its performance.

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