2019
DOI: 10.1177/1475921719861801
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Real-time damage detection of degrading systems

Abstract: In this article, a robust output-only real-time damage detection technique for multi-degree-of-freedom degrading systems using recursive canonical correlation analysis is presented. It has been observed that the impact of damage to a vibrating system gradually advances with time that sustains until the system degrades up to a considerable extent. Of significant interest is the effect of sudden damage in presence of continuous degradation in real-time, which is studied in the form of a sudden stiffness reductio… Show more

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Cited by 17 publications
(17 citation statements)
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References 54 publications
(123 reference statements)
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“…The presented numerical framework and related experiments could thus adapt itself to not just detection hardware [ 40 ] but also for other output-only detection or monitoring frameworks [ 41 , 42 , 43 ], degradation [ 44 ] or understanding of computing demands [ 45 ].…”
Section: Resultsmentioning
confidence: 99%
“…The presented numerical framework and related experiments could thus adapt itself to not just detection hardware [ 40 ] but also for other output-only detection or monitoring frameworks [ 41 , 42 , 43 ], degradation [ 44 ] or understanding of computing demands [ 45 ].…”
Section: Resultsmentioning
confidence: 99%
“…The performance and accuracy of inclinometers have significantly improved, and it is now possible to measure inclinations to microradian (10 −6 rad) accuracy using state-of-the-art sensors (Bruns, 2017;Tripura et al, 2019;Wu & Chuang, 2004;Wyler, 2016).…”
Section: Establishing Sensor Capability For Rotation Measurementmentioning
confidence: 99%
“…For several presented literature applications, storage of reference observations is required. However, recently developed recursive canonical correlation analysis algorithm do not require a reference for accurate assessment [17]. Another approach to ND also relies on a distance metric, but this time the distance is not measured from reference points stored in memory but from a sample's reconstructed version [5,[18][19][20][21].…”
Section: Novelty Detection In Condition Monitoringmentioning
confidence: 99%