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    A Data Driven Mode Identification Algorithm for Riser Fatigue Damage Assessment

    Source: Journal of Offshore Mechanics and Arctic Engineering:;2014:;volume( 136 ):;issue: 003::page 31702
    Author:
    Shi, C.
    ,
    Park, J.
    ,
    Manuel, L.
    ,
    Tognarelli, M. A.
    DOI: 10.1115/1.4027292
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A wellestablished empirical procedure, which we refer to as weighted waveform analysis (WWA), is employed to reconstruct a model riser's response over its entire length using a limited number of strain measurements. The quality of the response reconstruction is controlled largely by identification of the participating riser response modes (waveforms); hence, mode selection is vital in WWA application. Instead of selecting a set of consecutive riser vibratory modes, we propose a procedure that automatically identifies a set of nonconsecutive riser modes that can thus account for higher harmonics in the riser response (at multiplies of the Strouhal frequency). Using temporal data analysis of the discrete timestamped samples, significant response frequencies are identified on the basis of power spectrum peaks; similarly, using the spatial data analysis of the sparse nonuniformly sampled data, significant wavenumbers are identified using Lomb–Scargle periodograms. Knowing the riser length, the most important wavenumber is related to a specific mode number; this dominant mode is, in turn, related to the dominant peak in power spectra based on the temporal data analysis. The riser's fundamental frequency is estimated as the ratio of the empirically estimated dominant spectral frequency to the dominant mode number. Additional mode numbers are also identified as spectral peak frequencies divided by the fundamental frequency. This mode selection technique is an improvement over similar WWA procedures that rely on a priori knowledge of the riser's fundamental frequency or on the knowledge of the physical properties and assumptions on added mass contributions. At selected target locations, we compare fatigue damage rates, estimated based on the riser response reconstructed using the WWA method with the proposed automated mode selection technique (we refer to this as the “improvedâ€‌ WWA) and those based on the “originalâ€‌ WWA method (that relies on a theoretically computed fundamental natural frequency of the riser). In both cases, predicted fatigue damage rates based on the empirical methods and data at various locations (other than the target) are crossvalidated against damage rates based directly on measurements at the target location. The results show that the improved WWA method, which empirically estimates the riser's fundamental natural frequency and automatically selects significant modes of vibration, may be employed to estimate fatigue damage rates quite well from limited strain measurements.
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      A Data Driven Mode Identification Algorithm for Riser Fatigue Damage Assessment

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    http://yetl.yabesh.ir/yetl1/handle/yetl/156066
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    • Journal of Offshore Mechanics and Arctic Engineering

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    contributor authorShi, C.
    contributor authorPark, J.
    contributor authorManuel, L.
    contributor authorTognarelli, M. A.
    date accessioned2017-05-09T01:11:44Z
    date available2017-05-09T01:11:44Z
    date issued2014
    identifier issn0892-7219
    identifier otheromae_136_03_031702.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/156066
    description abstractA wellestablished empirical procedure, which we refer to as weighted waveform analysis (WWA), is employed to reconstruct a model riser's response over its entire length using a limited number of strain measurements. The quality of the response reconstruction is controlled largely by identification of the participating riser response modes (waveforms); hence, mode selection is vital in WWA application. Instead of selecting a set of consecutive riser vibratory modes, we propose a procedure that automatically identifies a set of nonconsecutive riser modes that can thus account for higher harmonics in the riser response (at multiplies of the Strouhal frequency). Using temporal data analysis of the discrete timestamped samples, significant response frequencies are identified on the basis of power spectrum peaks; similarly, using the spatial data analysis of the sparse nonuniformly sampled data, significant wavenumbers are identified using Lomb–Scargle periodograms. Knowing the riser length, the most important wavenumber is related to a specific mode number; this dominant mode is, in turn, related to the dominant peak in power spectra based on the temporal data analysis. The riser's fundamental frequency is estimated as the ratio of the empirically estimated dominant spectral frequency to the dominant mode number. Additional mode numbers are also identified as spectral peak frequencies divided by the fundamental frequency. This mode selection technique is an improvement over similar WWA procedures that rely on a priori knowledge of the riser's fundamental frequency or on the knowledge of the physical properties and assumptions on added mass contributions. At selected target locations, we compare fatigue damage rates, estimated based on the riser response reconstructed using the WWA method with the proposed automated mode selection technique (we refer to this as the “improvedâ€‌ WWA) and those based on the “originalâ€‌ WWA method (that relies on a theoretically computed fundamental natural frequency of the riser). In both cases, predicted fatigue damage rates based on the empirical methods and data at various locations (other than the target) are crossvalidated against damage rates based directly on measurements at the target location. The results show that the improved WWA method, which empirically estimates the riser's fundamental natural frequency and automatically selects significant modes of vibration, may be employed to estimate fatigue damage rates quite well from limited strain measurements.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Data Driven Mode Identification Algorithm for Riser Fatigue Damage Assessment
    typeJournal Paper
    journal volume136
    journal issue3
    journal titleJournal of Offshore Mechanics and Arctic Engineering
    identifier doi10.1115/1.4027292
    journal fristpage31702
    journal lastpage31702
    identifier eissn1528-896X
    treeJournal of Offshore Mechanics and Arctic Engineering:;2014:;volume( 136 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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