Multiscale Poincaré plot analysis of time series from laser speckle contrast imaging data

Humeau-Heurtier, Anne; Hunault, Gilles; Gascoin, Lydie; Ábrahám, Pierre

doi:10.1016/j.bspc.2017.07.003

Cited by 3 publications

(3 citation statements)

References 62 publications

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“…Step 2: The multiscale time series Σ s (j) are obtained by the coarse-grained time series using a non-overlapping moving average low-pass filter with a certain window length [22].…”

Section: Signal Processing Using Mmsppmentioning

confidence: 99%

“…Information on the external magnetic leakage signal in the PP can be quantified using the indices SD1 and SD2 under multiscale conditions [19,22]. Furthermore, the ratio SD2/SD2 and the area of the fitting ellipse (AFE) can be further obtained.…”

Section: Signal Processing Using Mmsppmentioning

confidence: 99%

“…In contrast to conventional and entropy-based approaches, multiscale poincare plots (MSPP) [22] and generalized multiscale poincare plots (GMPOP) [19], as novel nonlinear methods, were recently proposed and developed based on the poincare plot (PP) [23,24], exhibiting a preference for extracting valuable insights from the underlying structural characteristics. The GMPOP [19] is achieved through comparative quantification and visualization [20], to explore the temporal nuances of signals and their associated dynamic changes during periods of degradation.…”

Section: Introductionmentioning

confidence: 99%

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Incipient fault detection and condition assessment in DFIGs based on external leakage flux sensing and modified multiscale poincare plots analysis

Zhao,

Chen,

Liang

et al. 2023

Meas. Sci. Technol.

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Although doubly fed induction generators (DFIG) are widely used, difficulties in early fault detection and severity assessment for inter-turn short-circuit (ITSC) faults are highly prominent. In this manuscript, a novel incipient fault detection and state assessment method based on external leakage flux sensing and modified multiscale poincare plots (MMSPP) is proposed. An external leakage flux sensor is placed on the axial-end position of the generator to monitor the presence and evolution of ITSC faults. Multiscale poincare mapping is a novel nonlinear tool that is further developed and modified using the normal cumulative distribution function (NCDF) and multiscale computing methods to capture the behavior evolution and changes in the generator’s external leakage flux signals. The healthy indicator is based on the analysis of elliptical orbit features extracted from modified multiscale poincare plots, established by support vector data description (SVDD) with parameter optimization. The effectiveness of the proposed method was implemented and verified under an experimental environment on a 100 kW DFIG platform to detect incipient inter-turn short circuits (mainly considering the two-turn ITSC) and evaluate the performance degradation (three- to eight-turn ITSC) with 0%, 50%, and 100% different load conditions. The experimental results showed the viability of the approach and fault indicator for incipient fault detection and condition assessment of the wind generator’s low inter-turn insulation faults and for relative quantification of inter-turn short-circuit fault severity.

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“…Step 2: The multiscale time series Σ s (j) are obtained by the coarse-grained time series using a non-overlapping moving average low-pass filter with a certain window length [22].…”

Section: Signal Processing Using Mmsppmentioning

confidence: 99%

Section: Signal Processing Using Mmsppmentioning

confidence: 99%