Relevance of Wavelet Shape Selection in a complex signal

Bigerelle, Maxence; Guillemot, Gildas; Khawaja, Zahra; Mansori, Mohamed El; Antoni, Jérôme

doi:10.1016/j.ymssp.2013.07.001

Cited by 14 publications

(15 citation statements)

References 38 publications

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“…The topographic profile of the abraded surface can be seen as the superposition of a unique elementary pattern that physically represents the footprint of the elementary mechanical process that creates the abrasion of the surface [18,19] (Fig. 8).…”

Section: Influence Of Wavelet Shape and Decomposition Levels On Wavelmentioning

confidence: 99%

“…6 and 7), but it is obvious that, in this case, the representation of surface features will became sparse and each pertinent information will be diluted between several wavelet scales and spatial Fig. 8 Schematic representation of groove and ridge profiles generated by individual abrasive grit [19] positions, thus making it difficult to properly detect all the textural characteristics.…”

Section: Influence Of Wavelet Shape and Decomposition Levels On Wavelmentioning

confidence: 99%

“…However, one of the major limitations is the difficulty of the choice of the optimal mother wavelet function and decomposition levels [18,19]. In fact, this choice can influence the spatial and frequency resolution of the decomposition, which is directly proportional to the width of the used wavelet in the spatial and the Fourier space [20].…”

Section: Introductionmentioning

confidence: 99%

“…Further, the authors demonstrate that the regularity that is useful for getting nice features such as smoothness of the reconstructed signal or image is a fundamental property of the wavelet family for the topographic profile analysis goal. In another study, Bigerelle et al show, by comparison of eight wavelet functions based on a statistical indicator, that the analysis of the topographic profile of abraded surfaces leads to the same spatial localization regardless of the parameters of the abrasive process and the wavelet shapes [19]. It appears from literature that there is not yet a universal methodology or criterion allowing the identification of relevant wavelet function, but it can be remarked that all approaches take into consideration the quality of data reconstruction from all its components.…”

Section: Introductionmentioning

confidence: 99%

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Identification of relevant wavelet functions for multiscale characterization of manufactured surfaces using a genetically optimized neural network

Mezghani

2018

Int J Adv Manuf Technol

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Multiscale surface characterization is a powerful tool that is used for process monitoring, surface quality control, and manufacturing optimization by establishing a link between process variables and functional performances. The multiscale decomposition approach using continuous and discrete wavelets is widely applied to take into account scales dependency. However, the optimal choice of the analysis wavelet function and the number of decomposition level is still a big issue. In this article, the artificial neural network theory was combined with the wavelet concept and was optimized based on the genetic algorithm to identify the relevant wavelet function for multiscale characterization of abraded surface topographies. Then, an extensive wavelet function library was developed and the proposed algorithm was applied to topographic data obtained from various abrasive finishing processes. The results show the pertinence of this approach to select the relevant wavelet, and a universal relevant wavelet function for abraded surface characterization was determined.

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Section: Influence Of Wavelet Shape and Decomposition Levels On Wavelmentioning

confidence: 99%

Section: Influence Of Wavelet Shape and Decomposition Levels On Wavelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identification of relevant wavelet functions for multiscale characterization of manufactured surfaces using a genetically optimized neural network

Mezghani

2018

Int J Adv Manuf Technol

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“…Moreover, the relevance to characterize the appropriate scales of surface finish by abrasion does not depend on the shape of the wavelet, as demonstrated in [9]. Subsequently, the decomposition using the "db2" wavelet is considered.…”

Section: Multiscale Surface Finish Analysismentioning

confidence: 99%

Multiscale assessment of structured coated abrasive grits in belt finishing process

Serpin

Mezghani

Mansori

2015

Wear

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a b s t r a c tThis paper outlines the link between grit morphology and surface roughness of belt-finished workpieces. It features a comparative analysis of a new generation of abrasive belts with diverse abrasive structures, and a multi-scale roughness characterization of abrasive belt wear on a variety of finished surfaces. The ultimate thickness of the mechanically deformed layer and surface profile projections depends, to a great extent, on the abrasive mechanisms of friction and wear employed in the finishing process. By modifying the physical mechanisms (cutting, plowing or sliding), it is possible to achieve a concomitant change in the rate of material removal and, consequently, to the specific surface roughness of the finished parts.Our research shows that the active roughness scale resulting from belt finishing is strongly dependent on the grit orientation and the binder distribution. The results are promising for increasing the efficiency of the abrasion processes and for improving the surface texturing of finished parts.

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