2020
DOI: 10.1109/access.2020.2970086
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Automatic Process Parameters Tuning and Surface Roughness Estimation for Laser Cleaning

Abstract: An image analysis-based two-stage process parameters tuning and Surface Roughness (SR) estimation algorithm is proposed for the laser cleaning application. A Cartesian coordinate robot is utilized to collect image and implement cleaning. Before cleaning, in order to tune the proper laser parameters, first, the environment lighting is controlled for the metal image collection. Second, lots of classification features are computed for the images above. The Gray-Level Co-occurrence Matrix (GLCM) texture features, … Show more

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Cited by 6 publications
(5 citation statements)
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“…Besides, the authors in [48] analyzed the relationship between the homogeneity and contrast parameters of GLCM and surface roughness, and a roughness regression model was constructed by the polynomial fitting (Method 2). In addition, we also used the Tamura coarseness, GLCM, and concavo-convex region features to construct the SVR roughness-estimation model in our previous work [25] (Method 3). Therefore, we conduct a comparative experiment under the same experimental conditions as Section 3.3, and the corresponding experimental results are shown in Table 18.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Besides, the authors in [48] analyzed the relationship between the homogeneity and contrast parameters of GLCM and surface roughness, and a roughness regression model was constructed by the polynomial fitting (Method 2). In addition, we also used the Tamura coarseness, GLCM, and concavo-convex region features to construct the SVR roughness-estimation model in our previous work [25] (Method 3). Therefore, we conduct a comparative experiment under the same experimental conditions as Section 3.3, and the corresponding experimental results are shown in Table 18.…”
Section: Discussionmentioning
confidence: 99%
“…In our previous research work, we successfully built an experimental system for a Q235 carbon steel workpiece cleaning with a Cartesian robot as a core, supplemented by a visible-light camera and a fiber laser for image acquisition and laser cleaning [25]. In our experimental system, the Cartesian robot was equipped with the same motor in the x-axis and y-axis degrees of freedom to ensure that it had the same moving speed in two moving directions.…”
Section: Introductionmentioning
confidence: 99%
“…Third, the product quality data package can be formed according to RC prediction results to judge whether the products are qualified or unqualified. To improve the automation level of system, both the femtosecond laser and SEM can be installed into an integrated device (see [12]). The proposed method at least has three merits.…”
Section: Discussionmentioning
confidence: 99%
“…In this paper, a blackening effect estimation, i.e., the RC estimation of femtosecond laser surface processing is proposed. First, the femtosecond laser processing is performed and the laser process parameters [12] are saved. Second, after laser processing, the ablation diameters of femtosecond laser are measured by typical SEM images.…”
Section: Introductionmentioning
confidence: 99%
“…In [12], a coupling algorithm of dynamic threshold location was proposed to solve the problem of uneven illumination on the material surface and separate the qualified area from the unqualified area. In [13], a method of surface roughness estimation based on image analysis was proposed. The authors used the machine vision method to judge the effect of laser cleaning and determine whether the cleaning performance was qualified.…”
Section: Introductionmentioning
confidence: 99%