Automatized computer system for evaluation of rust using modified single-scale retinex

Vorobel, Roman; Ivasenko, Iryna; Berehulyak, Olena

doi:10.1109/ukrcon.2017.8100401

Cited by 10 publications

(4 citation statements)

References 8 publications

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“…Nowadays, image processing is widely used in the inspection of objects of critical infrastructure due to its ability to provide both qualitative and quantitative assessments of the condition of inspected objects [77]. Moreover, the automation of the inspection process based on image processing leads to an increase in the degree of objectivity compared to expert evaluation [78,79]. With the development and widespread use of digital methods of image acquisition, the application of image processing methods has become widespread in both destructive [80][81][82] and non-destructive [83,84] testing.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Degree of Degradation of Brake Pad Friction Surfaces Using Image Processing

Mandziy,

Ivasenko,

Berehulyak

et al. 2024

Lubricants

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The improvement of drilling rig systems to ensure a reduction in unproductive time spent on lowering and lifting operations for replacing drilling tools and restoring the performance of drilling equipment units is an important task. At the same time, considerable attention is paid to the reliable and efficient operation of the braking systems of drilling rig winches. In the process of operation, the polymer pads periodically come into contact with the outer cylindrical surface of the metal pulley during braking, work in extreme conditions and wear out intensively, so they need periodic replacement. Tests were carried out on a modernized stand and in industrial conditions for the brakes of drilling winches. A methodology for evaluating the degradation of the brake pad friction surface during its operation is proposed. The assessment of the degradation degree is carried out based on the image of the brake pad surface using image processing techniques. Geometric transformations of the input image were performed to avoid perspective distortions caused by the concave shape of the brake pads and the spatial angle at which the image is acquired to avoid glares. The crack detection step was implemented based on the scale-space theory, followed by contour detection and skeletonization. The ratios of the area and perimeter of segmented and skeletonized cracks to the total area were chosen as integral characteristics of the degradation degree. With the help of scanning electron microscopy, the character of the destruction of the friction surface and the degradation of the polymer material was investigated. Experimental studies were performed, and the application of the proposed method is illustrated.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the Degree of Degradation of Brake Pad Friction Surfaces Using Image Processing

Mandziy,

Ivasenko,

Berehulyak

et al. 2024

Lubricants

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“…Our previous works [ 70 , 71 , 72 , 73 , 74 ] were dedicated to rust damage segmentation under conditions that can distort its damage percentage assessment. They were focused on the detection of one type of damage—rust.…”

Section: Introductionmentioning

confidence: 99%

“…They were focused on the detection of one type of damage—rust. In particular, rust detection based on HSV image color model [ 71 ], the use of the single-scaled retinex method [ 72 ], the influence of color restoration based on a color checker [ 73 ], and the reduction of shadow effects [ 74 ] algebraic model with an asymmetric characteristic [ 75 ] and methods of logarithmic type image processing [ 76 ] as well as the application of inhomogeneity inforced piecewise smooth model [ 77 ] for image segmentation were considered. A dimensionality reduction PCA technique was applied in [ 78 ] for the rust segmentation in images obtained in irregular lighting conditions.…”

Section: Introductionmentioning

confidence: 99%

Multiclass Level-Set Segmentation of Rust and Coating Damages in Images of Metal Structures

Bembenek

Mandziy

Ivasenko

et al. 2022

Sensors

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This paper describes the combined detection of coating and rust damages on painted metal structures through the multiclass image segmentation technique. Our prior works were focused solely on the localization of rust damages and rust segmentation under different ambient conditions (different lighting conditions, presence of shadows, low background/object color contrast). This paper method proposes three types of damages: coating crack, coating flaking, and rust damage. Background, paint flaking, and rust damage are objects that can be separated in RGB color-space alone. For their preliminary classification SVM is used. As for paint cracks, color features are insufficient for separating it from other defect types as they overlap with the other three classes in RGB color space. For preliminary paint crack segmentation we use the valley detection approach, which analyses the shape of defects. A multiclass level-set approach with a developed penalty term is used as a framework for the advanced final damage segmentation stage. Model training and accuracy assessment are fulfilled on the created dataset, which contains input images of corresponding defects with respective ground truth data provided by the expert. A quantitative analysis of the accuracy of the proposed approach is provided. The efficiency of the approach is demonstrated on authentic images of coated surfaces.

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“…In particular, image processing and pattern recognition methods are widely used in non-destructive testing and technical diagnostics [1][2][3]. They are especially used in radiography, for coating condition monitoring on structural elements of important structures and for rust detection [4][5][6], for condition monitoring and the diagnostics of complex mechanisms [7], followed by quantitative fractography and metallography and so forth [8]. Such approaches are based on the development of modern algebraic theories [9], fuzzy logic and optimization methods [10].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Fatigue Crack Growth Rate in Heat-Resistant Steel by Processing of Digital Images of Fracture Surfaces

Maruschak

Vorobel

Student

et al. 2021

Metals

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The micro- and macroscopic fatigue crack growth (FCG) rates of a wide class of structural materials were analyzed and it was concluded that both rates coincide either during high-temperature tests or at high stress intensity factor (SIF) values. Their coincidence requires a high level of cyclic deformation of the metal along the entire crack front as a necessary condition for the formation of fatigue striations (FS). Based on the analysis of digital fractographic images of the fatigue fracture surfaces, a method for the quantitative assessment of the spacing of FS has been developed. The method includes the detection of FS by binarization of the image based on the principle of local minima, rotation of the highlighted fragments of the image using the Hough transform, and the calculation of the distances between continuous lines. The method was tested on 34KhN3M steel in the initial state and after long-term operation (~3 × 105 h) in the rotor disk of a steam turbine at a thermal power plant (TPP). Good agreement was confirmed between FCG rates (both macro and microscopic, determined manually or using digital imaging techniques) at high SIF ranges and their noticeable discrepancy at low SIF ranges. Possible reasons for the discrepancy between the micro- and macroscopic FCG rates at low values of the SIF are analyzed. It has also been noted that FS is easier to detect on the fracture surface of degraded steel. Hydrogen embrittlement of steel during operation promotes secondary cracking along the FS, making them easier to detect and quantify. It is shown that the invariable value of the microscopic FCG rate at a low SIF range in the operated steel is lower than observable for the steel in the initial state. Secondary cracking of the operated steel may have contributed to the formation of a typical FS pattern along the entire crack front at a lower FCG rate than in unoperated steel.

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Automatized computer system for evaluation of rust using modified single-scale retinex

Cited by 10 publications

References 8 publications

Evaluation of the Degree of Degradation of Brake Pad Friction Surfaces Using Image Processing

Evaluation of the Degree of Degradation of Brake Pad Friction Surfaces Using Image Processing

Multiclass Level-Set Segmentation of Rust and Coating Damages in Images of Metal Structures

Estimation of Fatigue Crack Growth Rate in Heat-Resistant Steel by Processing of Digital Images of Fracture Surfaces

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