Si3N4 Ceramic Ball Surface Defects’ Detection Based on SWT and Nonlinear Enhancement

In order to improve the detection accuracy and efficiency of silicon nitride ceramic ball surface defects, a defect detection algorithm based on SWT and nonlinear enhancement is proposed. In view of the small surface defect area and low contrast of the silicon nitride ceramic ball, a machine vision-based nondestructive inspection system for surface images is constructed. Sobel operation is used to eliminate the nonuniform background, and the silicon nitride ceramic ball surface image is decomposed by SWT. And frequency-domain index low-pass filtering is used to modify the decomposition coefficients, and an adaptive nonlinear model is proposed to enhance defects; finally, the image is reconstructed and segmented by the stationary wavelet inverse transform and the dynamic threshold method, respectively. The enhanced algorithm can effectively identify surface defects and is superior to traditional defect detection algorithms.

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Self-Lubricated Modification for Silicon Nitride Ceramic Ball Surface

STLE/ASME 2010 International Joint Tribology Conference ◽

10.1115/ijtc2010-41161 ◽

2010 ◽

Cited By ~ 1

Author(s):

Le Gu ◽

Guangze Tang ◽

Chuanwei Zhang ◽

Cuini Jing ◽

Liqin Wang

Keyword(s):

Silicon Nitride ◽

Solid Lubricants ◽

Test Results ◽

Silicon Nitride Ceramic ◽

Ceramic Ball ◽

Dlc Film ◽

Dlc Coating ◽

Ceramic Surfaces ◽

Mos2 Film ◽

Ball Surface

Some thin films were prepared as solid lubricants on the surfaces of silicon nitride ceramic disk and ball. DLC film about 500–800 nm thickness was deposited on the ceramic surfaces using ion implantation and deposition technology. The surface roundness measure results, as well as 80 to 90 nm, showed that DLC film was shaped uniformly on the ceramic ball surfaces. The ball-on-disk tests showed DLC coating on silicon nitride surfaces could lead the friction coefficient to about 0.1 and endure about 7h at 1.5GPa and 30 mm/s. Ball milling technology was employed to prepare MoS2 film on the ceramic ball surfaces. The film thickness and tribological test results showed that the thin MoS2 film on the ball surfaces, which hardly changed the surface roughness, also improved their wear behaviors.

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Hot Rolling Steels and Super Alloys with Silicon Nitride Tools

Advances in Science and Technology ◽

10.4028/www.scientific.net/ast.65.92 ◽

2010 ◽

Vol 65 ◽

pp. 92-99

Author(s):

R. Danzer

Keyword(s):

Silicon Nitride ◽

Fatigue Cracks ◽

High Strength ◽

Ceramic Tool ◽

Silicon Nitride Ceramic ◽

Small Surface ◽

Metal Parts ◽

Improved Performance ◽

Montanuniversität Leoben ◽

Super Alloy

Tools for rolling steels and super alloys, which are nowadays in general made from steel or cemented carbides, suffer from wear and/or from surface cracking caused by thermal fatigue. New tools made from silicon nitride show improved performance in respect to thermal shock loading and wear. But their low toughness manifests also a high risk of brittle failure. Nevertheless the successful use of silicon nitride rolls with having more than a manifold lifetime (compared to the conventional solutions) has been reported in the last years [1 -3]. In this paper earlier work of the Institut für Struktur- und Funktionskeramik at Montanuniversität Leoben on highly loaded silicon nitride rolls is summarized, where the limits of the Application of silicon nitride rolling tools are discussed. On the extreme example of rolls for super alloy wire rolling the behaviour of small surface cracks in the roll track is discussed. It is shown that – for the investigated conditions - rolling high strength steel wires is manageable but rolling of super alloy wires will cause the growth of fatigue cracks, which may destroy the rolls after some tons of rolled wire. A not trivial problem to be solved is the connection of the ceramic tool with the metal parts of the roll stand. Thermal strains of the metal parts can be several times larger than those of the silicon nitride ceramic and can therefore cause very high thermal misfit strains, even if the heating of metal parts seems to be modest. This case is discussed on the example of a catastrophically failed ceramic tool. This clearly shows that not only the tool but also the joint of the tool to the rest of the machinery has to be designed carefully. In summary this work demonstrates that a successful use of silicon nitride ceramic tools for cold and hot forming of metals and alloys is possible.

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Visual Detection of Surface Defects Based on Self-Feature Comparison in Robot 3-D Printing

Applied Sciences ◽

10.3390/app10010235 ◽

2019 ◽

Vol 10 (1) ◽

pp. 235 ◽

Cited By ~ 2

Author(s):

Hongyao Shen ◽

Wangzhe Du ◽

Weijun Sun ◽

Yuetong Xu ◽

Jianzhong Fu

Keyword(s):

Feature Extraction ◽

3D Printing ◽

Defect Detection ◽

Point Cloud ◽

Fused Deposition Modeling ◽

Surface Defects ◽

Detection Accuracy ◽

Feature Extraction Method ◽

Fused Deposition ◽

Detection Technology

Fused Deposition Modeling (FDM) additive manufacturing technology is widely applied in recent years. However, there are many defects that may affect the surface quality, accuracy, or even cause the collapse of the parts in the printing process. In the existing defect detection technology, the characteristics of parts themselves may be misjudged as defects. This paper presents a solution to the problem of distinguishing the defects and their own characteristics in robot 3-D printing. A self-feature extraction method of shape defect detection of 3D printing products is introduced. Discrete point cloud after model slicing is used both for path planning in 3D printing and self-feature extraction at the same time. In 3-D printing, it can generate G-code and control the shooting direction of the camera. Once the current coordinates have been received, the self-feature extraction begins, whose key steps are keeping a visual point cloud of the printed part and projecting the feature points to the picture under the equal mapping condition. After image processing technology, the contours of pictured projected and picture captured will be detected. At last, the final defects can be identified after evaluation of contour similarity based on empirical formula. This work will help to detect the defects online, improve the detection accuracy, and reduce the false detection rate without being affected by its own characteristics.

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Research on Surface Defect Detection Technique of Rolling Element Based on Computer Vision

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1006-1007.773 ◽

2014 ◽

Vol 1006-1007 ◽

pp. 773-778 ◽

Cited By ~ 1

Author(s):

Chuan Ren ◽

Xiao Yu Xiu ◽

Guo Hui Zhou

Keyword(s):

Computer Vision ◽

Defect Detection ◽

High Speed ◽

Surface Defect ◽

Surface Defects ◽

Median Filter ◽

Image Sensor ◽

Threshold Method ◽

Rolling Element ◽

Surface Defect Detection

This paper proposed a new method of surface defect detection of rolling element based on computer vision, which adopted CCD digital camera as image sensor, and used digital image processing techniques to defect the surface defects of rolling element. The main steps include collect image, use an improved median filter to reduce the noise, increase or decrease the exposure to achieve the image enhancement, create a binary image with threshold method and detect the edge of the image, and use subtraction method for surface defects identification. The experiment indicates that the above methods the advantages of simple, the capability of noise resistance, high speed processing and better real-time.

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Polishing of Silicon Nitride Ceramic Balls by Clustered Magnetorheological Finish

Micromachines ◽

10.3390/mi11030304 ◽

2020 ◽

Vol 11 (3) ◽

pp. 304

Author(s):

Xiao-lan Xiao ◽

Guang-xian Li ◽

Hai-juan Mei ◽

Qiu-sheng Yan ◽

Hua-tay Lin ◽

...

Keyword(s):

Silicon Nitride ◽

Analytical Model ◽

Surface Finish ◽

Experimental Results ◽

Machined Surface ◽

Silicon Nitride Ceramic ◽

Ceramic Ball ◽

Contact Points ◽

Micro Morphology ◽

Improve Surface Finish

In this study, a novel finishing method, entitled clustered magnetorheological finish (CMRF), was proposed to improve surface finish of the silicon nitride ( Si 3 N 4 ) balls with ultra fine precision. The effects of different polishing parameters including rotation speeds, eccentricities and the machining gaps on surface finish of Si 3 N 4 balls were investigated by analyzing the roughness, sphericity and the micro morphology of the machined surface. The experimental results showed that the polishing parameters significantly influenced the surface finish. The best surface finish was obtained by using the polishing parameters: the machining gap of 0.8 mm, the eccentricity of 10 mm and the rotation ratio of 3/4. To further investigate the influence of the polishing parameters on the surface finish, an analytical model was also developed to analyze the kinematics of the ceramic ball during CMRF process. The resulting surface finish, as a function of different polishing parameters employed, was evaluated by analyzing the visualized finishing trace and the distribution of the contact points. The simulative results showed that the distribution and trace of the contact points changed with different polishing parameters, which was in accordance with the results of experiments.

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The Friction and Wear of Silicon Nitride Ceramic with BSA Lubricant

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.642.125 ◽

2015 ◽

Vol 642 ◽

pp. 125-129

Author(s):

Jing Ling Zhou ◽

Chun Shu Zhai ◽

Su Yun Yang ◽

Shu Qian Wu ◽

Guo Qing Wu ◽

...

Keyword(s):

Stainless Steel ◽

Silicon Nitride ◽

Bovine Serum Albumin ◽

Serum Albumin ◽

Bovine Serum ◽

Friction And Wear ◽

Physiological Saline ◽

Deionized Water ◽

Silicon Nitride Ceramic ◽

Ceramic Ball

To research the friction and wear of silicon nitride ceramic with bovine serum albumin lubricant, the tribological properties of silicon nitride ceramic against stainless steel were investigated on CETR UMT-2 under lubrication of bovine serum albumin, deionized water, physiological saline and physiological saline mixed with bovine serum albumin. The worn surfaces of silicon nitride ceramic ball and stainless steel pin were examined with a digital microscope (VHX-2000). The friction coefficients of steady state are 0.26, 0.35, 0.69 and 0.8 under bovine serum albumin, physiological saline mixed with bovine serum albumin, physiological saline and deionized water. The lowest friction coefficient of steady state is 0.26 which is under lubrication of bovine serum albumin. The highest friction coefficient is 0.8 under the lubrication of deionized water. The measured worn areas of silicon nitride ceramic balls are 1282.3μm2, 1898.6μm2, 2753.9μm2 and 3645.7μm2 under bovine serum albumin, physiological saline mixed with bovine serum albumin, physiological saline and deionized water. The smallest worn area of silicon nitride ceramic ball is 1282.3μm2 which is measured under the lubrication of bovine serum albumin. The highest worn area of silicon nitride ceramic ball is 3645.7μm2 which was measured under the lubrication of deionized water. The same wear mechanism of silicon nitride ceramic ball had been found under the lubrication of bovine serum albumin, deionized water, physiological saline and physiological saline mixed with bovine serum albumin. The depth of scratches of worn surface of silicon nitride ceramic ball lubricated with BSA is 3μm which are the shallowest.

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YOLOv4-MN3 for PCB Surface Defect Detection

Applied Sciences ◽

10.3390/app112411701 ◽

2021 ◽

Vol 11 (24) ◽

pp. 11701

Author(s):

Xinting Liao ◽

Shengping Lv ◽

Denghui Li ◽

Yong Luo ◽

Zichun Zhu ◽

...

Keyword(s):

Defect Detection ◽

High Performance ◽

Surface Defect ◽

Printed Circuit Board ◽

Surface Defects ◽

Activation Function ◽

Production Quality ◽

Circuit Board ◽

Detection Accuracy ◽

Surface Defect Detection

Surface defect detection for printed circuit board (PCB) is indispensable for managing PCB production quality. However, automatic detection of PCB surface defects is still a challenging task because, even within the same category of surface defect, defects present great differences in morphology and pattern. Although many computer vision-based detectors have been established to handle these problems, current detectors struggle to achieve high detection accuracy, fast detection speed and low memory consumption simultaneously. To address those issues, we propose a cost-effective deep learning (DL)-based detector based on the cutting-edge YOLOv4 to detect PCB surface defect quickly and efficiently. The YOLOv4 is improved upon with respect to its backbone network and the activation function in its neck/prediction network. The improved YOLOv4 is evaluated with a customized dataset, collected from a PCB factory. The experimental results show that the improved detector achieved a high performance, scoring 98.64% on mean average precision (mAP) at 56.98 frames per second (FPS), outperforming the other compared SOTA detectors. Furthermore, the improved YOLOv4 reduced the parameter space of YOLOv4 from 63.96 M to 39.59 M and the number of multiply-accumulate operations (Madds) from 59.75 G to 26.15 G.

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The Crack Propagation Trend Analysis in Ceramic Rolling Element Bearing considering Initial Crack Angle and Contact Load Effect

Shock and Vibration ◽

10.1155/2021/5559296 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Zhe Yuan ◽

Bohan Wang ◽

Chao Liu ◽

Zhan Wang ◽

Xiaochen Zhang ◽

...

Keyword(s):

Finite Element ◽

Silicon Nitride ◽

Crack Propagation ◽

Crack Growth ◽

Surface Crack ◽

Initial Crack ◽

Silicon Nitride Ceramic ◽

Ball Surface ◽

Crack Angle ◽

Bearing Ball

Silicon nitride ceramic bearings are widely used for their excellent performance. However, due to their special manufacturing method, cracks will occur on ceramic ball surface, and this initial surface crack will propagate under the action of cyclic stress, which will lead to material spalling. This will greatly limit its service life in practical applications, especially under heavy load at high speed. Therefore, it is necessary to study the surface crack propagation of silicon nitride ceramic bearings. In this paper, the effect of initial crack angle and contact load on crack growth is analysed by the finite element method (FEM). A three-dimensional finite element model of a silicon nitride bearing ball containing an initial crack is created by the FEM. The cracks are initially classified based on the angle between the crack and the bearing ball surface, and the location of the most dangerous load for each type of crack is known by theoretical analysis. The stress intensity factors (SIFs) are calculated for the crack front to investigate the effect of load position on crack growth. Subsequently, the SIFs are calculated for each type of crack angle subdivided again to investigate the effect of crack angle on crack propagation.

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