Machine vision system for automatic inspection of surface defects in aluminum die casting

A camera based machine vision system for the automatic inspection of surface defects in aluminum die casting is presented. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production.

Machine vision system for automatic inspection of surface defects in aluminium die casting

A machine vision system is presented for the automatic inspection of surface defects in aluminium die casting. The system uses a hybrid image processing algorithm based on mathematic morphology to detect defects with different sizes and shapes. The defect inspection algorithm consists of two parts. One is a parameter learning algorithm, in which a genetic algorithm is used to extract optimal structuring element parameters, and segmentation and noise removal thresholds. The second part is a defect detection algorithm, in which the parameters obtained by a genetic algorithm are used for morphological operations. The machine vision system has been applied in an industrial setting to detect two types of casting defects: parts mix-up and any defects on the surface of castings. The system performs with a 99% or higher accuracy for both part mix-up and defect detection and is currently used in industry as part of normal production.

Automatic inspection of metallic surface defects using genetic algorithms

This paper is concerned with the problem of automatic inspection of metallic surface using machine vision. An experimental system has been developed to take images of external metallic surfaces and an intelligent approach based on morphology and genetic algorithms is proposed to detect structural defects on bumpy metallic surfaces. The approach employs genetic algorithms to automatically learn morphology processing parameters such as structuring elements and defect segmentation threshold. This paper describes the detailed procedures which include encoding scheme, genetic operation and evaluation function.

The proposed method has been implemented and tested on a number of metallic surfaces. The results suggest that the method can provide an accurate identification to the defects and can be developed into a viable commercial visual inspection system.

Genetic learning based texture surface inspection

This paper presents a novel approach of visual inspection for texture surface defects. It is based on the measure of texture energy acquired by a kind if high performance 2D detection mask, which is learned by genetic algorithms. Experimental results of texture defect inspection on textile images are presented to illustrate the merit and feasibility of the proposed method.

Stereocomplexation and monolayer morphologies of a stereoregular poly(methylmethacrylate) mixture formed at the air/water surface

The stereocomplexation of stereoregular PMMA at the air/water interface was proved by structure determination using reflection-absorption IR and grazing incidence X-ray diffraction. Morphological studies on LB films of i- and s-PMMA blends with different ratios help to disclose the stereocomplexation process of stereoregular PMMA at the air/water interface. It was found that the stereocomplexes exist in particle aggregates randomly dispersed at the air/water interface. In the systems with the i:s ratio deviated from 1:2, the molecules, either i-PMMA or s-PMMA, that do not participate in the stereocomplexation build separate layer surrounding the stereocomplexes. This layer is much thinner than the particle aggregates of the stereocomplexes. If the i-PMMA molecules are rich in this thinner layer, crystallization of i-PMMA takes place, which generates lamellar structure besides the stereocomplexes.

A surface characterisation and microstructural study by scanning electron microscopy of the N-methyl-n-alkylpyrrolidinium tetrafluoroborate organic salts

A microstructural characterisation of the family of N-methyl-N-alkylpyrrolidinium tetrafluoroborate organic salts was carried out by observation of powder surface morphologies with the aim of extending the microstructure-property correlation. Inherent difficulties limiting extensive studies of organic solids by SEM, including volatility under vacuum, charging due to electron beam irradiation, and air-sensitivity were overcome with the use of a Field Emission SEM and cryostage attachment. This technique, providing considerable improvements in image quality at low accelerating voltages, enabled direct observation of complex microstructural features in samples exhibiting high temperature plastic crystalline phases (N,N-dimethylpyrrolidinium tetrafluoroborate [P11BF4]; N-methyl-N-ethylpyrrolidinium tetrafluoroborate [P12BF4]; N-methyl-N-propylpyrrolidinium tetrafluoroborate [P13BF4]). Extensive lattice imperfections including grain boundaries, slip planes and dislocation pits were observed within particles of approximately 200 mgrm diameter. The N-methyl-N-butylpyrrolidinium tetrafluoroborate (P14BF4) sample in this series revealed columnar single crystals with high aspect ratios. The origin of plastic flow properties is discussed using single crystal and polycrystalline slip observations and a relationship proposed between defect characteristics and transport properties.

Kinetic effects of halide ions on the morphological evolution of silver nanoplates

Time-resolved extinction spectroscopy is employed to study the reaction kinetics in the shape-conversion reaction involving halide ions (including Cl-, Br- and I-) etching (sculpturing) silver nanoplates. A series of time-resolved extinction spectra are obtained during the in situ etching process and the evolution of surface plasmon resonance (SPR) of the silver nanoparticles is analyzed. Spectral analysis indicates that the conversion of nanoprisms starts simultaneously with the emergence of nanodisks when the halide ions are added. The etching rate of different halide ions is evaluated through the in-plane dipole resonance peak intensity of silver nanoplates vs. the reaction time (dI/dt). The relationship between the etching rate and the halide ion concentration shows that the halide ion etching reaction can be considered as a pseudo-first-order reaction. The effect of different halide ions on the shape-conversion of silver nanoplates is compared in detail. The activation energy of the etching reaction is calculated, which indicates that the etching ability of different halide ions is on the order of Cl - < I- < Br-.

The boundary lubrication of chemically grafted and cross-linked hyaluronic acid in phosphate buffered saline and lipid solutions measured by the surface forces apparatus

High molecular weight hyaluronic acid (HA) is present in articular joints and synovial fluid at high concentrations; yet despite numerous studies, the role of HA in joint lubrication is still not clear. Free HA in solution does not appear to be a good lubricant, being negatively charged and therefore repelled from most biological, including cartilage, surfaces. Recent enzymatic experiments suggested that mechanically or physically (rather than chemically) trapped HA could function as an “adaptive” or “emergency” boundary lubricant to eliminate wear damage in shearing cartilage surfaces. In this work, HA was chemically grafted to a layer of self-assembled amino-propyl-triethoxy-silane (APTES) on mica and then cross-linked. The boundary lubrication behavior of APTES and of chemically grafted and cross-linked HA in both electrolyte and lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) solutions was tested with a surface forces apparatus (SFA). Despite the high coefficient of friction (COF) of μ ≈ 0.50, the chemically grafted HA gel significantly improved the lubrication behavior of HA, particularly the wear resistance, in comparison to free HA. Adding more DOPC lipid to the solution did not improve the lubrication of the chemically grafted and cross-linked HA layer. Damage of the underlying mica surface became visible at higher loads (pressure >2 MPa) after prolonged sliding times. It has generally been assumed that damage caused by or during sliding, also known as “abrasive friction”, which is the main biomedical/clinical/morphological manifestation of arthritis, is due to a high friction force and, therefore, a large COF, and that to prevent surface damage or wear (abrasion) one should therefore aim to reduce the COF, which has been the traditional focus of basic research in biolubrication, particularly in cartilage and joint lubrication. Here we combine our results with previous ones on grafted and cross-linked HA on lipid bilayers, and lubricin-mediated lubrication, and conclude that for cartilage surfaces, a high COF can be associated with good wear protection, while a low COF can have poor wear resistance. Both of these properties depend on how the lubricating molecules are attached to and organized at the surfaces, as well as the structure and mechanical, viscoelastic, elastic, and physical properties of the surfaces, but the two phenomena are not directly or simply related. We also conclude that to provide both the low COF and good wear protection of joints under physiological conditions, some or all of the four major components of joints—HA, lubricin, lipids, and the cartilage fibrils—must act synergistically in ways (physisorbed, chemisorbed, grafted and/or cross-linked) that are still to be determined.

Analysis of phasic and tonic electromyographic signal characteristics: electromyographic synthesis and comparison of novel morphological and linear-envelope approaches

The pattern of tonic and phasic components in an EMG signal reflects the underlying behaviour of the central nervous system (CNS) in controlling the musculature. One avenue for gaining a better understanding of this behaviour is to seek a quantitative characterisation of these phasic and tonic components. We propose that these signal characteristics can range between unvarying, tonic and intermittent, phasic activation through a continuum of EMG amplitude modulation. In this paper, we present two new algorithms for quantifying amplitude modulation: a linear-envelope approach, and a mathematical morphology approach. In addition we present an algorithm for synthesising EMG signals with known amplitude modulation. The efficacy of the synthesis algorithm is demonstrated using real EMG data. We present an evaluation and comparison of the two algorithms for quantifying amplitude modulation based on synthetic data generated by the proposed synthesis algorithm. The results demonstrate that the EMG synthesis parameters represent 91.9% and 96.2% of the variance of linear-envelopes extracted from lumbo-pelvic muscle EMG signals collected from subjects performing a repetitive-movement task. This depended, however, on the muscle and movement-speed considered (F=4.02, p<0.001). Coefficients of determination between input and output amplitude modulation variables were used to quantify the accuracy of the linear-envelope and morphological signal processing algorithms. The linear-envelope algorithm exhibited higher coefficients of determination than the most accurate morphological approach (and hence greater accuracy, T=8.16, p<0.001). Similarly, the standard deviation of the coefficients of determination was 1.691 times smaller (p<0.001). This signal processing algorithm represents a novel tool for the quantification of amplitude modulation in continuous EMG signals and can be used in the study of CNS motor control of the musculature in repetitive-movement tasks.