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.

A benchmark study on housing defects in Victoria, Australia

The construction industry consists of many small businesses employing less than five people. A challenge to the construction industry is to ensure that the many small firms and sub-contractors keep producing quality housing to meet the needs of their customers and clients. In attempts to continually improve the quality of housing various policies and mechanisms have been adopted. These have included industry sponsored quality programs and industry administered builder registration. However, these attempts have failed because of consumer mistrust of industry-sponsored programs. In addition, these mechanisms have been introduced in isolation and not as a part of an integrated industry initiative that includes education and training from the trade to tertiary level construction management courses. This work contributes to knowledge through a detailed on-going study of housing quality and defects. This research identifies the common forms of defects, which occur in housing and their incidences. The overall aim of this paper is to report the identification of defects in housing and the establishment of benchmarks (or a baseline) for the incidence defects in various functional elements within a house. It also suggests the areas where defects are likely to occur. From the knowledge gained from the study, industry and governments may make informed decisions of where resources may be directed to the areas where it will be most beneficial both to the house builder and the end user (customer). For this to occur the findings of this research will be disseminated into the housing industry and eventually integrated into tertiary courses in building and construction
management.

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.

Seeding of single crystal superalloys--Role of seed melt-back on casting defects

Single crystal seeds of the nickel-base superalloy CMSX-4 have been partially melted in a temperature gradient and then quenched. Small islands of random orientation are observed throughout the melted-back semi-solid. These random orientations appear to be pinched-off secondary dendrite arms, but there is no evidence that they are transported ahead of the dendrite tips to nucleate stray grains during directional solidification.

Modelling of porosity defects in high pressure die casting with a neural network

High Pressure Die Casting (HPDC) is a complex process that results in casting defects if configured improperly. However, finding out the optimal configuration is a non-trivial task as eliminating one of the casting defects (for example, porosity) can result in occurrence of other casting defects. The industry generally tries to eliminate the defects by trial and error which is an expensive and error -prone process. This paper aims to improve current modelling and understanding of defects formation in HPDC machines. We have conducted conventional die casting tests with a neural network model of HPDC machine and compared the obtained results with the current understanding of formation of porosity. While most of our findings correspond well to established knowledge in the field, some of our findings are in conflict with the previous studies of die casting.

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.

Numerical modeling of interactions between a macro-crack and a cluster of micro-defects

The interactions between a macro-crack and a cluster of micro-defects are studied numerically by using a series of special finite elements each containing a defect. These special finite elements, which contain defects such as holes, cracks, and inhomogeneities, are developed based on the hybrid displacement, complex potential and conformal mapping techniques. These hybrid-type elements can be used together with the conventional finite elements without any difficulty. Thus, simple finite element models can be devised to study the interactions between a macro-crack and a cluster of micro-defects. In this paper, the mathematical and finite element modeling procedures for the study of the above-mentioned problems are presented.

Cultured muscle cells display defects of mitochondrial myopathy ameliorated by anti-oxidants

The mitochondrial DNA A3243G mutation causes neuromuscular disease. To investigate the muscle-specific pathophysiology of mitochondrial disease, rhabdomyosarcoma transmitochondrial hybrid cells (cybrids) were generated that retain the capacity to differentiate to myotubes. In some cases, striated muscle-like fibres were formed after innervation with rat embryonic spinal cord. Myotubes carrying A3243G mtDNA produced more reactive oxygen species than controls, and had altered glutathione homeostasis. Moreover, A3243G mutant myotubes showed evidence of abnormal mitochondrial distribution, which was associated with down-regulation of three genes involved in mitochondrial morphology, Mfn1, Mfn2 and DRP1. Electron microscopy revealed mitochondria with ultrastructural abnormalities and paracrystalline inclusions. All these features were ameliorated by anti-oxidant treatment, with the exception of the paracrystalline inclusions. These data suggest that rhabdomyosarcoma cybrids are a valid cellular model for studying muscle-specific features of mitochondrial disease and that excess reactive oxygen species production is a significant contributor to mitochondrial dysfunction, which is amenable to anti-oxidant therapy.

The effect of artificial defects on the compressive properties of hollow sphere cellular aluminium (HSCA)

Hollow sphere cellular aluminium (HSCA) samples were fabricated by bonding together two kinds of single aluminium hollow spheres with the same outside diameter of 4 mm but different wall thicknesses of 0.1 mm and 0.3 mm, in which the hollow spheres with the thinner sphere wall thickness were used as artificial defects. Four types of HSCA samples with the same relative density but various distributions of artificial defects were prepared by simple cubic packing. For comparing, HSCA sample without defective hollow spheres inside was also prepared. The effects of the distribution of the artificial defects on the deformation behaviours and mechanical properties were investigated by compressive tests. Results indicated that the nominal stress - nominal strain curve and the deformation behavior of the HSCA samples varied with the distribution of the artificial defects in spite of the same relative density. It is therefore suggested that the deformation behavior and mechanical property of cellular materials were also significantly affected by the distribution of defects. In particular, the plateau stress of the HSCA samples increased with the decrease in number of contact points between the normal hollow spheres and the defective hollow spheres in the loading direction during deformation.

Comparison of defects in houses constructed by owners and registered builders in Victoria 1988-1996

The lack of attention to quality control by house builders in the Australian State of Victoria has been a contentious issue for more than two decades. Ina an attempt to improve the quality of housing, various mechanisms such as voluntary and compulsory registration schemes have been adopted and discarded by industry-based organisations and government. While builders are encouraged to improve construction quality, little is known and published about the quality of housing produced by owner builders specifically during the seven year warranty period after construction is completed. With this in mind, this thesis presents research findings that compare the latent defects in houses built by owner builders with those of registered builders. Using inspection reports provided by Archicentre a sample of 1772 houses, of which 1002 were owner builders and 770 were registered builders

Clustering of Th cell epitopes on exposed regions of HIV envelope despite defects in antibody activity

A long-standing question in the field of immunology concerns the factors that contribute to Th cell epitope immunodominance. For a number of viral membrane proteins, Th cell epitopes are localized to exposed protein surfaces, often overlapping with Ab binding sites. It has therefore been proposed that Abs on B cell surfaces selectively bind and protect exposed protein fragments during Ag processing, and that this interaction helps to shape the Th cell repertoire. While attractive in concept, this hypothesis has not been thoroughly tested. To test this hypothesis, we have compared Th cell peptide immunodominance in normal C57BL/6 mice with that in C57BL/6MT/MT mice (lacking normal B cell activity). Animals were first vaccinated with DNA constructs expressing one of three different HIV envelope proteins, after which the CD4 T cell response profiles were characterized toward overlapping peptides using an IFN- ELISPOT assay. We found a striking similarity between the peptide response profiles in the two mouse strains. Profiles also matched those of previous experiments in which different envelope vaccination regimens were used. Our results clearly demonstrate that normal Ab activity is not required for the establishment or maintenance of Th peptide immunodominance in the HIV envelope response. To explain the clustering of Th cell epitopes, we propose that localization of peptide on exposed envelope surfaces facilitates proteolytic activity and preferential peptide shuttling through the Ag processing pathway.

Formation of defects in boron nitride by low energy ion bombardment

Formation of defects in hexagonal and cubic boron nitride (h -BN and c -BN, respectively) under low-energy argon or nitrogen ion-bombardment has been studied by near-edge x-ray absorption fine structure (NEXAFS) around boron and nitrogen K -edges. Breaking of B-N bonds for both argon and nitrogen bombardment and formation of nitrogen vacancies, VN, has been identified from the B K -edge of both h -BN and c -BN, followed by the formation of molecular nitrogen, N2, at interstitial positions. The presence of N 2 produces an additional peak in photoemission spectra around N 1s core level and a sharp resonance in the low-resolution NEXAFS spectra around N K -edge, showing the characteristic vibrational fine structure in high-resolution measurements. In addition, several new peaks within the energy gap of BN, identified by NEXAFS around B and N K -edges, have been assigned to boron or nitrogen interstitials, in good agreement with theoretical predictions. Ion bombardment destroys the cubic phase of c -BN and produces a phase similar to a damaged hexagonal phase. © 2009 American Institute of Physics.