Detection of pitting corrosion in steel using image processing

This paper presents an image processing based detection method for detecting pitting corrosion in steel structures. High Dynamic Range (HDR) imaging has been carried out in this regard to demonstrate the effectiveness of such relatively inexpensive techniques that are of immense benefit to Non – Destructive – Tesing (NDT) community. The pitting corrosion of a steel sample in marine environment is successfully detected in this paper using the proposed methodology. It is observed, that the proposed method has a definite potential to be applied to a wider range of applications.

Improved image analysis based corrosion assessment using preprocessing techniques

The importance of non-destructive techniques (NDT) in structural health monitoring programmes is being critically felt in the recent times. The quality of the measured data, often affected by various environmental conditions can be a guiding factor in terms usefulness and prediction efficiencies of the various detection and monitoring methods used in this regard. Often, a preprocessing of the acquired data in relation to the affecting environmental parameters can improve the information quality and lead towards a significantly more efficient and correct prediction process. The improvement can be directly related to the final decision making policy about a structure or a network of structures and is compatible with general probabilistic frameworks of such assessment and decision making programmes. This paper considers a preprocessing technique employed for an image analysis based structural health monitoring methodology to identify sub-marine pitting corrosion in the presence of variable luminosity, contrast and noise affecting the quality of images. A preprocessing of the gray-level threshold of the various images is observed to bring about a significant improvement in terms of damage detection as compared to an automatically computed gray-level threshold. The case dependent adjustments of the threshold enable to obtain the best possible information from an existing image. The corresponding improvements are observed in a qualitative manner in the present study.

Ruthenibacterium lactatiformans gen. nov., sp.nov., an anaerobic, lactate-producing member of the family Ruminococcaceae isolated from human faeces

Two novel strains of Gram-stain-negative, rod-shaped, obligately anaerobic, non-spore-forming, non-motile bacteria were isolated from the faeces of healthy human subjects. The strains, designated as 585-1T and 668, were characterized by mesophilic fermentative metabolism, production of d-lactic acid, succinic acid and acetic acid as end products of d-glucose fermentation, prevalence of C18 : 1 ω9, C18 : 1 ω9 aldehyde, C16 : 0 and C16 : 1 ω7c fatty acids, presence of glycine, glutamic acid, lysine, alanine and aspartic acid in the petidoglycan peptide moiety and lack of respiratory quinones. Whole genome sequencing revealed the DNA G+C content was 56.4–56.6 mol%. The complete 16S rRNA gene sequences of the two strains shared 91.7/91.6 % similarity with Anaerofilum pentosovorans FaeT, 91.3/91.2 % with Gemmiger formicilis ATCC 27749T and 88.9/88.8 % with Faecalibacterium prausnitzii ATCC 27768T. On the basis of chemotaxonomic and genomic properties it was concluded that the strains represent a novel species in a new genus within the family Ruminococcaceae , for which the name Ruthenibacterium lactatiformans gen. nov., sp. nov. is proposed. The type strain of Ruthenibacterium lactatiformans is 585-1T (=DSM 100348T=VKM B-2901T).