Diagnostics of gear faults using ensemble empirical mode decomposition, hybrid binary bat algorithm and machine learning algorithms

Early fault detection is a challenge in gear fault diagnosis. In particular, efficient feature extraction and feature selection is a key issue to automatic condition monitoring and fault diagnosis processes. In order to focus on those issues, this paper presents a study that uses ensemble empirical mode decomposition (EEMD) to extract features and hybrid binary bat algorithm (HBBA) hybridized with machine learning algorithm to reduce the dimensionality as well to select the predominant features which contains the necessary discriminative information. Efficiency of the approaches are evaluated using standard classification metrics such as Nearest neighbours, C4.5, DTNB, K star and JRip. The gear fault experiments were conducted, acquired the vibration signals for different gear states such as normal, frosting, pitting and crack, under constant motor speed and constant load. The proposed method is applied to identify the different gear faults at early stage and the results demonstrate its effectiveness

INSULIN SECRETAGOGUE EFFECT OF ROOTS OF RAVENALA MADAGASCARIENSIS SONN. - AN IN VITRO STUDY

Objective: The objective of this study was to establish the cytotoxicity profile and to evaluate the insulin secretagogue effect of ethanolic root extract of Ravenala madagascariensis Sonn. Methods: The cell viability of rat insulinoma 5F (RIN5F) cell lines over the treatment of plant extract was assessed by 3-(4,5-dimethyl-2-thiazolyl)- 2,5-diphenyltetrazolium bromide assay. The insulin-releasing effect was evaluated by insulin secretion assay over RIN5F cell lines by enzyme-linked immunosorbent assay. Results: The ethanolic extract of the roots of R. madagascariensis Sonn. showed negligible cytotoxicity at 20–40 μg/ml, and hence, concentrations up to 40 μg/ml were used in insulin secretion assay. The ethanolic root extract at 20 and 40 μg/ml significantly (p<0.05 compared to control) stimulated the insulin release in a dose-dependent manner even in the presence of glucose at lower and higher concentrations (5 and 10 mM). Conclusion: Thus, our results validate its traditional claim in the treatment of diabetes by stimulating the secretion of insulin, thereby suggesting a possible mechanism of its antidiabetic effect

Effect of ethanol, propanol and butanol on karanja biodiesel with vegetable oil fuelled in a single cylinder diesel engine

There is a significant need for alternative fuels as a result of increased fuel usage and resource depletion. Esters made from vegetable oils, waste cooking oil and bio alcohols are majorly used in IC engines as a substitute. Coconut oil (Co) and sunflower oil (Su), which have sufficient productivity in India, biodiesel synthesized from karanja oil. In this study, fossil diesel (D) was mixed with karanja biodiesel (B), neat coconut oil and sunflower oil along with ethanol (Et), propanol (Pr) and n-butanol (Bu) alcohols was used. Quinary fuel blends of DB, DBCoSuEt, DBCoSuPr and DBCoSuBu were prepared. The physio-chemical properties of blends were tested and performance and emission tests were carried out on a single cylinder four stroke diesel engine. The results indicate that DBCoSuPr fuel combination increases brake thermal efficiency by 9.2% and DBCoSuEt fuel decreases HC and CO emissions by 37.2% and 53.93% respectively