Industrial Lubrication and Tribology

The wear behavior of mild steel under vertical vibration : Table of Contents

Dr. Mohammad Asaduzzaman Chowdhury, Dr. Md. Maksud Helali — Sun Jul 05 14:15:04 BST 2009

Abstract:
Purpose - The present paper investigates experimentally the effect of external vertical vibration on wear property of mild steel. To do so, a pin-on-disc apparatus having facility of vibrating the test samples at vertical direction was designed and fabricated. The experimental setup has the facility to vary the amplitudes and frequencies of vibration while velocity of vibration is kept constant. During experiment the frequency and amplitude of vibration were varied from 0 to 500 Hz and 0 to 200 µm, respectively. Results show that the wear rate decreases with the increase of amplitude and frequency of vibration for mild steel. These results are analyzed by dimensional analysis to correlate the wear rate with sliding velocity, normal load, frequency and amplitude of vibration. The experimental results are also compared with those available in literature and simple physical explanations are provided.Design/methodology/approach - Experimental and Dimensional AnalysisFindings - Considering the lack of correlation between wear rate and other vibration related operating parameters, the present research was started to find out suitable correlation and a way of reducing wear rate by applying known frequency and amplitude of vibration at a particular direction. Practical implications - It is expected that the applications of these results will contribute to the improvement of different concerned mechanical systems. Originality/value - It can be used for design related purposes

Oils quality and performance analysis of vehicle’s engines using radial basis neural networks : Table of Contents

Prof. SAHIN YILDIRIM — Sun Jul 05 14:15:04 BST 2009

Abstract:
Purpose - To improve the application of neural networks on vehicle engine system for fault detecting and analysing engine’s oilsDesign/methodology/approach - Three types of neural network are employed to find exact neural network predictor of vehicle engine’s oil performance and quality. Nevertheless, two types oil are analysed for predicting performance in the engine. These oils are used oil and unused oil. In experimental work two accelerometers are located at the bottom of the car engine to measure related vibrations for analysing oil quality of both cases.Findings - The result of both computer simulation and experimental work show that the radial basis neural network predictor gives good performance at adapting different cases.Research limitations/implications - The results of the proposed neural network analyser follow desired results of the vehicle engine’s vibration variation. However, this kind of neural network schemes could be used to analyse oil quality of the car in experimental applications.Practical implications - As theoretical and practical study is evaluated together, it is hoped that oil analysers and interested researchers will obtain significant results in this application area.Originality/value - This paper is consisted of original contribution on vehicle’s oil quality analysis using a proposed artificial neural network. On the other hand, it should be helpful for vehicles industry applications of oil quality analysis and fault detection.