Abstract
Wear properties of two different crushers used for grinding raw materials of cement industry are compared using pin on disk wear test. The wear test was carried out with different loads on a pin. Abrasive wear behavior of two crushers made of Hadfield steel and high chromium cast iron was evaluated by comparing weight loss, wear resistance, microhardness and friction coefficient. The results showed that abrasive wear of high chromium cast iron was lower than Hadfield steel because of the larger amount of carbides and higher work hardening in the steel at the higher applied loads. Increase in surface hardness of Hadfield steel was more noticeable compare to high chromium cast iron due to the work hardening and formation of the twining sites during the wear test. Owing to the presence of M7C3 carbides in high chromium cast iron matrix, impact crushers exhibited higher friction coefficient. In addition, a wear loss equation was derived based on a real crushing condition. However, a new approach in optimization of the wear parameters was developed and wear behavior of the materials was predicted based on the maximum number of the effective factors. The optimization of the parameters by genetic algorithm showed that optimum wear loss for hammer and impact crushers under real condition is 5.2958 mg and 3.8449 mg, respectively. Results of the numerical simulation show that the genetic algorithm optimization is effective and very useful in designing the hammer and impact crushers. In addition, some recent patents on abrasive wear behavior of the high chromium cast iron and Hadfield steel are discussed in details.
Keywords: Abrasive wear, genetic algorithm, Hadfield steel, hammer crusher, high chromium cast iron, impact crusher, optimization, wear resistance
Recent Patents on Mechanical Engineering
Title:Optimization of Abrasive Wear Behavior of High Chromium Cast Iron and Hadfield Steel
Volume: 5 Issue: 2
Author(s): Mehdi Mazar Atabaki, Roohollah Kalatehjari and Sajjad Jafari
Affiliation:
Keywords: Abrasive wear, genetic algorithm, Hadfield steel, hammer crusher, high chromium cast iron, impact crusher, optimization, wear resistance
Abstract: Wear properties of two different crushers used for grinding raw materials of cement industry are compared using pin on disk wear test. The wear test was carried out with different loads on a pin. Abrasive wear behavior of two crushers made of Hadfield steel and high chromium cast iron was evaluated by comparing weight loss, wear resistance, microhardness and friction coefficient. The results showed that abrasive wear of high chromium cast iron was lower than Hadfield steel because of the larger amount of carbides and higher work hardening in the steel at the higher applied loads. Increase in surface hardness of Hadfield steel was more noticeable compare to high chromium cast iron due to the work hardening and formation of the twining sites during the wear test. Owing to the presence of M7C3 carbides in high chromium cast iron matrix, impact crushers exhibited higher friction coefficient. In addition, a wear loss equation was derived based on a real crushing condition. However, a new approach in optimization of the wear parameters was developed and wear behavior of the materials was predicted based on the maximum number of the effective factors. The optimization of the parameters by genetic algorithm showed that optimum wear loss for hammer and impact crushers under real condition is 5.2958 mg and 3.8449 mg, respectively. Results of the numerical simulation show that the genetic algorithm optimization is effective and very useful in designing the hammer and impact crushers. In addition, some recent patents on abrasive wear behavior of the high chromium cast iron and Hadfield steel are discussed in details.
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Mazar Atabaki Mehdi, Kalatehjari Roohollah and Jafari Sajjad, Optimization of Abrasive Wear Behavior of High Chromium Cast Iron and Hadfield Steel, Recent Patents on Mechanical Engineering 2012; 5 (2) . https://dx.doi.org/10.2174/2212797611205020113
DOI https://dx.doi.org/10.2174/2212797611205020113 |
Print ISSN 2212-7976 |
Publisher Name Bentham Science Publisher |
Online ISSN 1874-477X |
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