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A Novel Prediction Perspective to the Bending Over Sheave Fatigue Lifetime of Steel Wire Ropes by Means of Artificial Neural Networks

A Novel Prediction Perspective to the Bending Over Sheave Fatigue Lifetime of Steel Wire Ropes by Means of Artificial Neural Networks
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Author(s): Tuğba Özge Onur (Zonguldak Bulent Ecevit University, Turkey)and Yusuf Aytaç Onur (Zonguldak Bulent Ecevit University, Turkey)
Copyright: 2020
Pages: 20
Source title: Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering
Source Author(s)/Editor(s): Gebrail Bekdaş (Istanbul University-Cerrahpaşa, Turkey), Sinan Melih Nigdeli (Istanbul University-Cerrahpaşa, Turkey)and Melda Yücel (Istanbul University-Cerrahpaşa, Turkey)
DOI: 10.4018/978-1-7998-0301-0.ch003

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Abstract

Steel wire ropes are frequently subjected to dynamic reciprocal bending movement over sheaves or drums in cranes, elevators, mine hoists, and aerial ropeways. This kind of movement initiates fatigue damage on the ropes. It is a quite significant case to know bending cycles to failure of rope in service which is also known as bending over sheave fatigue lifetime. It helps to take precaution in the plant in advance and eliminate catastrophic accidents due to usage of rope when allowable bending cycles are exceeded. To determine bending fatigue lifetime of ropes, experimental studies are conducted. However, bending over sheave fatigue testing in laboratory environments require high initial preparation cost and longer time to finalize the experiments. Due to those reasons, this chapter focuses on a novel prediction perspective to the bending over sheave fatigue lifetime of steel wire ropes by means of artificial neural networks.

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