Optimization of spring fatigue life prediction model for vehicle ride using hybrid multi-layer perceptron artificial neural networks-Reference-Cited by-同舟云学术

Optimization of spring fatigue life prediction model for vehicle ride using hybrid multi-layer perceptron artificial neural networks

Published:2019-05 Issue: Volume:122 Page:597-621
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Kong Y.S.,Abdullah S.,Schramm D.,Omar M.Z.,Haris S.M.

Funder

Ministry of Education

Universiti Kebangsaan Malaysia

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference40 articles.

1. Failure analysis of a helical compression spring for a heavy vehicle’s suspension system;Zhu;Case Stud. Eng. Fail. Anal.,2014

2. Mission profiling of road data measurement for coil spring fatigue life;Kong;Measurement,2017

3. Multiaxial fatigue and failure analysis of helical compression springs;Del Llano-Viscaya;Eng. Fail. Anal.,2006

4. Weakest link concept for springs fatigue;Kobelev;Mech. Des. Struct. Mach.,2016

5. Weight minimisation of helical compression spring using gravitational search algorithm;Hafizah;Appl. Mech. Mater.,2015

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