Fault Diagnosis usingImproved Ant Colony Optimization Algorithm

Abstract

:In this paper a novel method for solving diagnostic problems more effectively was designed by using a soft computing method. Firstly, vibration signal was measured and analyzed, secondly, the diagnostic tasks were solved by Ant Colony Optimization technique (ACO) and Genetic algorithm technique (GA) using analyzed data. The purpose of using GA and ACO is to compare them with our proposed method that combines advantages of both, GA and ACO algorithms. The created method integrates principles of both approaches and illustrates benefits of applying the integration of ACO and GA to solve diagnostic problems. The novel method provides better performance in both effectiveness and efficiency than the simple GA and ACO algorithms.

Authors and Affiliations

Sakena Alsadig Altahr Saied

Keywords

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  • EP ID EP394434
  • DOI 10.9790/9622-0806046370.
  • Views 124
  • Downloads 0

How To Cite

Sakena Alsadig Altahr Saied (2018). Fault Diagnosis usingImproved Ant Colony Optimization Algorithm. International Journal of engineering Research and Applications, 8(6), 63-70. https://europub.co.uk/articles/-A-394434