Using genetic algorithms and finite element methods to detect shaft crack for rotor-bearing system

By Yongyong He, Dan Guo, F. Chu. 2001

74 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/eb316f4ddb1181780832307eb52737beef88a902

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. Haim Waisman
2. Hao Sun
3. Gang Yan

In Mechanical Engineering

1. Hao Sun
2. Haim Waisman
3. Gang Yan
4. Hui Ma
5. Bangchun Wen
6. Oral Büyüköztürk
7. Raimondo Betti

In Mechanics of Materials

1. Hao Sun
2. Haim Waisman
3. Gang Yan
4. Oral Büyüköztürk
5. Raimondo Betti

Citations in the corpus

• A guided Bayesian inference approach for detection of multiple flaws in structures using the extended finite element method (2015, methodology): “Among these developments are model-based methods, which can quantitatively identify the location and size (extent) of flaws and have drawn significant attention [4–15].”
• Analysis of dynamic characteristics for a rotor system with pedestal looseness (2011, methodology): “For shaft crack detection, a genetic algorithm [16] was proposed, which can make the shaft crack detection as an optimization problem by means of the finite element method.”