Particle swarm optimisation algorithm for crack shape reconstruction in magnetic flux leakage nondestructive testing
Source abstract
Abstract
Magnetic flux leakage testing is widely used to examine ferromagnetic materials. Considering the importance of estimating the size of surface crack in metals, which is used in nuclear power, railway and piping industries, a method based on particle swarm optimisation algorithm is proposed in this article. This approach maps the size of crack to the location of particles. After initialising the locations and velocities of the particle population, it evaluates the fitness value of the individual particle and tracks the optimal one. It then updates the positions and velocities of particles with the previous fitness values and repeats these steps until the best possible result is obtained. The fitness value is obtained by summing the absolute measurement error of the magnetic leakage field intensity of the crack. The results of simulation experiments demonstrate the effectiveness of the proposed method.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Non-Destructive Testing Techniques · Ultrasonics and Acoustic Wave Propagation · Structural Health Monitoring Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
a School of Computer and Information , Hefei University of Technology , Hefei , P. R. China
b Institute of Statistical Signal Processing , University of Science and Technology of China , Hefei , P. R. China
References (7)
Show source-provided references
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