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Mahalanobis classification system (MCS) integrated with binary particle swarm optimization for robust quality classification of complex metallic turbine blades

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Control and Systems Engineering, Signal Processing, Mechanical Engineering, Civil and Structural Engineering, Aerospace Engineering, Computer Science Applications, Mahalanobis taguchi system, Mahalanobias classification system, Mahalanobis distance, Feature selection, Classification, Binary particle swarm optimization, Process compensated resonance testing, Non-destructive testing, Threshold determination, TAGUCHI SYSTEM, ALGORITHM

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MLA
Cheng, Liangliang, et al. “Mahalanobis Classification System (MCS) Integrated with Binary Particle Swarm Optimization for Robust Quality Classification of Complex Metallic Turbine Blades.” MECHANICAL SYSTEMS AND SIGNAL PROCESSING, vol. 146, 2020, doi:10.1016/j.ymssp.2020.107060.
APA
Cheng, L., Yaghoubi Nasrabadi, V., Van Paepegem, W., & Kersemans, M. (2020). Mahalanobis classification system (MCS) integrated with binary particle swarm optimization for robust quality classification of complex metallic turbine blades. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 146. https://doi.org/10.1016/j.ymssp.2020.107060
Chicago author-date
Cheng, Liangliang, Vahid Yaghoubi Nasrabadi, Wim Van Paepegem, and Mathias Kersemans. 2020. “Mahalanobis Classification System (MCS) Integrated with Binary Particle Swarm Optimization for Robust Quality Classification of Complex Metallic Turbine Blades.” MECHANICAL SYSTEMS AND SIGNAL PROCESSING 146. https://doi.org/10.1016/j.ymssp.2020.107060.
Chicago author-date (all authors)
Cheng, Liangliang, Vahid Yaghoubi Nasrabadi, Wim Van Paepegem, and Mathias Kersemans. 2020. “Mahalanobis Classification System (MCS) Integrated with Binary Particle Swarm Optimization for Robust Quality Classification of Complex Metallic Turbine Blades.” MECHANICAL SYSTEMS AND SIGNAL PROCESSING 146. doi:10.1016/j.ymssp.2020.107060.
Vancouver
1.
Cheng L, Yaghoubi Nasrabadi V, Van Paepegem W, Kersemans M. Mahalanobis classification system (MCS) integrated with binary particle swarm optimization for robust quality classification of complex metallic turbine blades. MECHANICAL SYSTEMS AND SIGNAL PROCESSING. 2020;146.
IEEE
[1]
L. Cheng, V. Yaghoubi Nasrabadi, W. Van Paepegem, and M. Kersemans, “Mahalanobis classification system (MCS) integrated with binary particle swarm optimization for robust quality classification of complex metallic turbine blades,” MECHANICAL SYSTEMS AND SIGNAL PROCESSING, vol. 146, 2020.
@article{8667967,
  articleno    = {{107060}},
  author       = {{Cheng, Liangliang and Yaghoubi Nasrabadi, Vahid and Van Paepegem, Wim and Kersemans, Mathias}},
  issn         = {{0888-3270}},
  journal      = {{MECHANICAL SYSTEMS AND SIGNAL PROCESSING}},
  keywords     = {{Control and Systems Engineering,Signal Processing,Mechanical Engineering,Civil and Structural Engineering,Aerospace Engineering,Computer Science Applications,Mahalanobis taguchi system,Mahalanobias classification system,Mahalanobis distance,Feature selection,Classification,Binary particle swarm optimization,Process compensated resonance testing,Non-destructive testing,Threshold determination,TAGUCHI SYSTEM,ALGORITHM}},
  language     = {{eng}},
  pages        = {{21}},
  title        = {{Mahalanobis classification system (MCS) integrated with binary particle swarm optimization for robust quality classification of complex metallic turbine blades}},
  url          = {{http://dx.doi.org/10.1016/j.ymssp.2020.107060}},
  volume       = {{146}},
  year         = {{2020}},
}

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