Abstract
The aerospace power is widely used in the aerospace system. Its reliability directly affects the safety of the whole system. However, the particles generated in the production process usually cause failures to the aerospace power. In this paper, a novel automatic detection method for particles in the aerospace power is proposed based on Particle Impact Noise Detection (PIND) test. Firstly, stochastic resonance algorithm is presented to detect the existence of tiny particles. Secondly, in order to obtain the sources of particles, wavelet packet transform is used to extract energy distribution vectors of different material particles, and Learning Vector Quantization(LVQ) network is brought in for material identification of particles. Finally, the results indicate that the accuracy meets the requirements of practical application.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Gao, H.L., Zhang, H., Wang, S.J.: Research on Auto-detection for Remainder Particles of Aerospace Relay based on Wavelet Analysis. Chinese Journal of Aeronautics 20(1), 74–80 (2007)
Wang, S.J., Gao, H.L., Zhai, G.F.: On Feature Extraction of Remnant Particles of Aerospace Relays. Chinese Journal of Aeronautics 20(6), 253–259 (2007)
Harmer, G.P., Davis, B.R., Abbott, D.: A Review of Stochastic Resonance: Circuits and Measurement. IEEE Transactions on Instrumentation and Measurement 51(2), 209–309 (2002)
Leng, Y.G., Wang, T.Y., Qin, X.D.: Power Spectrum Research of Twice Samplings to Resonance Response in a Bistable System. ACTA Physica Sinica, 53(3), 717–723 (2004) (in Chinese)
Li, D.Q., Pedrycz, W., Pizzi, N.L.: Fuzzy Wavelet Packet based Feature Extraction Method and Its Application to Biomedical Signal Classification. IEEE Transactions on Biomedical Engineering 52(6), 1132–1139 (2005)
Wang, B.C., Omatu, S., Abe, T.: Identification of the Defective Transmission Devices Using the Wavelet Transform. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(6), 919–928 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, S., Chen, R., Zhang, L., Wang, S. (2010). Research on Detection and Material Identification of Particles in the Aerospace Power. In: Li, K., Fei, M., Jia, L., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science, vol 6329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15597-0_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-15597-0_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15596-3
Online ISBN: 978-3-642-15597-0
eBook Packages: Computer ScienceComputer Science (R0)