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Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition
المؤلفون المشاركون
Cheng, En
Sun, Haixin
Yan, Jiaquan
Kuai, Xiaoyan
Zhang, Xiaoliang
المصدر
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-05-17
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
Under the complex oceanic environment, robust and effective feature extraction is the key issue of ship radiated noise recognition.
Since traditional feature extraction methods are susceptible to the inevitable environmental noise, the type of vessels, and the speed of ships, the recognition accuracy will degrade significantly.
Hence, we propose a robust time-frequency analysis method which combines resonance-based sparse signal decomposition (RSSD) and Hilbert marginal spectrum (HMS) analysis.
First, the observed signals are decomposed into high resonance component, low resonance component, and residual component by RSSD, which is a nonlinear signal analysis method based not on frequency or scale but on resonance.
High resonance component is multiple simultaneous sustained oscillations, low resonance component is nonoscillatory transients, and residual component is white Gaussian noises.
According to the low-frequency periodic oscillatory characteristic of ship radiated noise, high resonance component is the purified ship radiated noise.
RSSD is suited to noise suppression for low-frequency oscillation signals.
Second, HMS of high resonance component is extracted by Hilbert-Huang transform (HHT) as the feature vector.
Finally, support vector machine (SVM) is adopted as a classifier.
Real audio recordings are employed in the experiments under different signal-to-noise ratios (SNRs).
The experimental results indicate that the proposed method has a better recognition performance than the traditional method under different SNRs.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yan, Jiaquan& Sun, Haixin& Cheng, En& Kuai, Xiaoyan& Zhang, Xiaoliang. 2017. Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition. Shock and Vibration،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1204862
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yan, Jiaquan…[et al.]. Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition. Shock and Vibration No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1204862
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yan, Jiaquan& Sun, Haixin& Cheng, En& Kuai, Xiaoyan& Zhang, Xiaoliang. Ship Radiated Noise Recognition Using Resonance-Based Sparse Signal Decomposition. Shock and Vibration. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1204862
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1204862
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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