Yıl 2017,
Cilt: 7 Sayı: 13, 25 - 31, 30.06.2017
Umut Fırat
,
Tayfun Akgül
Öz
Pervane ve makine kaynaklı gemi gürültülerinden çıkarılan frekans hatları su altı hedef sınıflandırmada kullanılan en önemli verilerdir. Kavitasyon sonucu ortaya çıkan genlik modülasyonlu geniş bant pervane gürültüsü zımnen pervane tonellerini içerirken gemi itki sistemi ve yardımcı makinelerinin su altına yayılan dar bant bileşenleri makine tonellerini oluşturur. Zarf tespitine dayalı Demon ve alçak frekans analizine dayalı Lofar yöntemleri sırasıyla pervane ve makine tonellerinin tespiti için başvurulan temel yöntemlerdir. Bu çalışmada, bu iki yöntemin hedef sınıfını belirlemede nasıl kullanılabileceği İstanbul Boğazı'nda kaydedilmiş gerçek gemi gürültülerinden yararlanılarak tartışılmaktadır. Farklı tipte gemilerin farklı frekanslarda pervane ve makine tonelleri ürettiği gösterilmiştir. Yaşanan başlıca zorluklar arasında, durağan olmayan sinyallere yol açan çevresel şartlar ve gemi gürültülerinin kontrollü deneylerle kaydedilmemiş olması sayılabilir. Gelecek çalışmalarda bu zorlukları aşmak için farklı yöntemler denenmelidir.
Kaynakça
- [1] R. J. Urick, Principles of underwater sound, 3rd ed. New York: McGraw-Hill, 1983.
- [2] D. Ross, Mechanics of underwater noise. Los Altos, California: Peninsula Publishing, 1987.
- [3] J. G. Lourens and M. W. Coetzer, “Detection of mechanical ship features from underwater acoustic sound,” in Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP’87., vol. 12. IEEE, 1987, pp. 1700–1703.
- [4] J. Lourens, “Classification of ships using underwater radiated noise,” in Underwater Acoustic Data Processing. Springer, 1989, pp. 591–596.
- [5] A. Kummert, “Fuzzy technology implemented in sonar systems,” Oceanic Engineering, IEEE Journal of, vol. 18, no. 4, pp. 483–490, 1993.
- [6] H. Amindavar and P. P. Moghaddam, “Estimation of propeller shaft rate and vessel classification in multipath environment,” in Sensor Array and Multichannel Signal Processing Workshop. 2000. Proceedings of the 2000 IEEE.
- [7] R. Fischer and R. D. Collier, “Noise prediction and prevention on ships,” Handbook of Noise and Vibration Control (2007): 1216-1232.
- [8] R. O. Nielsen, “Cramer-rao lower bounds for sonar broad-band modulation parameters,” Oceanic Engineering, IEEE Journal of, vol. 24, no. 3, pp. 285–290, 1999.
- [9] A. Kudryavtsev, K. Luginets, and A. Mashoshin, “Amplitude modulation of underwater noise produced by seagoing vessels,” Acoustical Physics, vol. 49, no. 2, pp. 184–188, 2003.
- [10] F. Bao, X. Wang, Z. Tao, Q. Wang, and S. Du, “Adaptive extraction of modulation for cavitation noise,” The Journal of the Acoustical Society of America, vol. 126, no. 6, pp. 3106–3113, 2009.
Ship Acoustic Signature Analysis
Yıl 2017,
Cilt: 7 Sayı: 13, 25 - 31, 30.06.2017
Umut Fırat
,
Tayfun Akgül
Öz
The frequency lines extracted from ship-radiated propeller and machinery noise give the essential information for underwater target classification. Amplitude modulated broadband propeller noise imposed by cavitation contains the implicit propeller tonals while underwater-radiated narrowband propulsion and auxiliary machinery noise gives rise to machinery tonals. Detection of these propeller and machinery tonals are mainly handled by an envelope detection method, Demon and by a low frequency analysis method, Lofar, respectively. In this paper we discuss the utilization of these methods on the identification of targets employing real-world ship noise recorded in the Strait of Istanbul. We showed that different ship types yield different propeller and machinery tonal frequencies. Main challanges are environmental conditions causing nonstationary signals as well as lack of data from controlled experiments. Thus, future work should include the investigation of suitable methods to cope these challenges.
Kaynakça
- [1] R. J. Urick, Principles of underwater sound, 3rd ed. New York: McGraw-Hill, 1983.
- [2] D. Ross, Mechanics of underwater noise. Los Altos, California: Peninsula Publishing, 1987.
- [3] J. G. Lourens and M. W. Coetzer, “Detection of mechanical ship features from underwater acoustic sound,” in Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP’87., vol. 12. IEEE, 1987, pp. 1700–1703.
- [4] J. Lourens, “Classification of ships using underwater radiated noise,” in Underwater Acoustic Data Processing. Springer, 1989, pp. 591–596.
- [5] A. Kummert, “Fuzzy technology implemented in sonar systems,” Oceanic Engineering, IEEE Journal of, vol. 18, no. 4, pp. 483–490, 1993.
- [6] H. Amindavar and P. P. Moghaddam, “Estimation of propeller shaft rate and vessel classification in multipath environment,” in Sensor Array and Multichannel Signal Processing Workshop. 2000. Proceedings of the 2000 IEEE.
- [7] R. Fischer and R. D. Collier, “Noise prediction and prevention on ships,” Handbook of Noise and Vibration Control (2007): 1216-1232.
- [8] R. O. Nielsen, “Cramer-rao lower bounds for sonar broad-band modulation parameters,” Oceanic Engineering, IEEE Journal of, vol. 24, no. 3, pp. 285–290, 1999.
- [9] A. Kudryavtsev, K. Luginets, and A. Mashoshin, “Amplitude modulation of underwater noise produced by seagoing vessels,” Acoustical Physics, vol. 49, no. 2, pp. 184–188, 2003.
- [10] F. Bao, X. Wang, Z. Tao, Q. Wang, and S. Du, “Adaptive extraction of modulation for cavitation noise,” The Journal of the Acoustical Society of America, vol. 126, no. 6, pp. 3106–3113, 2009.