During ANC system design we will have to answer questions such as: “How is the acoustic pressure distributed in the interior?”, “What are the positions of the primary noise sources?” or “What will be the control profit, if active noise cancellation is applied? As we know, it will in many projects be impossible to perform time and cost intensive measurement campaigns. This is especially true in an early design stage in which we have neither a functional model nor a prototype. For this reason, the distribution of acoustic field variables has to be predicted by a numerical simulation that is based on an appropriate mathematical model. In view of the second question it must be emphasized that because of standing waves localization of sound sources in weakly damped enclosed sound fields is—especially in the low frequency range—a difficult mission. Noise source identification therefore requires advanced experimental and also advanced numerical approaches. In order to answer the third question we will have to estimate the amount of noise reduction that can be realized by a feed-forward ANC-system. Therefore, it will be necessary to analyze the correlation between the reference signals and the disturbance as well as to analyze the effect of transducer locations on the control profit. It is obvious that we need some specific instruments to process work packages that are associated with these questions. For this reason the upcoming chapter is dedicated to some tools that can be used in the ANC-system design process.


Boundary Element Method Sound Pressure Finite Difference Method Acoustic Velocity Column Matrix 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Anderssohn R, Marburg S, Großmann C (2006) FEM-based reconstruction of sound pressure field damped by partially absorbing boundary conditions. Mech Res Commun 33:851–859 zbMATHCrossRefGoogle Scholar
  2. ANSYS (2010) Product description ANSYS. Cited 09 June 2010
  3. Bathe KJ (1996) Finite element procedures. Prentice Hall, London Google Scholar
  4. Berbbia CA (1978) The boundary element method for engineers. Pentech Press, London Google Scholar
  5. Björck A (1996) Numerical methods for least squares problems. SIAM, Philadelphia zbMATHCrossRefGoogle Scholar
  6. Chargin M, Gartmeier O (1990) A finite element procedure for calculating fluid-structure interaction using MSC/NASTRAN. NASA Technical Memorandum 102857 Google Scholar
  7. Christensen JJ, Hald J (2004) Beamforming. Technical Review 1, Brüel & Kjaer, 1–35 Google Scholar
  8. COMSOL (2010) COMSOL Multiphysics. Product description COMSOL Cited 09 June 2010
  9. Drenckhan J, Sachau D (2004) Identification of sound sources using inverse FEM. In: Proc of ICSV11, 11th int congress on sound and vibration, St. Petersburg, Russia, July 5–8 Google Scholar
  10. Drenckhan J, Sachau D (2005) Influence of smoothing to the inverse finite element method for acoustic hot-sport identification. In: Proc of InterNoise 2005, 34th international congress and exposition on noise control engineering, Rio de Janeiro, Brazil, August 7–10 Google Scholar
  11. Elliott SJ (2001) Signal processing for active noise control. Academic Press, London Google Scholar
  12. Fahy F, Gardonio P (2007) Sound and structural vibration. Elsevier, Amsterdam Google Scholar
  13. Frequency Devices Inc. (2009) Analog and digital products design/selection guide. Frequency Devices Inc., Ottawa, Canada. Cited 30 Sep 2009
  14. Fuller WA (1976) Introduction to statistical time series. Wiley, New York zbMATHGoogle Scholar
  15. Gaul L, Kögl M, Wagner M (1997) Boundary element methods for engineers and scientist—an introductory course with advanced topics. Springer, Berlin Google Scholar
  16. Golub GH, Kahan W (1965) Calculating the singular values and pseudo-inverse of a matrix. J Soc Ind Appl Math Ser B Numer Anal 2(2):205–224 MathSciNetCrossRefGoogle Scholar
  17. Guicking D (2002) An overview of ASVC: from laboratory curiosity to commercial products. In: Tokhi O, Veres S (eds) Active sound and vibration control. Institution of Electrical Engineers, London, pp 3–23 CrossRefGoogle Scholar
  18. Hald J (1989) STSF a unique technique for scan-based near-field acoustic holography without restrictions on coherence. Technical Review 1, Brüel & Kjaer, 1–50 Google Scholar
  19. Hanke M (1996) Limitations of the L-curve method for ill-posed problems. BIT Numer Math 36:287–301 MathSciNetzbMATHCrossRefGoogle Scholar
  20. Hansen PC, O’Leary DP (1993) The use of the L-curve in the regularization of discrete ill-posed problems. SIAM J Sci Comput 14(6):1487–1503 MathSciNetzbMATHCrossRefGoogle Scholar
  21. Hansen PC, Kilmer M, Kjeldsen RH (2006) Exploiting residual information in the parameter choice for discrete ill-posed problems. BIT Numer Math 46:41–59 MathSciNetzbMATHCrossRefGoogle Scholar
  22. Holland KR, Nelson PA (2004) Sound source characterization: the focused beamformer vs the inverse method. In: Proc of ICSV11, 11th int congress on sound and vibration, St. Petersburg, Russia, July 5–8 Google Scholar
  23. Hundeck C (2008) Moderne Verfahren zur Schallquellenortung mit Arraysystemen. Lärmbekämpfung—Zeitschrift für Akustik Schallschutz und Schwingungstechnik 3(2):55–70 Google Scholar
  24. Maynard JD, Williams EG, Lee Y (1985) Nearfield acoustic holographie: I. Theory of generalized holography and the development of NAH. J Acoust Soc Am 78(4):395–1413 CrossRefGoogle Scholar
  25. Moschytz G, Hofbauer M (2000) Adaptive Filter—Eine Einführung in die Theorie mit Aufgaben und Matlab-Simulationen auf CD-ROM. Springer, Berlin Google Scholar
  26. NASTRAN (2010) MSC NATSRAN. Product description MSC software. Cited 09 June 2010
  27. Nelson PA, Elliott SJ (1992) Active control of sound. Academic Press, London Google Scholar
  28. Paige CC, Saunders MA (1982) LSQR: an algorithm for sparse linear equations and sparse least squares. ACM Trans Math Softw 8(1):43–71 MathSciNetzbMATHCrossRefGoogle Scholar
  29. Sachau D, Drenckhan J (2006) Sound source localization in cabins by inverse finite element analysis. In: Proc of DAGA ’06—32. Deutsche Jahrestagung für Akustik, Braunschweig, Mart 20–23 Google Scholar
  30. Sachau D, Drenckhan J, Kletschkowski T, Petersen S (2005b) Entwicklung von Messtechniken zur Lärmquellenidentifizierung in Kabinen. Final Report, Hamburg Aircraft Research Program (Lufo Hamburg 1), TUT-34, Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg Google Scholar
  31. Sachau D, Kletschkowski T, Gerner C (2007b) Noise source identification and optimized active noise control in aircraft cabins. In: Proc of AST 2007, Workshop on aircraft system technologies, Hamburg, Mart 31–April 1 Google Scholar
  32. Sachau D, Weber M, Kletschkowski T (2009) Schlussbericht zu Lufo IV “MONSOS”. Final Report, German Aircraft Research Program (Lufo IV), Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg Google Scholar
  33. SYSNOISE (2010) LMS SYSNOISE. Product description LMS engineering innovation. Cited 09 June 2010
  34. Tikhonov AN (1963) Solution of incorrectly formulated problems and the regularization method. Dokl Akad Nauk SSSR 151:501–504. Translated in Sov Math 4:1035–1038 MathSciNetGoogle Scholar
  35. Vapnyarskii BI (2001) Lagrange multipliers. In: Hazewinkel M Encyclopaedia of mathematics. Springer, Berlin. Cited 6 December 2009 Google Scholar
  36. Vogel CR (1996) Non-convergence of the L-curve regularization parameter selection method. Inverse Probl 12:535–547 zbMATHCrossRefGoogle Scholar
  37. von Estorff O, Coyette JP, Migeot JL (2000) Governing formulations of the BEM in acoustics. In: von Estorff O (ed) Boundary elements in acoustics, advances and applications. WIT Press, Southampton Google Scholar
  38. Weber M (2009) Inverse Schallquellenortung in Flugzeugkabinen. Dissertation, Helmut-Schmidt-University/University of the Federal Armed Forces Hamburg Google Scholar
  39. Weber M, Sachau D, Kletschkowski T (2008a) Identifikation von Schallquellen mittels inverser FEM mit realen Messdaten. In: Proc of DAGA ’08-34. Deutsche Jahrestagung für Akustik, Dresden, Mart 10–13 Google Scholar
  40. Weber M, Kletschkowski T, Samtleben B (2008b) Identification of noise sources by means of inverse finite element method. In: Proc of COMSOL conference ’08, Hannover, Nov 4–6 Google Scholar
  41. Weber M, Kletschkowski T, Samtleben B (2008c) Identification of noise sources by means of inverse finite element method using measured data. In: Proc of acoustics ’08—organized by the Acoustical Society of America, the European Acoustics Association, and the Societe Francaised Acoustique. Paris, June 29–July 04 Google Scholar
  42. Weber M, Kletschkowski T, Sachau D, Samtleben B (2009a) Tracking down the noise—identification of noise sources in aircraft cabins using simulated acoustics. Physics’ Best. Wiley-VCH, Weinheim, pp 32–34 Google Scholar
  43. Weber M, Sachau D, Kletschkowski T (2009b) Noise source identification in a cross-section of a long-range airliner by means of the inverse finite element method. In: Proc of NAG/DAGA 2009, int conf on acoustics, including the 35th German annual conference on acoustics (DAGA), Rotterdam, Mart 23–26 Google Scholar
  44. Weber M, Sachau D, Kletschkowski T (2009c) Inverse identification of noise sources in aircraft interiors. In: Proc of AST 2009 workshop on aircraft system technologies, Hamburg, Mart 26–27 Google Scholar
  45. Wu SF (2008) Methods for reconstructing acoustic quantities based on acoustic pressure measurements. J Acoust Soc Am 124(5):2680–2697 CrossRefGoogle Scholar
  46. Zienkiewicz OC, Taylor RL (2000) Finite element method, vol 1—the basis. Elsevier, Amsterdam zbMATHGoogle Scholar
  47. Zwillinger D (1989) Handbook of differential equations. Academic Press, San Diego zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Mechanical Engineering, MechatronicsHelmut-Schmidt-University/University of the Federal Armed Forces HamburgHamburgGermany

Personalised recommendations