Structural Health Monitoring of Beams

  • Prashant M. Pawar
  • Ranjan Ganguli


Chapter 3 illustrates the genetic fuzzy system for structural health monitoring of a beam. The cantilever beam structure is fixed at one end and free at the other and can model airplane wings, helicopter blades, and turbine blades, among other things. A finite element model of the undamaged and damaged beam is used to simulate the damaged system. Damage is introduced in the beam by a localized stiffness reduction in accordance with continuum mechanics theory. A genetic fuzzy system is formulated for the beam structure to find the damage location and size from modal data. Initially, the genetic fuzzy system is developed for a uniform beam. It is shown that the method is robust to noise in the data and to missing measurements. The genetic fuzzy system is then illustrated for a nonuniform beam and for a more refined discretization of the damage locations. It is shown that the architecture of the genetic fuzzy system allows for a simple approach for recreating the pattern recognition algorithms as the measurements and outputs change. For each input-output set, a genetic algorithm is used to maximize the success rate of fault isolation for a set of noisy data. The approach is finally illustrated for a non-rotating helicopter main rotor blade using frequency and mode shape data. It is found that the genetic fuzzy system performs very well for the structural health monitoring of beams.


Fuzzy System Cantilever Beam Damage Detection Structural Health Monitoring Fuzzy Logic System 
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. 1.
    Chandrupatla, T.R., Belegundu, A.D.: Introduction to Finite Elements in Engineering. Prentice-Hall, Englewood Cliffs (2001) Google Scholar
  2. 2.
    Reddy, J.N.: An Introduction to the Finite Element Method. McGraw-Hill Higher Education, New York (2006) Google Scholar
  3. 3.
    Bathe, K.J.: Finite Element Procedures. Prentice-Hall, Englewood Cliffs (1996) Google Scholar
  4. 4.
    Zienkiewicz, O.C., Tylor, R.L.: The Finite Element Method. Butterworth-Heinemann, Oxford (2000) MATHGoogle Scholar
  5. 5.
    Ganguli, R.: Health monitoring of helicopter rotor in forward flight using fuzzy logic. AIAA J. 40(12), 2773–2781 (2002) CrossRefGoogle Scholar
  6. 6.
    Ganguli, R.: A fuzzy logic system for ground based structural health monitoring of a helicopter rotor using modal data. J. Intell. Mater. Syst. Struct. 12(6), 397–408 (2001) CrossRefGoogle Scholar
  7. 7.
    Pawar, P.P., Ganguli, R.: Genetic fuzzy system for damage detection in beams and helicopter rotor blades. Comput. Methods Appl. Mech. Eng. 192(16–18), 2031–2057 (2003) MATHCrossRefGoogle Scholar
  8. 8.
    Chandrasekhar, M., Ganguli, R.: Uncertainty handling in structural damage detection using fuzzy logic and probabilistic simulation. Mech. Syst. Signal Process. 23(2), 384–404 (2009) CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.College of EngineeringShri Vithal Education and Research InstitutePandharpurIndia
  2. 2.Department of Aerospace EngineeringIndian Institute of ScienceBangaloreIndia

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