Acoustic emissions from some stressed polypropylene—glass fibre composites have been studied. Pattern recognition has enabled several classes of signal to be identified. These classes and the distribution of the signals in them varies from material to material. By the use of an averaging technique a characteristic acoustic emission signal can be obtained for a particular type of material. Event timing used in conjunction with the data obtained by the analysis of individual signals has led to some speculation on the fracture processes involved.
Get full access to this article
View all access options for this article.
References
1.
J.H. Williams and S.S. Lee, "Acoustic Emission Monitoring of Fiber Composite Materials and Structures," J. Composite Materials , Vol. 12, October, 1978, pp. 348-370.
2.
J.H. Williams , S.S. Lee and T.K. Wang, "Quantitative Nondestructive Evaluation of Automotive Glass Fiber Composites," J. Composite Materials , Vol. 16, January 1982, pp. 20-39.
3.
D. Betteridge , P.A. Connors, T. Lilley, N.R. Shoko, M.E.A. Cudby and D.G.M. Wood, "Analysis of Acoustic Emissions from Polymers ," Polymer (in press).
4.
D.R. Cox and P.A.W. Lewis, "The Statistical Analysis of Series of Events," Methuen, London, 1966.
5.
D. Betteridge , J.V. Cridland, T. Lilley, N.R. Shoko, M.E.A. Cudby and D.G.M. Wood, "Acoustic Emission and ESR Studies of Polymers under Stress," Polymer, Vol. 23, February 1982, pp. 178-184.
6.
B. Woodward , "Identification of Acoustic Emission Source Mechanisms by Energy Spectrum Analysis," Ultrasonics, Vol. 14, No. 6 November 1976, pp. 249-255.
7.
B.R. Kowalski and C.F. Bender, "Pattern Recognition II. Linear and Nonlinear Methods for Displaying Chemical Data," J. Amer. Chem. Soc. , Vol. 95, No. 3, February 1973, pp. 686-693.
8.
B. Everitt, "Cluster Analysis," Heinemann Educational Books , 1974.
9.
A. Peterlin in "Probing Polymer Structure," (Ed. S. L. Koenig), "Advances in Chemistry Series No. 174," Amer. Chem. Soc., Washington D.C.1979.