- Email: [email protected]
An expert system for eddy current signal evaluation of steam generator tubes
system for detection of cracks with/without human involvement. By using several robots simultaneously, the inspection time can be reduced with more consistent results.
46667
Thomsen, JJ.; Lund, K.
Q u a l i t y control of composite materials by n e u r a l n e t w o r k a n a l y s i s of ultrasonic power spectra Materials Evaluation, Vol. 49, No. 5, pp. 594-600 (May 1991) A new concept of spectral analysis of ultrasonic test measurements is presented. An artificial neural network was implemented in software trained to classify measured ultrasonic power spectra of composite laminates according to fabrication quality. In a laboratory test, the network was able to classify correctly 83 percent of 365 spectra from epoxy laminate plares in which localized areas of delamination, anomalous fiber concentration, and matrix porosity had been artificially induced.
Chiou, C.-P. Model-based ultrasonic flaw classification and sizing
46652
Dissertation Abstracts International. Vol. 51, No. 8. pp. 4013-B (Feb. 1991) (DA 9101339) In this work. we describe new techniques for both classification and sizing. In particular, a flaw classification technique is considered that employs mode-converted diffracted signals in a quasi-pulse-echo configuration to distinguish smooth vs. sharp-edged flaws. For the flaw sizing applications, three approaches are presented. These approaches include (I) a non-iterative equivalent sizing method, where the best equivalent ellipsoid (for volumetric flaws) or ellipse (for cracks) is found that matches the scattering data, (2) a spherical harmonics expansion algorithm and (3) the use of neural networks for equivalem flaw sizing. In addition, we consider the effect of classification information on the sizing problem, describe a technique for correcting systematic errors in sizing cracks due to the finite bandwidths of ultrasonic transducers. and present an enhanced adaptive learning method that can speed up the training of a neural network.
Grabec, I.; Sachse. W. Automatic modeling of physical phenomena: Application to ultrasonic
46634
data Journal of Applied Physics, Vol. 69, No. 9, pp. 6233-6244, (1 May 1991) The physical modeling of natural phenomena is treated in this paper as an information transforming process which can be performed by a general modeler compo~d of an array of sensors, a central processing unit, a memory, and an array of actuators. The most characteristic properly of such a system is its capability of predicting some properties of observed phenomena from partial perception and past experience. The proposed modeler was simulated on a laboratory minicomputer which was part of a general data acquisition system. It was applied to the modeling of acoustic emission and ultrasonic scattering phenomena. It is shown experimentally that forward and inverse acoustic emission problems can be solved and a simple characterization of material inhomogeneities can be performed by the modeler. A mutual mapping of conditional data to estimated ones and the reverse is the basis of an iteration procedure which corresponds to a discrete dynamical process in the multidimensional data space. Numerical examples show that attractors of this process in the multidimensional data space. Numerical examples show that attractors of this process are the vectors of the data base. Therefore, the iteration can be efficiently applied for noise reduction. The operation of the dynamical system is comparable to the operation of neural networks in which the memory corresponds to the data base.
Udpa, L.; Udpa, S.S. Application of neural networks to nondestructive evaluation
46594
Proceedings of the Ist International Conference on Artificial Neural Networks, London (United Kingdom). 16-18 Oct. 1989. pp 143-147. Institution of Electrical Engineers, ISBN 0852963882, (I 989) This paper proposes the u ~ of massively parallel learning networks for classifying signals form electromagnetic transducers used in nondestructive evaluation. One of the major contributions of the paper lies in the development-of a distributed processing network for preprocessing the transducer signal. Pl"eprocessing is required for achieving invariance under rotation, translation and ~aling of the signal. Results of implementing the network as well as a brief discussion on the performance of the network are presented.
Rose. J.L.; Huung, Y. Ultrasonic NDE for advanced material property determination
46565
Advanced Materials: The Big Payoff. Proceedings of the 21st International S A M P E Technical Conference, Atlantic City, New Jersey (United States), 25-28 Sep. 1989. pp. 221-230, Edited by Wegman, Kliger and Hogan. Society for the Advancement o f Material and Process Engineering (1989) Advanced materials such as ceramics composites, and unusually formed metals or powdered metal products are often inhomogeneous and anisotmpic. A great need exists to determine both global and local material characteristics to insure performance to engineering specifications. NDE holds the potential to provide accurate and precise information regarding material properties. Emphasis in this paper is placed on the description of bulk and surface wave ultrasonic techniques for the determination of effective stiffness coefficients, material homogeneity, and global porosity or fiber volume fraction variations within advanced engineering materials. Local defect characterization is also discussed. Implementation of these advanced bulk and guided wave techniques is considered by way of expert systems and artificial intelligence.The potential utility in an on-line manufacturing environment will also be discussed.
Woo. H.G.; Yung, I.K; Kim. K.Y. An expert system for eddy current signal evaluation of steam generator tubes
46489
Collected Reprints By KAERI Research Papers in 1989, Vol. 17, KAERI/RP- 17/89, pp. 648-656. KAERI (1989) Conventional eddy current testing (ECT) used in the nuclear steam generator (S/G)
42
needs many high quality inspectors who evaluate eddy current (EC) signals on a continuously rolling-up screen. Since most EC signals are normal signals and only a small portion is flaw signals, the EC signal evaluation is tedious time-consuming work which can cause inspectors to incorrectly interpret the EC signals. Therefore. an expert system for automatic evaluation of eddy current signal of S/G tubes was built in an attempt to correct the problems. The other problem of the traditional ECT inspection is that it also needs many man-hours in handling huge EC signal data. EC data are usually analyzed again by off-line, which requires many man-hours. However, the expert system supplies such functions by on-line since it has a powerful data base management function and all EC data are stored in optical disks, 46169 Lytton. R.L.; Germann, F.P.; Chou, YJ.; Stoffels, S.M. D e t e r m i n i n g a s p h a l t i c concrete pavement s t r u c t u r a l p r o p e r t i e s by nondestructive testing Texas Transportation Inst., College Station (United States), PB-90272048/GAR, 112 pp. (Jun. 1990) The high-volume data collection capabilities of modem nondestructive testing equipment require an analysis method which is capable of rapid backcalculation of pavement layer moduli in a production mode of data reduction. A layered elastic analysis method named MODULUS was developed for a microcomputer that is very fast operation and provides consistently reliable results. Random errors in the measurements and systematic errors in the measurements and systematic errors in the backcalculation process may be reduced, the former by repeating the measurements and the latter by use of a microcomputer expert system named PASELS. to provide consistently acceptable layer moduli values. Users' guides to both microcomputer programs are provided.
Billington, R. Application of expert systems for vibration based diagnosis
46099
Proceedings of the Vibration Analysis for Condition Monitoring Techniques and User Experience Seminar, Solihull (United Kingdom). 20 Feb. 1990, pp. 63-72. The British Institute of Non-Destructive Testing (1990) ISBN 0903132192 This paper deals with theapplication of an Expert system shell for vibration based diagnosis. It is well accepted that vibration may be used as an early indication of machine health, however, the techniques used are often hidden by myth and tainred by suspicion. This paper is concerned with the application of rare expertise to a complex problem in a cool, calculating environment, that of the personal computer. 46098 Nicholls, C. E x p e r t system to diagnose machinery vibration problems Proceedings of the Vibration Analysis for Condition Monitoring Techniques and User Experience Seminar, Solihull (United Kingdom), 20 Feb. 1990, pp. 86-95. The British Institute of Non-Destructive Testing (1990) ISBN 0903132192 Expert systems are fast becoming valuable tools in machine maintenance organisations worldwide. The DXPERT system has incorporated senior expert diagnostician and engineers' knowledge to resolve teal world vibration problems on six different kinds of machines. 46082 Lucia, A.C.; Brlinnhuber, R.; Elbaz, J.M.; Schwarz, U. A n a l y t i c a l methods and inspection procedures for lifetime prediction of
components subject to fatigue damage accumulation Reactor Safety Research. Edited by W. Krischer. pp. 693-718. Elsevier Applied Science (1990) The assessment of the reliability and of the residual life-time of a structure is achieved by means of a global procedure relying on a number of steps to be concatenated and merged:non-destructive testing and monitoring, material characterization, load analysis, stress analysis, fracture mechanics analysis, damage accumulation analysis, etc. hnpmvements are suggested for some of these steps. Attention is paid to data analysis, treatment of uncertainties, use of non algorithmic knowledge and expert system development.
Upda, L.," Upda. S.S. Application of neural networks for classification of eddy current NDT
45990
data Review of Progress in Quantitative Nondestructive Evaluation, Brunswick, Maine (United States), 23-28 Jul. 1989. Vol. 9A, pp. 673: 680. Edited by D.O. Thompson and D,E. Chimenti. Plenum Press (1990) This paper studies the application of neural network models for classifying defect signals from eddy current transducers used in nondestructive evaluation of materials. The following presents a brief introduction to neural net models and the learning algorithm. The preprocessing of the transducer signals for data compression is discussed. The results of performance of the network are presented and compared with results obtained by using the K-means clustering algorithm.
Mann, J.M.; Schmerr, L.W.; Moulder, J.C. Inversion of uniform field eddy c u r r e n t d a t a using neural networks
45989
Review of Progress in Quantitative Nondestructive Evaluation, Brunswick, Maine (United States), 23-28 Jal. 1989. Vol. 9A, pp. 681- 688. Edited by D.O. Thompson and D.E. Chimenti. Plenum Press (1990) Inversion of eddy current flaw signals has typically been based upon models of the field-flaw interaction. Although the feasibility of inverting eddy current data in this fashion has been demonstrated before, the complexity of s~ch procedures has hampered their widespread acceptance and use in industry. The goal of this study is to develop an inversion method that is easy to use and implement outside the research community. This paper pre~nts preliminary results on the use of neural networks for the inversion of eddy current flaw signals to obtain flaw sizes.
N D T & E International Volume 25 Number 1 1992
46667
Thomsen, JJ.; Lund, K.
Q u a l i t y control of composite materials by n e u r a l n e t w o r k a n a l y s i s of ultrasonic power spectra Materials Evaluation, Vol. 49, No. 5, pp. 594-600 (May 1991) A new concept of spectral analysis of ultrasonic test measurements is presented. An artificial neural network was implemented in software trained to classify measured ultrasonic power spectra of composite laminates according to fabrication quality. In a laboratory test, the network was able to classify correctly 83 percent of 365 spectra from epoxy laminate plares in which localized areas of delamination, anomalous fiber concentration, and matrix porosity had been artificially induced.
Chiou, C.-P. Model-based ultrasonic flaw classification and sizing
46652
Dissertation Abstracts International. Vol. 51, No. 8. pp. 4013-B (Feb. 1991) (DA 9101339) In this work. we describe new techniques for both classification and sizing. In particular, a flaw classification technique is considered that employs mode-converted diffracted signals in a quasi-pulse-echo configuration to distinguish smooth vs. sharp-edged flaws. For the flaw sizing applications, three approaches are presented. These approaches include (I) a non-iterative equivalent sizing method, where the best equivalent ellipsoid (for volumetric flaws) or ellipse (for cracks) is found that matches the scattering data, (2) a spherical harmonics expansion algorithm and (3) the use of neural networks for equivalem flaw sizing. In addition, we consider the effect of classification information on the sizing problem, describe a technique for correcting systematic errors in sizing cracks due to the finite bandwidths of ultrasonic transducers. and present an enhanced adaptive learning method that can speed up the training of a neural network.
Grabec, I.; Sachse. W. Automatic modeling of physical phenomena: Application to ultrasonic
46634
data Journal of Applied Physics, Vol. 69, No. 9, pp. 6233-6244, (1 May 1991) The physical modeling of natural phenomena is treated in this paper as an information transforming process which can be performed by a general modeler compo~d of an array of sensors, a central processing unit, a memory, and an array of actuators. The most characteristic properly of such a system is its capability of predicting some properties of observed phenomena from partial perception and past experience. The proposed modeler was simulated on a laboratory minicomputer which was part of a general data acquisition system. It was applied to the modeling of acoustic emission and ultrasonic scattering phenomena. It is shown experimentally that forward and inverse acoustic emission problems can be solved and a simple characterization of material inhomogeneities can be performed by the modeler. A mutual mapping of conditional data to estimated ones and the reverse is the basis of an iteration procedure which corresponds to a discrete dynamical process in the multidimensional data space. Numerical examples show that attractors of this process in the multidimensional data space. Numerical examples show that attractors of this process are the vectors of the data base. Therefore, the iteration can be efficiently applied for noise reduction. The operation of the dynamical system is comparable to the operation of neural networks in which the memory corresponds to the data base.
Udpa, L.; Udpa, S.S. Application of neural networks to nondestructive evaluation
46594
Proceedings of the Ist International Conference on Artificial Neural Networks, London (United Kingdom). 16-18 Oct. 1989. pp 143-147. Institution of Electrical Engineers, ISBN 0852963882, (I 989) This paper proposes the u ~ of massively parallel learning networks for classifying signals form electromagnetic transducers used in nondestructive evaluation. One of the major contributions of the paper lies in the development-of a distributed processing network for preprocessing the transducer signal. Pl"eprocessing is required for achieving invariance under rotation, translation and ~aling of the signal. Results of implementing the network as well as a brief discussion on the performance of the network are presented.
Rose. J.L.; Huung, Y. Ultrasonic NDE for advanced material property determination
46565
Advanced Materials: The Big Payoff. Proceedings of the 21st International S A M P E Technical Conference, Atlantic City, New Jersey (United States), 25-28 Sep. 1989. pp. 221-230, Edited by Wegman, Kliger and Hogan. Society for the Advancement o f Material and Process Engineering (1989) Advanced materials such as ceramics composites, and unusually formed metals or powdered metal products are often inhomogeneous and anisotmpic. A great need exists to determine both global and local material characteristics to insure performance to engineering specifications. NDE holds the potential to provide accurate and precise information regarding material properties. Emphasis in this paper is placed on the description of bulk and surface wave ultrasonic techniques for the determination of effective stiffness coefficients, material homogeneity, and global porosity or fiber volume fraction variations within advanced engineering materials. Local defect characterization is also discussed. Implementation of these advanced bulk and guided wave techniques is considered by way of expert systems and artificial intelligence.The potential utility in an on-line manufacturing environment will also be discussed.
Woo. H.G.; Yung, I.K; Kim. K.Y. An expert system for eddy current signal evaluation of steam generator tubes
46489
Collected Reprints By KAERI Research Papers in 1989, Vol. 17, KAERI/RP- 17/89, pp. 648-656. KAERI (1989) Conventional eddy current testing (ECT) used in the nuclear steam generator (S/G)
42
needs many high quality inspectors who evaluate eddy current (EC) signals on a continuously rolling-up screen. Since most EC signals are normal signals and only a small portion is flaw signals, the EC signal evaluation is tedious time-consuming work which can cause inspectors to incorrectly interpret the EC signals. Therefore. an expert system for automatic evaluation of eddy current signal of S/G tubes was built in an attempt to correct the problems. The other problem of the traditional ECT inspection is that it also needs many man-hours in handling huge EC signal data. EC data are usually analyzed again by off-line, which requires many man-hours. However, the expert system supplies such functions by on-line since it has a powerful data base management function and all EC data are stored in optical disks, 46169 Lytton. R.L.; Germann, F.P.; Chou, YJ.; Stoffels, S.M. D e t e r m i n i n g a s p h a l t i c concrete pavement s t r u c t u r a l p r o p e r t i e s by nondestructive testing Texas Transportation Inst., College Station (United States), PB-90272048/GAR, 112 pp. (Jun. 1990) The high-volume data collection capabilities of modem nondestructive testing equipment require an analysis method which is capable of rapid backcalculation of pavement layer moduli in a production mode of data reduction. A layered elastic analysis method named MODULUS was developed for a microcomputer that is very fast operation and provides consistently reliable results. Random errors in the measurements and systematic errors in the measurements and systematic errors in the backcalculation process may be reduced, the former by repeating the measurements and the latter by use of a microcomputer expert system named PASELS. to provide consistently acceptable layer moduli values. Users' guides to both microcomputer programs are provided.
Billington, R. Application of expert systems for vibration based diagnosis
46099
Proceedings of the Vibration Analysis for Condition Monitoring Techniques and User Experience Seminar, Solihull (United Kingdom). 20 Feb. 1990, pp. 63-72. The British Institute of Non-Destructive Testing (1990) ISBN 0903132192 This paper deals with theapplication of an Expert system shell for vibration based diagnosis. It is well accepted that vibration may be used as an early indication of machine health, however, the techniques used are often hidden by myth and tainred by suspicion. This paper is concerned with the application of rare expertise to a complex problem in a cool, calculating environment, that of the personal computer. 46098 Nicholls, C. E x p e r t system to diagnose machinery vibration problems Proceedings of the Vibration Analysis for Condition Monitoring Techniques and User Experience Seminar, Solihull (United Kingdom), 20 Feb. 1990, pp. 86-95. The British Institute of Non-Destructive Testing (1990) ISBN 0903132192 Expert systems are fast becoming valuable tools in machine maintenance organisations worldwide. The DXPERT system has incorporated senior expert diagnostician and engineers' knowledge to resolve teal world vibration problems on six different kinds of machines. 46082 Lucia, A.C.; Brlinnhuber, R.; Elbaz, J.M.; Schwarz, U. A n a l y t i c a l methods and inspection procedures for lifetime prediction of
components subject to fatigue damage accumulation Reactor Safety Research. Edited by W. Krischer. pp. 693-718. Elsevier Applied Science (1990) The assessment of the reliability and of the residual life-time of a structure is achieved by means of a global procedure relying on a number of steps to be concatenated and merged:non-destructive testing and monitoring, material characterization, load analysis, stress analysis, fracture mechanics analysis, damage accumulation analysis, etc. hnpmvements are suggested for some of these steps. Attention is paid to data analysis, treatment of uncertainties, use of non algorithmic knowledge and expert system development.
Upda, L.," Upda. S.S. Application of neural networks for classification of eddy current NDT
45990
data Review of Progress in Quantitative Nondestructive Evaluation, Brunswick, Maine (United States), 23-28 Jul. 1989. Vol. 9A, pp. 673: 680. Edited by D.O. Thompson and D,E. Chimenti. Plenum Press (1990) This paper studies the application of neural network models for classifying defect signals from eddy current transducers used in nondestructive evaluation of materials. The following presents a brief introduction to neural net models and the learning algorithm. The preprocessing of the transducer signals for data compression is discussed. The results of performance of the network are presented and compared with results obtained by using the K-means clustering algorithm.
Mann, J.M.; Schmerr, L.W.; Moulder, J.C. Inversion of uniform field eddy c u r r e n t d a t a using neural networks
45989
Review of Progress in Quantitative Nondestructive Evaluation, Brunswick, Maine (United States), 23-28 Jal. 1989. Vol. 9A, pp. 681- 688. Edited by D.O. Thompson and D.E. Chimenti. Plenum Press (1990) Inversion of eddy current flaw signals has typically been based upon models of the field-flaw interaction. Although the feasibility of inverting eddy current data in this fashion has been demonstrated before, the complexity of s~ch procedures has hampered their widespread acceptance and use in industry. The goal of this study is to develop an inversion method that is easy to use and implement outside the research community. This paper pre~nts preliminary results on the use of neural networks for the inversion of eddy current flaw signals to obtain flaw sizes.
N D T & E International Volume 25 Number 1 1992