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2002 №05 (06) 2002 №05 (08)


The Paton Welding Journal, 2002, #5, 25-27 pages

System of in-process quality control of welding equipment during its manufacturing

B.E. Paton1, A.E. Korotynsky1, M.I. Skopyuk1, V.I. Yumatova1, E.A. Kopilenko2, G.V. Pavlenko2, G.L. Pavlenko2, N.V. Chmykhov2

1E.O. Paton Electric Welding Institute of the NASU 11 Kazymyr Malevych Str., 03150, Kyiv, Ukraine.
2Company «SELMA», Simferopol, Ukraine

Abstract
In view of the increasing number and diversity of the types of welding equipment and higher requirements to its quality, practical implementation of the requirements of GOST 25616-83 in production testing involves a considerable material consumption and time. A variant of forecasting the technological properties of welding equipment is proposed, which is based on the results of electric testing, using a variable resistive load. Various variants of applying the hardware, program and algorithmic elements of the systems of in-process control of welding equipment parameters are considered
Keywords: welding, welding equipment, system testing, fuzzy logic, simulation mode, linguistic variables

References

1. GOST 25616-83. Arc welding power sources. Procedure of welding properties testing. Introd. 28.01.83.
2. Pentegov, I.V., Sidorets, V.N., Genis, I.A. (1984) Welding arc modelling as an element of electric circuit and construc¬tion of equivalent circuits. Avtomatich. Svarka, 12, 26−30.
3. Sidorets, V.N., Pentegov, I.V. (1991) Simulator of welding arc to evaluate current sources applied in arc welding. Ibid., 7, 15−18.
4. Melton, G. (2001) Validation of arc welding equipment − revision of BS 7570. Welding&Metal Fabric., 5, 10−12.
5. Bogatyrev, L.L. (1995) Methods of diagnostics of technical systems under the conditions of fuzzy initial information. Izv. Vuzov, Elektromekhanika, 2, 130−131.
6. Gladkov, E.A. (1996) Problems of prediction of quality and control of weld formation during welding with application of neural network models. Svarochn. Proizvodstvo, 10, 36−41.
7. Orlovsky, S.A. (1981) Problem-solving with fuzzy initial information. Moscow: Nauka.

Suggested Citation

B.E. Paton, A.E. Korotynsky, M.I. Skopyuk, V.I. Yumatova, E.A. Kopilenko, G.V. Pavlenko, G.L. Pavlenko, N.V. Chmykhov (2002) System of in-process quality control of welding equipment during its manufacturing. The Paton Welding J., 05, 25-27.