E. Rubio*¹, J.C. Jáuregui–Correa²

^1,2 CIATEQ A.C., Centro de Tecnología Avanzada, Cto. Aguascalientes Nte. 135, Parque Ind. del Valle de Aguascalientes, Aguascalientes, Ags., C.P. 20358, MÉXICO * eduardo.rubio@ciateq.mx

ABSTRACT

The manufacturing process of metal parts is subjected to machining instabilities that can degrade the surface finish quality and the reliability of products. Some instabilities are of transient nature and traditional inspection systems are unable to adequately estimate the grade of affectation in the finished parts. Time–frequency analyses are techniques that overcome these limitations and have recently been incorporated in special industry inspection equipment to improve the quality of the manufactured parts. Grinding is a process used to get high precision and very smooth surface in flat or cylindrical parts because of the target applications such as the automotive industry where the highest standards can be found. This paper reports a technique to estimate the quality of ground parts based on time–frequency transforms that are used to enhance the defects. This makes it easier to implement the technique for surface characterization in online pass/no–pass inspection machines. The fundamentals of the methodology are revised and the technique is applied to the identification of vibration marks in cylindrical ground rods. Results show that this approach identifies adequately imperfections of transient nature and it is able to estimate the extension and amplitude of the defects on the surface of the manufactured parts.

Keywords: grinding, time–frequency, wavelets, surface quality.

Los procesos de manufactura de partes metálicas se encuentran sujetos a inestabilidades en la maquinaria que pueden degradar la calidad superficial de los productos y su confiabilidad. Algunas inestabilidades son de naturaleza transitoria por lo que los sistemas de inspección tradicionales no son capaces de estimar adecuadamente el grado de afectación del acabado superficial. Los análisis de información en el dominio tiempo–frecuencia son técnicas que superan estas limitaciones y se han incorporado gradualmente en equipos especiales en la industria para mejorar la calidad de las partes manufacturadas. El rectificado es un proceso utilizado para obtener una superficie de gran precisión y calidad en piezas planas o cilíndricas, en aplicaciones tales como la automotriz, en donde se tienen las más altas exigencias de calidad. En este trabajo se reporta una técnica para estimar la calidad del acabado en piezas rectificadas, basada en una transformada tiempo–frecuencia, la cual es utilizada para destacar los defectos producidos durante el maquinado. Esto facilita la implementación de técnicas para caracterización superficial en sistemas de inspección en línea pasa/no–pasa. Se revisan los fundamentos de la metodología y se aplica el método en la identificación de defectos en piezas cilíndricas rectificadas. Los resultados muestran que la técnica es capaz de identificar defectos de naturaleza transitoria así como la extensión y amplitud de los defectos sobre la pieza inspeccionada.

DESCARGAR ARTÍCULO EN FORMATO PDF

References

[1] Inasaki, I., Sensor fusion for monitoring and controlling grinding processes, International Journal of Advanced Manufacturing Technology, Vol. 15, 1999, pp. 730–736.         [ Links ]

[2] Raja J., Muralikrishnan B., Shengyu F., Recent advances in separation of roughness, waviness and form, Precision Engineering, Vol. 26, 2002, pp. 222–235.         [ Links ]

[3] Wong P.L., Li K.Y., In–process roughness measurement on moving surfaces, Optics and Laser Technology, Vol. 31, 1999, pp. 543–548.         [ Links ]

[4] Carnero M.C., González–Palma R., Almorza D., Mayorga P., López–Escobar C., Statistical quality control through overall vibration analysis, Mechanical Systems and Signal Processing, Vol. 24, 2010, pp. 1138–1160.         [ Links ]

[5] Luo G.Y., Osypiw D., Irle M., Surface quality monitoring for process control by on–line vibration analysis using an adaptive spline wavelet algorithm, Journal of Sound and Vibration, Vol. 263, 2003, pp. 85–111.         [ Links ]

[6] Grzesik W., Brol S., Wavelet and fractal approach to surface roughness characterization after finish turning of different workpiece materials, Journal of Materials Processing Technology, Vol. 209, 2009 pp. 2522–2531.         [ Links ]

[7] Wu Y., Du R., Feature extraction and assessment using wavelet packets for monitoring of machining processes, Mechanical Systems and Signal Processing, Vol. 10, no. 1, 1996, pp. 29–53.         [ Links ]

[8] Haosheng L., Su W., Kratz H., FFT and wavelet–based analysis of the influence of machine vibrations on hard turned surface topographies, Tsinghua Science and Technology, Vol. 12, no. 4, 2007, pp. 441–446.         [ Links ]

[9] Wang A.L., Yang C.X., Yuan X.G., Evaluation of the wavelet transform method for machined surface topography I: methodology validation, Tribology International, Vol. 36, 2003, pp. 517–526.         [ Links ]

[10] Yao Z., Mei D., Chen Z., On–line chatter detection and identification based on wavelet and support vector machine, Journal of Material Processing Technology, Vol. 210, 2010, pp. 713–719.         [ Links ]

[11] Wang H.X., Zong W.J., SunT., Liu Q., Modification of three dimensional topography of the machined KDP crystal surface using wavelet analysis method, Applied Surface Science, Vol. 256, 2010, pp. 5061–5068.         [ Links ]