Skip to main content
Log in

Adaptive logging module for monitoring applications using control internal digital drive signals

  • Machine Tool
  • Published:
Production Engineering Aims and scope Submit manuscript

Abstract

Monitoring and collision avoidance systems are a standardized part in nowadays machine tools. The configuration and parameterisation of these systems require expert knowledge about the process and the machine tool. Using the monitoring system in different process types and with varying tools makes it necessary to adapt and change the parameterisation. Considering the acceleration and friction influences, these perturbations are independent from the process itself. This paper describes a solution method which identifies these perturbations, monitors the characteristics during the process and adapts the correction model if required. Then the possibilities for monitoring operation based only on digital drive signals will be explained.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Dimla DE (2000) Sensor signals for tool-wear monitoring in metal cutting operation: A review of methods. Int J Mach Tools Manuf (40):1073–1098

  2. Klocke F, Reuber M, Klocke F, Reuber M (2000) Sicheres Freiformfräsen mit on-line-Prozessüberwachung: on-line process monitoring in sculptured milling. wt Werkstattstechnik online 90(4):119–122

    Google Scholar 

  3. Dimla DE, Lister PM (2000) On-line metal cutting tool condition monitoring: I: force and vibration analyses. Int J Mach Tools Manuf 40:739–768

    Google Scholar 

  4. Lou K-N, Lin C-J (1996) An intelligent sensor fusion system for tool monitoring on a Machining Center. pp 208–214

  5. Konrad H, Isermann R, Heintz N (1995) Model based fault detection in milling by classification of estimated cutting parameters. In: IEEE international conference on systems, man and cybernetics. Intelligent systems for the 21st Century, vol 3, pp. 2193–2198

  6. Konrad H (1996) Fault detection in milling using parameter estimation and classification methods. Control Eng Pract 4(11):1573–1578

    Article  Google Scholar 

  7. Klocke F, Reuber M, Kratz H (2000) Application of a wavelet-based signal analysis for evaluating the tool state in cutting operations. In: 26th annual conference of the IEEE Industrial Electronics Society, 22–28 October 2000, Nagoya, Aichi, Japan, vol 3, pp. 1967–1972. doi:10.1109/IECON.2000.972577

  8. Shi D, Axinte D, Gindy N (2006) Online machining process monitoring using wavelet transformation and SPC. pp 2081–2086

  9. Franco-Gasca LA, Herrera-Ruiz G, Peniche-Vera R, Remero-Troncoso J, Leal-Tafolla W (2006) Sensorless tool failure monitoring system for drilling machines. Int J Mach Tools Manuf 46:381–386

    Google Scholar 

  10. Kaever M, Weck M (1997) Intelligent process monitoring for rough milling operations based on drive currents and machine integrated sensors. In: Wiens HG (ed) Manufacturing science and engineering, vol 1. Dallas, pp. 97–104

  11. Kaever M, Brouer N, Rehse M, Weck M (1997) NC integrated process monitoring and control for intelligent autonomouse manufacturing systems. pp 69–74

  12. Kaever M (2005) Steuerungsintegrierte Fertigungsprozeßüberwachung bei spanender Bearbeitung, Diss. Norderstedt: Books on Demand

  13. Weck M, Plapper V (2001) Sensorless machine tool condition monitoring based on Open NCs. In: IEEE Power Engineering Society, international conference on robotics and automation, 21–26 May 2001, Coex Seoul, Korea

  14. Plapper V (2003) Steuerungsintegrierte Zustands-überwachung von Vorschubantrieben an Werkzeugmaschinen”, Diss., RWTH

  15. Adam W, Pritschow G, Uhlmann E, Weck M, Adam W (eds) Zukunftsweisende Anwendungen integrierter Sensorsysteme. Düsseldorf: VDI-Verl., 1999///2000

  16. Xiaoli L (2005) Development of current sensor for cutting force measurement in turning. IEEE Trans Instrum Meas 54(1)

  17. Payandeh S, Adams J (1996) On methods for low velocity friction Compensation: theory and experimental study, in Journal of Robotic Systems, pp 391–404

  18. Olsson H, Astrom KJ, Cabudas de Wit C, Gäfert M, Lischinsky P (2007) Friction models and friction compensation. Available at http://www.lag.ensieg.inpg.fr/canudas/publications/friction/dynamic_friction_EJC_98.pdf

  19. Konrad H (1997) Modellbasierte Methoden zur sensorarmen Fehlerdiagnose beim Fräsen, Diss. Düsseldorf: VDI-Verl

  20. Hänsler E (1997) Statistische Signale: Grundlagen und Anwendungen, 2nd edn. Springer, Berlin

  21. Maragos P, Kaiser JF, Quatieri TF, Maragos P, Kaiser JF, Quatieri TF (1993) Energy separation in signal modulations with application to speech analysis. IEEE Trans Signal Process 41(10): 3024–3051

    Google Scholar 

  22. Kaiser JF (1990) On a simple algorithm to calculate the “energy” of a signal. IEEE, New Jersey

  23. Li X, Du R, Denkena B, Imiela J, Li X, Du R, Denkena B, Imiela J (2005) Tool breakage monitoring using motor current signals for machine tools with linear motors”. IEEE Trans Ind Electron 52(5):1403–1408. Available at doi:10.1109/TIE.2005.855656

    Google Scholar 

Download references

Acknowledgments

The research project IP 011815 NEXT Generation Production Systems is funded under the 6th Framework Program. The Laboratory for Machine Tools and Production Engineering gratefully acknowledges this support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Rudolf.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brecher, C., Rudolf, T. Adaptive logging module for monitoring applications using control internal digital drive signals. Prod. Eng. Res. Devel. 3, 305–312 (2009). https://doi.org/10.1007/s11740-009-0160-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11740-009-0160-6

Keywords

Navigation