FPGA Implementation of a Tool Breakage Detection Algorithm in CNC Milling Machines

  • René de Jesús Romero-Troncoso
  • Gilberto Herrera Ruiz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3203)


In this paper, an on-line tool breakage detection algorithm in CNC milling machines is implemented into a single 32,000-gate FPGA from Actel. The tool breakage detection algorithm is based on three pipelined processing units: a two-channel modulo operator, a one dimension wavelet transform and an asymmetry correlator. The two-channel modulo operator performs two twelve-bit square operations and a 25-bit square root. The one dimension wavelet transform performs a 256x8 point matrix per a 256 point vector multiplication over the incoming data from the modulo operator. The third processor performs an asymmetry correlation over the wavelet data to give a single value which contains the estimation of the tool condition. The overall processing unit cost is kept low by using optimized numeric digital structures, suited to fit into a 32,000-gate FPGA while allowing the system to give on-line tool condition estimation. Results are presented in order to show overall system performance.


Discrete Wavelet Transform Finite Impulse Response FPGA Implementation Tool Breakage Dimension Wavelet 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Prickett, P.W., Johns, C.: An overview of approaches to end milling tool monitoring. International Journal of Machine Tools & Manufacture 39, 105–122 (1999)CrossRefGoogle Scholar
  2. 2.
    Kasashima, K., Mori, K., Herrera-Ruiz, G.: Diagnosing cutting tool conditions in milling using wavelet transform. In: 7th International Conference on Production/Precision Engineering, JSPE, Chiba, Japan, September 15-17, pp. 339–344 (1994)Google Scholar
  3. 3.
    Bejhem, M., Nicolescu, C.M.: Machining condition monitoring for automation. In: 3rd International Conference on Machining & Grinding, Society of Manufacturing Engineers, Cincinnati, Ohio, October 4-7, MR99-231 (1999)Google Scholar
  4. 4.
    Trang, Y.S., Lee, B.Y.: Use of model-based cutting simulation system for tool breakage monitoring in milling. International Journal of Machine Tools and Manufacture 32, 641–649 (1992)CrossRefGoogle Scholar
  5. 5.
    Daubechies, I.: Orthonormal bases of compactly supported wavelets. Communications on Pure and Applied Mathematics 41, 909–996 (1988)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Vetterli, M., Herley, C.: Wavelets and filter banks: theory and design. IEEE Transactions on Signal Processing 40, 2207–2232 (1992)zbMATHCrossRefGoogle Scholar
  7. 7.
    Parhami, B.: Computer arithmetic, Algorithms and hardware design. Oxford University Press, Oxford (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • René de Jesús Romero-Troncoso
    • 1
  • Gilberto Herrera Ruiz
    • 2
  1. 1.FIMEE – U. de GtoSalamancaMéxico
  2. 2.Facultad de Ingeniería, Cerro de las campanas s/nUniversidad Autónoma de QuerétaroQuerétaroMéxico

Personalised recommendations