F. Lee-Orantes’s research while affiliated with Universidad Politécnica de Chiapas and other places

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Publications (1)


Digital filter passbands and stopbands for predefined IPF ranges IPF range (Hz) Passband frequencies (Hz) Stopband frequencies (Hz)
Set of calculated filter coefficients for an IPF between 300 and 325 Hz
Experimental test arrangement
Tool failure detection method for high-speed milling using vibration signal and reconfigurable bandpass digital filtering
  • Article
  • Full-text available

May 2015

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83 Reads

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41 Citations

The International Journal of Advanced Manufacturing Technology

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F. Lee-Orantes

This paper presents a monitoring method for on-line detection and indication of the occurrence of a cutting tool failure during high-speed face milling. The method consists of processing of the vibration signal using a reconfigurable infinite impulse response (IIR) bandpass digital filter and statistical techniques. The healthy tool threshold and the filter passband are adjusted and configured based on the cutting parameters that were set up during the machining process. For this process, sets of filter coefficients are pre-calculated for a number of defined insert passing frequencies ranges. The method is verified on-line during machining tests that are carried out at different tool failure levels and using various cutting parameters. In all experimental tests, the method allows the tool condition to be detected and indicated correctly. The proposed method is therefore shown to be simple, fast, computationally efficient, and reliable for the detection and indication of the presence of several types of tool failures for various cutting parameters, and the use of this method does not require any modification of the machine tool structure.

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Citations (1)


... Compared with the direct method of post-process inspection, the indirect method can effectively monitor tool wear without halting machining, helping to improve machining efficiency. Sevilla et al [11] used reconfigurable digital bandpass filtering to the vibration signal to extract the characteristic features of tool faults and compared them with the features of a healthy tool signal for tool fault detection. Maia et al [12] proposed a new spectral analysis method for associating acoustic emission signals with the tool wear state to detect wear mechanisms and monitor tool wear progression. ...

Reference:

Turning tool wear state recognition based on EMDResNeStTime and sequence-global-encoding
Tool failure detection method for high-speed milling using vibration signal and reconfigurable bandpass digital filtering

The International Journal of Advanced Manufacturing Technology