An approach based on current and sound signals for in-process tool wear monitoring

Advanced monitoring of machining operations

“…This time, they found that only the RMS and standard deviation of the medium and high frequency signals of the longitudinal vibration and the RMS and standard deviation of the high-frequency components of the transverse vibration showed a monotonic behavior with tool wear. Salgado and Alonso [102] also used SSA to extract information correlated with tool wear from audible sound signals.…”

A Case Study of Assessing Button Bits Failure through Wavelet Transform Using Rock Drilling Induced Noise Signals

“…noise generated by the neighbouring surrounding can influence the frequency region of 0 to 2 kHz of the signal [9] and it is difficult to detect the frequencies below 100 Hz with the use of microphones [4]. Signal analysis techniques are used to convert the hectic original signal to a simple and effective signal by extracting and enhancing the relevant data.…”

Computer Vision-Based Approach to End Mill Tool Monitoring

“…In those works the researchers measure the cutting forces during machining and on their basis, with various deterministic approaches and with the use of intelligent methods; they classify the tool condition according to the features gained from measured cutting forces. The researches are also concerned about the indirect approach to tool monitoring on the basis of the noise captured by the use of microphone, while the signal is properly processed and classified [8][9][10]. In case of direct methods, the tool monitoring is effected by means of optical systems and by the use of computer vision.…”