Tool wear monitoring with wavelet packet transform—fuzzy clustering method
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Surface roughness assessment on hole drilled through the identification and clustering of relevant external and internal signal statistical features
2022, CIRP Journal of Manufacturing Science and TechnologyA non-destructive fault diagnosis method for a diaphragm compressor in the hydrogen refueling station
2019, International Journal of Hydrogen EnergyStudy of spindle power data with neural network for predicting real-time tool wear/breakage during inconel drilling
2017, Journal of Manufacturing SystemsCitation Excerpt :An accelerometer is an option to detect tool vibration and breakage, but it: i) works in a specific range of machining speed, ii) is sensitive to mounting position, and iii) is sensitive to environment (coolant, chip strike). Acoustic emission (AE) sensors, which work based on microstructure change of materials due to noises occur at the tool-workpiece interface during the material removal process, are recently employed in TCM [17,18]. Although they are cost effective and easy to install, but are not recommended for a production environment since calibration is very important to avoid overload and non-voluntary noises.
Control of deviations and prediction of surface roughness from micro machining of THz waveguides using acoustic emission signals
2017, Mechanical Systems and Signal ProcessingCitation Excerpt :FFTs have been used for TCM in the past, however they do not define the time when the event occurred. This is fundamental to the nature of spontaneously-released transient elastic energy accompanying deformation or fracture of materials, or a combination of both [4], instead FFT has to be used alongside another technique that produces both the time and frequency band information. Short Time Fourier Transforms (STFT) are a similar function to FFT, albeit the FFT is calculated for equally-spaced time slots designated across the raw extracted time signal.
Tool life predictions in milling using spindle power with the neural network technique
2016, Journal of Manufacturing ProcessesCitation Excerpt :The advantage of AE sensor is that the range of frequency is much higher than the environmental frequencies, making it a less-intrusive sensor. AE sensors have been successfully used for tool wear monitoring [22] and for tool breakage detection [23]. But despite their low cost and the facilities for the installation, this device is not recommended for a production environment since AE calibration is very important to avoid overload and non-voluntary noises.