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An experimental study to understand the characteristics related to chatter occurrence in micro milling operations is presented. Accelerometers are used to measure the vibration signals in the machining process. The acceleration signals are then analysed in the time domain and the frequency domain. Along with the onset of chatter, it is found that there is a characteristic shift of the dominant frequency components in addition to the change of vibration amplitude. A modulation of the spindle frequency around the chatter frequency is also found to be present in the vibration signal. A dimensionless chatter indicator based on revolution RMS values is designed and used to evaluate the stability of the micro-milling process. It is shown that the proposed indicator provides a simple, but effective way to detect chatter onset.

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To provide faster, more repeatable, and stronger microelectronics bonding technology, this article presents the design and implementation of a robust and precision controller for a highspeed linear voice-coil motor, direct-drive, XY positioning table. Moreover, the dynamic design methodology of the control system for the positioning table is proposed based on electromechanical co-simulation. Using the finite-element method and dynamic analysis, the rigid-flexible coupled mechanical model of the XY table is established. With the aid of the system identification approach, the open-loop model of the control system for the X -axis table is obtained. On this basis, the proportion integration differentiation controller with incomplete derivation and the sliding mode controller (SMC) with the exponential reaching law are designed to control the X -axis table. The performances of the controllers are investigated using electromechanical cosimulations and experimental tests, and the results show that the motion overshoot and settling time are reduced using the SMC with an exponential reaching law. The SMC with the exponential reaching law also shows strong robustness against external disturbances. The experiment and co-simulation results are in good agreement, which confirms the validity and feasibility of the dynamic design methodology for a high-speed and high-accuracy positioning table based on electromechanical co-simulation.

Extensive studies have been carried out to investigate the stability of superhydrophobic surfaces under acid, alkali, and salt solutions. It is noted that previous literature studies just demonstrated a variety of experimental phenomena. However, very few works have focused on the protection mechanism or failure mechanism of fluorinated superhydrophobic surfaces from the perspective of chemical aspects. Herein, this paper aims to investigate the effects of acid, alkali, and salt solutions on the stability of fluorinated superhydrophobic surfaces, and the anticorrosion/corrosion mechanism will be further proposed. The superhydrophobic coating was obtained on silicon substrates by laser surface texturing followed by fluoroalkyl silane modification. The resultant surfaces presented a water contact angle (WCA) of 157.6 ± 0.4° with a small water sliding angle (WSA) of 1.3 ± 0.3°. The newly fabricated superhydrophobic surfaces were then immersed in different concentrations of corrosive solutions (acid, alkali, and salt solutions). The revolution of surface wettability and surface morphology on treated silicon surfaces was evaluated through WCAs, scanning electron microscopy, and white light confocal microscopy. The results indicate that the hydrogen ions (H+) played a positive role in the retention of superhydrophobicity. However, the hydroxyl (OH–) and chloride ions (Cl–) presented the negative influence. The protection mechanism or corrosion mechanism under different solutions was proposed based on the X-ray photoelectron spectroscopy results. In addition, the potentiodynamic polarization and electrochemical impedance spectroscopy measurements provided strong support in data and were conducted to verify the rationality of the proposed mechanism.

Chatter is a self-excited vibration that affects the part quality and tool life in the machining process. This paper introduces an intelligent chatter detection method based on image features and the support vector machine. In order to reduce the background noise and highlight chatter characteristics, the average FFT is applied to identify the dominant frequency bands that divide the time-frequency image of the short-time Fourier transform into several sub-images. The non-stationary properties of the machining conditions are quantified using sub-images features. The area under the receiver operating characteristics curve ranks the extracted image features according to their separability capabilities. The support vector machine is designed to automatically classify the machining conditions and select the best feature subset based on the ranked features. The proposed method is verified by using dry micro-milling tests of steel 1040 and high classification accuracies for both the stable and unstable tests are obtained. In addition, the proposed method is compared with two additional methods using either image features from the continuous wavelet transform or time-domain features. The results present a better classification performance than the two additional methods, indicating the efficiency of the proposed method for chatter detection.

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