Appl. Sci.2016, 6(7), 205; doi:10.3390/app6070205 - published 19 July 2016 Show/Hide Abstract
Abstract: We proposed heterodyne angle deviation interferometry (HADI) for angle deviation measurements. The phase shift of an angular sensor (which can be a metal film or a surface plasmon resonance (SPR) prism) is proportional to the deviation angle of the test beam. The method has been demonstrated in bubble and speaker’s vibration measurements in this paper. In the speaker’s vibration measurement, the voltage from the phase channel of a lock-in amplifier includes the vibration level and frequency. In bubble measurement, we can count the number of bubbles passing through the cross section of the laser beam and measure the bubble size from the phase pulse signal.
Appl. Sci.2016, 6(7), 204; doi:10.3390/app6070204 - published 14 July 2016 Show/Hide Abstract
Abstract: A systematic method to identify key factors that control the synthesis of Physical Vapor Deposition (PVD)-based graphene on copper is necessary for engineering graphene growth. The statistical design-of-experiments method is employed and demonstrated in this work in order to fulfill the necessity. Full-factorial design-of-experiments are performed to examine the significance of the main effects and the extent of the interactions of the controlling factors, which are responsible for the number of layers and the quality of the grown graphene. We found that a thinner amorphous carbon layer and a higher annealing temperature are suitable for the growth of mono-layer/few-layer graphene with low defects, while the effect of annealing time has a trade-off and needs to be optimized further. On the other hand, the same treatment, but with larger annealing times will result in multi-layer graphene and low defects. The results obtained from the analysis of the design-of-experiments are verified experimentally with Raman characterization.
Appl. Sci.2016, 6(7), 202; doi:10.3390/app6070202 - published 13 July 2016 Show/Hide Abstract
Abstract: This paper describes the fabrication of a series of micro ball-ended stylus tips by applying micro-EDM (Electrical Discharge Machining) and OPED (One Pulse Electrical Discharge) processes, followed by a manual assembly process of a static tri-switches tactile structure on a micro-CMM (Coordinate Measuring Machine). This paper further proves that the essential performance of the proposed system meets an acceptable benchmark among peer micro-CMM systems with a low cost. The system also adjusts for ambient temperature and humidity as the ordinary lab environmental conditions. For demonstration, several experiments used a randomly selected glass stylus with the diameters of stem and sphere of 0.07 mm and 0.12 mm, respectively. By leveraging research guidelines and common practice, this paper further investigates the probing relationship between measurement accuracy and its associated critical characteristics, namely triggering scenarios and geometric feature probing validation. The experimental results show that repeated detections in the uncertainty, in vertical and horizontal directions of the same point, achieved as small as 0.11 μm and 0.29 μm, respectively. This customized tri-switches tactile probing structure was also capable of measuring geometric features of micro-components, such as the inner profile and depth of a micro-hole. Finally, extensions of the proposed approach to pursue higher accuracy measurement are discussed.
Appl. Sci.2016, 6(7), 201; doi:10.3390/app6070201 - published 12 July 2016 Show/Hide Abstract
Abstract: With the development of intelligent machine tools, monitoring the vibration by the accelerometer is an important issue. Accelerometers used for measuring vibration signals during milling processes require the characteristics of high sensitivity, high resolution, and high bandwidth. A commonly used accelerometer is the lead zirconate titanate (PZT) type; however, integrating it into intelligent modules is excessively expensive and difficult. Therefore, the micro electro mechanical systems (MEMS) accelerometer is an alternative with the advantages of lower price and superior integration. In the present study, we integrated two MEMS accelerometer chips into a low-pass filter and housing to develop a low-cost dual-axis accelerometer with a bandwidth of 5 kHz and a full scale range of ±50 g for measuring machine tool vibration. In addition, a platform for measuring the linearity, cross-axis sensitivity and frequency response of the MEMS accelerometer by using the back-to-back calibration method was also developed. Finally, cutting experiments with steady and chatter cutting were performed to verify the results of comparing the MEMS accelerometer with the PZT accelerometer in the time and frequency domains. The results demonstrated that the dual-axis MEMS accelerometer is suitable for monitoring the vibration of machine tools at low cost.
Appl. Sci.2016, 6(7), 203; doi:10.3390/app6070203 - published 12 July 2016 Show/Hide Abstract
Abstract: Focusing on incremental bulk metal forming processes, the indentation process is gaining interest as a fundamental part of these kinds of processes. This paper presents the analysis of the pressure obtained in indentation under the influence of different punch geometries. To this end, an innovative Upper Bound Theorem (UBT) based solution is introduced. This new solution can be easily applied to estimate the necessary force that guarantees plastic deformation by an indentation process. In this work, we propose an accurate analytical approach to analyse indentation under different punches. The new Modular Upper Bound (MUB) method presents a simpler and faster application. Additionally, its complexity is not considerably increased by the addition of more Triangular Rigid Zones. In addition, a two-dimensional indentation model is designed and implemented using the Finite Element Method (FEM). The comparison of the two methods applied to the indentation process analysed—the new Modular Upper Bound technique and the Finite Element Method—reveal close similarities, the new Modular Upper Bound being more computationally efficient.
Appl. Sci.2016, 6(7), 200; doi:10.3390/app6070200 - published 11 July 2016 Show/Hide Abstract
Abstract: In this work, we developed a Selective Dynamic Sampling Approach (SDSA) to deal with the class imbalance problem. It is based on the idea of using only the most appropriate samples during the neural network training stage. The “average samples”are the best to train the neural network, they are neither hard, nor easy to learn, and they could improve the classifier performance. The experimental results show that the proposed method is a successful method to deal with the two-class imbalance problem. It is very competitive with respect to well-known over-sampling approaches and dynamic sampling approaches, even often outperforming the under-sampling and standard back-propagation methods. SDSA is a very simple method for automatically selecting the most appropriate samples (average samples) during the training of the back-propagation, and it is very efficient. In the training stage, SDSA uses significantly fewer samples than the popular over-sampling approaches and even than the standard back-propagation trained with the original dataset.