Chamaporn Chianrabutra

Evaluating the Influence of Current on the Wear Processes of Au/Cr-Au/MWCNT Switching Surfaces

Wear processes of the switching contact pair consisting of a gold layer on multiwall carbon nanotubes (Au/MWCNT) and a chromium and gold coated hemispherical ball (Au/Cr) are evaluated over a range of current conditions. The switching experiments were conducted using typical conditions for a MEMS relay application, i.e. 4 V, with static contact force 1 mN with currents level of 20-200mA. The Au coated MWCNT substrate exhibited a transfer process over a large number of switching cycles. On the assumption that the transfer process was a combination of a fine transfer and delamination processes; a previous experimental investigation was considered by dividing the wear processes into four stages of a failure behavior. It is observed that the fine transfer process dominates in the unstable and stable contact resistance stage and then the delamination dominates in the rising stage and a failure process. The increase of contact resistance was used to identify contact failure.

Gold Coated Carbon-Nanotube Surfaces as Low Force Electrical Contacts for MEMS Devices: Part II, Fine Transfer Mechanisms

Material transfer in switching contacts is considered at very low currents, (below 20mA). The transfer process is critical to a wide range of electronic switching technologies and is a limiting factor for MEMs relays. A test system is described and characterized for bench-marking surfaces. This is followed by a study of Multi-walled CNTs (MWCNTs), synthesized on a silicon planar and sputter coated with a gold film. The planar surfaces are mounted on the tip of a piezo-electric actuator and mated with a Au coated hemispherical surface. The switching contacts are tested under conditions typical of MEMS relay applications; 4V, 1mA; with a static contact force of 1mN, results are presented on the bounce process and on the opening characteristic with respect to the melting and boiling voltages for the materials tested.

The Effect on Switching Lifetime of Chromium Adhesion Layers in Gold-Coated Electrical Contacts under Cold and Hot Switching Conditions

Gold is commonly used for electrical contacts due to its many desirable electrical and mechanical properties. Throughout the switch lifetime, the contacts are required to survive a large number of opening and closing cycles and therefore it is important to understand the failure mechanisms. Adhesion layers (e.g. chromium or titanium) can be deposited to increase the adhesion of the gold layer to the contact surface. In this work, the inclusion of a chromium adhesion layer shows an improvement of the switching lifetime of gold-coated electrical contacts under cold and hot switching conditions. These testing conditions further the understanding of the failure mechanisms (e.g. fine transfer, etc.). The mechanism of failure when no chromium adhesion layer was used is attributed to delamination of the gold layer from one contact to the other. This failure mechanism is different in the cases where a chromium adhesion layer is included. We present a model which was developed in line with experimental results. These describe the effect of load current on material transfer between gold contacts and the contact failure.

Development of a MEMS test platform for investigating the use of multi-walled CNT composites electric contacts

The use of gold-coated multi-walled carbon nanotube (Au/MWCNT) composites have been shown to extend the life of electrical contacts, in previous work. Due to the long lifetimes (which are of the order of 106 up to 108 cycles) the lifetime testing tends to be highly time consuming. In this work we discuss the design and development of an electrostatically actuated MEMS cantilever beam which enables testing at higher frequencies than our previous experimental rig. Following calculations using fundamental cantilever beam equations, a computational model of the designed beam was developed to accurately predict the characteristics of the beam, including the resonant frequency, pull-in voltage and contact force. Where possible the values from the model have been compared with the fabricated MEMS cantilever beam. A MEMS-based electrostatically actuated cantilever beam has been fabricated and incorporated with Au/MWCNT composite surfaces to form a MEMS switch test platform. Initial results show the improved performance over a PZT based test platform.

Baby Shrimp Counting via Automated Image Processing

The aim of this research is to investigate the method of detecting and counting baby shrimps by image processing technique. The experimental devices consist of a 1920x1080 pixels color image processing system and a light box. This light box is used as an indirect lighting source to avoid the bright spot from the target if the direct light technique is used. The shrimps are taken by a video camcorder, then the real time video is executed from the moving video to images and recorded them as the image files. The images are considered and converted to binary data types. Blob detection algorithm is used to detect the difference properties of color within the regions in the digital image. After that, the results from the image processing methodology are compared with the real value. It found that the shrimp quantity getting from the image processing technique is comparable and corresponding to the real shrimp quantity counting by manual with error is less than 7% of real quantity.

Human fall detection by using the body vector

Due to a problem of current research occurring when detecting a human falling in a camera direction, we propose a new method for detecting human fall detection by using body vector technique. This method consists of three steps. Two image sequence is used as the input of the system. Firstly markers are affixed on sixteen joints. These markers are extracted by using mahalanobis distance. Secondly, the stereo vision technique is used to construct human joints in three dimensional space. Finally, joint coordinates are used to compute principal component vector. Human falling is detected from an angle between the human body vector and the vertical axis and the human center velocity. To test the performance of the proposed method, subject walks to the cameras. Falling down in the camera direction by twenty subjects is used. Accuracy is 100%. This method perform effectively for detecting human falling in the camera direction.

Applying 2 k Factorial Design to Study on Parameters Affecting Springback of Forming of Advanced High Strength Steel Sheets (AHSS)

Advanced high strength steels (AHSS) are widely used in the automotive industry due to their appropriate strength to weight ratio. This alloy has unique hardening behavior and variable unloading elastic modulus; however, the unavoidable obstacle of AHSS sheet metal forming is springback. The springback is a result of elastic recovery and residual stress. The aim of this study is to determine the proper process parameters enabling the reduction of the springback defects in AHSS forming process. This work was divided into two parts, regarding to the effects of numerical parameters and process parameter on forming AHSS. In this paper, a U-shape forming was used to examine the springback behaviors, such as springback angle, sidewall curl, and thickness, through an experiment. To achieve this purpose, 2k factorial statistical experimental design has been employed to investigate the parameters affecting the springback of forming in AHSS to find out the main effect in the springback reduction focusing on using as a guideline for die design. It showed that the blank holder force is the most influential parameter. The second is the punch radius. However, the blank holder force and punch radius is not simple to adjust in die design, the die radius becomes the important parameter to be used to reduce the springback angle.

Development of facial expression recognition by significant sub-region

A problem of previous research concerning facial expression recognition using the face plane is that redundant elements are also used for recognition. In this paper, we propose to develop facial expression recognition method to maximize the accuracy by using significant sub-regions on the face plane. This method consists of five steps: image acquisition, the face plane computation, the significant sub-region identification, the displacement vector computation, and classification. In order to recognize facial expression, the face plane is applied. Area on face plane is divided into 196 (14×14) sub-regions. The cross points pass though the face plane in each sub-region is counted and used as an information for computing significant level of each sub-region. By using Principal Component Analysis (PCA), significant sub-regions on the face plane are determined. The displacement vectors are used for facial expression recognition. The support vector machine is applied for classification. To test the performance of the proposed method, the experiments were done for four expressions (happiness, angry, surprise, and sadness) by using the BU3DFE database, the maximum recognition rate is 71.20 % for using 133 significant sub-regions. The results show that the redundant elements are eliminated and the accuracy is improved.