Topological design of electromechanical actuators with robustness toward over- and under-etching
Abstract In this paper, we combine the recent findings in robust topology optimization formulations and Helmholtz partial differential equation based density filtering to improve the topological design of electromechanical actuators. For the electromechanical analysis, we adopt a monolithic formulation to model the coupled electrostatic and mechanical equations. For filtering, we extend the Helmholtz-based projection filter with Dirichlet boundary conditions to ensure appropriate design boundary conditions. For the optimization, we use the method of moving asymptotes, where the sensitivity is obtained from the adjoint approach. Our study shows that the robust filter approach produces topology optimized actuators with minimal length control and crisp structural boundaries. In particular, the minimal length control of both structural features and gap widths avoids common modeling artifacts in topology optimization, i.e. one-element wide structural parts or gaps. It thus leads to physically realizable designs that are robust against manufacturing imprecision such as over- and under-etching.
Frequency Tuning of Work Modes in Z-Axis Dual-Mass Silicon Microgyroscope
Frequency tuning of work modes in the silicon vibratory gyroscope is studied by the theoretical, numerical, and experimental methods in this paper. First, the schematic structure and simplified kinematics model of the gyroscope were presented for deducing the natural frequencies. Then, the width and length of support beams were optimized to tune work frequencies at their designed value. Besides, the frequency difference was experimentally tested and manually tuned by varying the voltage applied on the tuning capacitors. The test on a prototype showed that the difference could be localized between −55.8 Hz and 160.2 Hz when the tuning voltage limit is 20 V. Finally, a frequency control loop was developed to automatically tune the sense frequency toward the drive frequency. Both the theoretical analysis and numeric simulation show that the difference is stabilized at 0.8 Hz when no Coriolis force or quadrature coupling force is applied. It is proved that the frequency difference is successfully tuned by modifying the size of support beams before fabrication as well as the voltage applied on the tuning capacitors after fabrication. The automatic tuning loop, used to match the work modes, is beneficial to enhance the performance of the gyroscope as well as its resistance to environment disturbances.
ImageCLEF 2017: ImageCLEF Tuberculosis Task - the SGEast Submission
In this paper, we describe our methodologies in an attempt to improve the diagnosis accuracy of drug resistant tuberculosis and also of identifying the type of tuberculosis present in the patient, as per the requirements of the ImageCLEF tuberculosis task of ImageCLEF 2017. Firstly, we employed the concept of Convolutional Neural Networks (CNN), which can be used to identify useful features in the Computerized Tomography (CT) scans that were provided in the competition and perform the classification based on them. Secondly, Recurrent Neural Networks (RNN) were used on top of CNNs by utilizing CNNs as a feature extractor and the RNNs as a classifier. In order for our model to produce acceptable results, proper preprocessing was performed prior to providing the input data to the models for training, such as image slicing and data augmentation. Our methods were able to reach rank 4 and 5 for the subtask involving drug-resistant tuberculosis and rank 1 and 2 for the other subtask of identifying the tuberculosis type, according to the evaluation performed by ImageCLEF.