This paper presents the optimum load-speed diagram evaluation for a linear micromotor, including multitude cantilever piezoelectric bimorphs, briefly. Each microbeam in the mechanism can be actuated in both axial and flexural modes simultaneously. For this design, we consider quasi-static and linear conditions, and a relatively new numerical method called the smoothed finite element method (S-FEM) is introduced here. For this purpose, after finding an optimum volume fraction for piezoelectric layers through a standard numerical method such as quadratic finite element method, the relevant load-speed curves of the optimized micromotor are examined and compared by deterministic topology optimization (DTO) design. In this regard, to avoid the overly stiff behavior in FEM modeling, a numerical method known as the cell-based smoothed finite element method (CS-FEM, as a branch of S-FEM) is applied for our DTO problem. The topology optimization procedure to find the optimal design is implemented using a solid isotropic material with a penalization (SIMP) approximation and a method of moving asymptotes (MMA) optimizer. Because of the higher efficiency and accuracy of S-FEMs with respect to standard FEMs, the main micromotor characteristics of our final DTO design using a softer CS-FEM are substantially improved.

Structural health monitoring (SHM) is an application area of Wireless Sensor Networks (WSNs) which usually needs high data communication rate to transfer a large amount of monitoring data. Traditional sink node can only process data from one communication channel at the same time because of the single radio chip structure. The sink node constitutes a bottleneck for constructing a high data rate SHM application giving rise to a long data transfer time. Multi-channel communication has been proved to be an efficient method to improve the data throughput by enabling parallel transmissions among different frequency channels. This paper proposes an 8-radio integrated sink node design method based on Field Programmable Gate Array (FPGA) and the time synchronization mechanism for the multi-channel network based on the proposed sink node. Three experiments have been performed to evaluate the data transfer ability of the developed multi-radio sink node and the performance of the time synchronization mechanism. A high data throughput of 1020Kbps of the developed sink node has been proved by experiments using IEEE.805.15.4.

An innovative cage for spinal fusion surgery is presented within this work. The cage utilizes shape memory alloy for its hinge actuation. Because of the use of SMA, a smaller incision is needed which makes the cage deployment minimally invasive. In the development of the cage, a model for predicting the torsional behavior of SMAs was developed and verified experimentally. The prototype design of the cage was developed and manufactured. The prototype was subjected to static tests per ASTM specifications. The cage survived all of the tests, alluding to its safety within the body.

This paper presents a nonlinear time series analysis technique for evaluating machine defect severity, based on the Recurrence Plot (RP) entropy. The RP entropy is calculated from the probability distribution of the diagonal line length in the recurrence plot, which graphically depicts a system's dynamics and provides a global picture of the autocorrelation in a time series over all available time-scales. Results of experimental studies conducted on a spindle-bearing test bed have demonstrated that, as the working condition of the bearing deteriorates due to the initiation and/or progression of structural damages, the frequency information contained in the vibration signal becomes increasingly complex, leading to the increase of the RP entropy. As a result, RP entropy can serve as an effective indicator for defect severity assessment of rolling bearings.

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.