Electromagnetic shunt damping is a sensorless vibration control method that uses a single voice coil motor (VCM) and may also be used for energy harvesting. If an amplifier is used to control the current of a VCM, the current control law has the same function as a shunt circuit. In this paper, we focus on a current-controlled VCM and propose a new method that analyzes not only the performance of conventional shunt vibration control but also the energy consumption and the servo performance of current. From a numerical example, it was clarified that the energy was consumed without being regenerated if the PI gain with the maximum damping effect was used. There is a trade-off between the damping effect and energy regeneration.
Recently, the amount of data obtained from astronomical instruments has been increasing explosively, and data science methods such as Machine Learning/Deep Learning gain attention on the back of the growth in demand for automatic analysis. Using these methods, the number of applications to the target sources that have clear boundaries with the background i.e., stars, planets, and galaxies is increasing year by year. However, there are a few studies which applied the data science methods to the interstellar medium (ISM) distributed in the Galactic plane, which have complicated and ambiguous silhouettes. We aim to develop classifiers to automatically extract various structures of the ISM by Convolutional Neural Network (CNN) that is strong in image recognition even in deep learning. In this study, we focus on the infra-red (IR) ring structures distributed in the Galactic plane. Based on the catalog of Churchwell et al. (2006, 2007), we created a “Ring” dataset from the Spitzer/GLIMPSE 8 μm and Spitzer/MIPSGAL 24 μm data and optimized the parameters of the CNN model. We applied the developed model to a range of 16.5° ≤ l ≤ 19.5°, |b| ≤ 1° . As a result, 234 “Ring” candidates are detected. The “Ring” candidates were matched with 75% Milky Way Project (MWP, Simpson et al. 2012) “Ring” and 65% WISE Hii region catalog (Anderson et al. 2014). In addition, new“Ring”and Hii region candidate objects were also found. For these results, we conclude that the CNN model may have a recognition accuracy equal to or better than that of human eyes.
In this paper, a new sensor-less parameter estimation method is proposed for electromagnetic shunt damping. The purpose is to estimate parameters of an electromagnetic transducer and a vibrating structure. The frequency domain measurements of an electrical admittance are only supposed to be available but any other sensor measurements are not; therefore, the estimation problem is nontrivial. Two types of numerical optimization, a linear optimization to select an initial seed and a nonlinear optimization to determine a final estimate, are presented. The effectiveness of the method is demonstrated by vibration control experiments as well as parameter estimation experiments.
This paper studies the stability problem for a piezoelectric shunt damping system with a simple negative capacitor circuit. A key issue is to consider perturbations of parasitic series and parallel-leakage resistances in a piezoelectric element. Then, it is a bit surprising that the perturbed system becomes unstable, in particular, due to the effect of the parasitic leakage resistance. This instability phenomenon is analytically proved based on the Routh-Hurwitz stability criterion and is also demonstrated by numerical simulations. This paper then illustrates robustification of a negative capacitor circuit by inserting a negative resistance in parallel with the negative capacitor in the simple negative capacitor circuit. This robustification is also demonstrated by a numerical simulation.