Faba, AntonioRimal, Hari PrasadLaudani, AntoninoChilosi, Francesco...
8页
查看更多>>摘要：The knowledge of the magnetic characteristic of an inductor is a key factor for the design of filters of power converter systems for electric grid interfaces. The accurate and reliable definition and measurement of the parameters such as the differential inductance, the saturation level and the linearity range is a difficult task, in particular for high current inductors. In this paper a comparison between different methods of measure of the magnetic characteristic of a gapped filtering inductor versus current, in the range from zero magnetization to the saturation, is presented and discussed. It is shown that the different measurement methods provide appreciable differences in the evaluation of the magnetic characteristic of a benchmark inductor. The differences found are also analyzed by suitable numerical simulations.
查看更多>>摘要：In this paper, a low-cost and real-time pose measurement method for straight pipe jacking machine in tunneling guidance is proposed, which utilizes an instruction laser and a dual-screen laser target. The precise localization of light-spot on target is realized by high-performance processing of the image and grid calibration of the target. The spatial matrix transformation method is used to calculate the parameters for the specified position of the pipe jacking machine. Subsequently, the horizontal/vertical deviation between the actual moving route of the straight pipe jacking machine and the design tunnel axis (DTA) can be calculated. The results of the experiment show that the precision and absolute error of the azimuth angle measurement are better than 0.03 degrees (1 Sigma) and 0.05 degrees, respectively. The measurement error of horizontal/vertical deviation is less than 3 mm. Hence, this method is feasible and highly accurate, which can effectively solve the guidance problem of pipe jacking construction.
Cheng, ZhuoqiDall'Alba, DiegoSchwaner, Kim LindbergFiorini, Paolo...
9页
查看更多>>摘要：Intraoperative tissue identification is important and frequently required in modern surgical approaches for guiding operation. For this purpose, a novel robot assisted sensing system equipped with a wide-band impedance spectroscope is developed. Without introducing an external sensor probe to the operating site, the proposed system incorporates two robotic instruments for electric current excitation and voltage measurement. Based on the developed measurement strategy and algorithm, the electrical conductivity and permittivity of the tissue region can be calculated. Experiments based on simulation, salines and ex-vivo tissue phantoms are conducted. The experimental results demonstrate that the proposed system has a high measurement accuracy (>= 97%). Through a simple support vector machine, a 100% accuracy is achieved for identifying five different tissues. Given the convincing results, the presented sensing system shows great potential in offering effective, fast, and safe tissue inspection.
查看更多>>摘要：Various sensors of Metglas/PZT configuration based on magnetoelectric effect, including open-magnetic-circuit in bar-shape (IS), U-shape (US), and closed-magnetic-circuit in square-ring-shape (SS), with different dimensions are investigated from simulation, theoretical calculation to experiments, in homogeneous and vortex magnetic field. While the IS has great privilege in homogeneous field owing to the amendment shape anisotropy, the US/SS are well adapted in vortex field. For measuring current, the results indicate that the induced magnetization in the US and SS is equivalent and both larger than that of IS. The US sensitivities of 310.4 mV.A(-1) and 69.1 V.A(-1) are achieved in direct and indirect approaches, respectively, which are ~1.27 times higher compared to the IS and the same increasing factor of measured magnetic susceptibility. Simple assembling, high sensitivity and high resolution make this US competitive with practical current measurement ranging from 5 mu A to 33 A replying on different types of setup.
查看更多>>摘要：The volume fraction of the primary a phase affects the mechanical and processing properties of the dual-phase titanium alloy, its online detection is necessary and important for product quality control. In this study, samples with different microstructural characteristics were obtained by solution treated from 920 degrees C to 1000 degrees C, and the volume fraction of the primary a phase was counted by Image-Pro Plus software. Then, calculate the velocity of ultrasonic longitudinal waves in different samples and time-frequency analysis according to the signals obtained from the laser ultrasonic experiment. Finally, a prediction model of the volume fraction of the primary a phase linearly related to the ultrasonic longitudinal wave velocity was established, and the linear fit has a higher R-2 than 0.96. This study can provide a reference for the online detection of phase volume fraction.
查看更多>>摘要：The fiber strapdown inertial navigation system (INS) has been widely utilized in aircraft, autonomous driving, robotics, and other fields due to the rapid growth of fiber technology. The core components of INS, the fiber optic gyroscope (FOG) and quartz flexible accelerometer (QFA), are prone to affected by the environmental temperature variation. The traditional temperature drift compensation method requires a considerable time to calibrate each inertial sensor individually. But after the six inertial sensors are integrated, the temperature environment inside the INS will become more complex. As a result, this device-level method has an unsatisfactory effect in the practical application of INS. Furthermore, the traditional method ignores the fact that the temperature drift characteristics of FOG are not the same at different working states. To solve the above problems, we propose a novel temperature drift compensation method of INS based on gravitational search algorithm (GSA) tuning support vector regression (SVR). The startup state and stable working state are modeled independently based on the FOG's features. Without adding additional thermometers to the inertial sensors, the temperature field is constructed by making full use of the information provided by the built-in thermometer of six inertial sensors. The experimental results verify the effectiveness of our method during different working states. And compared with the traditional polynomial fitting method, our method has better performance in the navigation experiment, the navigation accuracy increased by more than 50%.
查看更多>>摘要：The high temperature properties of fiber Bragg gratings (FBGs) fabricated by overexposure using femtosecond laser phase mask technology are investigated. It is found that the overexposed FBG (FBG-II) has exhibited a temperature resistance of up to1000 degrees C and a reflection intensity of over 12 dB after air cooling treatment at 1000 degrees C for 5 h, as well as showing better high temperature stability than the unexposed gratings (FBG-I). Moreover, the temperature stability of FBG-II can be enhanced obviously through the rapid air cooling treatment after high temperature annealing, as well as the higher the air cooling rate, the more significant the effect. In addition, the wavelength hysteresis and spectral repeatability of the FBG-IIs can be significantly improved through the method. This research essentially provides a new approach to enhance the thermal properties of FBG and shows great potential in a harsh environment.
查看更多>>摘要：In recent years, the worldwide road network has grown rapidly and reached an enormous size. Parallel to this size of the road network, the imperfections on the road surfaces are just as large. This has led to a significant increase in road maintenance costs for traffic management departments. Researchers have proposed methods for automatic flaw detection using deep neural networks to reduce road maintenance costs. However, these methods are insufficient in terms of performance and lightness. In this study, a convolutional neural network-based approach is proposed, which provides more successful road surface crack detection and requires less lightweight compared to other studies. Since the performance of the proposed approach is higher and more lightweight, it can be used more effectively and efficiently in mobile systems.
查看更多>>摘要：Accurate identification of vehicle loads plays a great significance in design, monitoring and evaluation of bridges. However, it is hard to acquire them via conventional methods because of their weak practicality or low modeling accuracy. To this end, this study proposes an innovative method to perform load identification based on the random response power spectral density (PSD) and deep transfer learning strategy. This method belongs to a data-driven model, which avoids the expensive facility requirement or ill-posed inverse problem in conventional methods. Specifically, a vehicle-bridge interaction dynamic system considering the disturbance of road surface excitation is firstly established to generate structural response for any specified vehicle loads. Then, the corresponding response PSD is transformed to a three-dimensional matrix in the form of color image, by which the deep transfer learning strategy is incorporated in deep convolutional neural network for describing the mapping relationship between structural response and these specified vehicle loads. On this basis, load identification can be performed via inputting any interested response PSD into the established relationship. Finally, the effectiveness of the proposed method is validated numerically. The results demonstrate that it can accurately identify the vehicle weight, vehicle speed and road surface roughness with an overall accuracy exceeding 98% and presents an excellent anti-noise capacity.
查看更多>>摘要：Thermal equilibrium of machine tools is needed before machining to ensure the accuracy. To shorten the warmup time and improve the machining efficiency, a rapid identification of thermal errors is proposed. It can predict the thermal errors in the shortest identification time so that the thermal error compensation can be started in advance to shorten the thermal equilibrium time. A Singular Value Decomposition-Adaptive Unscented Kalman Filter algorithm (SVD-AUKF) is proposed with singular value decomposition and adaptive rule for the fast identification. A general exponential thermal error model is established and applied into the SVD-AUKF. RMSE of the thermal error data within each time is calculated for the evaluation to obtain the shortest identification time. K hysteresis rule, Delta t judgment rule and maximum time rule are proposed for the prediction accuracy. Different experiments are proposed with two machine tools to testify the effectiveness of the shortest identification time.
NSTL
Elsevier