Thermally Stimulated Depolarization Current Evaluation of Molding Compounds

TSDC (thermally stimulated depolarization current) is one of the most important and popular technique for investigating electret materials. TSDC technique can indicate the magnitude of polarization and depolarization, relaxation time, charge-storage, glass transition, and activation energy. To fully investigate polarization and relaxation for pure epoxy and filled epoxy materials, a TSDC system was built and verified by the research. The article describes the building processes and verification of the TSDC system. TSDC, TSPC, and TWC tests data for epoxy and filled epoxy samples are presented in the article. To compare TSDC technique with other related techniques, DEA (dielectric analysis), DMA (dynamic mechanical analysis), and DSC (differential scanning calorimetry) tests are introduced

Dynamic characteristics and optimal design of the manipulator for automatic tool changer

In order to improve the reliability of changing tool for ATC (automatic tool changer), a horizontal tool changer of machining center is chosen as the example to study the dynamic characteristics in the condition of changing a heavy tool. This paper analyzes the structure and properties of the tool changer by simulation and experiment, and the space trajectory equations of the manipulator and tool are derived. The maximum force is calculated in the processing of changing tool. A virtual platform for the automatic tool changer is built to simulate and verify the dynamic performance of the tool changer; the simulation results show an obvious vibration in the process of changing tool, which increases the probability of failure for changing tool. Moreover, in order to find out the device's vibration reasons, a professional experiment platform is built to test the dynamic characteristics. Based on the testing results for a horizontal tool changer, it is known that the unstable vibration is mainly caused by the collision of the tool. Finally, an optimization method for the manipulator is proposed to reduce this vibration and improve the reliability of the tool changer. The final simulation and experiment results show that the optimized manipulator can grasp the heavy tool stably, and the vibration amplitude is significantly reduced in the process of changing tool

Analysis and Design of Network-Based Control Systems with Binary Modulation

Network-based control systems have been emerging technologies in control and computer communication fields over the past decade. This paper focuses on the analysis and design of network-based control systems with binary modulation. First, it is shown that different modulations can result in different delays which are inevitable in network-based control systems. The delay can be seen as constant delay when the transmission time is the main consideration. Second, channel noise can result in bit error while bit error is seen as active packet loss in this paper, in this context, the conditions of signal-to-noise ratio (SNR) for binary modulation that can guarantee the stability of systems are obtained according to the proposed algorithm. Third, the system with delay and noisy communication can be modeled as an asynchronous dynamic system (ADS); in addition, the stability is analyzed and controller is designed in terms of Lyapunov function and linear matrix inequality (LMI) scheme. Finally, without loss of generality, numerical simulation demonstrates the effectiveness of the proposed scheme and designed controller based on binary amplitude shift keying (2ASK) modulation

IAIFNet: An Illumination-Aware Infrared and Visible Image Fusion Network

Infrared and visible image fusion (IVIF) is used to generate fusion images with comprehensive features of both images, which is beneficial for downstream vision tasks. However, current methods rarely consider the illumination condition in low-light environments, and the targets in the fused images are often not prominent. To address the above issues, we propose an Illumination-Aware Infrared and Visible Image Fusion Network, named as IAIFNet. In our framework, an illumination enhancement network first estimates the incident illumination maps of input images. Afterwards, with the help of proposed adaptive differential fusion module (ADFM) and salient target aware module (STAM), an image fusion network effectively integrates the salient features of the illumination-enhanced infrared and visible images into a fusion image of high visual quality. Extensive experimental results verify that our method outperforms five state-of-the-art methods of fusing infrared and visible images.Comment: Submitted to IEE

SSPFusion: A Semantic Structure-Preserving Approach for Infrared and Visible Image Fusion

Most existing learning-based infrared and visible image fusion (IVIF) methods exhibit massive redundant information in the fusion images, i.e., yielding edge-blurring effect or unrecognizable for object detectors. To alleviate these issues, we propose a semantic structure-preserving approach for IVIF, namely SSPFusion. At first, we design a Structural Feature Extractor (SFE) to extract the structural features of infrared and visible images. Then, we introduce a multi-scale Structure-Preserving Fusion (SPF) module to fuse the structural features of infrared and visible images, while maintaining the consistency of semantic structures between the fusion and source images. Owing to these two effective modules, our method is able to generate high-quality fusion images from pairs of infrared and visible images, which can boost the performance of downstream computer-vision tasks. Experimental results on three benchmarks demonstrate that our method outperforms eight state-of-the-art image fusion methods in terms of both qualitative and quantitative evaluations. The code for our method, along with additional comparison results, will be made available at: https://github.com/QiaoYang-CV/SSPFUSION.Comment: Submitted to IEE