Northeastern University (China)

About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).

Enhanced tensile properties of aluminium matrix composites reinforced with graphene encapsulated SiC nanoparticles

Abstract: Due to a high propensity of nano-particles to agglomerate, making aluminium matrix composites with a uniform dispersion of the nano-particles using liquid routes is an exceptionally difficult task. In this study, an innovative approach was utilised to prevent agglomeration of nano-particle by encapsulating SiC nano-particles using graphene sheets during ball milling. Subsequently, the milled mixture was incorporated into A356 molten alloy using non-contact ultrasonic vibration method. Two different shapes for graphene sheets were characterised using HRTEM, including onion-like shells encapsulating SiC particles and disk-shaped graphene nanosheets. This resulted in 45% and 84% improvement in yield strength and tensile ductility, respectively. The former was ascribed to the Orowan strengthening mechanism, while the latter is due primarily to the fiber pull-out mechanism, brought about by the alteration of the solidification mechanism from particle pushing to particle engulfment during solidification as a consequence of high thermal conductive graphene sheets encapsulating SiC particles.

Fault detection in finite frequency domain for Takagi-Sugeno fuzzy systems with sensor faults.

Abstract: This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit.