Robust fault detection for networked systems with distributed sensors

Copyright [2011] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper is concerned with the robust fault detection problem for a class of discrete-time networked systems with distributed sensors. Since the bandwidth of the communication channel is limited, packets from different sensors may be dropped with different missing rates during the transmission. Therefore, a diagonal matrix is introduced to describe the multiple packet dropout phenomenon and the parameter uncertainties are supposed to reside in a polytope. The aim is to design a robust fault detection filter such that, for all probabilistic packet dropouts, all unknown inputs and admissible uncertain parameters, the error between the residual (generated by the fault detection filter) and the fault signal is made as small as possible. Two parameter-dependent approaches are proposed to obtain less conservative results. The existence of the desired fault detection filter can be determined from the feasibility of a set of linear matrix inequalities that can be easily solved by the efficient convex optimization method. A simulation example on a networked three-tank system is provided to illustrate the effectiveness and applicability of the proposed techniques.This work was supported by national 973 project under Grants 2009CB320602 and 2010CB731800, and the NSFC under Grants 60721003 and 60736026

Processing of immiscible alloys by a twin-screw rheomixing process

Immiscible alloys with a microstructure in which a soft phase dispersed homogeneously in a hard matrix have great potential applications in advanced bearing systems, especially for automotive industry. Though the melt of an immiscible alloy is miscible at the temperature above the miscibility gap, it decomposes into two liquids when it passes through the liquid miscibility gap. Despite great efforts made worldwide, including extensive space experiments, no casting techniques so far can produce the desirable microstructure. Based on the extensive experience in mixing the immiscible organic liquids offered by the polymer processing community, a rheomixing process for immiscible alloys has been successfully developed at Brunel University using a twin-crew extruder. This paper presents the twin-screw rheomixing process and the experimental results on rheomixing of the immiscible Zn-Pb alloys

Twin-screw rheomoulding of AZ91D Mg-alloys

Twin-screw rheomoulding is a new semisolid process for the near net shape production of metal’s components. It includes the advantage combination in both die-casting and injection moulding. In this unique process, a liquid alloy is fed into a twin-screw extruder, where the alloy is intensively sheared and cooled into the interval of liquidus and solidus to produce semisolid slurry with fine primary particles of pre-determined volume fraction. The well-sheared semisolid slurry is then discharged into a shot cylinder and subsequently injected into a mould cavity for component shaping. This paper introduces the development of the prototype machine and the experimental work carried out with industrial AZ91D magnesium alloy. The operating characteristics of the newly developed machine, microstructures and mechanical properties of rheomoulded AZ91D magnesium alloy will be reported

Aging Behavior and Mechanism Evolution of Nano-Al2O3/Styrene-Butadiene-Styrene-Modified Asphalt under Thermal-Oxidative Aging

The goal of this paper is to analyze the aging behavior and the mechanism evolution of nano-Al2O3 (NA)-reinforced styrene-butadiene-styrene (SBS) asphalt under different thermal-oxidative aging conditions. First, NA/SBS-modified asphalt and SBS-modified asphalt with different aging levels were prepared. Second, the viscosity and high temperature rheological performance of the specimens were tested and the property-related aging indexes were calculated and compared. Third, a Fourier transform infrared (FTIR) test of the specimen was conducted and the chemical group-related aging indexes were calculated and analyzed. Fourth, gel permeation chromatography (GPC) was used to analyze the molecular weight of the specimens under different aging levels. Then, an atomic force microscope (AFM) was adopted to analyze the microsurface morphology of different specimens. Finally, correlation analysis between property-related indexes and chemical group indexes was conducted. The results show that NA can enhance the thermal-oxidative aging resistance of SBS asphalt. NA can inhibit the increase in sulfoxide groups and the degradation of the SBS polymer with the increase in aging. NA can slow down the formation of large molecule during the aging process. The degree of change in both the bee structures and micromorphological roughness of NA/SBS asphalt is lower than that of SBS asphalt under different aging levels

Use of evidential reasoning and AHP to assess regional industrial safety

China’s fast economic growth contributes to the rapid development of its urbanization process, and also renders a series of industrial accidents, which often cause loss of life, damage to property and environment, thus requiring the associated risk analysis and safety control measures to be implemented in advance. However, incompleteness of historical failure data before the occurrence of accidents makes it difficult to use traditional risk analysis approaches such as probabilistic risk analysis in many cases. This paper aims to develop a new methodology capable of assessing regional industrial safety (RIS) in an uncertain environment. A hierarchical structure for modelling the risks influencing RIS is first constructed. The hybrid of evidential reasoning (ER) and Analytical Hierarchy Process (AHP) is then used to assess the risks in a complementary way, in which AHP is hired to evaluate the weight of each risk factor and ER is employed to synthesise the safety evaluations of the investigated region(s) against the risk factors from the bottom to the top level in the hierarchy. The successful application of the hybrid approach in a real case analysis of RIS in several major districts of Beijing (capital of China) demonstrates its feasibility as well as provides risk analysts and safety engineers with useful insights on effective solutions to comprehensive risk assessment of RIS in metropolitan cities. The contribution of this paper is made by the findings on the comparison of risk levels of RIS at different regions against various risk factors so that best practices from the good performer(s) can be used to improve the safety of the others

A single device based Voltage Step Stress (VSS) Technique for fast reliability screening

A new wafer-level reliability qualification methodology is proposed. Unlike conventional method which usually takes days to completion, the total test time of the new technique can be shortened within 2 hours. Besides, it only requires a single device. This new technique is easy to implement on commercial equipment and it has been successfully validated on different processes including the most advanced 28nm process with both SiON and high-k gate stacks. This new technique can be an effective tool for fast reliability screening during process development in future

Delay-dependent robust stability of stochastic delay systems with Markovian switching

In recent years, stability of hybrid stochastic delay systems, one of the important issues in the study of stochastic systems, has received considerable attention. However, the existing results do not deal with the structure of the diffusion but estimate its upper bound, which induces conservatism. This paper studies delay-dependent robust stability of hybrid stochastic delay systems. A delay-dependent criterion for robust exponential stability of hybrid stochastic delay systems is presented in terms of linear matrix inequalities (LMIs), which exploits the structure of the diffusion. Numerical examples are given to verify the effectiveness and less conservativeness of the proposed method

Exciton Valley Dynamics probed by Kerr Rotation in WSe2 Monolayers

We have experimentally studied the pump-probe Kerr rotation dynamics in WSe$_2$ monolayers. This yields a direct measurement of the exciton valley depolarization time $\tau_v$. At T=4K, we find $\tau_v\approx 6$ps, a fast relaxation time resulting from the strong electron-hole Coulomb exchange interaction in bright excitons. The exciton valley depolarization time decreases significantly when the lattice temperature increases with $\tau_v$ being as short as 1.5ps at 125K. The temperature dependence is well explained by the developed theory taking into account the exchange interaction and a fast exciton scattering time on short-range potentials.Comment: 5 pages, 3 figure

Visual information processing through the interplay between fine and coarse signal pathways

Object recognition is often viewed as a feedforward, bottom-up process in machine learning, but in real neural systems, object recognition is a complicated process which involves the interplay between two signal pathways. One is the parvocellular pathway (P-pathway), which is slow and extracts fine features of objects; the other is the magnocellular pathway (M-pathway), which is fast and extracts coarse features of objects. It has been suggested that the interplay between the two pathways endows the neural system with the capacity of processing visual information rapidly, adaptively, and robustly. However, the underlying computational mechanism remains largely unknown. In this study, we build a two-pathway model to elucidate the computational properties associated with the interactions between two visual pathways. Specifically, we model two visual pathways using two convolution neural networks: one mimics the P-pathway, referred to as FineNet, which is deep, has small-size kernels, and receives detailed visual inputs; the other mimics the M-pathway, referred to as CoarseNet, which is shallow, has large-size kernels, and receives blurred visual inputs. We show that CoarseNet can learn from FineNet through imitation to improve its performance, FineNet can benefit from the feedback of CoarseNet to improve its robustness to noise; and the two pathways interact with each other to achieve rough-to-fine information processing. Using visual backward masking as an example, we further demonstrate that our model can explain visual cognitive behaviors that involve the interplay between two pathways. We hope that this study gives us insight into understanding the interaction principles between two visual pathways