Development of the data buffer holding time-series data across multiple applications

大規模計算機システム利用者研究報

The DNA Methylome of Human Peripheral Blood Mononuclear Cells

Analysis across the genome of patterns of DNA methylation reveals a rich landscape of allele-specific epigenetic modification and consequent effects on allele-specific gene expression

Energy absorption analysis of density graded aluminum foam

A numerical approach is carried out to investigate the energy absorption efficiency of density graded aluminium foam. Effects of blast load impact velocity, loading duration and sample thickness on the input energy density and output energy density of the graded foam are investigated. The stochastic meso-scale aluminium foam structure is generated by adopting a 2D Voronoi technique and the commercial software ANSYS/LS-DYNA is used for the FE modelling. Parametric study shows that the density graded aluminium foam is effective in improving energy absorption capability while keeping a lower stress transmitted to the substrate or the protected structure if it is properly designed.Accepted versio

Design of Metal Foam Cladding Subjected to Close-Range Blast

The response of a blast mitigation cladding consisting of a face sheet and metal foam core subjected to a close-range blast is predicted. Whereas the cladding is sufficiently wide compared to the standoff distance between the explosion center and the cladding, the boundary of the blast induced bulge is released. The face sheet is considered as a rigid perfectly plastic membrane as the deformation of the sheet always exceeds half its thickness. A procedure predicting the depth and extent of the bulge is proposed with energy method. Subsequently, the minimum thickness of the foam layer is calculated based on the bulge depth. This design-oriented approach, in a ready-to-use manner, can be straightforwardly applied, facilitating the preliminary design of blast mitigation claddings with metal foam core

Design of data acquisition and LED display system

Conference Name:3rd international Conference on Manufacturing Science and Engineering, ICMSE 2012. Conference Address: Xiamen, China. Time:March 27, 2012 - March 29, 2012.Fujian University of Technology; Xiamen University; Fuzhou University; Huaqiao University; University of WollongongThis paper set up a data acquisition system by AT89C52 single chip microcomputer as control core, using the RS-232 serial manner communicated with responsibled for data acquisition of microprocessor, and used LED to display. System can be divided into data acquisition module, serial communication module, control module, keyboard module, display module, etc. System of multi-channel data acquisition can be displayed in the LED after processed. The hardware circuit and software realized design functions: data acquisition and LED display. 漏 (2012) Trans Tech Publications

Industrial Application of Data-Driven Process Monitoring with an Automatic Selection Strategy for Modeling Data

The increasing scale of industrial processes has significantly motivated the development of data-driven fault detection and diagnosis techniques. The selection of representative fault-free modeling data from operation history is an important prerequisite to establishing a long-term effective process monitoring model. However, industrial data are characterized by a high dimension and multimode, and are also contaminated with both outliers and frequent random disturbances, making automatic modeling data selection a great challenge in industrial applications. In this work, an information entropy-based automatic selection strategy for modeling data is proposed, based on which a general real-time process monitoring framework is developed for a large-scale industrial methanol to olefin unit with multiple operating conditions. Modeling data representing normal operating conditions are automatically selected with only a few manually defined normal samples. A long-term effective process monitoring model is then established based on a multi-layer autoencoder, through which unexpected disturbances in real-time operation can be detected early and the root cause can be preliminarily diagnosed by contribution plots. The adjustment of operating conditions has also been considered through a model update strategy. Details of the proposed data selection strategy and modeling process have been provided to facilitate the industrial application of process monitoring systems by other researchers or companies

Industrial Application of Data-Driven Process Monitoring with an Automatic Selection Strategy for Modeling Data

The increasing scale of industrial processes has significantly motivated the development of data-driven fault detection and diagnosis techniques. The selection of representative fault-free modeling data from operation history is an important prerequisite to establishing a long-term effective process monitoring model. However, industrial data are characterized by a high dimension and multimode, and are also contaminated with both outliers and frequent random disturbances, making automatic modeling data selection a great challenge in industrial applications. In this work, an information entropy-based automatic selection strategy for modeling data is proposed, based on which a general real-time process monitoring framework is developed for a large-scale industrial methanol to olefin unit with multiple operating conditions. Modeling data representing normal operating conditions are automatically selected with only a few manually defined normal samples. A long-term effective process monitoring model is then established based on a multi-layer autoencoder, through which unexpected disturbances in real-time operation can be detected early and the root cause can be preliminarily diagnosed by contribution plots. The adjustment of operating conditions has also been considered through a model update strategy. Details of the proposed data selection strategy and modeling process have been provided to facilitate the industrial application of process monitoring systems by other researchers or companies

Design of monitoring the PV-Wind power system based on King View

Conference Name:3rd international Conference on Manufacturing Science and Engineering, ICMSE 2012. Conference Address: Xiamen, China. Time:March 27, 2012 - March 29, 2012.Fujian University of Technology; Xiamen University; Fuzhou University; Huaqiao University; University of WollongongThis paper set up high-quality and highly efficient automatic data collection and analysis system by King View configuration in order to improve the reliability and stability of PV-Wind power system monitoring and decrease the workload, the design of its functions, structure, interface, control strategy and system variables, protection, and so on are detailed. It uses configuration software based on PC to exploit the operation interface in host computer, and adopt Wide-Plus Intelligent Instrument as the lower computer to data-acquisition. It monitors and controls PV-Wind power System, acquires field data, deals with device faults in real-time. 漏 (2012) Trans Tech Publications