A Methodology for Identifying Defects in Wire Rope Based on Permanent Magnet Excitation

A wire rope defects detection method based on permanent magnet excitation is proposed.A detection system,mainly composed of permanent magnet excitation,distance detection,multi-sensor magnetic flux leakage signal acquisition and data analysis device,is set up.According to the different characteristics of the multi-sensor magnetic flux leakage signal,the localized fault(LF)and loss of metallic cross-sectional area(LMA)signal is separated,and then the two defects can be detected.The experiments show that the method can effectively detect the two defects when they appear simultaneously on the wire rope.

Images on Locally Separable Metric Spaces

In this paper internal characterizations on certain quotient images of locally separable metric spaces are discussed.We obtain some descriptions of quotient s-images,pseudo-open s- images,quotient compact images and closed images of locally separable metric spaces,and establish some relations between these and certain quotient images of metric spaces by the local separability of suitable subspaces.

T_D Property and Spatial Sublocales

As one of main backgrounds of locale theory, topologies have close connections with locales. But locales have other backgrounds such as algebra, mathematical logic, etc. So there are many differences between locales and topologies. Spatiality is an important localic property to investigate the connections between locales and topologies. The T_D property is a special separation property which plays an important role in this kind of investigations. Just as it will be proved in this paper, the T_D property often appears as the lowest requirement for many topological spaces such that they can be described with localic properties and vice versa. In this paper, we show these special properties of the T_D axiom and investigate some other interesting and important problems of T_D-spatiality of locales.

Deep Audio-visual Learning:A Survey

Audio-visual learning,aimed at exploiting the relationship between audio and visual modalities,has drawn considerable attention since deep learning started to be used successfully.Researchers tend to leverage these two modalities to improve the performance of previously considered single-modality tasks or address new challenging problems.In this paper,we provide a comprehensive survey of recent audio-visual learning development.We divide the current audio-visual learning tasks into four different subfields:audiovisual separation and localization,audio-visual correspondence learning,audio-visual generation,and audio-visual representation learning.State-of-the-art methods,as well as the remaining challenges of each subfield,are further discussed.Finally,we summarize the commonly used datasets and challenges.

Influence of Some Physical Parameters on the Separation Efficiency of a Gas Centrifuge

To increase the separation efficiency of a gas centrifuge is one of the key objectives for uranium isotope separation. It can provide great benefit with little effort. The separation efficiency is affected by many parameters.Some physical parameters, such as the pressure of UF, at the wall of the centrifuge cylinder. the position of the wastescoop. the tempwrature profile on the wall of the centrituge cylindwer. the direction of the feed into the gas centrifuge are chosen as variables to optimize the separation efficiency of a gas centrifuge. The optimization is based on analytical and experimental results. Local separation efficiency distribution is a good method to describe the separation phenomena in the gas centrifuge.