Authenticity as a Social Contract—We Are Our Records

This poster presents the authors’ work to date on developing an application profile for authenticity metadata (the IPAM, or InterPARES Authenticity Metadata), including (1) the functional requirements,(2) metadata elements derived from the Chain of Preservation model from the InterPARES research project, (3) a crosswalk of a sample of IPAM elements to Dublin Core, PREMIS, and MoReq2010,(4) those elements deemed essential to presume the authenticity of a record as it moves from creation to permanent preservation, and (5) next steps, integrating the application profile into the Archivematica preservation system the core elements of the application profile relating to maintaining the presumption of authenticity through preservation and access.

Reliability evaluations of railway power supplies by fault-tree analysis

High reliability of railway power systems is one of the essential criteria to ensure quality and cost-effectiveness of railway services. Evaluation of reliability at system level is essential for not only scheduling maintenance activities, but also identifying reliability-critical components. Various methods to compute reliability on individual components or regularly structured systems have been developed and proven to be effective. However, they are not adequate for evaluating complicated systems with numerous interconnected components, such as railway power systems, and locating the reliability critical components. Fault tree analysis (FTA) integrates the reliability of individual components into the overall system reliability through quantitative evaluation and identifies the critical components by minimum cut sets and sensitivity analysis. The paper presents the reliability evaluation of railway power systems by FTA and investigates the impact of maintenance activities on overall reliability. The applicability of the proposed methods is illustrated by case studies in AC railways.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.

Analysis of electromagnetic forces in high voltage superconducting fault current limiters with saturated core

This paper presents a three-dimensional numerical analysis of the electromagnetic forces within a high voltage superconducting Fault Current Limiter (FCL) with a saturated core under short-circuit conditions. The effects of electrodynamics forces in power transformer coils under short-circuit conditions have been reported widely. However, the coil arrangement in an FCL with saturated core differs significantly from existing reactive devices. The boundary element method is employed to perform an electromagnetic force analysis on an FCL. The analysis focuses on axial and radial forces of the AC coil. The results are compared to those of a power transformer and important design considerations are highlighted.