Mobile Robot Lab Project to Introduce Engineering Students to Fault Diagnosis in Mechatronic Systems

This document is a self-archiving copy of the accepted version of the paper. Please find the final published version in IEEEXplore: http://dx.doi.org/10.1109/TE.2014.2358551This paper proposes lab work for learning fault detection and diagnosis (FDD) in mechatronic systems. These skills are important for engineering education because FDD is a key capability of competitive processes and products. The intended outcome of the lab work is that students become aware of the importance of faulty conditions and learn to design FDD strategies for a real system. To this end, the paper proposes a lab project where students are requested to develop a discrete event dynamic system (DEDS) diagnosis to cope with two faulty conditions in an autonomous mobile robot task. A sample solution is discussed for LEGO Mindstorms NXT robots with LabVIEW. This innovative practice is relevant to higher education engineering courses related to mechatronics, robotics, or DEDS. Results are also given of the application of this strategy as part of a postgraduate course on fault-tolerant mechatronic systems.This work was supported in part by the Spanish CICYT under Project DPI2011-22443

Partial Discharge Location within a Transformer Winding using Principal Component Analysis

Partial discharge (PD) may occur in a transformer winding due to ageing processes, operational over stressing or defects introduced during manufacture. The presence of PD does not necessarily indicate imminent failure of the transformer but it will lead to serious degradation and ageing mechanisms which can be considered as a precursor of transformer failure. A necessary step is required in order to prevent degradation due to PD activity which may ultimately lead to failure. PD might occur anywhere along the transformer winding, the discharge signal can propagate along the winding to the bushing and neutral to earth connections. As far as maintenance and replacement processes are concerned, it is important to identify the location of PD activity so any repair or replace decision is assured to be cost effective. Therefore, identification of a PD source as well as its location along the transformer winding is of great interest to both manufacturers and system operators. The proposed method for locating PD sources in windings is based on wavelet filtering and principal component analysis. An experiment has been developed based on a high voltage winding section that has been used to produce PD measurement data and to investigate the feasibility of the proposed approach