Torsional oscillations of series capacitor compensated AC/DCsystems

Torsional oscillations in an AC/DC power system that result from series-capacitor compensation and HVDC converter controllers are investigated. A feasible approach for damping the torsional modes by coordinating the controllers of a static VAr compensator (SVC) unit with the supplemental subsynchronous damping control (SSDC) of the HVDC rectifier is presented. An eigenvalue method is used for the studies, and the analytical results are verified by detailed digital computer simulation, using the BPA's Electromagnetic Transients Program (EMTP). The studies show that in a series-capacitor-compensated AC/DC system, the SSDC can be used to damp the subsynchronous resonance (SSR) modes only over a limited range of operating conditions. The coordinated SVC-SSDC approach provides adequate damping for all the SSR modes under all operating conditions, particularly at high series-compensation levels     

Effect of torsional dynamics on salient pole synchronousmotor-driven compressors

This paper presents a rigorous treatment of the starting problem of a salient pole synchronous motor driving a complex multicompressor load. This is aimed at analysing the resulting torsional oscillations and calculating the different transmitted torques and twist angles of the multi-shaft assembly. For this purpose, the necessary mathematical models and corresponding digital simulation are developed. The results obtained show that there is a pressing need for taking care of the torsional effects on the different shafts during the design stage, otherwise serious problems could arise     

Post-buckling analysis of piezo-magnetic nanobeams with geometrical imperfection and different piezoelectric contents

Microsystem Technologies - Thermal post-buckling behavior of a geometrically imperfect/perfect piezo-magnetic nano-scale beams made of two-phase composites is analyzed in the present paper based on...     

Nonlinear free and forced vibrations of graphene nanoplatelet reinforced microbeams with geometrical imperfection

Microsystem Technologies - Nonlinear free/forced vibration of a functionally graded graphene nanoplatelet (GNP) reinforced microbeam having geometrical imperfection which is rested on a non-linear...     

Crushing response of composite corrugated tubes to quasi-static axial loading

This paper is devoted to examine the crushing behaviour of axially crushed composite corrugated tubes. Two types of composites were tested, namely, carbon fibre/epoxy in a filament form and glass fibre/epoxy in woven roving form. A series of experiments was conducted for tubes with corrugation angle (β) ranging from 10° to 40°. Typical failure histories of their failure mechanisms are presented and discussed. The results showed that the crushing behaviour of composite corrugated tube is found to be sensitive to the change in corrugation angle and fibre type. Carbon/epoxy tubes with corrugation angle of 40° displayed the highest specific energy absorption capability. It is also found that introducing of corrugation could significantly enhance the energy absorption capability of composite tubes in a uniform manner.     

Pattern‐based prognostic methodology for condition‐based maintenance using selected and weighted survival curves

This paper proposes a pattern‐based prognostic methodology that combines logical analysis of data (LAD) as an event‐driven diagnostic technique, and Kaplan–Meier (KM) estimator as a time‐driven technique. LAD captures the effect of the instantaneous conditions on the health state of a monitored system, while KM estimates the baseline reliability curve that reflects the effect of aging, based on the observed historical failure times. LAD is used to generate a set of patterns from the observed values of covariates that represent the operating conditions and condition indicators. A pattern selection procedure is carried out to select the set of significant patterns from all the generated patterns. A survival curve is estimated, for each subset of observations covered by each selected pattern. A weight that reflects the coverage of each pattern is assigned to its survival curve. Given a recently collected observation, the survival curve of a monitored system is updated on the basis of the patterns covering that observation. The updated curve is then used to predict the remaining useful life of the monitored system. The proposed methodology is validated using a common dataset in prognostics: the turbofan degradation dataset that is available at NASA prognostic repository. Copyright © 2017 John Wiley & Sons, Ltd.     

Vibration of rotating functionally graded Timoshenko nano-beams with nonlinear thermal distribution

The vibration analysis of rotating, functionally graded Timoshenko nano-beams under an in-plane nonlinear thermal loading is studied for the first time. The formulation is based on Eringen's nonlocal elasticity theory. Hamilton's principle is used for the derivation of the equations. The governing equations are solved by the differential quadrature method. The nano-beam is under axial load due to the rotation and thermal effects, and the boundary conditions are considered as cantilever and propped cantilever. The thermal distribution is considered to be nonlinear and material properties are temperature-dependent and are changing continuously through the thickness according to the power-law form.     

Variable Selection‐based Multivariate Cumulative Sum Control Chart

High‐dimensional applications pose a significant challenge to the capability of conventional statistical process control techniques in detecting abnormal changes in process parameters. These techniques fail to recognize out‐of‐control signals and locate the root causes of faults especially when small shifts occur in high‐dimensional variables under the sparsity assumption of process mean changes. In this paper, we propose a variable selection‐based multivariate cumulative sum (VS‐MCUSUM) chart for enhancing sensitivity to out‐of‐control conditions in high‐dimensional processes. While other existing charts with variable selection techniques tend to show weak performances in detecting small shifts in process parameters due to the misidentification of the ‘faulty’ parameters, the proposed chart performs well for small process shifts in identifying the parameters. The performance of the VS‐MCUSUM chart under different combinations of design parameters is compared with the conventional MCUSUM and the VS‐multivariate exponentially weighted moving average control charts. Finally, a case study is presented as a real‐life example to illustrate the operational procedures of the proposed chart. Both the simulation and numerical studies show the superior performance of the proposed chart in detecting mean shift in multivariate processes. Copyright © 2016 John Wiley & Sons, Ltd.     

Face recognition using multi-class Logical Analysis of Data

This paper addresses the applicability of multi-class Logical Analysis of Data (LAD) as a face recognition technique (FRT). This new classification technique has already been applied in the field of biomedical and mechanical engineering as a diagnostic technique; however, it has never been used in the face recognition literature. We explore how Eigenfaces and Fisherfaces merged to multi-class LAD can be leveraged as a proposed FRT, and how it might be useful compared to other approaches. The aim is to build a single multi-class LAD decision model that recognizes images of the face of different persons. We show that our proposed FRT can effectively deal with multiple changes in the pose and facial expression, which constitute critical challenges in the literature. Comparisons are made both from analytical and practical point of views. The proposed model improves the classification of Eigenfaces and Fisherfaces with minimum error rate.     

Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation

Most of the reported prognostic techniques use a small number of condition indicators and/or use a thresholding strategies in order to predict the remaining useful life (RUL). In this paper, we propose a reliability-based prognostic methodology that uses condition monitoring (CM) data which can deal with any number of condition indicators, without selecting the most significant ones, as many methods propose. Moreover, it does not depend on any thresholding strategies provided by the maintenance experts to separate normal and abnormal values of condition indicators. The proposed prognostic methodology uses both the age and CM data as inputs to estimate the RUL. The key idea behind this methodology is that, it uses Kaplan–Meier as a time-driven estimation technique, and logical analysis of data as an event-driven diagnostic technique to reflect the effect of the operating conditions on the age of the monitored equipment. The performance of the estimated RUL is measured in terms of the difference between the predicted and the actual RUL of the monitored equipment. A comparison between the proposed methodology and one of the common RUL prediction technique; Cox proportional hazard model, is given in this paper. A common dataset in the field of prognostics is employed to evaluate the proposed methodology.