Applied fault detection and diagnosis for industrial gas turbine systems

The paper presents readily implementable approaches for fault detection and diagnosis (FDD) based on measurements from multiple sensor groups, for industrial systems. Specifically, the use of hierarchical clustering (HC) and self-organizing map neural networks (SOMNNs) are shown to provide robust and user-friendly tools for application to industrial gas turbine (IGT) systems. HC fingerprints are found for normal operation, and FDD is achieved by monitoring cluster changes occurring in the resulting dendrograms. Similarly, fingerprints of operational behaviour are also obtained using SOMNN based classification maps (CMs) that are initially determined during normal operation, and FDD is performed by detecting changes in their CMs. The proposed methods are shown to be capable of FDD from a large group of sensors that measure a variety of physical quantities. A key feature of the paper is the development of techniques to accommodate transient system operation, which can often lead to false-alarms being triggered when using traditional techniques if the monitoring algorithms are not first desensitized. Case studies showing the efficacy of the techniques for detecting sensor faults, bearing tilt pad wear and early stage pre-chamber burnout, are included. The presented techniques are now being applied operationally and monitoring IGTs in various regions of the world

OPTIMIZATION OF AEOLIAN ENERGY CONVERSION OPTIMISATION DE LA CONVERSION DE L’ENERGIE EOLIENNE

<p>The use of renewable energy increases, because people are increasingly concerned with environmental issues. Among renewable, wind power is now widely used. Their study showed that a value of wind speed, there is a maximum mechanical power supplied by the turbine. So, power is supplied are particularly changes with maximum speed.</p><p>However, the objective of this paper is to present an algorithm for optimal conversion of wind energy based on a criterion optimization that must maintain specific speed of the turbine at optimum speed which corresponds to the maximum power provided by the steady wind turbine. To this end, the object is to preserve the position of any static operating point on the characteristic of optimal.</p><p>To validate the model and algorithm for optimal conversion of wind energy, a series of numerical simulations carried out using the software MatLab Simulink will be presented is discussed.</p

Corresponding author Diagnosis and Fault Detection in Induction Motor drive Fed by PWM Voltage Source Inverter

The induction motor is one of the most used electric machines in variable speed system in the different field of industry and takes a particular interest for applications requiring high power and variable speed for its robust and simplicity. The early detection for motor deterioration can increase plant availability and safety in an economical way. Many publications have investigated the detection and diagnosis broken rotor bars in electrical machines supplied directly on line. However, much fewer research results have been published when the induction motor is fed by pulse width modulation (PWM) voltage source inverter which is the most common drive in the industry. This paper presents a technique method based on spectral analysis of stator currents to detect broken rotor bars fault in the rotor when it is fed from PWM-VSI. The obtained results show clearly the possibility of extracting signatures to detect and locate fault

Genetic homogenization of indigenous sheep breeds in Northwest Africa

Northwest-African sheep represent an ideal case-study for assessing the potential impact of genetic homogenization as a threat to the future of traditional breeds that are adapted to local conditions. We studied ten Algerian and Moroccan breeds of sheep, including three transboundary breeds, distributed over a large part of the Maghreb region, which represents a geographically and historically coherent unit. Our analysis of the dataset that involved carrying out Genome-wide SNP genotyping, revealed a high level of homogenization (ADMIXTURE, NetView, fineSTRUCTURE and IBD segments analyses), in such a way that some breeds from different origins appeared genetically undistinguished: by grouping the eight most admixed populations, we obtained a mean global FST value of 0.0024. The sPCA analysis revealed that the major part of Morocco and the Northern part of Algeria were affected by the phenomenon, including most of the breeds considered. Unsupervised cross-breeding with the popular Ouled-Djellal breed was identified as a proximate cause of this homogenization. The issue of transboundary breeds was investigated, and the Hamra breed in particular was examined via ROH fragments analysis. Genetic diversity was considered in the light of historical archives and anthropological works. All of these elements taken together suggest that homogenization as a factor affecting the Maghrebin sheep stock, has been particularly significant over the last few decades, although this process probably started much earlier. In particular, we have identified the policies set by the French administration during the colonial period of the region’s history as a causal factor that probably contributed significantly to this process. The genetic homogenization that we have observed calls into question the integrity of the farm animal genomic resources represented by these local breeds, whose conservation is of critical importance to the future of the livestock sector