Sensor selection based on principal component analysis for fault detection in wind turbines

Growing interest for improving the reliability of safety-critical structures, such as wind turbines, has led to the advancement of structural health monitoring (SHM). Existing techniques for fault detection can be broadly classified into two major categories: model-based methods and signal processing-based methods. This work focuses in the signal-processing-based fault detection by using principal component analysis (PCA) as a way to condense and extract information from the collected signals. In particular, the goal of this work is to select a reduced number of sensors to be used. From a practical point of view, a reduced number of sensors installed in the structure leads to a reduced cost of installation and maintenance. Besides, from a computational point of view, less sensors implies lower computing time, thus the detection time is shortened. The overall strategy is to firstly create a PCA model measuring a healthy wind turbine. Secondly, with the model, and for each fault scenario and each possible subset of sensors, it measures the Euclidean distance between the arithmetic mean of the projections into the PCA model that come from the healthy wind turbine and the mean of the projections that come from the faulty one. Finally, it finds the subset of sensors that separate the most the data coming from the healthy wind turbine and the data coming from the faulty one. Numerical simulations using a sophisticated wind turbine model (a modern 5MW turbine implemented in the FAST software) show the performance of the proposed method under actuators (pitch and torque) and sensors (pitch angle measurement) faults of different type: fixed value, gain factor, offset and changed dynamics.Postprint (published version

Wind turbine condition monitoring strategy through multiway PCA and multivariate inference

This article states a condition monitoring strategy for wind turbines using a statistical data-driven modeling approach by means of supervisory control and data acquisition (SCADA) data. Initially, a baseline data-based model is obtained from the healthy wind turbine by means of multiway principal component analysis (MPCA). Then, when the wind turbine is monitorized, new data is acquired and projected into the baseline MPCA model space. The acquired SCADA data are treated as a random process given the random nature of the turbulent wind. The objective is to decide if the multivariate distribution that is obtained from the wind turbine to be analyzed (healthy or not) is related to the baseline one. To achieve this goal, a test for the equality of population means is performed. Finally, the results of the test can determine that the hypothesis is rejected (and the wind turbine is faulty) or that there is no evidence to suggest that the two means are different, so the wind turbine can be considered as healthy. The methodology is evaluated on a wind turbine fault detection benchmark that uses a 5 MW high-fidelity wind turbine model and a set of eight realistic fault scenarios. It is noteworthy that the results, for the presented methodology, show that for a wide range of significance, a in [1%, 13%], the percentage of correct decisions is kept at 100%; thus it is a promising tool for real-time wind turbine condition monitoring.Peer ReviewedPostprint (published version

Una aproximació ontològica de la interfície d'Internet i les seves implicacions en el disseny

La seva estructura d'Internet no és uniforme ni ordenada en el sentit de "prevista", sinó que més aviat és adaptable i caòtica. El punt de contacte entre l'emissor i el receptor final de la informació digital és la interfície. La forma habitual de la interfície és la de pantalla.La interfície no ofereix una connexió neutre en cap de les dues direccions de la comunicació a la xarxa. El control de l'aparença de la interfície condicionarà aquesta comunicació. En un mitjà sincrètic com Internet, el disseny de la interfície té influència en el desplaçament dels centres de poder.La estructura de Internet no es uniforme ni ordenada en el sentido de " prevista ", sino que más bien es adaptable y caótica. El punto de contacto entre el emisor y el receptor final de la información digital es la interfaz. La forma habitual de la interfaz es la de pantalla.La interfaz no ofrece una conexión neutra en ninguna de las dos direcciones de la comunicación en la red. El control de la apariencia de la interfaz condicionará esta comunicación. En un medio sincrético como Internet , el diseño de la interfaz tiene influencia en el desplazamiento de los centros de poder.Internet consists of some nodes and communication channels through which information flows and then generating knowledge. Its structure is neither uniform or ordered in the sense of "planned", but is adaptable and chaotic. This complex structure, the point of contact between the transmitter and receiver digital information is the interface: the boundary between cyberspace and the user. The usual way of the interface is the screen.This paper expose that the interface does not provides a neutral connection in any of the two directions of the communication network. Controlling the appearance of the interface make a condition to communication. Internet is a syncretic medium and the interface design influences the displacement of the centers of power

Damage diagnosis for offshore fixed wind turbines

This paper proposes a damage diagnosis strategy to detect and classify different type of damages in a laboratory offshore-fixed wind turbine model. The proposed method combines an accelerometer sensor network attached to the structure with a conceived algorithm based on principal component analysis (PCA) with quadratic discriminant analysis (QDA). The paradigm of structural health monitoring can be undertaken as a pattern recognition problem (comparison between the data collected from the healthy structure and the current structure to diagnose given a known excitation). However, in this work, as the strategy is designed for wind turbines, only the output data from the sensors is used but the excitation is assumed unknown (as in reality is provided by the wind). The proposed methodology is tested in an experimental laboratory tower modeling an offshore-fixed jacked-type wind turbine. The obtained results show the reliability of the proposed approach.Peer ReviewedPostprint (published version

Condition Monitoring of Wind Turbine Structures through Univariate and Multivariate Hypothesis Testing

This chapter presents a fault detection method through uni- and multivariate hypothesis testing for wind turbine (WT) faults. A data-driven approach is used based on supervisory control and data acquisition (SCADA) data. First, using a healthy WT data set, a model is constructed through multiway principal component analysis (MPCA). Afterward, given a WT to be diagnosed, its data are projected into the MPCA model space. Since the turbulent wind is a random process, the dynamic response of the WT can be considered as a stochastic process, and thus, the acquired SCADA measurements are treated as a random process. The objective is to determine whether the distribution of the multivariate random samples that are obtained from the WT to be diagnosed (healthy or not) is related to the distribution of the baseline. To this end, a test for the equality of population means is performed in both the univariate and the multivariate cases. Ultimately, the test results establish whether the WT is healthy or faulty. The performance of the proposed method is validated using an advanced benchmark that comprehends a 5-MW WT subject to various actuators and sensor faults of different types

Equacions de transport generalitzades per a fluxos turbulents

Es dedueixen les equacions de transport en forma tensorial per a fluxos turbulents en coordenades generalitzades. Es presenten les equacions de continuïtat, les equacions de Navier-Stokes i les equacions de Reynolds, així com les equacions de transport de la vorticitat, de 1'energia cinètica turbulenta i de la velocitat de dissipació de 1'energia turbulenta mitjanes.The transport equation for turbulent flows are deduced in tensorial notation and for a generalized coordinate system. The equations of continuity, Navier-Stokes and Reynolds, as well as the transport equations for mean vorticity , turbulent kinetic energy and dissipation rate are presented