Adaptive Signal Processing Strategy for a Wind Farm System Fault Accommodation

In order to improve the availability of offshore wind farms, thus avoiding unplanned operation and maintenance costs, which can be high for offshore installations, the accommodation of faults in their earlier occurrence is fundamental. This paper addresses the design of an active fault tolerant control scheme that is applied to a wind park benchmark of nine wind turbines, based on their nonlinear models, as well as the wind and interactions between the wind turbines in the wind farm. Note that, due to the structure of the system and its control strategy, it can be considered as a fault tolerant cooperative control problem of an autonomous plant. The controller accommodation scheme provides the on-line estimate of the fault signals generated by nonlinear filters exploiting the nonlinear geometric approach to obtain estimates decoupled from both model uncertainty and the interactions among the turbines. This paper proposes also a data-driven approach to provide these disturbance terms in analytical forms, which are subsequently used for designing the nonlinear filters for fault estimation. This feature of the work, followed by the simpler solution relying on a data-driven approach, can represent the key point when on-line implementations are considered for a viable application of the proposed scheme

Robust statistics for deterministic and stochastic gravitational waves in non-Gaussian noise I: Frequentist analyses

Gravitational wave detectors will need optimal signal-processing algorithms to extract weak signals from the detector noise. Most algorithms designed to date are based on the unrealistic assumption that the detector noise may be modeled as a stationary Gaussian process. However most experiments exhibit a non-Gaussian ``tail'' in the probability distribution. This ``excess'' of large signals can be a troublesome source of false alarms. This article derives an optimal (in the Neyman-Pearson sense, for weak signals) signal processing strategy when the detector noise is non-Gaussian and exhibits tail terms. This strategy is robust, meaning that it is close to optimal for Gaussian noise but far less sensitive than conventional methods to the excess large events that form the tail of the distribution. The method is analyzed for two different signal analysis problems: (i) a known waveform (e.g., a binary inspiral chirp) and (ii) a stochastic background, which requires a multi-detector signal processing algorithm. The methods should be easy to implement: they amount to truncation or clipping of sample values which lie in the outlier part of the probability distribution.Comment: RevTeX 4, 17 pages, 8 figures, typos corrected from first version

Mitigation of Pulsed Interference to Redshifted HI and OH Observations between 960 and 1215 MHz

The neutral hydrogen 21-cm spectral line (1420.4 MHz) and the four 18-cm lines of the hydroxyl molecule (1612-1720 MHz) are observable at redshifts which put their measured line frequencies well below their protected frequency bands. Part of the redshift ranges (z = 0.171-0.477 for HI and z = 0.37-0.73 for OH) fall in the 960 to 1215 MHz band that is allocated to aircraft navigation. Most of the signals in this band are pulsed emissions of low duty cycle so much of the time between pulses is interference free. This paper outlines the structure and measured properties of signals in this band and demonstrates a signal processing strategy that is effective at removing the pulsed signals from spectra at sensitivities produced by several hours of integration.Comment: Astronomical Journal, May 2005, in pres

Ultimate decoherence border for matter-wave interferometry

Stochastic backgrounds of gravitational waves are intrinsic fluctuations of spacetime which lead to an unavoidable decoherence mechanism. This mechanism manifests itself as a degradation of the contrast of quantum interferences. It defines an ultimate decoherence border for matter-wave interferometry using larger and larger molecules. We give a quantitative characterization of this border in terms of figures involving the gravitational environment as well as the sensitivity of the interferometer to gravitational waves. The known level of gravitational noise determines the maximal size of the molecular probe for which interferences may remain observable. We discuss the relevance of this result in the context of ongoing progresses towards more and more sensitive matter-wave interferometry.Comment: 4 page

Linking HRM and innovation: formulating the research agenda

The aim of this paper is to explore the extent to which innovation and HRM are interdependent; how effective human resource management can enhance innovation capabilities within the organisation and how innovation culture may drive a need to reshape HRM systems. Its key aim is to investigate the depth and breadth of extant research which analyses the relationships between systems of human resource management and capacity for innovation. With few exceptions, HRM and innovation have emerged as quite separate fields of research and our aim is to draw these closer together. This paper builds a number of research questions from the growing literature and relatively few research findings in this area, to form the basis of future research

Detecting a stochastic background of gravitational radiation: Signal processing strategies and sensitivities

We analyze the signal processing required for the optimal detection of a stochastic background of gravitational radiation using laser interferometric detectors. Starting with basic assumptions about the statistical properties of a stochastic gravity-wave background, we derive expressions for the optimal filter function and signal-to-noise ratio for the cross-correlation of the outputs of two gravity-wave detectors. Sensitivity levels required for detection are then calculated. Issues related to: (i) calculating the signal-to-noise ratio for arbitrarily large stochastic backgrounds, (ii) performing the data analysis in the presence of nonstationary detector noise, (iii) combining data from multiple detector pairs to increase the sensitivity of a stochastic background search, (iv) correlating the outputs of 4 or more detectors, and (v) allowing for the possibility of correlated noise in the outputs of two detectors are discussed. We briefly describe a computer simulation which mimics the generation and detection of a simulated stochastic gravity-wave signal in the presence of simulated detector noise. Numerous graphs and tables of numerical data for the five major interferometers (LIGO-WA, LIGO-LA, VIRGO, GEO-600, and TAMA-300) are also given. The treatment given in this paper should be accessible to both theorists involved in data analysis and experimentalists involved in detector design and data acquisition.Comment: 81 pages, 30 postscript figures, REVTE