Modal Extraction for Wind Turbines using Moving Window Subspace Identification

This paper proposes a method for wind turbine mode identification using the multivariable output error statespace (MOESP) identification algorithm. The paper incorporates a fast moving window QR decomposition and propagator method from array signal processing, yielding a moving window subspace identification algorithm. The algorithm assumes that the system order is known as a priori and remains constant during identification. For the purpose of extracting modal information for turbines modelled as a linear parameter varying (LPV) system, the algorithm is applicable since a nonlinear system can be approximated as a piecewise time invariant system in consecutive data windows. The algorithm is exemplified using numerical simulations which show that the moving window algorithm can track the modal information. The paper also demonstrates that the low computational burden of the algorithm, compared to conventional batch subspace identification, has significant implications for online implementation.

Process monitoring approach using fast moving window PCA

This paper introduces a fast algorithm for moving window principal component analysis (MWPCA) which will adapt a principal component model. This incorporates the concept of recursive adaptation within a moving window to (i) adapt the mean and variance of the process variables, (ii) adapt the correlation matrix, and (iii) adjust the PCA model by recomputing the decomposition. This paper shows that the new algorithm is computationally faster than conventional moving window techniques, if the window size exceeds 3 times the number of variables, and is not affected by the window size. A further contribution is the introduction of an N-step-ahead horizon into the process monitoring. This implies that the PCA model, identified N-steps earlier, is used to analyze the current observation. For monitoring complex chemical systems, this work shows that the use of the horizon improves the ability to detect slowly developing drifts.

Extended electrochemical windows made accessible by room temperature ionic liquid/organic solvent electrolyte systems

The electrochemical windows of acetonitrile solutions doped with 0.1 m concentrations of several ionic liquids were examined by cyclic voltammetry at gold and platinum microelectrodes. These results were compared with those observed in the commonly used 0.1 m tetrabutylammonium perchlorate/acetonitrile system as well as with neat ionic liquids. The use of a trifluorotris(pentofluoroethyl)phosphate-based ionic liquid, specifically, as supporting electrolyte in acetonitrile solutions affords a wider anodic window, which is attributed to the high stability of the anionic component of these intrinsically conductive and thermally robust compounds.