In-service turbine monitoring is essential for maximizing the wind energy contribution to the global energy budget. Measurement of turbine shaft torque under transient wind conditions is fundamental to develop reliable condition monitoring techniques. Contact based measurements bring their own disadvantages and non-contactless measurements have many potential advantages. However, their performance needs to be validated against standard methods. This paper focuses on the development of an enhanced transient Feature Selective Validation (FSV) techniques to undertake this analysis with an emphasis on transient data processing. The nature of FSV makes it a natural technique to consider for this problem space. Open questions have existed as to how transients should be dealt with in FSV. This paper overcomes the limitations of previous approaches for step-function transient comparison and presents analytical methods to ensure the transient feature itself is considered, irrespective of how much pre- and post- transient data happens to be included.

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Diverse solar irradiance spectra can be observed under different conditions of time, date, location, weather, etc. Since the solar irradiance spectrum is required by certain scientific and engineering applications, obtaining accurate spectral data is essential. Measurements by spectrophotometers are able to achieve accurate real-time data with high resolution, but at high expense. While in some engineering applications, the requirements on accuracy and resolution are much lower than that in a typical scientific research. Therefore, a rapid method of estimating the solar spectrum is proposed based on an available spectral model in this paper. In order to achieve fast estimation, we simplify the input parameters of this model into five key inputs, including latitude and longitude, altitude, date and time, sky and ground type. The first three parameters are easy to obtain from GPS and the internet. Sky and ground types include common types of sky and ground, which can be input manually or processed automatically by analyzing a digital image of target sky or ground. The automatic input is realized through dominant color extraction or by training an artificial neural network. Results show that the proposed rapid method can generate different spectral power distributions based on distinct input conditions. Two device frameworks are also proposed to implement the rapid method, which is applicable to many fields. LED lighting is one of the most prominent applications. Users can easily share local sunlight with each other through an APP in mobile phones@en