No abstract

In order to estimate reference evapotranspiration (ET 0 ) with the widely accepted FAO-56 PM model especially, in developing countries like India, quality of data and difficulties in gathering all necessary, weather parameters can present serious limitations. Keeping in view, the relevance of precise ET 0 estimation, an attempt has been made to evaluate, decide and select alternative radiation-based methods to get almost at par ET 0 values (from observed climatic data) on the basis of their performance with widely acclaimed FAO-56 PM method as an index for sub-humid Tarai region of Uttarakhand, India. The higher value of Agreement index of ET 0 values obtained with FAO24-Radiation method confirms its appropriateness, whereas, value of ET 0 method/ET 0 FAO-56 PM ratio as 1.00 by Castaneda-Rao method validates its suitability in place of FAO-56 PM at the study area located in the Indian sub-humid region.

In this study, asite-specific radiation based equation for estimating reference evapotranspiration (ETo) was developed and its performance was statistically analysed in comparison to widely accepted FAO Penman-Monteith (FAO-56 PM) model and four radiation-based ETo methods for sub-humid Hazaribagh region of Jharkhand state. The equation was developed with daily values of incoming solar radiation in conjunction with air temperature (minimum and maximum) by considering daily FAO-56 PM ET0 values as index with weather dataset of 15 years (1990-2004). The performance of developed equation validated with eight years (2005-2012) daily weather dataset revealed that it estimated ETo values better than other radiation-based methods. The respective higher and lower values of agreement index and root mean square error with FAO-56 PM ET0 values during validation period confirms efficacy of developed equation whose performance tested at another Indian sub-humid location (Pantnagar) confirmed its suitability as well. Considering the limitations associated with reliability and availability of weather data especially in developing countries, developed equation is recommended as practical one to estimate ETo in sub-humid climatic conditions if FAO-56 PM model cannot be used due to non-availability of required weather parameters at a location.

The rolling element bearing is used in various machinery and produces vibration due to imperfections, surface irregularities during manufacture, damaged bearings, and inaccuracies in the allied element. Also, the rolling element bearing vibration generally shows non-linear dynamic characteristics and is masked with heavy background noise. This noble investigation advances a hybrid technique for removing background noise from the vibration signal and detecting bearing defects. Translation invariant wavelet denoising is the initial stage in this hybrid method for noise removal from the signal. The second phase uses Hierarchical Entropy (HE) for defect feature frequency extraction. Hierarchical entropy at scale four and SampEns of eight hierarchical decomposition nodes was utilized to determine the defect feature vector. In particular, low-frequency components are investigated through multi-scale entropy (MSE), but hierarchical entropy (HE) incorporates low-frequency and high-frequency components and can extract more defective information. Implemented a multi-class support vector machine (SVM) for extracting Hierarchical entropy as feature vectors. These feature vectors are trained by utilizing particle swarm optimization (PSO). To accomplish a prediction model, examine the optimal SVM parameters and then various bearing conditions with the variation of type, size, speed, and load severity identified by SVM. The investigation results show that hierarchical entropy can adequately and more precisely express the features of bearing vibration signals. It is beyond MSE, and the proposed Nobel hybrid Translation invariant wavelet denoising and Hierarchical entropy-based method will effectively remove the noisy background signal. Also, it distinguishes different bearings successfully, indicates the bearing conditions correctly, and is more prominent than those found on MSE.