In this study, vibration based non-destructive testing (NDT) technique is adopted for assessing the condition of in-service timber pole. Timber a natural material, and hence captured broadband signal (induced from impact using modal hammer) greatly affected by uncertainty on wood properties, structure, environment. Therefore, advanced processing essential in order to extract features associated...


 In many studies, Google Trends Data is efficient to analyze and estimate as explanatory variables, including tourism predictions. However, data retrieval are always plagued by noise. Without noise processing, the predictive ability of search engine may be weak, even invalid. As a processing method, Hilbert-Huang Transform (HHT) can reduce or clean Forecasting art science predicting futur...

Abstract-This paper presents the various methods for the spectral analysis of signals for the stationary as well as non-stationary signals. Due to non-stationary characteristics of the signals, it has been always a challenge to achieve time frequency distribution of such signals. Between the various techniques of signal analysis, this paper uses Fourier transform, Short time Fourier transform, ...

A novel approach to fault detection and diagnosis of gearbox based on Ensemble Empirical Mode Decomposition (EEMD) and Teager Kaiser Energy Operator (TKEO) technique is presented. The time-domain vibration signal of the gearbox with gear crack fault is measured. EEMD can adaptively decompose the vibration signal into a series of zero mean Amplitude Modulation-Frequency Modulation (AM-FM) Intrin...

Speech emotion recognition is an important issue in the development of human-computer interactions. In this paper a series of novel robust features for speech emotion recognition is proposed. Those features, which derived from the Hilbert-Huang transform (HHT) and Teager energy operator (TEO), have the characteristics of multi-resolution, self-adaptability and high precision of distinguish abil...

Image empirical mode decomposition (IEMD) is an empirical mode decomposition concept used in Hilbert–Huang transform (HHT) expanded into two dimensions for the use on images. IEMD provides a tool for image processing by its special ability to locally separate superposed spatial frequencies. The tendency is that the intrinsic mode functions (IMFs) other than the first are low-frequency images. I...

Through numerical simulations, it is predicted that the gravitational waves (GWs) reflect characteristics of core-collapse supernova (CCSN) explosion mechanism. There are multiple GW excitation processes occur inside a star before its explosion, and suggested GWs originating from CCSN have mode for each process in terms time-frequency representation. Therefore, we propose an application Hilbert...

-Support Vector Machines (SVMs) map inputs vectors nonlinearly into a high dimensional feature space and construct the optimum separating hyperplane in space to realize signal classification. Automatic classification of digital modulation signals plays an important role in communication applications such as an intelligent demodulator, interference identification and monitoring, so many investig...

Effective fault diagnosis for cascaded H-bridge multilevel inverter (CHMLI) can reduce failure rate and prevent the unscheduled shutdown. Nevertheless, traditional signal-based feature extraction selection methods show poor distinguishability insufficient features in a one-dimensional space. The shallow learning models are prone to fall into local extremum, slow convergence speed overfitting. T...

The broad diffusion of renewable energy-based technologies has introduced several open issues in the design and operation of smart grids (SGs) when distributed generators (DGs) inject a large amount of power into the grid. In this paper, a theoretical investigation on active and reactive power data is performed for one active line characterized by several photovoltaic (PV) plants with a great a...