Application Of Hilbert-Huang Transform Research Articles

The use of transmission line modelling to test the effectiveness of I-kaz as autonomous selection of intrinsic mode function

Pressure transient signal occurred due to sudden changes in fluid propagation filled in pipelines system, which is caused by rapid pressure and flow fluctuation in a system, such as closing and opening valve rapidly. The application of Hilbert-Huang Transform (HHT) as the method to analyse the pressure transient signal utilised in this research. However, this method has the difficulty in selecting the suitable IMF for the further post-processing, which is Hilbert Transform (HT). This paper proposed the implementation of Integrated Kurtosis-based Algorithm for z-filter Technique (I-kaz) to kurtosis ratio (I-kaz-Kurtosis) for that allows automatic selection of intrinsic mode function (IMF) that’s should be used. This work demonstrated the synthetic pressure transient signal generates using transmission line modelling (TLM) in order to test the effectiveness of I-kaz as the autonomous selection of intrinsic mode function (IMF). A straight fluid network was designed using TLM fixing with higher resistance at some point act as a leak and connecting to the pipe feature (junction, pipefitting or blockage). The analysis results using I-kaz-kurtosis ratio revealed that the method can be utilised as an automatic selection of intrinsic mode function (IMF) although the noise level ratio of the signal is lower. I-kaz-kurtosis ratio is recommended and advised to be implemented as automatic selection of intrinsic mode function (IMF) through HHT analysis.

Efficacy of Hilbert-Huang Transform (HHT) in the Analysis of Instantaneous Low Frequency Waves of Magnetosheath

The flow of supersonic plasma is accompanied by a highly thermalized region called the Magnetoshealth found after the bow shock. Enclosed within this region are different wave modes associated with classes of boundaries which have been determined by different methods. The efficacy of Hilbert-Huang transform (HHT) is based on the conditionality of allowing for the local analysis of frequencies, which presents the physical meaning of the original signal at that instant. The observed data have been taken from Cluster II Fluxgate Magnetometer (FGM) instrument that provides advantage for the analysis in three dimensions. The result compares favourably with instantaneous frequencies computed using simple Hilbert transform (SHT) with electric field measurements of Cluster II mission already carried out in literatures. The result of this study has shown that HHT provides the best applicability in the magnetosheath data analysis than the wavelet and Fast Fourier Transform (FFT). The application of HHT based on its advantages over other methods is viewed to be very critical in the analysis of multi-frequency signals where different frequencies could be determined distinctively at a point.

Wind Turbine Gearbox Fault Diagnosis Based on Improved HHT

The randomness of wind power and the nonstationarity of gearbox vibration signals greatly increased the difficulty of wind turbine gearbox faults feature diagnosis. Studies proved that Hilbert-Huang transform (HHT) has a satisfying performance when it be used to analyze nonlinear and non-stationary signals, but two troublesome problems in application of HHT are end effect problem and false intrinsic mode functions (IMFs). An improved solution method based on adaptive waveform matching endpoint extension is proposed to solve end effect problem. Meanwhile, an improved energy conservation method is proposed to eliminate false IMFs. Tests prove that improved HHT can greatly improve the accuracy of wind turbine gearbox faults diagnosis and with a balance efficiency.

Application of Hilbert-Huang Transform in Structural Health Monitoring: A State-of-the-Art Review

This paper reviews the development and application of HHT in the field of SHM in the last two decades. The challenges and future trends in the development of HHT based techniques for the SHM of civil engineering structures are also put forward. It also reviews the basic principle of the HHT method, which contains the extraction of the intrinsic mode function (IMF), mechanism of the EMD, and the features of HT; shows the application of HHT in the system identification, which contains the introduction of theoretical method, the identification of modal parameters, and the system identification on real structures; and discusses the structural damage detection using HHT based approaches, which includes the detection of common damage events, sudden damage events, and cracks and flaws.

An Application of Hilbert-Huang Transform on the Non-Stationary Astronomical Time Series: The Superorbital Modulation of SMC X-1

We present the Hilbert-Huang transform (HHT) analysis on the quasi-periodic modulation of SMC X-1. SMC X-1, consisting of a neutron star and a massive companion, exhibits superorbital modulation with a period varying between ~40 d and ~65 d. We applied the HHT on the light curve observed by the All-Sky Monitor onboard Rossi X-ray Timing Explorer (RXTE) to obtain the instantaneous frequency of the superorbital modulation of SMC X-1. The resultant Hilbert spectrum is consistent with the dynamic power spectrum while it shows more detailed information in both the time and frequency domains. According to the instantaneous frequency, we found a correlation between the superorbital period and the modulation amplitude. Combining the spectral observation made by the Proportional Counter Array onboard RXTE and the superorbital phase derived in the HHT, we performed a superorbital phase-resolved spectral analysis of SMC X-1. An analysis of the spectral parameters versus the orbital phase for different superorbital states revealed that the diversity of <TEX>$n_H$</TEX> has an orbital dependence. Furthermore, we obtained the variation in the eclipse profiles by folding the All Sky Monitor light curve with orbital period for different superorbital states. A dip feature, similar to the pre-eclipse dip of Her X-1, can be observed only in the superorbital ascending and descending states, while the width is anti-correlated with the X-ray flux.

Study of the Application of Hilbert-Huang Transform (HHT) based Filtering For A Dual Triangulate Bluff Body Vortex Flowmeter In Oscillatory Flow

Study of the Application of Hilbert-Huang Transform (HHT) based Filtering For A Dual Triangulate Bluff Body Vortex Flowmeter In Oscillatory Flow

Application of Hilbert-Huang Transform to Inertial Profile Verification: A Laboratory Approach

Abstract Past studies have shown that most inertial profiler verification procedures are conducted through repeated profile measurements on test sections with known profiles. This type of an evaluation can erroneously affect inertial profile results because of non-controllable parameters such as profiler equipment, analytical software, and operator variables. In order to improve the accuracy of inertial profiler certifications, a laboratory simulation method for inertial profilers was developed. This method uses an apparatus that combines sinusoidal vertical displacements of various frequencies and amplitude levels. As a result, errors attributed to operator variables are excluded, and errors induced by a profiler and software are further identified. This study utilizes the Hilbert-Huang transform (HHT) to improve the laboratory verification process by reducing measurement noise and creating a more stable signal in different frequency-amplitude combinations. The noise source is also identified by applying the HHT, which can provide guidance on further profiler verification enhancements.

Application of Hilbert-Huang Transform and SVM to Coal Gangue Interface Detection

In order to detect coal gangue interface on fully mechanized mining face, a new method of vibration signal analysis of coal and gangue based on Hilbert-Huang transform is presented in this paper . At first Empirical mode decomposition algorithm was used to decompose the original vibration signal of coal and gangue into intrinsic modes for further extract meaningful information contained in response signals under complicated environment. By analyzing local Hilbert marginal spectrum and local energy spectrum of the first four intrinsic mode function components, we found the difference of coal and gangue at specific frequency interval that the amplitude and energy mainly distributed at frequency interval between 100Hz and 600Hz when coal fell down, while the amplitude and energy were more concentrated at 1000Hz or so when gangue fell down. Furthermore, the further analysis result from marginal spectrum of each intrinsic mode function component agreed well with the conclusion above . Combined with time-domain parameters , we defined the energy function based on the above feature as inputs of support vector machine for simulation experiment. The results show that the extracted features with the proposed approach can be served as coal gangue interface recognition.

Application of Hilbert-Huang Transform to Predict Grinding Surface Quality On-Line

Predicting the precision of grinding process, especially correlating surface functionality generation to grinding conditions, would be of great significance to improve grinding accuracy of the end precision product. Huang developed a very promising revolutionary spectral data analysis technique based on the Hilbert transform. The concrete methods of the EMD, the local Hilbert spectrum are introduced. An artificial neural network (ANN) based on back propagation is developed to predict surface roughness Ra. An accelerometer is employed as in-process surface recognition sensor during grinding process to collect the vibration as input neurons. Changing the grinding condition, training and testing within the artificial neural networks to retrieve the weightings, the experimental results show that the proposed ANN surface recognition model is economical, efficient and the model has a high accuracy rate for predicting surface roughness.