Structural Health Monitoring Using the Hilbert-Huang Transform and Beating
نویسندگان
چکیده
In this paper, a combined approach to damage diagnosis of systems is proposed. The intention is to identify the natural frequencies and the presence of damage. In a first step, the basic concept of the Hilbert Huang Transform is presented where the empirical mode decomposition is applied on the signal using a sifting process to obtain intrinsic mode functions exhibiting monocomponent behavior. In the next step, the Hilbert Transform is used to identify the frequencies from the well behaved intrinsic mode functions. Finally, a time domain approach known as beating phenomenon is used to calculate the shift in frequencies and also the presence of damage. Simulations are done on linear and nonlinear structures. Results demonstrate that the proposed methods provide a new and useful tool for damage detection and evaluation of structures especially when the frequency shift is minimal.
منابع مشابه
Nonlinear and Non-stationary Vibration Analysis for Mechanical Fault Detection by Using EMD-FFT Method
The Hilbert-Huang transform (HHT) is a powerful method for nonlinear and non-stationary vibrations analysis. This approach consists of two basic parts of empirical mode decomposition (EMD) and Hilbert spectral analysis (HSA). To achieve the reliable results, Bedrosian and Nuttall theorems should be satisfied. Otherwise, the phase and amplitude functions are mixed together and consequently, the ...
متن کاملHilbert-Huang Transform-Based Vibration Signal Analysis for Machine Health Monitoring
This paper presents a signal analysis technique for machine health monitoring based on the Hilbert-Huang Transform (HHT). The HHT represents a time-dependent series in a two-dimensional (2-D) time-frequency domain by extracting instantaneous frequency components within the signal through an Empirical Mode Decomposition (EMD) process. The analytical background of the HHT is introduced, based on ...
متن کاملA technique to improve the empirical mode decomposition in the Hilbert-Huang transform
The Hilbert-based time-frequency analysis has promising capacity to reveal the time-variant behaviors of a system. To admit well-behaved Hilbert transforms, component decomposition of signals must be performed beforehand. This was first systematically implemented by the empirical mode decomposition (EMD) in the Hilbert-Huang transform, which can provide a time-frequency representation of the si...
متن کاملA Time-Frequency approach for EEG signal segmentation
The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...
متن کاملWireless Structural Monitoring of a Multi-span Footbridge with Decentralised Embedded Data Processing
A pedestrian footbridge in Singapore was monitored for two weeks with a network of eight wireless accelerometer sensor nodes (Imote2). The nodes acquired 10 minutes of vibration data in the vertical direction every half an hour, processed the data using a novel embedded data processing algorithm and transmitted only the required results to the on-site base station. The base station then transfe...
متن کامل