Automatic correcting method of discrete spectrum with rectangular window

Abstract

In order to meet the requirements of online condition monitoring and automatic fault diagnosis of plants, the leakage errors of spectra in discrete spectrum analysis are corrected automatically. Aiming at the leakage errors in spectra of signals windowed by rectangular window, a automatic correcting method of leakage errors is presented based on the extremum searching method(ESM) and the energy centrobaric correction method(ECCM). The steps of the method are: firstly, compute the Discrete Fourier Transform (DFT) of the signal by Fast Fourier Transform (FFT) method and get the amplitude spectrum of it; secondly, find the all points needed to be corrected by the extremum searching method; thirdly, correct the frequencies, amplitudes and phases of the corresponding points by energy centrobaric correction method; finally, get the corrected signal by Inverse Fast Fourier Transform (IFFT) method. The simulation results certify that the leakage errors of spectra after being corrected can be controlled within 3% when the minimal difference in neighbouring frequency components is greater than 10 times of the frequency resolution. This correcting method can meet the requirements of engineering practice.

Damage identification in beams using additional rove mass and wavelet transform

“…After obtaining these 26 and 31 acceleration spectra x ̈ (t) for Case-1 and Case-2, respectively (corresponding to different positions of the added masses on the nodes defined in the discretization) a technique of Time Signaling was applied to each of the positioning of the added mass. This simple technique can improve signal characteristics and reduce effects such as the inherent noise of electronic equipment or the spectral leakage effect [12]. There are several types of window functions that can be applied depending on the signal.…”

“…Techniques based on Wavelet Transforms can overcome this limitation. Such techniques have been applied over the years and have been presented satisfactory results [6,7,8,9,10,11,12]. However, the purpose of this paper is to use additional masses associated with wavelet transform in the processing of non-stationary signals and apply this methodology in experimental done in commercial profiles of steel beams under support conditions close to real situations.…”