Design of a Time-Frequency Distribution for Vibration Monitoring under Corrosions in the Pipe

2006 ◽  
Vol 321-323 ◽  
pp. 1257-1261
Author(s):  
Gi Young Park ◽  
C.K. Lee ◽  
Jung Taek Kim ◽  
K.C. Kwon ◽  
Sang J. Lee

To monitor the wear and degradation on a pipe by corrosion during a plant operation, the vibration signals were measured by an accelerometer and analyzed by several analysis techniques. From the conventional methods, it was difficult to identify the wear and degradation on the pipe. And hence, the time-frequency distribution (TFD) and the adaptive cone-kernel distribution (ACKD) devised for reducing the interfering cross-terms are applied to the acquired data. They can provide the distinguishing peak patterns between the normal and corrosion signals.

2013 ◽  
Vol 631-632 ◽  
pp. 1373-1378
Author(s):  
Xiu Li Du ◽  
Ming Ying Liu

To resolve the problem of Gabor transform window width and order selection for Time-Frequency Distribution Series (TFDS), a parameters selection method for TFDS based on normalized entropy has been proposed, especially the adaptive selection method of order. The normalized entropy is used to measure the concentration and cross-terms of TFDS firstly, and then the relation between the order and width of Gabor transform window function and the concentration and cross-terms of TFDS is used to realize adaptive selection of window width and order parameter, which overcomes the subjective selection problem of the order. The simulation results show that the proposed method can effectively select optimal TFDS parameters for simulated and experimental ultrasonic tesing signal, and can get TFDS with good concentration and high resolution.


1999 ◽  
Vol 121 (3) ◽  
pp. 328-333 ◽  
Author(s):  
G. T. Zheng ◽  
P. D. McFadden

Bilinear time-frequency distributions, which provide simultaneous high resolution in both time and frequency domains, offer advantages for the analysis of vibration signals where the harmonic components and sidebands may be closely spaced. However, the Choi-Williams exponential distribution is found to be unsuitable, and aliasing produced by distributions of the Cohen class also causes problems. An aliasfree exponential time-frequency distribution is introduced, which combines features of distributions of the Cohen class and the generalized Wigner distribution. The new distribution is shown to be well suited to the analysis of signals with transient components.


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