Vibration analysis of motors using Gabor expansion

Date of Publication


Document Type

Master's Thesis

Degree Name

Master of Science in Electronics and Communications Engineering


Gokongwei College of Engineering


Electronics And Communications Engg

Thesis Adviser

Felicito S. Caluyo

Defense Panel Chair

Jose Antonio Catalan

Defense Panel Member

Edwin Sybingco
Antonio Gonzales


Gabor expansion is applied to determine the severity of vibration of motors. An algorithm was developed to make classification of vibration severity possible. Codes were written in Matlab and Visual C++ to obtain the Gabor spectogram of different vibration signatures and to determine the energy of each. Data from National Power Corporation were used and analyzed to determine the severity of machine vibration using the signal energy as parameter. Results showed that as the energy of vibration signal increases, machine vibration severity also increases. The effect of varying the size of Gaussian window in the Gabor spectrogram was examined by simulating the vibration data of different values of Gauss variance. Within certain limits, varying the size of the Gaussian window did not have any marked effect on the value of energy. The effect of the sample size used to represent vibration signature for a particular time of measurement was examined and results showed that decreasing the sample size just results in the corresponding decrease in energy value and does not affect vibration severity classification. From the vibration data, severity mapping table was established based on the quadratic polynomial model determined from the energy and vibration severity relation. The effect of noise introduction into the vibration data was considered and results revealed that vibration energy is generally increased for an added random noise. However this change in energy did not shift the corresponding vibration severity. Specifications of hardware components for data acquisition system are recommended for accurate vibration data measurements.

Abstract Format






Accession Number


Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

114 numb. leaves ; 28 cm.


Vibration--Measurements; Machinery--Vibration; Algorithms

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