TIME DOMAIN DATA ANALYSIS AND WAVELET TRANSFORM PIPES THAT EXPERIENCE BLOCKING AND LEAKAGE

Abstract

In this study, a method was developed to detect damage to pipes using sound signals. The detection of damage to the pipe is done by using a signal sounds and four microphones. Methods of signal noise is a smart structural health monitoring that can detect damage at the cost of the more inexpensive. Excitation the sound is given by using a loudspeaker and the response signal noise is sampled using four microphones that are connected to the PC- Oscilloscope which serves to convert the signal analog results of recording sound into a signal of digital form of the value of domains of time and then use a Continuous Wavelet Transform (CWT) to determine the location of the damage that occurs in the pipe sheath. To detect the location of pipe damage in various positions of damage, it can be searched by comparing the wavelet coefficient of the four microphones. Damages are awarded in the form of plug and leaked to the distance and position of polar vary. From the experimental results obtained with the leakage conditions at a distance of 0.7 meters with a direction of 90 °, the highest wavelet coefficient occurs at microphone 2 at 0.02534 and leakage at a distance of 1.2 meters with the 90 ° direction , the highest wavelet coefficient occurs at microphone 2 of 0.05038 according to the location of the damage that occurs at an angle of 90 ° and for blockages at a distance of 1 meter, the highest wavelet coefficient occurs at microphone 4 at 0.200 and a blockage at a distance of 1.4 meters, the highest wavelet coefficient occurs at microphone 4 at 0.176 in accordance with the form of blockage that is given is the base pipe .