Correlation of structure-borne sound signal and internal piping surface condition using Integrated Kurtosis-based Algorithm for Z-notch filter (I-KAZ) technique

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The purpose of this paper is to study the correlation between structure-borne sound signal and internal pipe surface using a novel statistical analysis called I-kaz. Experiment has been done on a laboratory scale piping system which consists of two different types of internal piping surface i.e. smooth and rough. A structure-borne sound transducer was positioned at the outer surface of the pipe while measuring signal on the piping system. The frequency range of the measured signal was within 20 Hz to 20 kHz, which is classified as audible sound. The data acquisition process was duplicated for three times at different piping operating pressure of 140 kPa, 150 kPa and 160 kPa. Analysis of the measured signal was then being done using spectrum analysis i.e. Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT). The results clearly illustrate that the frequency components of the signal measured on the smooth pipe are comparatively more than the rough pipe. Besides, the dominant frequency for the smooth pipe demonstrates higher magnitude value compared to the rough pipe. In addition, a novel statistical analysis called Integrated Kurtosis-based Algorithm for Z-notch Filter (I-kaz) has been utilised in this study. As a result, the value of I-kaz coefficient for the rough internal pipe surface was relatively smaller than the smooth surface. The outcome of this study shows an excellent correlation between the structure-borne signal and the internal piping surface condition. In conclusion, the combination of structure-borne sound and the I-kaz analysis has a great deal to predict the internal piping surface condition.

Original languageEnglish
Title of host publication16th International Congress on Sound and Vibration 2009, ICSV 2009
Pages1502-1509
Number of pages8
Volume3
Publication statusPublished - 2009
Event16th International Congress on Sound and Vibration 2009, ICSV 2009 - Krakow
Duration: 5 Jul 20099 Jul 2009

Other

Other16th International Congress on Sound and Vibration 2009, ICSV 2009
CityKrakow
Period5/7/099/7/09

Fingerprint

kurtosis
notches
filters
acoustics
statistical analysis
sound transducers
data acquisition
spectrum analysis
frequency ranges
coefficients

ASJC Scopus subject areas

  • Acoustics and Ultrasonics

Cite this

Correlation of structure-borne sound signal and internal piping surface condition using Integrated Kurtosis-based Algorithm for Z-notch filter (I-KAZ) technique. / Nuawi, Mohd. Zaki; Abdullah, Shahrum; Lamin, F.; Ismail, A. R.; Mohd Nor, Mohd. Jailani.

16th International Congress on Sound and Vibration 2009, ICSV 2009. Vol. 3 2009. p. 1502-1509.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nuawi, MZ, Abdullah, S, Lamin, F, Ismail, AR & Mohd Nor, MJ 2009, Correlation of structure-borne sound signal and internal piping surface condition using Integrated Kurtosis-based Algorithm for Z-notch filter (I-KAZ) technique. in 16th International Congress on Sound and Vibration 2009, ICSV 2009. vol. 3, pp. 1502-1509, 16th International Congress on Sound and Vibration 2009, ICSV 2009, Krakow, 5/7/09.
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abstract = "The purpose of this paper is to study the correlation between structure-borne sound signal and internal pipe surface using a novel statistical analysis called I-kaz. Experiment has been done on a laboratory scale piping system which consists of two different types of internal piping surface i.e. smooth and rough. A structure-borne sound transducer was positioned at the outer surface of the pipe while measuring signal on the piping system. The frequency range of the measured signal was within 20 Hz to 20 kHz, which is classified as audible sound. The data acquisition process was duplicated for three times at different piping operating pressure of 140 kPa, 150 kPa and 160 kPa. Analysis of the measured signal was then being done using spectrum analysis i.e. Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT). The results clearly illustrate that the frequency components of the signal measured on the smooth pipe are comparatively more than the rough pipe. Besides, the dominant frequency for the smooth pipe demonstrates higher magnitude value compared to the rough pipe. In addition, a novel statistical analysis called Integrated Kurtosis-based Algorithm for Z-notch Filter (I-kaz) has been utilised in this study. As a result, the value of I-kaz coefficient for the rough internal pipe surface was relatively smaller than the smooth surface. The outcome of this study shows an excellent correlation between the structure-borne signal and the internal piping surface condition. In conclusion, the combination of structure-borne sound and the I-kaz analysis has a great deal to predict the internal piping surface condition.",
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AB - The purpose of this paper is to study the correlation between structure-borne sound signal and internal pipe surface using a novel statistical analysis called I-kaz. Experiment has been done on a laboratory scale piping system which consists of two different types of internal piping surface i.e. smooth and rough. A structure-borne sound transducer was positioned at the outer surface of the pipe while measuring signal on the piping system. The frequency range of the measured signal was within 20 Hz to 20 kHz, which is classified as audible sound. The data acquisition process was duplicated for three times at different piping operating pressure of 140 kPa, 150 kPa and 160 kPa. Analysis of the measured signal was then being done using spectrum analysis i.e. Fast Fourier Transform (FFT) and Short Time Fourier Transform (STFT). The results clearly illustrate that the frequency components of the signal measured on the smooth pipe are comparatively more than the rough pipe. Besides, the dominant frequency for the smooth pipe demonstrates higher magnitude value compared to the rough pipe. In addition, a novel statistical analysis called Integrated Kurtosis-based Algorithm for Z-notch Filter (I-kaz) has been utilised in this study. As a result, the value of I-kaz coefficient for the rough internal pipe surface was relatively smaller than the smooth surface. The outcome of this study shows an excellent correlation between the structure-borne signal and the internal piping surface condition. In conclusion, the combination of structure-borne sound and the I-kaz analysis has a great deal to predict the internal piping surface condition.

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