Crack identification using piezoelectric testing on carbon steel pipe for transverse, longitudinal and hole defects with low excitation frequency
-
2018-04-06 https://doi.org/10.14419/ijet.v7i2.14.12819 -
Piezoelectric, Non-Destructed Testing, Defect, Amplitude, Ac Excitation. -
Abstract
AC excitation signal is most widely used in Non Destructed Testing (NDT) devices for Piezoelectric Technique (PZT) method in an inspec-tion. This paper is presenting the application of piezoelectric with end to end method for defect identification for Carbon Steel Pipe (CSP) where the frequency is used around 1kHz until 6kHz for standard pipe, transverse defect pipe, longitudinal defect pipe and hole defect pipe. From here, the identification of defect signal by based on the signal pick value and different pick signal between ordinary pipe (without defect) and defects pipe are analysis. The result shows that the standard pipe will give the high amplitude of signal compare the defect pipe by based on the type of defect, size of defect and depth of defect. Findings from the comparative study, validate the application of piezoelec-tric show that the different amplitude of the signal is directly proportional with excitation signal frequency and through the experiment, the longitudinal defect is contributed the different high signal until 79.7% compared to the hole and transverse defect 74.4 %.
-
References
[1] Ali KB, Abdalla AN, Rifai D & Faraj MA (2017), Review on system development in Eddy current testing and technique for defect classification and characterization. IET Circuits, Devices and Systems 11, 330–343.
[2] Paw JK, Ali K, Hen CK, Abdallah AN, Ding TJ, Ahlam NA & Eirfan N (2018), Encircling probe with multi-excitation frequency signal for depth crack defect in eddy current testing. Journal of Fundamental and Applied Sciences 10, 949–964.
[3] Rao J, Ratassepp M, Lisevych D, Hamzah Caffoor M & Fan Z (2017), On-line corrosion monitoring of plate structures based on guided wave tomography using piezoelectric sensors. Sensors 17, 1–14.
[4] Rifai D, Abdalla AN, Ali K & Razali R (2016), Giant magnetoresistance sensors: A review on structures and non-destructive eddy current testing applications. Sensors 16, 1–30.
[5] Prassianakis IN & Prassianakis NI (2004), Ultrasonic testing of non-metallic materials: Concrete and marble. Theoretical and Applied Fracture Mechanics 42, 191–198.
[6] Chen L, He F & Sammut K (2007), Active vibration clamping absorber design. Proceedings of the 14th International Congress on Sound and Vibration.
[7] Faraj MA, Abdalla AN, Samsuri FB, Rifai D & Ali K (2017), Investigate of the effect of width defect on eddy current testing signals under different materials. Indian Journal of Science and Technology 10, 1–5.
[8] Elwalwal HM, Mahzan SB & Abdalla AN (2017), Crack inspection using guided waves (GWs)/structural health monitoring (SHM). Journal of Applied Sciences 17, 415–428.
[9] Drinkwater BW & Wilcox PD (2006), Ultrasonic arrays for non-destructive evaluation: A review. NDT and E International 39, 525–541.
[10] Mian A, Han X, Islam S & Newaz G (2004), Fatigue damage detection in graphite/epoxy composites using sonic infrared imaging technique. Composites Science and Technology 64, 657–666.
[11] Liu Y, Hu N, Xu H, Yuan W, Yan C, Li Y, Goda R, Qiu J, Ning H & Wu L (2014), Damage evaluation based on a wave energy flow map using multiple PZT sensors. Sensors 14, 1902–1917.
[12] Liu Y, Goda R, Samata K, Kanda A, Hu N, Zhang J, Ning H & Wu L (2014), An efficient algorithm embedded in an ultrasonic visualization technique for damage inspection using the AE sensor excitation method. Sensors 14, 20439–20450.
[13] Si L, Wang Q. Rapid multi-damage identification for health monitoring of laminated composites using piezoelectric wafer sensor arrays. Sensors 16, 1–12.
[14] Rifai D, Abdalla AN, Khamsah N, Aizat M & Fadzli M (2016), Subsurface defects evaluation using eddy current testing. Indian Journal of Science and Technology 9, 1–7.
[15] Faraj MA, Samsuri F, Abdalla AN, Rifai D & Ali K (2017), Adaptive neuro-fuzzy inference system model based on the width and depth of the defect in an Eddy current signal. Applied Sciences 7, 1–12.
[16] Ihn JB & Chang FK (2008), Pitch-catch active sensing methods in structural health monitoring for aircraft structures. Structural Health Monitoring 7, 5–19.
[17] Yu L & Giurgiutiu V (2007), In-situ optimized PWAS phased arrays for Lamb wave structural health monitoring. Journal of Mechanics of Materials and Structures 2, 459–487.
[18] Zhu R, Huang GL & Yuan FG (2013), Fast damage imaging using the time-reversal technique in the frequency-wavenumber domain. Smart Materials and Structures 22, 1–12.
[19] Qiu L, Liu M, Qing X & Yuan S (2013), a quantitative multidamage monitoring method for large-scale complex composite. Structural Health Monitoring 12, 183–196.
[20] Qiu L, Yuan S, Chang FK, Bao Q & Mei H (2014), On-line updating Gaussian mixture model for aircraft wing spar damage evaluation under time-varying boundary condition. Smart Materials and Structures 23, 1–16.
[21] Liu Y & Chattopadhyay A (2013), Low-velocity impact damage monitoring of a sandwich composite wing. Journal of Intelligent Material Systems and Structures 24, 2074–2083.
[22] Liu Y, Fard MY, Chattopadhyay a & Doyle D (2012), Damage assessment of CFRP composites using a time-frequency approach. Journal of Intelligent Material Systems and Structures 23, 397–413.
[23] Bro R & Smilde AK (2014), Principal component analysis. Analytical Methods 6, 2812–2831.
[24] Anaya M, Tibaduiza DA & Pozo F (2015), A bioinspired methodology based on an artificial immune system for damage detection in structural health monitoring. Shock and Vibration 2015, 1–15.
[25] Burgos DT (2012), Design and validation of a structural health monitoring system for aeronautical structures. PhD thesis, Barcelona: Technical University of Catalonia.
[26] Jeong DH, Ziemkiewicz C, Fisher B, Ribarsky W & Chang R (2009), iPCA: An interactive system for PCA-based visual analytics. Computer Graphics Forum, 28, 767–774.
-
Downloads
-
How to Cite
N. Abdalla, A., Ali, K., Koh Siaw Paw, J., Kok Hen, C., Jian Ding, T., Sham Maizal, M., & Izzat, M. (2018). Crack identification using piezoelectric testing on carbon steel pipe for transverse, longitudinal and hole defects with low excitation frequency. International Journal of Engineering & Technology, 7(2.14), 171-176. https://doi.org/10.14419/ijet.v7i2.14.12819Received date: 2018-05-14
Accepted date: 2018-05-14
Published date: 2018-04-06