Pattern recognition by wavelet transforms using macro fibre composites transducers

Abstract This paper presents a novel pattern recognition approach for a non-destructive test based on macro fibre composite transducers applied in pipes. A fault detection and diagnosis (FDD) method is employed to extract relevant information from ultrasound signals by wavelet decomposition technique. The wavelet transform is a powerful tool that reveals particular characteristics as trends or breakdown points. The FDD developed for the case study provides information about the temperatures on the surfaces of the pipe, leading to monitor faults associated with cracks, leaks or corrosion. This issue may not be noticeable when temperatures are not subject to sudden changes, but it can cause structural problems in the medium and long-term. Furthermore, the case study is completed by a statistical method based on the coefficient of determination. The main purpose will be to predict future behaviours in order to set alarm levels as a part of a structural health monitoring system.

[1]  Yucai Dong,et al.  Application of Wavelet Transform in MCG-signal Denoising , 2010 .

[2]  Marc Edwards,et al.  The Importance of Temperature in Assessing Iron Pipe Corrosion in Water Distribution Systems , 2002, Environmental monitoring and assessment.

[3]  Zwe-Lee Gaing,et al.  Wavelet-based neural network for power disturbance recognition and classification , 2004, IEEE Transactions on Power Delivery.

[4]  R. Naslain,et al.  The design of the fibre-matrix interfacial zone in ceramic matrix composites , 1998 .

[5]  A. Deraemaeker,et al.  Numerical evaluation of the equivalent properties of Macro Fiber Composite (MFC) transducers using periodic homogenization , 2010 .

[6]  Malcolm K. Lim,et al.  Combining multiple NDT methods to improve testing effectiveness , 2013 .

[7]  Sheng-Huoo Ni,et al.  Buried pipe detection by ground penetrating radar using the discrete wavelet transform , 2010 .

[8]  Zhengjia He,et al.  Pipe crack identification based on finite element method of second generation wavelets , 2010 .

[9]  Xidong Tang,et al.  Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application , 2007, Autom..

[10]  K. Kannan,et al.  Haar wavelet method for solving FitzHugh-Nagumo equation , 2012 .

[11]  M. Aktas,et al.  Wavelet-based switching faults detection in direct torque control induction motor drives , 2010 .

[12]  Rhys Pullin,et al.  Use of Macro Fibre Composite Transducers as Acoustic Emission Sensors , 2009, Remote. Sens..

[13]  Jae Sung Park,et al.  A study on failure characteristic of spherical pressure vessel , 2005 .

[14]  Seung-Bok Choi,et al.  Vibration control of smart hull structure with optimally placed piezoelectric composite actuators , 2011 .

[15]  Karen Margaret Holford,et al.  Damage assessment of corrosion in prestressed concrete by acoustic emission , 2013 .

[16]  Alaa Chateauneuf,et al.  Maintenance planning under imperfect inspections of corroded pipelines , 2013 .

[17]  S Seshan,et al.  Fibre-reinforced metal matrix composites --a review , 2013 .

[18]  J Dual,et al.  Active fiber composites for the generation of Lamb waves. , 2009, Ultrasonics.

[19]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[20]  Zheng Liu,et al.  State of the art review of inspection technologies for condition assessment of water pipes , 2013 .

[21]  Walid G. Morsi,et al.  Novel power quality indices based on wavelet packet transform for non-stationary sinusoidal and non-sinusoidal disturbances , 2010 .

[22]  Bruno Castanier,et al.  Maintenance optimization for subsea oil pipelines , 2006 .

[23]  S. Ogura,et al.  Development of an ultrasonic inspection system using array transducers , 1986 .

[24]  Ivelin V. Ivanov,et al.  Finite Element analysis and modelling of Active Fibre Composites including damages , 2011 .

[25]  Jung-Ryul Lee,et al.  A time-of-flight mapping method for laser ultrasound guided in a pipe and its application to wall thinning visualization , 2011 .

[26]  Jia Ming.  Application of Wavelet Transformation in Signal Processing for Vibrating Platform , 2003 .

[27]  Gyuhae Park,et al.  The use of macro‐fibre composites for pipeline structural health assessment , 2008 .

[28]  G Acciani,et al.  Angular and axial evaluation of superficial defects on non-accessible pipes by wavelet transform and neural network-based classification. , 2010, Ultrasonics.

[29]  Senthil S. Vel,et al.  Multiscale analysis of laminated plates with integrated piezoelectric fiber composite actuators , 2012 .

[30]  Reinhold Schneider,et al.  Daubechies wavelets as a basis set for density functional pseudopotential calculations. , 2008, The Journal of chemical physics.

[31]  Mauro Caresta.  Active control of sound radiated by a submarine in bending vibration , 2011 .

[32]  Marc Edwards,et al.  The role of temperature gradients in residential copper pipe corrosion , 2004 .

[33]  M. A. Wahab,et al.  Piezoelectric fiber composite transducers for health monitoring in composite structures , 2013 .

[34]  Donavan Marney,et al.  The science of pipe corrosion: A review of the literature on the corrosion of ferrous metals in soils , 2012 .

[35]  Hong Hao,et al.  Experimental study on subsea pipeline bedding condition assessment using wavelet packet transform , 2013 .

[36]  Charles R. Farrar,et al.  Performance assessment and validation of piezoelectric active-sensors in structural health monitoring , 2006 .

[37]  Lalita Udpa,et al.  Development of image fusion methodology using discrete wavelet transform for eddy current images , 2012 .

[38]  Huseyin Eristi,et al.  Fault diagnosis system for series compensated transmission line based on wavelet transform and adaptive neuro-fuzzy inference system , 2013 .

[39]  Michael Pedrick,et al.  Ultrasonic signal processing methods for detection of defects in concrete pipes , 2012 .

[40]  Sung-Hoon Ahn,et al.  Condition monitoring and fault detection of wind turbines and related algorithms: A review , 2009 .

[41]  David K. Hsu,et al.  Estimation of porosity content of composite materials by applying discrete wavelet transform to ultrasonic backscattered signal , 2013 .

[42]  Dieter Sporn,et al.  Composites with piezoelectric thin fibers – first evidence of piezoelectric behavior , 1999 .

[43]  Mehrdad Sharif Bakhtiar,et al.  LEAK DETECTION IN WATER-FILLED PLASTIC PIPES THROUGH THE APPLICATION OF TUNED WAVELET TRANSFORMS TO ACOUSTIC EMISSION SIGNALS , 2010 .

[44]  Gerald Pinter,et al.  Investigation of slow crack growth initiation in polyethylene pipe grades with accelerated cyclic tests , 2013 .

[45]  M. H. Deokate,et al.  An Algorithm for Image Compression Using 2 D Wavelet Transform , 2012 .

[46]  Jian Zhao,et al.  Structural health monitoring of underground facilities – technological issues and challenges , 2005 .

[47]  Hyung Jin Lim,et al.  Reference-free fatigue crack detection using nonlinear ultrasonic modulation under various temperature and loading conditions , 2014 .

[48]  Gangbing Song,et al.  Vibration control of civil structures using piezoceramic smart materials: A review , 2006 .

[49]  Kyung-Young Jhang,et al.  Single-mode guided wave technique using ring-arrayed laser beam for thin-tube inspection , 2008 .