Improvement of a vibration-based damage detection approach for health monitoring of bolted flange joints in pipelines

Early detection of bolt loosening is a major concern in the oil and gas industry. In this study, a vibration-based health monitoring strategy has been developed for detecting the loosening of bolts in a pipeline’s bolted flange joint. Both numerical and experimental studies are conducted to verify the integrity of our implementation as well as of an enhancement developed along with it. Several damage scenarios are simulated by the loosening of the bolts through varying the applied torque on each bolt. An electric impact hammer is used to vibrate (excite) the system in a consistent manner. The induced vibration signals are collected via piezoceramic sensors bonded onto the pipe and flange. These signals are transferred remotely by a wireless data acquisition module and then processed with a code developed in-house in the MATLAB environment. After normalization and filtering of the signals, the empirical mode decomposition is applied to establish an effective energy-based damage index. The assessment of the damage indices thus obtained for the various scenarios verifies the integrity of the proposed methodology for identifying the damage and its progression in bolted joints as well as the major enhancements applied onto the methodology.

[1]  S. J. Loutridis,et al.  Damage detection in gear systems using empirical mode decomposition , 2004 .

[2]  Fu-Kuo Chang,et al.  Detection of bolt loosening in C–C composite thermal protection panels: I. Diagnostic principle , 2006 .

[3]  Shlomo Engelberg Digital Signal Processing: An Experimental Approach , 2008 .

[4]  Fu-Kuo Chang,et al.  Detection of bolt loosening in C–C composite thermal protection panels: II. Experimental verification , 2006 .

[5]  E. Peter Carden,et al.  Vibration Based Condition Monitoring: A Review , 2004 .

[6]  Michele Meo,et al.  Structural health monitoring of bolted joints using linear and nonlinear acoustic/ultrasound methods , 2011 .

[7]  Yozo Fujino,et al.  Quantitative health monitoring of bolted joints using a piezoceramic actuator-sensor , 2004 .

[8]  Daniel J. Inman,et al.  Automated Structural Health Monitoring of Bolted Joints in Railroad Switches , 2009 .

[9]  Wen-Hsing Kuo,et al.  An intelligent positioning approach: RSSI-based indoor and outdoor localization scheme in Zigbee networks , 2010, 2010 International Conference on Machine Learning and Cybernetics.

[10]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[11]  W. D. Zhu,et al.  A vibration-based structural damage detection method and its applications to engineering structures , 2011 .

[12]  Farid Taheri,et al.  A damage index for structural health monitoring based on the empirical mode decomposition , 2007 .

[13]  Ramadan A. Esmaeel,et al.  Application of a robust vibration-based non-destructive method for detection of fatigue cracks in structures , 2011 .

[14]  Ranjan Ganguli,et al.  Structural Damage Detection Using Modal Curvature and Fuzzy Logic , 2009 .

[15]  Jeffrey A. Chambers Preloaded joint analysis methodology for space flight systems , 1995 .

[16]  Daniel J. Inman,et al.  Feasibility of using impedance‐based damage assessment for pipeline structures , 2001 .

[17]  David J. Ewins,et al.  Modal Testing: Theory, Practice, And Application , 2000 .

[18]  Jonathan M. Nichols,et al.  Modeling and Detection of Joint Loosening using Output-Only Broad-Band Vibration Data , 2008 .

[19]  Anindya Ghoshal,et al.  STRUCTURAL HEALTH MONITORING OF AN AIRCRAFT JOINT , 2003 .

[20]  Yozo Fujino,et al.  Quantitative health monitoring of bolted joints using piezoceramic actuator-sensor , 2003, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[21]  Farid Taheri,et al.  Computational simulation and experimental verification of a new vibration-based structural health monitoring approach using piezoelectric sensors , 2012 .

[22]  Farid Taheri,et al.  Experimental validation of a novel structural damage detection method based on empirical mode decomposition , 2009 .

[23]  Farid Taheri,et al.  Health monitoring of pipeline girth weld using empirical mode decomposition , 2010 .