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.
This paper presents the application of a novel vibration-based technique for detecting fatigue cracks in structures. The method utilizes the empirical mode decomposition method (EMD) to establish an effective energy-based damage index. To investigate the feasibility of the method, fatigue cracks of different sizes were introduced in an aluminum beam subjected to a cyclic load under a three-point bending configuration. The vibration signals corresponding to the healthy and the damaged states of the beam were acquired via piezoceramic sensors. The signals were then processed by the proposed methodology to obtain the damage indices. In addition, for the sake of comparison, the frequency and damping analysis were performed on the test specimen. The results of this study concluded with two major observations. Firstly, the method was highly successful in not only predicting the presence of the fatigue crack, but also in quantifying its progression. Secondly, the proposed energy-based damage index was proved to be superior to the frequency-based methods in terms of sensitivity to the damage detection and quantification. As a result, this technique could be regarded as an efficient non-destructive tool, since it is simple, cost-effective and does not rely on analytical modeling of structures. In addition, the capability of the finite element method (FEM) in mimicking the experiments, and hence for consideration as an effective tool for conducting future parametric studies, was also investigated.
This study presents numerical simulations and experimental verification of a vibration-based damage detection technique. Health monitoring of a submerged pipe's girth-weld against an advancing notch is attempted. Piezoelectric transducers are bonded on the pipe for sensing or actuation purposes. Vibration of the pipe is excited by two means: (i) an impulsive force; (ii) using one of the piezoelectric transducers as an actuator to propagate chirp waves into the pipe. The methodology adopts the empirical mode decomposition (EMD), which processes vibration data to establish energy-based damage indices. The results obtained from both the numerical and experimental studies confirm the integrity of the approach in identifying the existence, and progression of the advancing notch. The study also discusses and compares the performance of the two vibration excitation means in damage detection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.