This article presents a nondestructive evaluation (NDE) method to infer the axial stress in thick beams with the aim to extent the methodology to continuous welded rails. The method relies on the propagation of highly nonlinear solitary waves generated at one end of a chain of spherical particles in contact with the beam to be evaluated. The opposite end of the chain is in contact with the beam to be evaluated. Here the waves are reflected back to chain and the hypothesis is that the axial stress influences the amplitude and speed of the reflected waves. To verify this hypothesis a general finite element model of thermally stressed beams was developed and coupled to a discrete particle model able to predict the propagation of the waves along a L-shaped granular medium. The models were validated experimentally. The hypothesis was proven valid by both the numerical and the experimental results. In the future, these findings may be used to refine a NDE method to assess stress in columns, to infer the neutral temperature of continuous welded rails, and to prevent thermal buckling of critical structures.
Non-contact structural health monitoring is a promising field for assessing civil structures, such as bridges. Not having to access the structure avoids different issues: the closure of the structure, the use of special equipment to access it, and others. This study uses digital image processing, machine learning, and parallel computing to detect the vibration of a flexible structure. If a structure is too stiff, a reinforced concrete short-span bridge or a multi-story building, it is hard to identify its natural frequencies without some sort of target panel or target feature. Instead, if the structure is flexible, it is possible to identify its displacement and its natural frequencies, but it is a challenge with high computational cost. This study presents an unsupervised machine-learning algorithm to identify a structure, its displacement, and its natural frequencies. The algorithm was deployed on a simple supported beam using a commercially available camera and an inexpensive GPU.
In this paper, an integrated nondestructive evaluation / structural health monitoring (NDE / SHM) system based on the use of acoustic emission (AE), electromechanical impedance (EMI) and guided ultrasonic waves (GUWs) is presented. The system is integrated into a single hardware/software unit and is driven by a few graphical user interfaces created in the laboratory. The feasibility of this multi-modal monitoring approach is assessed by monitoring an aluminum plate with an array of six wafer-type piezoelectric transducers. AE events are generated with the pencil-lead break technique whereas damage is simulated in the form of permanent magnets attached to the plate. The waveforms associated with the AE are processed using a source localization approach, whereas the GUWs and EMI data are processed using simple metrics based on cross-correlation. The results presented here show that the proposed system is robust and the three NDT methods complement each other very well.
We describe the feasibility and the repeatability of highly nonlinear solitary waves (HNSWs) in nondestructive evaluation (NDE) of different materials and structures. HNSWs formed by tapping the first particle of a one-dimensional chain of spherical particles in contact with the material or the structure being assessed. This way, one pulse forms and travel within the chain, and one or more pulses (depending on the mechanical properties of the contact structure) reflect back to the chain at the chain/structure interface. The hypothesis is that the reflected pulses features such as their amplitude or velocity depend on the stiffness of the material or the structure in contact with the chain. The results show that the time-of-flight (TOF) is an appropriate wave feature for NDE applications because it is highly repeatable and influenced by the mechanical properties of contact material/structure. In the future, the proposed NDE method may potentially serve as a cost-effective tool for the rapid evaluation of existing structures.
We describe the feasibility of a nondestructive evaluation (NDE) method for concrete based on the propagation of highly nonlinear solitary waves (HNSWs) along a one-dimensional chain of spherical particles placed in contact with the concrete to be tested. The chain is part of a built-in transducer designed and assembled to excite and detect HNSWs. The method exploits the dynamic interaction between the particles and the concrete. The hypothesis is that the interaction depends on the stiffness of the concrete and influences the time of flight and amplitude of the solitary pulses reflected at the transducer/concrete interface, and traveling within the chain. The results show that the time of flight is monotonically dependent upon the modulus of elasticity of the concrete and that the transducers designed and assembled in this study are reliable and repeatable. In the future, the proposed NDE method may potentially serve as a cost-effective tool for the rapid evaluation of existing concrete structures.
In this paper we present a structural health monitoring (SHM) paradigm based on the simultaneous use of ultrasounds and electromechanical impedance (EMI) to monitor waveguides. The paradigm uses guided ultrasonic waves (GUWs) in pitch-catch mode and EMI simultaneously. The two methodologies are driven by the same sensing/hardware/software unit. To assess the feasibility of this unified system an aluminum plate was monitored for varying damage location. Damage was simulated by adding small masses to the plate. The results associated with pitch-catch GUW testing mode were used in ultrasonic tomography, and statistical analysis was used to detect the damages using the EMI measurements. The results of GUW and EMI monitoring show that the proposed system is robust and can be developed further to address the challenges associated with the SHM of complex structures.
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