Changgil Lee

Damage classification of pipelines under water flow operation using multi-mode actuated sensing technology

In a structure, several types of damage can occur, ranging from micro-cracking to corrosion or loose bolts. This makes identifying the damage difficult with a single mode of sensing. Therefore, a multi-mode actuated sensing system is proposed based on a self-sensing circuit using a piezoelectric sensor. In self-sensing-based multi-mode actuated sensing, one mode provides a wide frequency-band structural response from the self-sensed impedance measurement and the other mode provides a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement. In this experimental study, a pipeline system under water flow operation was examined to verify the effectiveness and robustness of the proposed structural health monitoring approach. Different types of structural damage were inflicted artificially on the pipeline system. To classify the multiple types of structural damage, supervised learning-based statistical pattern recognition was implemented by composing a three-dimensional space using the damage indices extracted from the impedance and guided wave features as well as temperature variations. For a more systematic damage classification, several control parameters were optimized to determine an optimal decision boundary for the supervised learning-based pattern recognition. Further research issues are also discussed for real-world implementations of the proposed approach.

Magnetic Flux Leakage Sensing-Based Steel Cable NDE Technique

Nondestructive evaluation (NDE) of steel cables in long span bridges is necessary to prevent structural failure. Thus, an automated cable monitoring system is proposed that uses a suitable NDE technique and a cable-climbing robot. A magnetic flux leakage- (MFL-) based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults (LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the levels of damage. Measured signals from the damaged specimen were compared with thresholds that were set for objective decision-making. In addition, the measured magnetic flux signals were visualized as a 3D MFL map for intuitive cable monitoring. Finally, the results were compared with information on actual inflicted damages, to confirm the accuracy and effectiveness of the proposed cable monitoring method.

Flaw Imaging Technique for Plate-Like Structures Using Scanning Laser Source Actuation

Recently, the longitudinal, shear, and surface waves have been very widely used as ultrasonic wave-based exploration methods to identify internal defects of host structures. In this context, a noncontact nondestructive testing (NDT) method is proposed to detect the damage of plate-like structures and to identify the location of the damage. To achieve this goal, a scanning laser source actuation technique is utilized to generate a guided wave and scans a specific area to find damage location more precisely. The ND:YAG pulsed laser is used to generate Lamb wave and a piezoelectric sensor is installed to measure the structural responses. The measured responses are analyzed using 3-dimensional Fourier transformation (3D FT). The damage-sensitive features are extracted by wavenumber filtering based on the 3D FT. Then, flaw imaging techniques of a plate-like structure are conducted using the damage-sensitive features. Finally, the plates with notches are investigated to verify the effectiveness and the robustness of the proposed NDT approach.

Advanced Fatigue Crack Detection Using Nonlinear Self-Sensing Impedance Technique for Automated NDE of Metallic Structures

This article reports the application of a nonlinear impedance technique under a low-frequency vibration to detect contact-type structural defects such as fatigue cracks. If the contact-type damage is developed within the structure due to the low-frequency dynamic load, the vibration can cause a nonlinear fluctuation of the structural impedance because of the contact acoustic nonlinearity (CAN). This nonlinear effect can lead to amplitude modulation and phase modulation of the current flow. The nonlinear characteristics of the structural impedance can be extracted by observing the coupled electromechanical impedance of a piezoelectric active sensor and utilizing nonlinear wave modulation spectroscopy. Experimentally, a low-frequency vibration was applied to a notched coupon at a certain natural frequency by a shaker, so that a nonlinear fatigue crack can be artificially formed at the notch tip. Then, the nonlinear features are extracted based on a self-sensing impedance measurement from a host structure under a low-frequency vibration. The damage metric was established based on the nonlinear fluctuation of the impedance due to the CAN.

De-Bonding Detection on a CFRP Laminated Concrete Beam using Self Sensing-Based Multi-Scale Actuated Sensing with Statistical Pattern Recognition

This paper reports a novel structural health monitoring (SHM) technique for detecting de-bonding defects between a concrete beam structure and a CFRP (Carbon Fiber Reinforced Polymer) sheet attached to the concrete surface. To achieve this purpose, a multi-scale actuated sensing system with a self-sensing circuit using piezoelectric active sensors was applied to a CFRP laminated concrete beam structure. In the self-sensing based multi-scale actuated sensing system, a wide frequency-band structural response from the self-sensed impedance measurements and a specific frequency-induced structural wavelet response from the self-sensed guided wave measurement were utilized to localize the de-bonding defects. Furthermore, in order to quantify the de-bonding levels, the supervised learning-based statistical pattern recognition was implemented by composing a two-dimensional (2D) plane using the damage indices extracted from the impedance and guided wave features. The different levels of de-bonding defects inflicted artificially on the CFRP laminated concrete beam structure were investigated to confirm the effectiveness of the proposed SHM approach.

Damage visualization of pipeline structures using laser-induced ultrasonic waves

In this study, a noncontact non-destructive testing method is implemented to visualize damages of a pipeline structure. An ND:YAG pulsed laser system was used to generate guided waves and a galvanometer-based laser scanner scans a specific area to find damage location. The wave responses were measured using a piezoelectric sensor attached to the pipeline. The measured time and spatial responses were transformed to data in frequency and wavenumber domains through three-dimensional Fourier transform. Damage-sensitive features could be obtained using wavenumber filter to extract standing wave energy. A flaw imaging technique of the pipeline structure was conducted by calculating root mean square. Notches and thickness reduction at a pipeline structure were investigated to verify the effectiveness and the robustness of the proposed non-destructive testing approach. Additionally, a series of experiments were repeated under heating condition to consider the real-world pipeline structures.

Damage Localization for CFRP-Debonding Defects Using Piezoelectric SHM Techniques

This study employed a piezoelectric sensors-based structural health monitoring (SHM) technique to monitor debonding defects in real-time. A carbon fiber–reinforced polymer (CFRP) concrete beam specimen was fabricated, and the debonding conditions were inflicted in three successive steps. When the damage level was increased, the electromechanical impedance and guided wave signals were measured at each different damage level from the piezoelectric sensor array already surface mounted on the CFRP. A damage metric based on the root mean square deviation (RMSD) was investigated to quantify the variations in the signals between the intact and progressive damage conditions. To improve the performance of “debonding damage localization,” a new damage metric obtained by the superposition of the damage sensitive features extracted from both the impedance and guided wave signals was introduced. Polynomial curve fitting was performed using the superposed damage metric values. The location corresponding to the highest peak of the curve was determined. The location point was then compared with the actual inflicted damage points to confirm the effectiveness of the proposed damage localization technique. Further research issues are discussed for real-world implementation of the proposed approach using the above experimental results.

Visualization of Fatigue Cracks at Structural Members Using a Pulsed Laser Scanning System

In this research, a noncontact nondestructive testing (NDT) method is proposed to detect the fatigue crack and to identify the location of the damage. To achieve this goal, Lamb wave propagation of a plate-like structure, which is induced by scanning laser source actuation system, is analyzed. A ND:YAG pulsed laser system is used to generate Lamb wave exerted at the multiple points of a steel coupon, and a piezoelectric sensor is installed to measure the structural responses. Multiple time signals measured by the piezoelectric sensor are aligned along the vertical and horizontal axes corresponding to laser impinging points so that 3-dimensional data can be constructed. Then, the 3-dimensional data is sliced along the time axis to visualize the wave propagation. The scattering of Lamb wave due to the damage can be described in the wave propagation image, and hence the damage can be localized and quantified. Damage-sensitive features, which are reflected wave from the damage, are clearly extracted by wave-number filtering based on the 3-dimensional Fourier transform of the visualized data. Structural members with fatigue cracks are investigated to verify the effectiveness and the robustness of the proposed NDT approach.

Magnetic flux leakage-based steel cable NDE and damage visualization on a cable climbing robot

The steel cables in long span bridges such as cable-stayed bridges and suspension bridges are critical members which suspend the load of main girders and bridge floor slabs. Damage of cable members can occur in the form of crosssectional loss caused by fatigue, wear, and fracture, which can lead to structural failure due to concentrated stress in the cable. Therefore, nondestructive examination of steel cables is necessary so that the cross-sectional loss can be detected. Thus, an automated cable monitoring system using a suitable NDE technique and a cable climbing robot is proposed. In this study, an MFL (Magnetic Flux Leakage- based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults (LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. In addition, the measured magnetic flux signal was visualized into a 3D MFL map for convenient cable monitoring. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

Local Fault Detection Technique for Steel Cable using Multi-Channel Magnetic Flux Leakage Sensor

In this study, Multi-Channel Magnetic Flux Leakage(MFL) sensor - based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults(LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. In addition, the magnetic flux density values measured from every channel were summed to focus on the detection of axial location. And, sum of flux density were displayed with threshold. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.