• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.4
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• pp.355-361
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• 2012

This paper presents an experimental study on the detection and location of nonlinear scattering source due to the presence of fatigue crack in a laboratory specimen. The proposed technique is based on a combination of nonlinear elastic wave spectroscopy(NEWS) and time reversal(TR) focusing approach. In order to focus on the nonlinear scattering position due to the fatigue crack, we employed only one transmitting transducer and one receiving transducer, taking advantage of long duration of reception signal that includes multiple linear scattering such as mode conversion and boundary reflections. NEWS technique was then used as a pre-treatment of TR for spatial focusing of reemitted second harmonic signal. The robustness of this approach was demonstrated on a cracked specimen and the nonlinear TR focusing behavior is observed on the crack interface from which the second harmonic signal was originated.

• Composites Research
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• v.13 no.1
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• pp.89-97
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• 2000

Fatigue damage detection and vibration sensing for a laminated composites and impact location detection for a steel beam have been carried out using optical fiber sensor. Intensity based optical fiber sensor is constructed by placing two cleaved fiber end in a hollow glass tube, and multiple reflection within the cavity is considered. Fatigue signals are measured by embedded optical fiber, surface mounted optical fiber sensor and strain gage simultaneously. For vibration sensing, optical fiber sensor is mounted on the carbon fiber composite beam and its response to free vibration and forced vibration is investigated. In impact location detection, two optical fiber sensors are used and the information obtained from two sensors is arrival time delay of vibration caused by impact. Impact location can be calculated from this time delay. The obtained results show that the intensity based optical fiber sensor provide reliable data during long-term fatigue loading, unlike strain gage which deteriorate during the early part of the fatigue test. Optical fiber sensor signals coincide with gap sensor in vibration sensing. The precise locations of impact can be detected within 4.1% error limit.

• Steel and Composite Structures
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• v.32 no.3
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• pp.305-312
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• 2019

In this study, we investigated the effect of fatigue crack propagation of the beams which have a vital importance in engineering applications, on the natural frequency of the system. Beams which have a wide range of applications, are used as fundamental structural elements in engineering structures. Therefore, early detection of any damages in these structures is of vital importance for the prevention of possible destructive damages. One of the widely used methods of early detection of damages is the vibration analysis of the structure. Hence, it is of vital importance to detect and monitor any changes in the natural frequencies of the structure. From this standpoint, in this study we experimentally investigated the effect of fatigue crack propagation on beams produced from 4140 steel, of the natural frequency of the beam. A crack was opened on the $8{\times}16{\times}500mm$ beam using a 3 mm long and 0.25 mm wide wire erosion. The beam, then, underwent 3 point bending tests at 10 Hz with a dynamic fatigue device and its natural frequencies were measured in scheduled intervals and any changes taking place on the natural frequencies of the beam were measured. This data allowed us to identify and measure the crack occurring on the beam subjected to dynamic loading, during the propagation phase. This method produced experimental data. The experimental data showed that the natural frequency of the beam decreased with the propagation of the fatigue crack on the beam.

• Smart Structures and Systems
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• v.6 no.4
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• pp.349-362
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• 2010

Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defect-sensitive features to perform a multivariate diagnosis of damage. This diagnosis is based on the PCA. The framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generation and measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead Zirconate Titanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method is general and applicable to any structure that can sustain the propagation of UGWs.

• Structural Engineering and Mechanics
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• v.44 no.4
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• pp.417-429
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• 2012

Taking the superficial temperature increment as the major fatigue damage indicator, the infrared thermography was used to predict fatigue parameters (fatigue strength and S-N curve) of welded joints subjected to fatigue loading with a high mean stress, showing good predictions. The fatigue damage status, related to safety evaluation, was tightly correlated with the temperature field evolution of the hot-spot zone on the specimen surface. An energetic damage model, based on the energy accumulation, was developed to evaluate the residual fatigue life of the welded specimens undergoing cyclic loading, and a good agreement was presented. It is concluded that the infrared thermography can not only well predict the fatigue behavior of welded joints, but also can play an important role in health detection of structures subjected to mechanical loading.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.6
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• pp.686-695
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• 2012

This paper proposes a noncontact thermography technique for fatigue crack evaluation under a cyclic tensile loading. The proposed technique identifies and localizes an invisible fatigue crack without scanning, thus making it possible to instantaneously evaluate an incipient fatigue crack. Based on a thermoelastic theory, a new fatigue crack evaluation algorithm is proposed for the fatigue crack-tip localization. The performance of the proposed algorithm is experimentally validated. To achieve this, the cyclic tensile loading is applied to a dog-bone shape aluminum specimen using a universal testing machine, and the corresponding thermal responses induced by thermoelastic effects are captured by an infrared camera. The test results confirm that the fatigue crack is well identified and localized by comparing with its microscopic images.

• Journal of the Korean Society for Railway
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• v.8 no.5
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• pp.419-424
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• 2005

This paper has performed fatigue and nondestructive test of bogie frame for Korean tilting train. Before the fatigue test, static tests were carried out. From the test, the structural safety was investigated using Goodman diagram. After the static test, the fatigue test were conducted under tilting load conditions. The fatigue test was conducted for $10{\times}10^6$ cycles. During the fatigue test, the nondestructive tests using magnetic particle and liquid penetrant were performed at $6{\times}10^6$ cycle and $10{\times}10^6$cycle. From the crack detection tests, it was known that there was no fatigue crack in the bogie frame.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2005.11a
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• pp.234-238
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• 2005

This paper explains the fatigue test procedure of a composite train carbody. The composite carbody with length of 23m was manufactured as a sandwich structure composed of a 40mm-thick aluminium honeycomb core and 5mm-thick woven fabric carbon/epoxy face. In order to evaluate fatigue strength of the composite carbody, the carbody will be excited by two 50-ton capacity hydraulic actuators. The excitation frequency will be measured by natural frequency evaluation test under full weight condition. The test The fatigue test is to be conducted For $2{\times}10^6$cycles. During the fatigue test, the nondestructive tests using X-ray and liquid penetrant will be performed. From crack detection tests, the location and Fatigue crack progress will be investigated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.2 s.245
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• pp.210-218
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• 2006

This paper has performed static, fatigue and nondestructive test of tilting' bolster frame for Korean tilting train. From the static test, the structural safety was investigated using Goodman diagram. After the static test, the fatigue test were conducted under tilting load conditions. The fatigue test was conducted for $10\times10^6$ cycles. During the fatigue test, the nondestructive tests using magnetic particle and liquid penetrant were performed at $6\times10^6$cycle and $10\times10^6$cycle. From the crack detection tests, it was known that there was no fatigue crack in the tilting bolster.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.471-478
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• 2024

Effective physical fatigue monitoring is crucial for ensuring the health, safety, and productivity of construction workers, given the physically demanding nature of their work and the challenging environment in which they operate. In recent years, wearable sensors have shown growing potential for physical fatigue monitoring among construction workers. However, such fatigue assessment methods exhibit a significant gap as they often overlook the impact of inter-individual variability, such as differences in height, weight, and body mass index, on physiological signals that indicate physical fatigue. Therefore, this study aimed to investigate the role of personal factors in altering physiological responses, thereby improving the reliability and accuracy of fatigue monitoring using wearable physiological sensors. To explore the impact of these inter-individual factors, we experimentally analyzed the relationship between personal characteristics, physiological signals, and physical fatigue. Our findings reveal that although the inter-individual factors may not be directly correlated with fatigue levels, they significantly affect fatigue through their influence on physiological signals. Incorporation of these factors into a random forest predictive model significantly enhanced its predictive performance. Furthermore, integrating personal features with other variables to create new features in the physical fatigue prediction model notably improves its accuracy, highlighting the potential for developing personalized fatigue detection systems.