Damage evaluation of railway structures by using train-induced AE

Luo, Xiu; Haya, Hiroshi; Inaba, Tomoaki; Shiotani, Tomoki; Nakanishi, Yasuhiro

doi:10.1016/j.conbuildmat.2003.10.011

Cited by 38 publications

(8 citation statements)

References 2 publications

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“…Considering that AE activity during the unloading process is generally an indication of structural instability [9], a relaxation ratio greater than one (relaxation dominant) implies a defective structure. A new index called the 'RTRI ratio' (ratio of Repeated Train load at the onset of AE activity to Relative maximum load for Inspection period) was proposed by Shiotani and coworkers [11,12] to overcome the difficulty to estimate the maximum load that has been ever experienced by existing structures. This modifies the definition of 'Load Ratio' by introducing the relative maximum load instead of the previous maximum one.…”

Section: Intensity Analysismentioning

confidence: 99%

“…This modifies the definition of 'Load Ratio' by introducing the relative maximum load instead of the previous maximum one. Values of Clam Ratio and RTRI ratio higher than 0.5 and lower than 0.8, respectively identify, following Luo et al [12] a condition of high damage level. A schematic representation of the different plots used in the IA is reported in Fig.…”

Section: Intensity Analysismentioning

confidence: 99%

“…In the first loading cycle the load was determined by a 30 tons (0. [12]. It means that in such structures damage accumulation could be related to a modification of the AE patterns.…”

Section: In-field Testsmentioning

confidence: 99%

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Evaluation of deterioration in reinforced concrete structures by AE technique

Proverbio

2010

Materials & Corrosion

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Acoustic emission (AE) technique is gaining increasing interest for applications in civil engineering. AE indeed is a passive nonintrusive technique that can be applicable either in structural health monitoring (global evaluation) and in defect localization (local evaluation). The most promising application of such a technique seems to be however in the evaluation of growing defects. Defects such as cracks and delamination can be caused by reinforcement corrosion as well as by other concrete deterioration mechanisms (alkali silica reaction, sulphate attack, etc.) as well as originating from improper concrete casting, curing or structure setting. Damage severity can be evaluated by means of the intensity analysis (IA) through the use of different indexes such as ‘Load Ratio’, ‘Calm Ratio’, ‘Felicity Ratio’ or ‘Historical Index’. Damage evolution analysis along time could be however significantly improved by adopting some procedure already used in the field of geophysics and earth science. Among various parameters, the most significant one is the b‐value which is derived from the amplitude distribution data of AE following the methods used in seismology. Several application examples applied to prestressed concrete structures are reported in the paper.

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Section: Intensity Analysismentioning

confidence: 99%

Section: Intensity Analysismentioning

confidence: 99%

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Evaluation of deterioration in reinforced concrete structures by AE technique

Proverbio

2010

Materials & Corrosion

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“…Ohno et al estimated the crack and degradation in concrete structures by AE techniques, and discussed two crack classification methods of the parameter analysis and the simplified Green’s functions for moment tensor analysis [20]. Luo et al demonstrated the applicability of the AE technique to assess the damage level of railway structures via the AE indices [21]. Shiotani et al investigated the crack or damage of concrete by AE detection and verified the ability of AE monitoring on the pile integrity [22].…”

Section: Introductionmentioning

confidence: 99%

Crack Detection of FRP-Reinforced Concrete Beam Using Embedded Piezoceramic Smart Aggregates

Jiang

Hong

Zheng³

et al. 2019

Sensors

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In this paper, the authors present a stress wave-based active sensing method to detect the crack in FRP-reinforced concrete beams. The embedded smart aggregates (SAs), which utilize Lead Zirconate Titanate (PZT) as transducers, are employed in this research to generate and sense the stress wave. Three specimens are involved in the experimental program and each is made of concrete, longitudinal distributed reinforcement, steel stirrups, main bar (FRP bar or steel bar), and four SAs. A pair of SAs installed on the lower part of the main bar and the other pair of SAs mounted on the upper part of main bar are utilized to monitor the crack occurrence and development in the three test specimens. The signals received by the SA sensors are analyzed in both time domain and frequency domain. The wavelet packet energy is used to extract damage features. The applied load–vertical displacement curves of mid-span in the specimen are obtained. Experimental results show the test specimens experience crushing failure when the concrete compression exceeds its compressive strength. Increasing the contact area between FRP bar and concrete can effectively improve the cracking load of the FRP-reinforced concrete beam and reduce the cracking speed and depth of FRP-reinforced concrete beam; on the other hand, increasing the elastic modulus of the main bar can slow down the crack development of concrete on the upper side of the main bar and decrease the displacement of reinforced concrete beam during the loading test process. The research results show that the developed piezoceramic-based active sensing method, though low-cost, can monitor the crack-induced damage and estimate the process of damage degree in real-time, and has potentials to provide an early warning of crack occurrence and development for FRP-reinforced concrete beams.

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“…AE is a typical NDT technique, which is capable of detecting material damage. 6,7 Monitoring AE signals in situ can give significant information about the microscopic damage mechanisms involved. 8 It has been shown that the AE technique is sensitive and reliable enough for the detection of material damage of in-service structures, 9,10 but building a relationship between the AE signal and the accumulated tensile damage is necessary.…”

Section: Introductionmentioning

confidence: 99%

Life prediction of the tensile damage progress for high-speed train gearbox shell based on acoustic emission sensor and an automatic optimization method

Sun

Zhang

2018

International Journal of Distributed Sensor Networks

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The high-speed train gearbox is one of the key components of the train system, and its working state is related to passengers’ safety. The gearbox shell is the protective shell for gears under harsh and complex service environment. Instantaneous impact of hard material during failure can lead to the rapid damage accumulation and fracture of the shell material. In this article, the accumulation of tensile damage of the high-speed train gearbox shell material has been studied. For the short tensile process leading to significant amount of damage, a real-time and non-destructive detection method has been used to monitor the tensile damage progression and predict the residual life of the material. An automatic optimization algorithm has been proposed to deal with data quality problems such as fluctuations, imbalances, and large intervals. In addition, an automatic life prediction optimization model for material tensile process has been established. The life prediction errors are controlled within 50 s, and the majority of errors are less than 20 s. For the accelerated test, in respect to real situation, a 6 h time slot is designed for disaster control such as passenger evacuation and train failure prevention.

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Damage evaluation of railway structures by using train-induced AE

Cited by 38 publications

References 2 publications

Evaluation of deterioration in reinforced concrete structures by AE technique

Evaluation of deterioration in reinforced concrete structures by AE technique

Crack Detection of FRP-Reinforced Concrete Beam Using Embedded Piezoceramic Smart Aggregates

Life prediction of the tensile damage progress for high-speed train gearbox shell based on acoustic emission sensor and an automatic optimization method

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