Acoustic emission of fatigue crack in pressure pipe under cyclic pressure

Ai, Qiong; Caixue, Liu; Chen, Xiangrong; He, Peng; Wang, Yao

doi:10.1016/j.nucengdes.2010.05.022

Cited by 33 publications

(12 citation statements)

References 20 publications

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“…This phenomenon leads to a period when only small AE activity occurs. Ai, Liu, Chen, He, and Wang (2010) found that a few burst-type AE signals appear at this stage due to the micro crack formation. During the last stage, crack start to grow and propagate and AE activities reactivate.…”

Section: Introductionmentioning

confidence: 92%

“…In Figure 10(g), the time domain AE signatures from the AECC group show the lowest amplitude with a nearly similar shape to the AE2C group. During crack initiation, burst-type AE appeared with very high amplitude and energy (Ai et al, 2010;Maslov & 1986), while the AE burst from the crack closure phenomenon has lower amplitude (Lee, Rhyim, Kwon, & Ono, 1995;Chang et al, 2007). AE signatures from the AECP and AEOC groups have similar burst behaviour and shape but different amplitudes.…”

Section: Time Domain Ae Signatures Behaviourmentioning

confidence: 99%

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Monitoring and Assessment of Acoustic Emission Signatures during Fatigue Mechanism of API5LX70 Gas Pipeline Steel

Fadhlan¹,

Kulthum²,

Abdullah³

et al. 2012

J MECH ENG SCI

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The detection of early fatigue phenomena in a gas pipeline is crucial in order to avoid catastrophic consequences. Therefore, appropriate inspection is needed to assess fatigue phenomena in a gas pipeline system. Acoustic emission (AE) technology is expected to be suitable in this regard. This paper presents the monitoring and assessment of AE signatures of the fatigue mechanism of gas pipeline material, API 5L X70 steel. The stress amplitude of 65%, 60%, 58% and 53% of the ultimate tensile strength were done in order to observe AE activity during the fatigue mechanism. Field measurements were also done by investigating AE signatures of an operational gas pipeline for comparison purposes. Based on the correlation of the AE signatures and fatigue mechanism, it was found that the AE activities generated during the fatigue mechanism were divided into three different stages. Analysis of the AE features and statistical parameters have shown that the kurtosis values of the time domain AE signatures from the third stage of the fatigue mechanism were different from the field measurements. This results show that the application of the kurtosis was expected to be able to detect the time domain AE signatures from the crack stage.

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Section: Introductionmentioning

confidence: 92%

Section: Time Domain Ae Signatures Behaviourmentioning

confidence: 99%

Monitoring and Assessment of Acoustic Emission Signatures during Fatigue Mechanism of API5LX70 Gas Pipeline Steel

Fadhlan¹,

Kulthum²,

Abdullah³

et al. 2012

J MECH ENG SCI

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“…AE relies on the (usually long-range) detection of stress waves that emanate from damage sites, either intrinsically due to the growth process of the damage or as a result of an external applied load to the 4.4 component. AE is well suited for online monitoring of passive components in nuclear power plants, and has been applied for crack growth detection (Harris and Dunegan 1974;Hutton et al 1984;Hutton 1993;Hutton et al 1993;Ai et al 2010;Meyer et al 2011b), leak detection (IAEA 2008b), and loose part monitoring (IAEA 2008b). GW also relies on the interaction of long-range stress waves with damage in the component (Rose 1999;Meyer et al 2012b).…”

Section: Data Collection -Nde For Passives Variable Sensing For Activesmentioning

confidence: 99%

“…A number of studies on the use of AE for monitoring nuclear components have been performed, and applications include crack growth monitoring, leak detection, and loose part detection and monitoring (Harris and Dunegan 1974;Hutton et al 1984;Hutton 1993;Hutton et al 1993;IAEA 2008b;Ai et al 2010;Meyer et al 2011b). AE was also deployed for a limited field trial to monitor the growth of cracks in two RPV nozzles at Limerick Generating Station Unit 1 (BWR) reactor and the Watts Bar Unit 1 (PWR) reactor (Hutton et al 1991;Hutton et al 1993).…”

Section: Metalsmentioning

confidence: 99%

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Coble¹,

Ramuhalli²,

Bond³

et al. 2012

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Recent years have seen a resurgence of nuclear power worldwide, with interest in extending the operating life of the approximately 436 reactors currently in service (as of March, 2012), 61 new reactors being constructed, and as many as 162 under consideration. Renewed worldwide interest in nuclear power has been somewhat tempered by the March 2011 incident at Fukushima Dai-ichi in Japan. However, nuclear power is still considered a key element in meeting future worldwide sustainable energy, energy security, and emissions goals. Currently, three separate thrusts to safe and economical nuclear power development for energy security are being pursued in the United States: (i) longer term operation for the legacy fleet, from 40-60 and possibly 60-80 years; (ii) near-term new nuclear plants with a 60-year design life; and (iii) small modular reactors, which are expected to employ light water reactor technology at least in the medium term. Within these activities, attention is turning to enhanced methods for plant component and structural health management.The operating U.S. fleet includes 104 light water reactors. In addition, there are now (as of May 2012) four new nuclear power plants (AP-1000 plants) under construction in the United States, and two delayed plants are being completed by the Tennessee Valley Authority. There is also interest in the United States in small modular reactors (SMRs), which could be easier to match to existing grid infrastructure and which could replace aging coal fired plants. The current low price for natural gas presents a challenge to the economics of nuclear power, at least in the short term; however, some recent studies have demonstrated that nuclear generation will be competitive in the longer term (at least in some markets) when anticipated escalation in gas prices and the cost of building, operating, and maintaining gas-fired plants are considered over those same time periods.This report reviews the current state of the art of prognostics and health management (PHM) for nuclear power systems and related technology currently applied in field or under development in other technological application areas, as well as key research needs and technical gaps for increased use of PHM in nuclear power systems. The historical approach to monitoring and maintenance in nuclear power plants (NPPs), including the Maintenance Rule for active components and Aging Management Plans for passive components, are reviewed. An outline is given for the technical and economic challenges that make PHM attractive for both legacy plants through Light Water Reactor Sustainability (LWRS) and new plant designs. There is a general introduction to PHM systems for monitoring, fault detection and diagnostics, and prognostics in other, non-nuclear fields. The state of the art for health monitoring in nuclear power systems is reviewed. A discussion of related technologies that support the application of PHM systems in NPPs, including digital instrumentation and control systems, wired and wireless sensor techno...

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“…When the number of recorded signals to process becomes very important, classical data-mining methods based on these variables are used to classify them and then the physical source mechanism associated with each class is identified. However, depending on the diversity of source mechanisms (cracks, fractures, delaminations ...) and the type of material (nuclear fuel, zircaloy, inox...) very different types of variables constructed from the AE signals can be discriminant [4,3,2,9]. In the case of nuclear safety experiment which is of interest in this article, the test device is composed of several types of materials and interact with a very complex environment, leading to a difficulty to get enough discriminant variables for a very heterogeneous sample of source mechanisms.…”

Section: Introductionmentioning

confidence: 99%

Contribution of Functional Approach to the Classification and the Identification of Acoustic Emission Source Mechanisms

Traoré

Cristini

Favretto-Cristini

et al. 2017

Contributions to Statistics

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Acoustic emission of fatigue crack in pressure pipe under cyclic pressure

Cited by 33 publications

References 20 publications

Monitoring and Assessment of Acoustic Emission Signatures during Fatigue Mechanism of API5LX70 Gas Pipeline Steel

Monitoring and Assessment of Acoustic Emission Signatures during Fatigue Mechanism of API5LX70 Gas Pipeline Steel

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Contribution of Functional Approach to the Classification and the Identification of Acoustic Emission Source Mechanisms

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