The Experts below are selected from a list of 183 Experts worldwide ranked by ideXlab platform
Lei Qiu - One of the best experts on this subject based on the ideXlab platform.
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an adaptive guided wave gaussian mixture model for damage monitoring under time varying conditions validation in a full scale Aircraft fatigue test
Structural Health Monitoring-an International Journal, 2017Co-Authors: Lei Qiu, Shenfang Yuan, Christian BollerAbstract:Structural health monitoring technology has gradually developed from the research in laboratory to engineering validations and applications. However, the problem of reliable damage evaluation under...
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crack propagation monitoring in a full scale Aircraft fatigue test based on guided wave gaussian mixture model
Smart Materials and Structures, 2016Co-Authors: Lei Qiu, Shenfang Yuan, Qiao Bao, Hanfei Mei, Yuanqiang RenAbstract:For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real Aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a Full-Scale Aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback–Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the Full-Scale Aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.
Yuanqiang Ren - One of the best experts on this subject based on the ideXlab platform.
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crack propagation monitoring in a full scale Aircraft fatigue test based on guided wave gaussian mixture model
Smart Materials and Structures, 2016Co-Authors: Lei Qiu, Shenfang Yuan, Qiao Bao, Hanfei Mei, Yuanqiang RenAbstract:For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real Aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a Full-Scale Aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback–Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the Full-Scale Aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.
Shenfang Yuan - One of the best experts on this subject based on the ideXlab platform.
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an adaptive guided wave gaussian mixture model for damage monitoring under time varying conditions validation in a full scale Aircraft fatigue test
Structural Health Monitoring-an International Journal, 2017Co-Authors: Lei Qiu, Shenfang Yuan, Christian BollerAbstract:Structural health monitoring technology has gradually developed from the research in laboratory to engineering validations and applications. However, the problem of reliable damage evaluation under...
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crack propagation monitoring in a full scale Aircraft fatigue test based on guided wave gaussian mixture model
Smart Materials and Structures, 2016Co-Authors: Lei Qiu, Shenfang Yuan, Qiao Bao, Hanfei Mei, Yuanqiang RenAbstract:For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real Aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a Full-Scale Aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback–Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the Full-Scale Aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.
Christian Boller - One of the best experts on this subject based on the ideXlab platform.
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an adaptive guided wave gaussian mixture model for damage monitoring under time varying conditions validation in a full scale Aircraft fatigue test
Structural Health Monitoring-an International Journal, 2017Co-Authors: Lei Qiu, Shenfang Yuan, Christian BollerAbstract:Structural health monitoring technology has gradually developed from the research in laboratory to engineering validations and applications. However, the problem of reliable damage evaluation under...
Qiao Bao - One of the best experts on this subject based on the ideXlab platform.
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crack propagation monitoring in a full scale Aircraft fatigue test based on guided wave gaussian mixture model
Smart Materials and Structures, 2016Co-Authors: Lei Qiu, Shenfang Yuan, Qiao Bao, Hanfei Mei, Yuanqiang RenAbstract:For aerospace application of structural health monitoring (SHM) technology, the problem of reliable damage monitoring under time-varying conditions must be addressed and the SHM technology has to be fully validated on real Aircraft structures under realistic load conditions on ground before it can reach the status of flight test. In this paper, the guided wave (GW) based SHM method is applied to a Full-Scale Aircraft fatigue test which is one of the most similar test status to the flight test. To deal with the time-varying problem, a GW-Gaussian mixture model (GW-GMM) is proposed. The probability characteristic of GW features, which is introduced by time-varying conditions is modeled by GW-GMM. The weak cumulative variation trend of the crack propagation, which is mixed in time-varying influence can be tracked by the GW-GMM migration during on-line damage monitoring process. A best match based Kullback–Leibler divergence is proposed to measure the GW-GMM migration degree to reveal the crack propagation. The method is validated in the Full-Scale Aircraft fatigue test. The validation results indicate that the reliable crack propagation monitoring of the left landing gear spar and the right wing panel under realistic load conditions are achieved.
