Integrity Testing of Model Pile with Embedded Accelerometers

Lai, Jiunnren; Yang, Pei-Cheng; Yang, Bo-Huan; Chang, Der-Wen

doi:10.12783/dtmse/ictim2017/10063

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…In order to accurately verify the accuracy of the method and establish an intuitive understanding about the defects of foundation piles and their corresponding testing data [46], we designed and processed seven concrete model piles. Through the observation and the test of these actual piles, a more intuitive and convenient verification process can be established for the artificial intelligence method, which can also provide the effective verification for the technical level of testing personnel and the accuracy of pile testing equipment.…”

Section: Concrete Model Pile Used For Testingmentioning

confidence: 99%

Classification of Low-Strain Foundation Pile Testing Signal Using Recurrent Neural Network

Wang

Zhang

et al. 2023

Buildings

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The testing of the foundation pile is an important means to ensure the quality of the foundation pile in the construction process, and the low-strain pile test is one of the most commonly used testing technologies. However, in order to ensure that the testing signal is effective and reliable, it is necessary to provide the preliminary judgment results when acquiring the testing signal in the field. In this paper, we propose a data classification method for low-strain pile testing data using a recurrent neural network as the core. In this method, after identification, tailoring, and normalization, the input feature vector with a sequential structure is sent into this model. The model ensures the efficient use of data values while considering the sequential relationship among the data. At last, we designed and produced one complete model pile and six asymmetric model piles, which can form thirteen kinds of testing signals. The optimal application model was selected by the 10-fold cross verification method, and the influence of increasing the input feature dimension on the accuracy was discussed. Finally, compared with the other two methods, this model has the highest accuracy, at 98.46%, but it requires more training parameters and a longer training time.

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Section: Concrete Model Pile Used For Testingmentioning

confidence: 99%

Classification of Low-Strain Foundation Pile Testing Signal Using Recurrent Neural Network

Wang

Zhang

et al. 2023

Buildings

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Integrity Testing of Three Model Piles with a Pile Cap

Lai

Yang

2019

Journal of Testing and Evaluation

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Nondestructive pile integrity testing (PIT) methods based on the propagation of sonic/ultrasonic waves have been widely used for the quality assurance of newly constructed drilled shafts. However, application of these techniques for forensic investigations of existing piles may encounter difficulties that are due to the existence of a pile cap. In this article, the boundary effects of pile caps on the signal of PIT methods were studied by numerical simulation and tests on three model piles. The feasibility of assessing the integrity of a capped pile by embedded accelerometers was also investigated. Results of this study indicate that it is too difficult to assess the integrity of a capped pile with the conversional Sonic Echo PIT method. On the other hand, it is possible to detect the defect or pile toe with embedded accelerometers, especially when multiple receivers are used with the Ultra Seismic techniques.

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Integrity Testing of Model Pile with Embedded Accelerometers

Cited by 2 publications

References 2 publications

Classification of Low-Strain Foundation Pile Testing Signal Using Recurrent Neural Network

Classification of Low-Strain Foundation Pile Testing Signal Using Recurrent Neural Network

Integrity Testing of Three Model Piles with a Pile Cap

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