Time–frequency analyses of pile-integrity testing using wavelet transform

Ni, Sheng Huoo; Lo, Kuo Feng; Lehmann, Lutz; Yan, Huaxiang

doi:10.1016/j.compgeo.2007.09.003

Cited by 40 publications

(9 citation statements)

References 8 publications

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“…A wavelet transform was used to eliminate high‐frequency noise signals from the original signals and to improve the signal characteristics substantially, because ultrasonic waves are nonstable and transient (e.g., 21,38,39 ). The db5 wavelet was selected to disassemble the receiving wave signals into five levels.…”

Section: Methodsmentioning

confidence: 99%

Detection of the freezing state and frozen section thickness of fine sand by ultrasonic testing

Zhang

Murton

Liu

et al. 2020

Permafrost & Periglacial

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Determining the freezing state and frozen section thickness is fundamental to assessing the development of artificial frozen walls but is commonly difficult or inaccurate because of a limited number and fixed position of thermometer holes under complex field conditions. We report a novel experimental design that measures soil temperature, water content, and ultrasonic properties to monitor movement of the cryofront (0°C isotherm), water migration, and acoustic parameters during progressive upward freezing of fine sand under laboratory conditions. Ultrasonic testing during different stages of freezing revealed changes in three acoustic parameters (wave velocity, wave amplitude, and frequency spectrum). As the cryofront ascended through the sand at different water contents, wave velocity continually increased, whereas wave amplitude initially decreased and then increased. Wave velocity measurements revealed the cryofront position during freezing, but measurements of wave amplitude did not. The frequency components indicated the frequency of different evolving freezing regions during upward freezing and the freezing state of fine sand during later stages of freezing. The freezing state can be evaluated on the basis of single vs multiple peaks and the kurtosis of frequency spectrum change. An equation developed to predict the thickness of the frozen section and tested against measured values in the laboratory and field showed accuracies of 86.84–99.33%. The equation is used successfully to estimate frozen wall thickness in artificially frozen fine sand in Guangzhou, China.

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Section: Methodsmentioning

confidence: 99%

Detection of the freezing state and frozen section thickness of fine sand by ultrasonic testing

Zhang

Murton

Liu

et al. 2020

Permafrost & Periglacial

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“…To determine the flexural wave velocity using SKM also varies and the range of error to determine the location of damage and embedded length is often very high [4,20,21]. Continuous wavelet transform (CWT) is adopted by a number of researchers [22][23][24][25][26][27][28]. However, these literatures only focus on one type of wave, i.e.…”

Section: Introductionmentioning

confidence: 99%

Separation of longitudinal and flexural wave in a cylindrical structure based on sensor arrangement for non-destructive evaluation

Subhani

Samali

2016

J Civil Struct Health Monit

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Low strain integrity testing is commonly used to assess the in situ condition of the poles or piles. For poles, it is important to calculate the embedment length and location of damage which is highly influenced by the accurate determination of the wave velocity. In general, depending on impact location and orientation, both longitudinal and bending waves may generate inside the pole, and these two waves have very distinct characteristics and wave velocity. These differences are even more prominent in the low frequency which is usually induced in the low strain non-destructive testing. Consequently, it will be useful if these two waves can be separated for the condition assessment of the poles. In this paper, a numerical analysis is performed on a pole considering that both waves are generated, and a method is proposed to differentiate these two waves based on an appropriate sensor arrangement that includes the location and the orientation of the sensors. Continuous wavelet transform is applied on the numerical signal to calculate the phase velocity of the waves and compared with analytical phase velocity curves. From the results, it can be seen that appropriate location and orientation of the sensors can separate the longitudinal and flexural waves as they match significantly well with the corresponding analytical phase velocity curves of these two waves.

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“…The low-strain dynamic test, also known as the pulse echo method (PEM), is a method that is usually used to check the integrity of the pile. The PEM is widely used [2][3][4] and recommended by many codes [5][6][7][8]. The transient response method (TRM), also known as the mechanical mobility method, is a method similar to the PEM and was proposed in the 1960s∼1970s [9].…”

Section: Introductionmentioning

confidence: 99%

Bearing Capacity Estimation of Bridge Piles Using the Impulse Transient Response Method

Liu

Zhuang

et al. 2016

Shock and Vibration

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A bearing capacity estimation method for bridge piles was developed. In this method, the pulse echo test was used to select the intact piles; the dynamic stiffness was obtained by the impulse transient response test. A total of 680 bridge piles were tested, and their capacities were estimated. Finally, core drilling analysis was used to check the reliability of this method. The results show that, for intact piles, an obvious positive correlation exits between the dynamic stiffness and bearing capacity of the piles. The core drilling analysis proved that the estimation method was reliable.

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Time–frequency analyses of pile-integrity testing using wavelet transform

Cited by 40 publications

References 8 publications

Detection of the freezing state and frozen section thickness of fine sand by ultrasonic testing

Detection of the freezing state and frozen section thickness of fine sand by ultrasonic testing

Separation of longitudinal and flexural wave in a cylindrical structure based on sensor arrangement for non-destructive evaluation

Bearing Capacity Estimation of Bridge Piles Using the Impulse Transient Response Method

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