A Study on Detection of Potential Risk of Slope Failure by Monitoring of Shear Strain in Shallow Sub-Surface of a Slope at Excavations

Tamate, Satoshi; Hori, Tomohito; Mikuni, Chiharu; Suemasa, Naoaki

doi:10.2208/jscejge.70.213

J. JSCE, Ser. C

2014

DOI: 10.2208/jscejge.70.213

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A Study on Detection of Potential Risk of Slope Failure by Monitoring of Shear Strain in Shallow Sub-Surface of a Slope at Excavations

Satoshi Tamate¹,

Tomohito Hori²,

Chiharu Mikuni³

et al.

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Cited by 2 publications

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労働災害防止のためのアンサンブル学習による斜面崩壊の異常検知

NAKANE,

HIRAOKA,

NAKAJO

et al. 2023

Japanese Journal of JSCE

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労働災害防止のためのアンサンブル学習による斜面崩壊の異常検知

NAKANE,

HIRAOKA,

NAKAJO

et al. 2023

Japanese Journal of JSCE

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Anomaly detection from slope surface strain using linear regression

NAKANE,

HIRAOKA,

KIKKAWA

et al. 2024

Jiban Kogaku Janaru

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In recent years, measurement devices and monitoring systems involving information and communications technology have been developed and used for slope monitoring in Japan. Although it is possible to measure slope monitoring data during slope failure, systems to determine slope anomalies are also required. In this study, anomalies were detected and verified from slope monitoring data using linear regression model based on machine learning. In this method, the data was predicted from time series of the slope surface strain by eight sensors installed in a slope failure experiment using a centrifuge, and verified with the measured data. For evaluation of the slope monitoring data, the machine learning method used slope monitoring data from normal state during slope stability as reference. When a pattern of data different from the normal state was detected, the slope was considered to be unstable and an alert was issued.Consequently, from the time series change in the number of anomalies detected by the eight installed surface strain sensors, it was confirmed that the anomalies on the slope can be detected before the collapse of the slope.

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A Study on Detection of Potential Risk of Slope Failure by Monitoring of Shear Strain in Shallow Sub-Surface of a Slope at Excavations

Cited by 2 publications

References 1 publication

労働災害防止のためのアンサンブル学習による斜面崩壊の異常検知

労働災害防止のためのアンサンブル学習による斜面崩壊の異常検知

Anomaly detection from slope surface strain using linear regression

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