Anomaly identification of foundation uplift pressures of gravity dams based on DTW and LOF. Issue 5 (31st January 2018)
- Record Type:
- Journal Article
- Title:
- Anomaly identification of foundation uplift pressures of gravity dams based on DTW and LOF. Issue 5 (31st January 2018)
- Main Title:
- Anomaly identification of foundation uplift pressures of gravity dams based on DTW and LOF
- Authors:
- Hu, Jiang
Ma, Fuheng
Wu, Suhua - Abstract:
- Summary: Anomaly can provide valuable information for dam safety monitoring. In this paper, a methodology integrating dynamic time warping and local outlier factor to identify anomalies of time series on various time scales is proposed. The main steps of the methodology are introduced in detail. First, measured time series are preprocessed using moving average and normalization, respectively, to eliminate influence of random and amplitude variations. Following this, time series of independent variables (predictors) are selected as templates to calculate dynamic time warping distances using the global constraint to measure similarities with the dependent variable (a predicant) on a large time scale. Then, traditional regression models are built to find out contributions of independent variables to structural behavior, as well as to highlight unwanted behaviors at relatively on a small time scale. Furthermore, local outlier factor values of multivariate are computed, which helps finding anomalies on a small time scale. Finally, causes of anomalies are analyzed comprehensively. A case study is presented focus on the measured foundation uplift beneath the local riverbed blocks of Xixi reservoir dam. Results show that point anomalies occur with sudden changes of independent variables, but contextual anomalies boil down to coupled effect of high reservoir level and low ambient temperature. The natural condition of the rock foundation underlying blocks, which is characterized asSummary: Anomaly can provide valuable information for dam safety monitoring. In this paper, a methodology integrating dynamic time warping and local outlier factor to identify anomalies of time series on various time scales is proposed. The main steps of the methodology are introduced in detail. First, measured time series are preprocessed using moving average and normalization, respectively, to eliminate influence of random and amplitude variations. Following this, time series of independent variables (predictors) are selected as templates to calculate dynamic time warping distances using the global constraint to measure similarities with the dependent variable (a predicant) on a large time scale. Then, traditional regression models are built to find out contributions of independent variables to structural behavior, as well as to highlight unwanted behaviors at relatively on a small time scale. Furthermore, local outlier factor values of multivariate are computed, which helps finding anomalies on a small time scale. Finally, causes of anomalies are analyzed comprehensively. A case study is presented focus on the measured foundation uplift beneath the local riverbed blocks of Xixi reservoir dam. Results show that point anomalies occur with sudden changes of independent variables, but contextual anomalies boil down to coupled effect of high reservoir level and low ambient temperature. The natural condition of the rock foundation underlying blocks, which is characterized as intensively open tension joints, is responsible for uplift anomalies. … (more)
- Is Part Of:
- Structural control and health monitoring. Volume 25:Issue 5(2018)
- Journal:
- Structural control and health monitoring
- Issue:
- Volume 25:Issue 5(2018)
- Issue Display:
- Volume 25, Issue 5 (2018)
- Year:
- 2018
- Volume:
- 25
- Issue:
- 5
- Issue Sort Value:
- 2018-0025-0005-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2018-01-31
- Subjects:
- anomaly identification -- dam safety monitoring -- dynamic time warping -- local outlier factor -- similarity measurement -- uplift
Structural engineering -- Periodicals
Structural control (Engineering) -- Periodicals
Automatic data collection systems -- Periodicals
Detectors -- Periodicals
624.17 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/stc.2153 ↗
- Languages:
- English
- ISSNs:
- 1545-2255
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8476.924000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 10817.xml