Missing Interpolation and Singular Value Correction of Dam Monitoring Data
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摘要:
大坝长效运行过程中,由于仪器故障或设备改造等问题,会引发监测数据失真或缺失等问题,容易造成结构安全性态误判。采用时空相关性原理对缺失的监测数据进行插补,利用格拉布斯−小波去噪组合方法对奇异值进行识别与处理,求得坝体的重构监测数据,并对奇异值进行修正。实例验证证明,该方法可以有效插补缺失变形监测数据,并对奇异值进行修正,从而使得监测数据结果愈加科学合理。
Abstract:During long-term operation of the dam, due to problems such as instrument failure or equipment transformation, monitoring data will be distorted or missing, which is easy to cause misjudgment of structural safety.Missing monitoring data were interpolated with principle of spatio-temporal correlation, and singular value was identified and processed by combination method of Grabus-wavelet denoising.Reconstructed monitoring data of the dam body were obtained, and singular value was corrected.Example proved that this method could effectively interpolate missing deformation data and calibrate singular value to make monitoring data more scientific and reasonable.
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Keywords:
- dam /
- monitoring data /
- spatiotemporal correlation /
- Grubbs-wavelet denoising
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表 1 重构数据与原始数据对比
Table 1. Comparison of reconstructed data with original data
单位:mm 日期 原始测量值 加噪测量值 修正测量值 2012/12/13 24.13 25.25 24.11 2012/12/16 24.02 21.28 24.01 2012/12/21 23.86 23.00 23.84 -
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