Considering that dam deformation and its influencing factors present complex nonlinearities, a modified deformation monitoring model is proposed in this study. On the basis of the systematic analysis of the effects of environmental influencing factors on dam deformation, this study attempts to explore the functional relation between dam deformation and sediment deposition based on the theory of classical dam deformation monitoring model, and the theory of dam deformation monitoring is developed. Meanwhile, considering that the residual sequence of monitoring model contains certain periodic components, singular spectrum analysis is adopted to denoise and to reconstruct residual by extracting the trend and periodic components, and then the reconstructed residual sequence is trained and forecasted by autoregressive integrated moving average model. By superimposing the residual forecast value with forecast value of classical statistical model, a modified deformation monitoring modeling method is established. Examples show that, compared with conventional models, the forecast capacity of the proposed method is improved to a large extent, which effectively corroborates the rationality and effectiveness of the modeling method. A new technical support for guaranteeing the safe operation of dams is provided.

中文翻译：

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考虑残差序列中周期性分量的大坝变形监测模型

考虑到大坝变形及其影响因素存在复杂的非线性，提出了一种改进的变形监测模型。在对环境影响因素对大坝变形影响的系统分析的基础上，本研究试图基于经典大坝变形监测模型理论和大坝变形监测理论探讨大坝变形与泥沙沉积之间的功能关系。被开发。同时，考虑到监测模型的残差序列包含一定的周期性成分，采用奇异频谱分析对趋势和周期性成分进行去噪和重构残差，然后利用自回归综合移动平均模型对重构的残差序列进行训练和预测。 。通过将剩余预测值与经典统计模型的预测值相叠加，建立了一种改进的变形监测建模方法。实例表明，与常规模型相比，该方法的预测能力有了较大的提高，有效地证实了该建模方法的合理性和有效性。为保证大坝的安全运行提供了新的技术支持。