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Study on prediction of foundation settlement of Qingshan Power Plant in Wuhan

机译:武汉青山电厂基础沉降基础结算研究

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The equal time-interval original data is the precondition of the grey model establishment. As the acquired data in the practical using is usually unequal time-interval, there are some errors in the predicting results. On the basis of the grey model GM (1, 1), a new grey prediction model with time-dependent parameters is established. The parameters of model, which can be expressed in polynomial expression, are assumed to be continuous functions of time. The undetermined coefficients of polynomial expression can be solved by the principle of least square method based on the previous information. In the model, both time-varying property and the correcting effect of the forgetting factor are considered, so the prediction error is smaller. The improved model is applied to predict the foundation settlement of Qingshan power plant chimney in Wuhan. The predicted value by the model is compared with those by measuring and three-point method, the result shows that the value derived from three-point method is slight more than the actual settlement, and the value derived from improved GM(1,1) model is close to that from measuring, the predicted error is less than 2%. The example showed that the short-term predicted value from the model is quite exact and the predicted ultimate settlement value can be used as reference for the engineer. Based on the improved GM (1, 1) model, the foundation settlement is predicted from the observed data of the previous 468 days. The result shows that the predicted value from the model is very close to that from the three years observation.
机译:平等的时间间隔原始数据是灰色模型建立的前提。由于在实际使用中的获取数据通常是不等的时间间隔,因此预测结果存在一些错误。在灰色模型GM(1,1)的基础上,建立了具有时间相关参数的新灰度预测模型。假设可以在多项式表达式中表达的模型参数是连续的时间函数。可以通过基于先前信息的最小二乘法的原理来解决多项式表达的未确定系数。在模型中,考虑时变性和遗忘因子的校正效果,因此预测误差较小。改进的模型适用于预测武汉青山电厂烟囱的基础沉降。通过测量和三点法的比较模型的预测值,结果表明,从三点法导出的值略高于实际结算,并且源自改进的GM(1,1)模型接近测量,预测误差小于2%。该示例表明,模型的短期预测值非常精确,并且预测的最终结算值可以用作工程师的参考。基于改进的GM(1,1)模型,从预期468天的观察到数据预测基础结算。结果表明,模型的预测值非常接近三年观察。

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