冻融循环对不同塑性路基土剪切强度的影响研究

Study on Effect of Freeze-thaw Cycles on Shear Strength of Different Plastic Subgrade Soil

摘要:

为了研究冻融循环对不同塑性路基土剪切强度的影响，通过室内三轴试验和冻融循环试验对3种塑性指数的土样进行了研究。结果得到：当冻融循环次数增加时，剪切强度随着塑性指标的增加而有所增大；当塑性指数相同时，剪切强度随冻融次数增加与围压增加改变各不相同，与冻融循环次数成反比，与围压成正比。并且冻融循环6~7次后，3种塑性指数土样的剪切强度的变化均会趋于平缓。

Abstract:

In order to master a large amount of hidden information contained in bridge health monitoring data and improve the shortcomings of traditional structural damage identification methods, a damage identification method based on bridge monitoring data is proposed. The acceleration response is extracted from the finite element simulation data and the actual monitoring data. And the raw data are preprocessed. By using the convolution neural network and stacked auto-encoding neural network, the visual images and time series of monitoring data of Mingzhou Bridge are identified respectively, at the same time, are compared with the identification accuracy of the shallow neural network. The results show that the damage identification methods based on deep learning and monitoring data all have the excellent performances whether through the image identification or through the data sequence identification. The identification accuracy rate is over 85%. Compared with the shallow neural network, the deep neural network has the stronger ability to classify the damage conditions, and the identification accuracy rate is increased by more than 20%.