智能集料监测颗粒内部变形数据

智能集料封装结构设计：通过工业CT扫描方法获取集料断面图像构建智能集料封装结构模型，通过VG Studio MAX2.2体积分析软件导出集料二维断面灰度图像并进行二值化处理然后重构导出封装结构网格模型并进行3D打印。
仪器振动噪声研究：数据来源于室内试验，利用车辙试验仪和智能集料，测定仪器振动噪声并利用快速傅里叶变换方法抑制仪器振动噪声。
智能集料监测颗粒骨架稳定性试验：数据来源于室内试验，利用智能集料监测荷载作用下颗粒骨架变形状况，并通过智能集料信号判断骨架稳定性。
智能集料监测沥青混合料车辙变形：数据来源于室内试验，采集沥青混合料车辙变形过程中智能集料信号，并通过灰关联系数法和非线性回归方法构建智能集料监测车辙变形模型，分析模型与实测值的关系。

Design of Intelligent Aggregate Packaging Structure: The intelligent aggregate packaging structure model is constructed by acquiring cross-sectional images of aggregates via industrial CT scanning. The 2D cross-sectional grayscale images of aggregates are exported using VG Studio MAX2.2 volume analysis software, followed by binarization processing, then the grid model of the packaging structure is reconstructed and exported for 3D printing.
Instrument Vibration Noise Research: The data is sourced from laboratory tests. The rutting tester and intelligent aggregates are employed to measure the instrument's vibration noise, and the Fast Fourier Transform method is utilized to suppress such noise.
Intelligent Aggregate Monitoring of Particle Skeleton Stability Test: The data originates from laboratory tests. Intelligent aggregates are used to monitor the deformation state of the particle skeleton under loading, and the stability of the skeleton is evaluated based on the signals from the intelligent aggregates.
Intelligent Aggregate Monitoring of Asphalt Mixture Rutting Deformation: The data is derived from laboratory tests. The signals of intelligent aggregates during the rutting deformation process of asphalt mixtures are collected. An intelligent aggregate monitoring model for rutting deformation is constructed via the Grey Correlation Coefficient Method and Nonlinear Regression Method, and the correlation between the model and the measured values is analyzed.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于道路工程中的智能集料技术，通过工业CT扫描、3D打印和车辙试验等方法，监测颗粒内部变形和沥青混合料车辙变形。数据集包含智能集料封装结构设计、仪器振动噪声抑制以及基于灰关联系数法和非线性回归的变形模型构建，旨在支持道路基础设施的智能感知研究。