破碎速度对碎石化后碎石颗粒级配范围的影响分析数据

本数据聚焦于分析破碎速度对碎石化后碎石颗粒级配范围的影响，揭示了破碎速度与碎石颗粒分布特性之间的定量关系。公司可通过本数据分析不同破碎速度对碎石颗粒级配范围的影响规律，精准调控破碎设备的操作参数，提升碎石施工质量，优化碎石的颗粒分布和均匀性。本数据可以给碎石施工领域的相关科研工作者、技术研发人员、工程监理人员、工程质量检验人员等使用，为他们围绕破碎速度工况、碎石颗粒级配范围等角度开展碎石工程的相关预测分析、质量控制、科学研究、技术优化等工作提供支撑。1.数据采集：记录不同破碎速度工况下碎石化处理后碎石颗粒的级配范围测试数据，具体包括测试点编号、测试时间、破碎速度/m/s、碎石颗粒级配范围/%等字段。
2.数据预处理：(1)对采集的数据进行去噪处理，确保数据准确性。(2)把历史采集的数据（包含本次采集）进行聚合，形成数据集X，并针对数据集X中的碎石颗粒级配范围字段，计算出其平均值。
3.计算线性回归斜率a和截距b：基于数据集X（以破碎速度为自变量、碎石颗粒级配范围为因变量），运用SLOPE函数，基于最小二乘法原理确定斜率a，运用INTERCEPT函数确定截距b。斜率a表示单位破碎速度变化对碎石颗粒级配范围的影响程度，截距b表示基准破碎速度下碎石化后碎石颗粒的级配范围值。
4.结果运用：（1）计算比例系数k：k=|a/碎石颗粒级配范围平均值|×100%；（2）若k≥10%，则判定为“高影响”，若5%≤k＜10%，则判定为“中影响”，若k＜5%，则判定为“低影响”。

This dataset focuses on analyzing the impact of crushing speed on the particle size gradation range of crushed stones after rubblization, and reveals the quantitative relationship between crushing speed and the distribution characteristics of crushed stone particles. Enterprises can use this dataset to analyze the influence law of different crushing speeds on the particle size gradation range of crushed stones, accurately adjust the operating parameters of crushing equipment, improve the quality of crushed stone construction, and optimize the particle distribution and uniformity of crushed stones. This dataset is applicable to relevant researchers, technical R&D personnel, engineering supervisors, engineering quality inspectors and other practitioners in the crushed stone construction field, and provides support for them to carry out related work such as predictive analysis, quality control, scientific research and technical optimization of crushed stone engineering from the perspectives of crushing speed working conditions and particle size gradation range of crushed stones.
1. Data Collection: Record the test data of the particle size gradation range of crushed stones after rubblization under different crushing speed working conditions, specifically including fields such as test point number, test time, crushing speed (unit: m/s), and particle size gradation range of crushed stones (unit: %).
2. Data Preprocessing: (1) Denoise the collected data to ensure data accuracy. (2) Aggregate the historically collected data (including this collection) to form dataset X, and calculate the average value of the particle size gradation range field in dataset X.
3. Calculation of Linear Regression Slope a and Intercept b: Based on dataset X (with crushing speed as the independent variable and particle size gradation range of crushed stones as the dependent variable), use the SLOPE function to determine the slope a based on the principle of least squares, and use the INTERCEPT function to determine the intercept b. The slope a represents the influence degree of unit crushing speed change on the particle size gradation range of crushed stones, and the intercept b represents the gradation range value of crushed stone particles after rubblization under the reference crushing speed.
4. Result Application: (1) Calculate the proportional coefficient k: k = |a / average value of particle size gradation range of crushed stones| × 100%; (2) If k ≥ 10%, it is judged as "high impact"; if 5% ≤ k < 10%, it is judged as "medium impact"; if k < 5%, it is judged as "low impact".