煤矿皮带系统监测预警分析数据集合

1、基础处理：采用Excel完成数据录入、字段分类（按“参数类型/监测维度”划分，如无符号16位值-运行时间、二进制变量-保护状态）与可视化查看，快速识别参数关联关系；2、深度处理：使用Python（集成pandas库）开展数据清洗——剔除重复采集的启停状态记录（如多次记录的“皮带停止”）、按“无符号16位值/二进制变量/ 32位浮点数IEEE 754”分类标注参数，同时标记异常值（如电机电流/电压/功率长期为0时，核验是否为设备停机或传感器故障）。

1. Basic Processing: Utilize Excel for data entry, field classification (categorized by "parameter type/monitoring dimension", e.g., unsigned 16-bit value - running time, binary variable - protection status) and data visualization, to quickly identify the correlations between parameters; 2. Advanced Processing: Adopt Python (integrated with the pandas library) to carry out data cleaning: eliminate repeatedly collected start-stop status records (such as multiple recorded "belt stopped" entries), classify and label parameters in accordance with the categories of "unsigned 16-bit value / binary variable / 32-bit IEEE 754 floating-point number", and flag abnormal values (e.g., when the motor current, voltage and power stay at 0 for an extended period, verify whether it is due to equipment shutdown or sensor malfunction).

搜集汇总

背景与挑战

背景概述

该数据集规模为1GB，每日更新，专注于煤矿皮带运输系统的安全监测与故障预警。它通过多维度参数（如运行状态、保护装置数据）支持全流程应用，包括实时监控、预警分析和运维优化，数据处理采用Excel和Python工具进行清洗和分类。