动载螺栓故障特征数据

本数据用于轨道交通动载螺栓的故障特征分析，通过超声无损检测判断列车动载螺栓故障特征，分析螺栓故障原因并指导轨道交通列车的检修工作，进一步保障旅客的人身财产安全。1、数据收集与清洗：对高速列车CRH380系列车体及转向架部位的螺栓不定时的发射收集超声信号测得动载螺栓故障特征，利用对数据集进行清洗，去除调试设备时产生的异常数据并处理缺失值。2、数据转换: 将检测得到的数据进行归集，根据螺栓预紧力公式：σ=（A/B-C*∆t）*∆t。式中A、B、C均为预紧力系数（需根据螺栓特性标定），σ为螺栓预紧力大小，∆t为时延。通过不定时的发射超声波监测螺栓预紧力，分析总结其故障特征行为。3、数据应用：对轨道交通动载螺栓的故障特征分析，通过超声无损检测判断列车动载螺栓故障特征，分并指导轨道交通列车的检修工作，进一步保障旅客的人身财产安全。

This dataset is designed for fault feature analysis of dynamically loaded bolts in rail transit systems. It utilizes ultrasonic non-destructive testing to identify fault characteristics of train dynamically loaded bolts, analyzes the causes of bolt failures, guides the maintenance of rail transit trains, and further safeguards the personal and property safety of passengers.
1. Data Collection and Cleaning: Ultrasonic signals are transmitted and collected irregularly from bolts on the carbody and bogie of CRH380 series high-speed trains to measure fault features of dynamically loaded bolts. The dataset is cleaned to remove abnormal data generated during equipment debugging and handle missing values.
2. Data Transformation: The detected data is aggregated. According to the bolt preload formula: σ = (A/B - C×Δt) × Δt. Here, A, B, and C are preload coefficients that need to be calibrated based on bolt characteristics, σ represents the magnitude of the bolt preload, and Δt is the time delay. The bolt preload is monitored by transmitting ultrasonic waves irregularly, and their fault feature behaviors are analyzed and summarized.
3. Data Application: This dataset supports fault feature analysis of dynamically loaded bolts in rail transit, identifies the fault features of train dynamically loaded bolts through ultrasonic non-destructive testing, guides the maintenance work of rail transit trains, and further ensures the personal and property safety of passengers.

搜集汇总

数据集介绍

特点

该数据集名为'动载螺栓故障特征数据'，由四川声探科技有限公司提供，包含39954条数据，主要用于轨道交通动载螺栓的故障特征分析。通过超声无损检测技术收集和清洗数据，数据更新频次不定时，应用场景包括分析螺栓故障原因并指导轨道交通列车的检修工作。