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一种数据挖掘解释方法,通过结合DBSCAN和Findpeaks函数来解释路面动态响应信号

Hailong Liu^1,2, Ruqing Yao^2,3, Chunyi Cui^1,2

¹College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China.

Sensors (Basel, Switzerland)

|February 10, 2024

概括

本研究引入了一种用于实时监测青路面的新方法,使用DBSCAN和findpeaks来检测车辆负载数据中的异常. 这提高了应变特征提取的准确性,以更好地管理路面.

科学领域:

土木工程土木工程是指土木工程.
数据科学数据科学数据科学
材料科学材料科学材料科学

背景情况:

在繁忙的交通中,青路面应变数据经常显示出由于复杂的环境而导致的波动和异常.
对异常数据进行有效的实时诊断对于准确的路面监测和维护至关重要.

研究的目的:

为青路面开发一个实时异常数据诊断系统.
从传感器数据中有效提取动态应变特征.
提高路面监测数据处理和信息利用的效率.

主要方法:

使用低通波器进行数据无声化.
一个改进的DBSCAN (基于密度的应用程序与噪音的空间聚类) 算法与K-Dist方法用于异常检测.
一个精细的findpeaks函数用于对被删除数据的自适应特征提取.

主要成果:

增强的DBSCAN算法有效地检测出道路动态响应信号中的异常数据.
精致的findpeaks功能准确地识别了峰值和应变信号峰值,即使是复杂的多轴卡车.
拟议的方法在处理大型数据集和提取关键特征方面表现出有效性.

结论:

开发的方法提供了一种有效的实时异常数据诊断方法,用于青路面监测.
使用DBSCAN和findpeaks精确的特征提取可以增强路面管理和维护策略.
这项研究有助于在路面工程领域更有效地处理和利用数据.

关键词:

在 DBSCAN 算法.异常数据诊断诊断异常数据适应性特征提取适应性特征提取路面的动态反应.在 findpeaks 函数中找到峰值.

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