A multi-time scale vibration surveillance system for third-party threats on urban pipeline

IF 2.1 3区 工程技术 Q2 ENGINEERING, CIVIL
Suzhen Li, Zelong Liu, Renzhu Peng, Yan Zhang
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引用次数: 1

Abstract

Third-party interference caused by construction activities have seriously jeopardized the security of underground pipelines. Following the process of "signal collection—feature extraction and selection—multi-time scale identifying— combining results by voting", this paper proposes a multi-time scale surveillance system for interference prevention of thirdparty threats on the nearby pipeline by using ground vibration monitors. The system focuses on the two major urban construction activities induced by excavator breaking hammers and road cutters, and presents excellent performance under the noise of traffic and pedestrian. Three features including the short-time zero-crossing rate, subset differential parameter and the Mel frequency cepstrum coefficients are selected by the analysis of the maximal information coefficient and feature importance for identifying the patterns of different third-party activities. The crucial part of the surveillance system consists of the two random forest-based classifiers trained by 0.5 s samples and 8 s samples respectively, and the alarm depends on the voting of the two classifiers, which brings the perspectives on different time scales for decision making. In the test, 96.14% of the threat vibration signals can be detected, while only 0.45% of the environmental noise signals cause false alarms.
针对城市管道第三方威胁的多时间尺度振动监测系统
施工活动造成的第三方干扰严重危害了地下管线的安全。根据“信号采集——特征提取与选择——多时间尺度识别——投票结合结果”的过程,本文提出了一种利用地面振动监测仪对附近管道第三方威胁进行干扰预防的多时间尺度监测系统。该系统专注于挖掘机破碎锤和道路切割机引发的两大城市建设活动,在交通和行人的噪音下表现出优异的性能。通过对最大信息系数和特征重要性的分析,选择了短时过零率、子集微分参数和梅尔频率倒谱系数三个特征,用于识别不同第三方活动的模式。监控系统的关键部分由两个分别由0.5s样本和8s样本训练的随机森林分类器组成,警报取决于两个分类器的投票,这为决策带来了不同时间尺度的视角。在测试中,96.14%的威胁振动信号可以被检测到,而只有0.45%的环境噪声信号会引起误报。
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来源期刊
Smart Structures and Systems
Smart Structures and Systems 工程技术-工程:机械
CiteScore
6.50
自引率
8.60%
发文量
0
审稿时长
9 months
期刊介绍: An International Journal of Mechatronics, Sensors, Monitoring, Control, Diagnosis, and Management airns at providing a major publication channel for researchers in the general area of smart structures and systems. Typical subjects considered by the journal include: Sensors/Actuators(Materials/devices/ informatics/networking) Structural Health Monitoring and Control Diagnosis/Prognosis Life Cycle Engineering(planning/design/ maintenance/renewal) and related areas.
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