Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

doi:10.3390/s91007943

Cited by 41 publications

(25 citation statements)

References 6 publications

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“…The main challenge for NOR is to increase the number of successful axle identifications, particularly when using less suitable structures, such as integral bridges. Current axle detection data generally require significant post processing to identify axles, such as wavelet transforms but the signals are still sensitive to interference from bridge vibrations [21]. The figures provided in this section confirm the suitability of FOS to provide accurate axle detection in a particularly stiff structure.…”

Section: Nor Axle Detectionsupporting

confidence: 58%

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

Lydon

Robinson

Taylor

et al. 2017

J Civil Struct Health Monit

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Bridge weigh-in-motion (B-WIM) systems provide a non-destructive means of gathering traffic loading information by using an existing bridge as a weighing scale to determine the weights of vehicles passing over. In this research critical locations for sensors for the next-generation B-WIM were determined from a full 3D explicit finite element analysis (FEA) model. Although fiber optic sensors (FOS) have become increasingly popular in SHM systems there are currently no commercially available fiber optic WIM systems available. The FEA in this research facilitated the development of the first ever full fiber optic B-WIM and its potential has been demonstrated with the site installation of this system. The system combined nothing-on-the-road axle detection and alternative methods of measuring strain at the supports. The system was installed on a 20-m span beam and slab RC bridge in Northern Ireland and the results presented in this paper confirm the suitability of FOS in providing the clear defined peaks required for accurate axle detection in B-WIM.

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Section: Nor Axle Detectionsupporting

confidence: 58%

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

Lydon

Robinson

Taylor

et al. 2017

J Civil Struct Health Monit

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“…Untuk kasus sistem cerdas yang diterapkan pada sistem pengawasan kesehatan struktur jembatan, telah dikembangkan wireless intelligent sensor and actuator network [4] dan statistical classifier seperti support vector machine (SVM), Gaussian mixture model (GMM), dan hidden Markov model (HMM) [5]. Penelitian terkait dengan area komputasi di jaringan sensor nirkabel juga telah dikembangkan untuk kasus pengawasan kesehatan struktur jembatan, khususnya untuk kualitas pemrosesan data [6], [7]. Mekanisme pemrosesan data di jaringan sensor nirkabel beserta pengembangan peranti keras yang mendukung sistem pengawasan kesehatan struktur jembatan juga menjadi perhatian di penelitian ini [8]- [12].…”

Section: Pendahuluanunclassified

Sistem Penilaian Kondisi Jembatan Menggunakan Respons Dinamik dengan Wireless Sensor Network

Putra¹,

Sani²,

Nurwijaya³

et al. 2018

Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

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Wireless Sensor Network (WSN) is small embedded devices deployed in large scale network and has capability to sense, compute, and communicate with others. It combines modern sensor, microelectronic, computer, communication, and distributed processing technology. It takes into account in several aspects of live especially in structural health monitoring system of bridge. Due to environmental circumstance, a bridge should be monitored to make sure that it can perform its service safely. Therefore, it is necessary to develop WSN application to monitor bridge condition and send warning message to control room if the bridge is under abnormal condition. This paper proposes the development of automatic WSN system for measuring the level of bridge structural health based on its dynamic responses. The main contribution of this work is developing WSN system for vibration-based bridge condition assessment in which identifies the bridge's fundamental frequency and mode shape. Experimental result shows that the fundamental frequency measured by our proposed system is close to the value analyzed using finite element analysis (FEA) and according to Modal Assurance Criteriation (MAC), our proposed measurement system has correlation with FEA.

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“…Vehicle loads including traffic flow, vehicle speed and vehicle weight of each axle, numbers of axles are often acquired by a weigh-in-motion (WIM) system [ 55 , 56 ]. A WIM system should be installed in all lanes of a cross section of an arch bridge.…”

Section: Deployment Of Shm Systems For Long-span Arch Bridgesmentioning

confidence: 99%

Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study

Chen

Zhou

Wang

et al. 2017

Sensors

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Structural health monitoring (SHM) technology for surveillance and evaluation of existing and newly built long-span bridges has been widely developed, and the significance of the technique has been recognized by many administrative authorities. The paper reviews the recent progress of the SHM technology that has been applied to long-span bridges. The deployment of a SHM system is introduced. Subsequently, the data analysis and condition assessment including techniques on modal identification, methods on signal processing, and damage identification were reviewed and summarized. A case study about a SHM system of a long-span arch bridge (the Jiubao bridge in China) was systematically incorporated in each part to advance our understanding of deployment and investigation of a SHM system for long-span arch bridges. The applications of SHM systems of long-span arch bridge were also introduced. From the illustrations, the challenges and future trends for development a SHM system were concluded.

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Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

Cited by 41 publications

References 6 publications

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

Improved axle detection for bridge weigh-in-motion systems using fiber optic sensors

Sistem Penilaian Kondisi Jembatan Menggunakan Respons Dinamik dengan Wireless Sensor Network

Deployment of a Smart Structural Health Monitoring System for Long-Span Arch Bridges: A Review and a Case Study

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