Ms. Yilan Zhang Profile

Yilan Zhang

at Univ of Michigan

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Author

Publications (6)

Proceedings Article | 20 April 2016 Paper

A cloud-based information repository for bridge monitoring applications

Seongwoon Jeong, Yilan Zhang, Rui Hou, Jerome Lynch, Hoon Sohn, Kincho Law

Proceedings Volume 9803, 980313 (2016) https://doi.org/10.1117/12.2219064

KEYWORDS: Bridges, Databases, Sensors, Clouds, Data modeling, Roads, Finite element methods, Standards development, Systems modeling, Data storage

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Proceedings Article | 1 April 2015 Paper

Automated outlier detection framework for identifying damage states in multi-girder steel bridges using long-term wireless monitoring data

Sean O'Connor, Yilan Zhang, Jerome Lynch

Proceedings Volume 9437, 94370N (2015) https://doi.org/10.1117/12.2086273

KEYWORDS: Bridges, Sensors, Data modeling, Data processing, Composites, General packet radio service, Corrosion, Statistical analysis, Data storage, Structural health monitoring

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Proceedings Article | 10 April 2014 Paper

Automated analysis of long-term bridge behavior and health using a cyber-enabled wireless monitoring system

Sean O'Connor, Yilan Zhang, Jerome Lynch, Mohammed Ettouney, Gwen van der Linden

Proceedings Volume 9063, 90630Y (2014) https://doi.org/10.1117/12.2045244

KEYWORDS: Bridges, Sensors, Data modeling, Composites, Structural health monitoring, Data acquisition, Inspection, Sensor networks, Roads, Damage detection

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A worthy goal for the structural health monitoring field is the creation of a scalable monitoring system architecture that abstracts many of the system details (e.g., sensors, data) from the structure owner with the aim of providing “actionable” information that aids in their decision making process. While a broad array of sensor technologies have emerged, the ability for sensing systems to generate large amounts of data have far outpaced advances in data management and processing. To reverse this trend, this study explores the creation of a cyber-enabled wireless SHM system for highway bridges. The system is designed from the top down by considering the damage mechanisms of concern to bridge owners and then tailoring the sensing and decision support system around those concerns. The enabling element of the proposed system is a powerful data repository system termed SenStore. SenStore is designed to combine sensor data with bridge meta-data (e.g., geometric configuration, material properties, maintenance history, sensor locations, sensor types, inspection history). A wireless sensor network deployed to a bridge autonomously streams its measurement data to SenStore via a 3G cellular connection for storage. SenStore securely exposes the bridge meta- and sensor data to software clients that can process the data to extract information relevant to the decision making process of the bridge owner. To validate the proposed cyber-enable SHM system, the system is implemented on the Telegraph Road Bridge (Monroe, MI). The Telegraph Road Bridge is a traditional steel girder-concrete deck composite bridge located along a heavily travelled corridor in the Detroit metropolitan area. A permanent wireless sensor network has been installed to measure bridge accelerations, strains and temperatures. System identification and damage detection algorithms are created to automatically mine bridge response data stored in SenStore over an 18-month period. Tools like Gaussian Process (GP) regression are used to predict changes in the bridge behavior as a function of environmental parameters. Based on these analyses, pertinent behavioral information relevant to bridge management is autonomously extracted.

Proceedings Article | 11 April 2013 Paper

Cyber-infrastructure design and implementation for structural health monitoring

Gwendolyn van der Linden, Abbas Emami-Naeini, Yilan Zhang, Jerome Lynch

Proceedings Volume 8694, 869419 (2013) https://doi.org/10.1117/12.2010445

KEYWORDS: Databases, Bridges, Data modeling, Sensors, Data storage, Human-machine interfaces, Structural health monitoring, Inspection, Data processing, Finite element methods

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Proceedings Article | 5 April 2012 Paper

Distributed cyberinfrastructure tools for automated data processing of structural monitoring data

Yilan Zhang, Masahiro Kurata, Jerome Lynch, Gwendolyn van der Linden, Hassan Sederat, Atul Prakash

Proceedings Volume 8347, 83471Y (2012) https://doi.org/10.1117/12.916050

KEYWORDS: Sensors, Bridges, Databases, Data processing, Sensor networks, Inspection, Data conversion, Structural health monitoring, Data acquisition, Data modeling

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Proceedings Article | 18 April 2011 Paper

Long-term assessment of an autonomous wireless structural health monitoring system at the new Carquinez Suspension Bridge

Masahiro Kurata, Junhee Kim, Yilan Zhang, Jerome Lynch, G. van der Linden, Vince Jacob, Ed Thometz, Pat Hipley, Li-Hong Sheng

Proceedings Volume 7983, 798312 (2011) https://doi.org/10.1117/12.880145

KEYWORDS: Bridges, Sensors, Sensor networks, Data communications, Data modeling, Databases, Wireless communications, Inspection, System identification, Telecommunications

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A dense network of sensors installed in a bridge can continuously generate response data from which the health and condition of the bridge can be analyzed. This approach to structural health monitoring the efforts associated with periodic bridge inspections and can provide timely insight to regions of the bridge suspected of degradation or damage. Nevertheless, the deployment of fine sensor grids on large-scale structures is not feasible using wired monitoring systems because of the rapidly increasing installation labor and costs required. Moreover, the enormous size of raw sensor data, if not translated into meaningful forms of information, can paralyze the bridge manager's decision making. This paper reports the development of a large-scale wireless structural monitoring system for long-span bridges; the system is entirely wireless which renders it low-cost and easy to install. Unlike central tethered data acquisition systems where data processing occurs in the central server, the distributed network of wireless sensors supports data processing. In-network data processing reduces raw data streams into actionable information of immediate value to the bridge manager. The proposed wireless monitoring system has been deployed on the New Carquinez Suspension Bridge in California. Current efforts on the bridge site include: 1) long-term assessment of a dense wireless sensor network; 2) implementation of a sustainable power management solution using solar power; 3) performance evaluation of an internet-enabled cyber-environment; 4) system identification of the bridge; and 5) the development of data mining tools. A hierarchical cyber-environment supports peer-to-peer communication between wireless sensors deployed on the bridge and allows for the connection between sensors and remote database systems via the internet. At the remote server, model calibration and damage detection analyses that employ a reduced-order finite element bridge model are implemented.

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