Please complete the following information
University and Department: Institute of Earthquake Engineering, Dalian University of Technology
Team Members: Ziguang Jia, Dandan Zhang
Faculty Advisors: Hongnan Li, Liang Ren
Primary Email Address: firstname.lastname@example.org
Primary Telephone Number: +86-411-84708512
Project Title: Development of Remote Structural Health Monitoring System Using NI LabVIEW
List all parts (hardware, software, etc.) you used to design and complete your project:
PXI-1033, LabVIEW 8.2
Describe the challenge your project is trying to solve.
Developing a remote monitoring system that can monitor engineering data real-timely and accomplish data acquisition, data storage and data analysis. The remote SHM system can improve work efficiency remarkably and get the information of structural response promptly so as to assess health condition of structure.
Describe how you addressed the challenge through your project.
Using the NI LabVIEW graphical programming environment and hardware platform, we can connect patented FBG strain sensors and temperature sensors to design a remote SHM system with good stability to monitor glass curtain wall of Innovation Campus of DUT.
Taking advantage of commercial off-the-shelf (COTS) technology, we created a new PXI system at a significant cost savings. With a built-in MXI-Express controller in the chassis, the NI PXI-1033 provides a transparent, remote link with up to 110 MB/s sustained throughput. The PXI-1033 chassis features compact, rugged packaging as well as acoustically quiet operation. PXI-1033 is used to collect acceleration, synchronized with MOI sm420 (FBG sensors) acquisition of optical signal.
As the communication is established, in-situ monitoring workstation and remote monitoring control centre work just like two non-interacting equipment. The former can transmit data at all times while the latter one can receive it at once. On the other hand, sending and receiving data are both controlled by bottom layer of TCP/IP, which guarantee accuracy and reliability of data.
Since the health of structures gradually degrades over time, we can compare key health indicators against previously recorded levels by performing remote continuous monitoring and realtime analysis through frequency and wavelet transform.
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