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Design of a Low-Power Wireless Structural Monitoring System for Collaborative Computational Algorithms
Yang Wang, Prof. Kincho H. Law Department of Civil and Environmental Engineering, Stanford University
- Prof. Jerome P. Lynch
Design of a Low-Power Wireless Structural Monitoring System for - - PowerPoint PPT Presentation
Design of a Low-Power Wireless Structural Monitoring System for Collaborative Computational Algorithms Yang Wang, Prof. Kincho H. Law Department of Civil and Environmental Engineering, Stanford University Prof. Jerome P. Lynch Department of
Over 580,000 highway bridges in U.S. mandated for biannual
Wireless SHM prototype system Jointly developed by researchers in Stanford University and the University of Michigan
Requirements for long-distance high-speed wireless data
Hardware Restricted communication range Limited bandwidth Unreliable wireless transmission Software Difficulty for data synchronization Difficulty for robust communication design
Power consumption: 75 – 80mA when active; 0.1mA standby Communication range: 90m indoor, 300m outdoor 16bit Analog-To-Digital conversion, 4 A2D channels Local data processing Point-to-multipoint, and peer-to-peer communication Low hardware cost
Broadcast Beacon signal to all WSUs Begin sensor data sampling and storage Verify with each WSU if it received the Beacon signal A WSU didn't receive the Beacon signal Inform WSUs* one by one to restart * WSU: Wireless Sensing Unit ** CS: Central Server
Y Received beacon signal
Wait and Respond to Beacon verification Restart and acknowledge with CS**, wait for Beacon signal Wait for data collection command from CS Receive restart command
Y
Start data collection from WSUs one by one, and round by round Transmit data to CS Received data collection request and data is ready
Central Server Wireless Sensing Unit
Finish one round of data transmission Wireless communication and its direction
Y Y
A pproxi m at e begi nni ng synchroni zat i on preci si on: 20 m i cro- S econds.
1 2 14 12 11 10 9 8 7 6 5 4 3 13 N O R TH P i er P i er P i er A but m ent 46.0m 18.7m 18.7m
0.5 mg 50 µg RMS Resolution (Noise Floor) 80 Hz 2000 Hz Bandwidth 0.7 V/g 10 V/g Sensitivity 3 g 1 g Maximum Range PCB MEMS Capacitive (Wireless System) PCB Piezoelectric (Cable System) Sensor Property
155 160 165 170 175 180 185 190
0.02 0.04 KAIST Data Aquisition System Time (sec) Acceleration (g) Sensor Location #8 155 160 165 170 175 180 185 190
0.02 0.04 Wireless Data Aquisition System Time (sec) Acceleration (g) Sensor Location #8
Wireless System Wire-based System
Difference in sensors and signal conditioning
2 4 6 8 10 12 14 16 1 2 3 4 FFT - KAIST DAQ Frequency (Hz) Magnitude Sensor Location #8 2 4 6 8 10 12 14 16 0.2 0.4 0.6 0.8 FFT - Wireless DAQ Frequency (Hz) Magnitude Sensor Location #8
Wireless System Wire-based System
Sensor signal conditioning Greater wireless communication range, higher data rate Large-scale data collection from densely allocated sensors Local data analysis and damage identification algorithm
National Science Foundation CMS-9988909 and CMS-0421180 The Office of Technology Licensing Stanford Graduate Fellowship The University of Michigan Rackham Grant and Fellowship Program