©2012 university of californiaprepublication data march 2012berkeley sensor & actuator center...
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©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
Wireless Sensing Applications for Critical Industrial Environments
Fabien ChraimProf. Kris Pister
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
2/12
Richmond Refinery Wireless Umbrella
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
3/12
Smart Fence – Proposed System Architecture
50uA / 20mA
10uA / 1 mA
10uA / 2mA
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
4/12
Sequential Hypothesis Testing• Used in radar, clinical trials, channel selection…• Decision making as samples are collected• Two hypotheses
– H0: no (or low) activity– H1: high activity
[1] A.Wald and J.Wolfowitz, “Optimum character of the sequential probability ratio test,” Ann. Math. Statist., vol. 19, pp. 326339, 1948.[2] Fellouris, G.; Moustakides, G.V.; , “Decentralized Sequential Hypothesis Testing Using Asynchronous Communication,” Information Theory, IEEE Transactions on , vol.57, no.1, pp.534-548, Jan. 2011
0 660ms 0 210ms
H1 transmitted
No transmission
H0 transmitted0 660ms
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
5/12
Sequential Hypothesis Testing – Example Outputs
0 8 seconds 0 1.6 seconds
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
6/12
Smart Fence - Continuation• Solar energy scavenging• Enclosure redesign• Air quality monitoring (H2S)
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
7/12
Valves
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
8/12
Valve Position Monitoring• Why?
– Detect abnormalities (alarms)– Better understanding of pressure gradients (plant-wide)
• Goals– Instrument a variety of valves (ball, butterfly, gate, globe)– Report position wirelessly– Accuracy of +/- 5 degrees (or 5%)– No calibration / Easy installation– Lifetime of ~5 years– Cheap
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
9/12
Valve Position Monitoring – Experimental Setup
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
10/12
Valve Position Monitoring – Data (quadrature)
50 60 70 80 90 100 110 120 130 140 150-50
0
50
100Yaw (from gyro)
50 60 70 80 90 100 110 120 130 140 150-200
0
200
400Smoothed accelerometer angle
50 60 70 80 90 100 110 120 130 140 150-100
0
100
200Valve angle estimate (Kalman filter)
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
11/12
Valve Position Monitoring – Data (rotary)
40 60 80 100 120 140 160 180 200
-100
0
100
200Valve angle
©2012 University of California Prepublication Data March 2012 Berkeley Sensor & Actuator Center
Spring 2012
12/12
Project Outlook
• Large fence deployment (Intrusion + gas sensing)• On-site valve testing• Motor Vibration sensing (pumps, small electric motors…)