Post Alarm Analysis using Active Connection

93 Pages·2013·2.37 MB·English

POST ALARM ANALYSIS USING ACTIVE CONNECTION
A Thesis submitted to the
Division of Research and Advanced Studies of the University of Cincinnati
In partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE (M.S.)
Department of Electrical Engineering
Of the College of Engineering & Applied Science
2013
By
Vindhya Vodela
B.E., Osmania University 2010
Committee Chair: Arthur J. Helmicki, Ph.D.
Abstract:
UCII has been involved with Bridge Monitoring for over two decades and a Bridge
Health Monitoring System for the Ironton – Russell Bridge was developed and is
being maintained by UCII. The Bridge Monitoring System collects data from the
sensors placed on the bridge and sends real time updates regarding any abnormal
behavior. Whenever an abnormal behavior is detected, ‘Alarms’ are sent out via
email and in order to be better understand the alarm scenario, the feature “Active
Connection” was developed. Active Connection involves establishing a dynamic
connection to the system on the bridge which makes two way communication
possible to get additional data points when the Alarms occur. By utilizing this
connection, additional data points are then obtained which are analyzed using
sequential analysis and a severity level for the alarm is declared. This feature of
active connection is helpful in better assessing the alarm situation and improving
the reliability of the bridge monitoring system on the Ironton – Russell Bridge.

Table of Contents:
Chapter 1: Introduction & Problem Statement……………………………………..1
Section 1.1: Overview of the Monitoring System at UCII………………......2
Section 1.2: Ironton-Russell Bridge…………………………………………2
Section 1.3: Bridge Monitoring System……………………………………..3
Section 1.4 Active Connection………………………………………………5
Chapter 2: Literature Review……………………………………………………..11
Chapter 3: Sequential Analysis……………………………………………………17
Section 3.1: Sequential Analysis for Active Connection…………………..17
Section 3.2: Active Connection…………………………………………….19
Section 3.3 Sequential Probability Ratio Test……………………………...22
Section 3.3.1 Gaussian distribution for the gages on Ironton Russell
Bridge………………………………………………………………..26
Section 3.4 Choosing the Limits A & B……………………………………32
Section 3.5 Probability Calculations……………………………………….36
Chapter 4: Implementation of Active Connection………………………………...42
Section 4.1 Overview of Monitoring System on Ironton-Russell Bridge….42
Section 4.2 Hardware Upgrade…………………………………………….43
Section 4.2.1 Vibrating Wire Gage………………………………….44
Section 4.2.2 Multiplexer……………………………………………44
Section 4.2.3 Data Logger…………………………………………...45
Section 4.2.4 Network Device………………………………………47
Section 4.2.5 Digital Signal Processing Equipment………………...48
Section 4.3 Programming Data Acquisition System……………………….50
Section 4.3.1 CRBasic Programming Language…………………….50
Section 4.4 Layout of the Equipment………………………………………51
Section 4.4.1 SDI-12 Protocol………………………………………52
Section 4.5 Implementation………………………………………………...54
Section 4.6 Timeline for Processing……………………………………….56
Section 4.7 Active Connection & Equipment Upgrade……………………59
Section 4.8 Processes Involved in Implementation of Active Connection...60
Section 4.9 Results…………………………………………………………68
Chapter 5: Conclusions & Future Work………………………………………......74
Section 5.1 Conclusions……………………………………………………74
Section 5.2 Future Work…………………………………………………...75
Bibliography……………………………………………………………………....77
Appendix………………………………………………………………………….80
List of Figures:
Figure 1.1 Ironton Russell Bridge…………………………………………………………………2
Figure 1.2 Monitoring System Overview for Ironton Russell Bridge…………………………….3
Figure 1.3 Active Connection Overview………………………………………………………….5
Figure 2.1 Reliability Curve during Useful life for a Structure………………………………….14
Figure 3.1 Alarm on Gage L23L24TW_OH due to Temperature Changes……………………..18
Figure 3.2 Linear Regression for a Gage which has an Outlier…………………………………20
Figure 3.3 Residual distribution for Gage L18U18S_KY (along with its shifted version at Delta
of Concern) …………………….………………………………………………………………..28
Figure 3.4 Residual distribution for Gage L11L12TE_OH (along with its shifted version at Delta
of Concern) ……………………………………………………………………………………...29
Figure 3.5 Representation of Decision Error…………………………………………………….33
Figure 3.6 Illustration of Residual & Alarm distribution………………………………………..36
Figure 3.7 Table Showing Delta of Concern for different members of the Ironton – Russell
Bridge…………………………………………………………………………………………….38
Figure 3.8 Plot of the Log Likelihood ratio for the member U6U7_KY (corresponding to the
Delta of Concern)………………………………….…………………………………………......39
Figure 3.9 Plot of the Log Likelihood ratio for the member U6U7_KY (corresponding
to16*sigma)………………………………….…………………………………………...............40
Figure 4.1 Gage Locations for Ironton – Russell Bridge………………………………………...42
Figure 4.2 Vibrating Wire Gage…………………………………………………………………45
Figure 4.3 Multiplexer…………………………………………………………………………...45
Figure 4.4 Data Logger Upgrade………………………………………………………………...46
Figure 4.5 Network Device Upgrade…………………………………………………………….47
Figure 4.6 Signal Processing Upgrade…………………………………………………………...48
Figure 4.7 Diagnostic Tool Frequency Response of Signal on the Gage………………………..49
Figure 4.8 Wiring Diagram for Data Acquisition System……………………………………….51
Figure 4.9 SDI-12 Bus…………………………………………………………………………...53
Figure 4.10 Timeline for Processing……………………………………………………………..56
Figure 4.11 Flow Chart for Active Connection………………………………………………….61
Figure 4.12 Severity Levels……………………………………………………………………...67
Figure 4.13 Plot of the Log Likelihood ratio for the member U6U7_KY (corresponding to the
4*sigma).………...…………………….………….…………………………………….……......39
Figure 4.14 Strain Graph for Gage L14U14S_KY [4*sigma Violation]…………………..…….68
Figure 4.15 Active Connection Data for L14U14S _KY………………………………………..70
Figure 4.16 Strain Graph for M5L6B_OH [4*sigma Violation]………………………………...71
Figure 4.17 Active Connection Data for M5L6B_OH…………………………………………..72
CHAPTER 1
Introduction and Problem Statement
1.1 Overview of the Monitoring System at UCII:
UCII has been involved with Bridge Health Monitoring for over a two decades and the aim
objective in Bridge Monitoring is to find abnormalities in the functioning of the bridge and there
by detect any changes or damage conditions at the bridge.
Since its inception, UCII has been involved in the testing and evaluation of several structures
including more than 60 bridges in the state of Ohio. UCII has developed and applied a number of
unique experimental and analytic tools in the evaluation of both laboratory model and full-scale
civil infrastructure systems including: modal testing, truckload testing, and field calibrated finite
element modeling. [1]
1.2 Ironton – Russell Bridge :
The Ironton Russell Bridge was opened in 1922 along the Ohio River. The Bridge is about 2400
feet long, has two lanes and connects the cities Ironton, OH and Russell, KY. The Ironton –
Russell Bridge is shown in Figure 1.1.
The main span consists of a three span cantilever through trusses supported by five concrete
piers and a suspended center span [3]. A long term bridge monitoring system was developed by
UCII for the Ironton – Russell Bridge.

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Figure 1.1 Ironton – Russell Bridge [3]
1.3 Bridge Monitoring System
Data Acquisition, Data Cleansing and Data Analysis are the steps in this Process. All three
processes are important in the system and all three are inter dependent. Bridge Monitoring
system collects the data from the sensors on the bridge, checks for any invalid data and
immediately the processing is done with the cleansed data. It can be considered as a Real Time
system, because the data collection, and processing are done scheduled times and the results of
this processing are immediately available for use of ODOT officials. It is very useful because the
system can alert the officials as soon as a change or damage is detected.
Data Acquisition involves collecting Data from the sensors (which are placed at specific
members of the bridge) at periodic intervals and storing them in a Database for further
processing for Data Analysis.
Data Cleansing ensures that there is no data corruption and all invalid data or any kind of noisy
data is removed before the data is processed and analyzed to get information. Hence it is
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