structural health monitoring using statistical pattern recognition

7/30/2019 Structural Health Monitoring Using Statistical Pattern Recognition

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Structural Health Monitoring Using

Statistical Pattern Recognition

Los Alamos Dynamics Structural Dynamics and Mechanical Vibration Consultants

Presented by

Charles R. Farrar, Ph.D., P.E. and Hoon Sohn, Ph. D.


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Structural Health Monitoring using Statistical Pattern Recognition

Course Demo 2

Overview of the Course

Summarize the rapidly evolving field of structural

health monitoring.

Summarize the historical developments of this technology. Provide overview of current methods.

Show real world application of this technology.

Identify the limitations of the current technology.

Present cutting edge statistical tools for diagnosis.

Discuss current and future research directions.

Course Theme: Structural Health Monitoring is aproblem in statistical pattern recognition.


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Course Demo 3

Actual

loadingand operating

conditions

Usage Monitoring

System

Response

measurement

Inputmeasurement

1. Instrumentation

2. Data management

System

assessment

model

1. Modeling & simulation

2. Data interrogation

Structural Health

MonitoringDamage Prognosis

1. Modeling & simulation


3. Embedded processing

Predictivemodel

Predictive

loading

model


Future Loading Estimation

Where Does Structural Health Monitoring Fit In The Big Picture


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Course Demo 4

Process of Structural Health Monitoring

Vibration-based damage detection is part of the more

general process of Structural Health Monitoring

The Structural Health Monitoring process includes:1. Operational evaluation of the structure

2. Data acquisition and cleansing

3. Feature extraction and information condensation

4. Statistical model development


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Course Demo 5

Rotating Machinery Application

Frequency in Hz

0 1000 2000 3000 4000 5000

0

0

0

0ax Amp.38

20-MAR-96

21-MAR-96

21-MAR-96

21-MAR-96

01-APR

18-

0

Before Bearing ReplacementBefore Bearing Replacement

Engineers at Intels Fab-11 plant

measure vibrations on a vacuum

blower motor

Spectral response of machine

vibrations before (bottom trace)

and after bearing replacement


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Course Demo 6

Early Work on Offshore Structures

Offshore Industry spent millions of

dollars during the 70s and 80s in an

effort to launch practical damage

detection and health monitoring ofoffshore platforms

Numerous examples in the literature of

numerical modeling efforts as well as

scale-model and full-scale experiments Many practical problems were

encountered: Machine noise

Non-uniform inputs Hostile environment for instrumentation

Marine growth

Changes in foundation with time

Modal frequencies can be

insensitive to many of the

damage types the offshore

industry is interested in


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Course Demo 7

Overview of Aerospace Applications

Aging aircraft

Rotorcraft

Reusable launch vehicles:

Space shuttle

X-33

DC-XA

International space station &

related truss test beds

MIR space station

Damage to 1988 Aloha

Airlines flight motivated the

development of an FAA

Aging Aircraft Center at

Sandia National Laboratory


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Course Demo 8

1. Operational Evaluation

Operational evaluation begins to answer questionsregarding implementation issues for a structuralhealth monitoring system.

Provide economic and/or life-safety justifications forperforming the monitoring.

Define system-specific damage including types of damageand expected locations.

Define the operational and environmental conditions underwhich the system functions.

Define the limitations on data acquisition in the operationalenvironment.

Operational evaluation will require input from manydifferent sources (designers, operators, maintenancepeople, financial analysts, regulatory officials)


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Course Demo 9

2. Data Acquisition: Conventional Monitoring vs. WiMMS

Centralized

Data Acquisition

SensorsCabling

Micro-

Processor

Wireless

Modem

SensorsA-to-D

Batteries

Wireless

Modem PC

Centralized

Data Storage

SU

SU

SUSU

Sensor Units

SU

WirelessCommunication

SU

SM

Sensors

Cables

Data Acq. Unix Box

Bus

Sensors

Sensors

From Straser, 1998


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Course Demo 10

2. Data Acquisition: Commercial Wireless Monitoring Systems

Developed at UCBerkeley EE Dept.

Marketed through

Crossbow, SanJose

See

www.xbow.com

2.5cm

Analog Devices

two axis accelerometer

Local processor

and transmitter Photo Detector

and thermalsensor


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Course Demo 11

2. Data Acquisition: Demonstration of the Mote System

A portal test structureThe preload in the bolt is varied

by a PZT actuator

The loosening of the bolt is detected and

reported by the LDE lights in the sensor Correlation reading between two sensors


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Course Demo 12

3. Feature Extraction: Flowchart of Model Update-Based Damage

Identification

FEM Correlated with

Undamaged Data

Modal Frequencies and

Mode Shapes from Test

of Damaged Structure

FEM Correlated with

Damaged Data

Damage is identified by

comparing two finite element

models: one correlated with

undamaged data; one

correlated with damaged data

DAMAGE?

Update

FEMwith

Data


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Course Demo 13

3. Feature Extraction: Uncracked vs. Cracked Beam Response:

Wigner-Ville Transform

Uncracked Cracked


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Course Demo 14

4. Statistical Modeling: Outline of the Statistical Process

3. FEATURE EXTRACTION

AR Coefficients

Residual Error

Modal Parameters

Flexibility Matrices

2. PREDICTION MODELING

AR

CVA

Kalman Filter

Neural Network

( )tx

time

( )tx

1. DATA ACQUISITION

From healthy structure

From damaged structure

time

*

**

*

* ** * *

*

* *

*

*

**

**

CL

UCL

LCL

ei

or

4. CONTROL CHART CONSTRUCTION

S Chart

CUSUM

X-bar Chart

5. MONITORING 6. DECISION MAKING


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Course Demo 15

How to Get Started in Structural Health Monitoring

We will be happy to help you get your program going: Consult for you on various aspects of your project:

Program and resource planning

Experiment design

Feature selection and identification

Statistical methods

Conduct an in-house short course tailored to your application Please contact us for any further information:

Email Hoon or Chuck directly:

[email protected]

[email protected]

http://www.la-dynamics.com

(435) 603-0375

structural health monitoring using statistical pattern recognition

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