Fault Diagnosis based on Particle Filter
Transcript of Fault Diagnosis based on Particle Filter
1
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Fault Diagnosis based on Particle Filter- with applications to marine crafts
Bo ZhaoCeSOS / Department of Marine Technology
Norwegian University of Science and Technology
…
…
…
2
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Danger and harmDanger and harm
PollutionPollution
Property lossProperty loss
Faults
SafetySafety
Environmental friendlyEnvironmental friendly
EconomyEconomy Purpose
3
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Data from: The Software Problem ++, Marine Cybernetics, 2004.
0
5
10
15
20
25
30
35
40
45
Incide
nt in
%
Year
Incident trends 1990 – 2001: Primary causes
Computer Reference Thruster
Operator Electrical Generator
Environment Other
Computer
Reference
Thruster
Operator
Electrical
Generator
Environment Other
Average incidents in percentage on primary causes
DP incident analysis
4
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
• Two divers on the sea bed, were testing within a subsea structure.
22:10• A series of alarms activated in the vessels in relation to the DP system.
• Vessel started drifting away.
• The Divers started to leave the structure and head back to the diving bell.
• Diver 2 noticed his umbilical had been snagged.
22:12• Communications and video was lost to Diver 2.
• The DP operator were trying to control the vessel by manual operation.
22:17• Regained control of the vessel having drifted off approx. 240m.
• The vessel was driven manually by the master back to the structure.
22:40 ‐ 22:46• The vessel was back in a position close to the drilling template.
• Both Divers were on the bell stage. Diver 2 was recovered into the bell.
• Vessel:• Date:• Wind:• Sea State: • Drifted:
Bibby Topaz18/09/1230 knots, 316°5 240m in 7min
DP incident report:
5
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Principle:• System with faults• Particle filter• Diagnosis of faults
Applications: • Diagnosis of DP
position reference system• Underwater robot navigation
Content
6
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Principle
…
…
time
• Hidden Markov model• State observer• Switching-mode HMM• Mode/state observer
• Kalman filter• Extended KF• Unscented KF• Particle filter
…
…
time
• Hidden Markov model• State observer• Switching-mode HMM• Mode/state observer
projectile rebounds on ground
7
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Principle • Hidden Markov model• State observer• Switching-mode HMM• Mode/state observer
…
…
…
time
…
…
…
time
…
…
…
time
• Kalman filter• Extended KF• Unscented KF• Particle filter
• Hidden Markov model• State observer• Switching-mode HMM• Mode/state observer
projectile rebounds on ground
8
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
How do we diagnose a fault?
PredictedFault free behavior
PredictedFaulty behavior
Prediction
9
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
How do we diagnose a fault?
PredictedFault free behavior
PredictedFaulty behavior
Prediction ObservationTake the measurement
Correction
H0
H1
Obs.
Compare
10
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Application toDiagnosis of DP position reference system
11
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Application toDiagnosis of DP position reference system
Challenge: Complex external disturbance
Wave‐frequency motion Wind and current force
Nonlinear system behaviorModel uncertaintyMultiple failure modes
GPS• Drifting• Bias• Outliers
HPR• Random excursion• Outliers
GPS drifting
wave
12
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Application toDiagnosis of DP position reference system
GPS driftingHPR in function
wave
Results: Alarm when faults happen Diagnosis faults Acceptable positioning during
failure
Pros: Avoids catastrophic consequences
by giving DPO time to handle faults Assists the DPO diagnosing faults
Cons: Relatively poor position estimation
comparing with other DP observer Time consuming
13
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Application toRobust Navigation of Underwater Robot
15
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Tunnel thruster
2×Main thrusters
2×Vertical thrustersVertical: 1.2 knot
Yaw rate: 60°/s
x
y
z
16
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
DVL (Dopple Velocity Log)depth sensor
HPR (Hydroacousticposition reference)
compassYaw rate gyro
x
y
z
17
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction
DVL‐ dropout‐ bias
HPR‐ dropout‐ outliers
Current
Robust Navigation of Underwater RobotROV Model
18
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
HPR – Hydro acoustic position reference
Faults: 1. Dropout – when no signal received2. Outlier – Measurement has
significant difference from the true position
19
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
DVL – Doppler velocity log
Faults: 1. Dropout – when no signal received2. Bias – small‐size constant difference
between the measurement and the true velocity
20
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction
DVL‐ dropout‐ bias
HPR‐ dropout‐ outliers
Current
Robust Navigation of Underwater RobotROV Model
21
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction
DVL‐ dropout‐ bias
HPR‐ dropout‐ outliers
Current
SystemModel
MeasurementModels
Robust Navigation of Underwater RobotInformation flow
Predictions
Estimation and
Diagnosis
Estimationfrom last
sampling time
22
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction DVL
‐
ut‐ bias
DVL‐dropout‐ bias
HPR‐ dropout‐ outliers
Current
Model Measurement
Robust Navigation of Underwater RobotExperiment
Estimationfrom time k‐1Estimation
from time k‐1
Prediction
Estimation and
Diagnosis
Full
Faults
Full‐scale test, ROV MinervaOctober 17‐18, 2012, Trondheimsfjord.
Real disturbance.Real measurement.
In the real‐time control loopFaults were triggered.
23
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction DVL
‐
ut‐ bias
DVL‐dropout‐ bias
HPR‐ dropout‐ outliers
Current
Model Measurement
Robust Navigation of Underwater RobotExperiment
Estimationfrom time k‐1Estimation
from time k‐1
Prediction
Estimation and
Diagnosis
‐16m ‐2m
‐2m
2m
Full
Faults
Full‐scale test, ROV MinervaOctober 17‐18, 2012, Trondheimsfjord.
Real disturbance.Real measurement.
In the real‐time control loopFaults were triggered.
measurmentestimationcommandfaultymeasurementKF estimation
measurmentestimationcommandfaultymeasurementKF estimation
24
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction DVL
‐
ut‐ bias
DVL‐dropout‐ bias
HPR‐ dropout‐ outliers
Current
Model Measurement
Robust Navigation of Underwater RobotExperiment
Estimationfrom time k‐1Estimation
from time k‐1
Prediction
Estimation and
Diagnosis
‐16m ‐2m
‐2m
2m
NormalFull
Faults
Full‐scale test, ROV MinervaOctober 17‐18, 2012, Trondheimsfjord.
Real disturbance.Real measurement.
In the real‐time control loopFaults were triggered.
measurmentestimationcommandfaultymeasurementKF estimation
measurmentestimationcommandfaultymeasurementKF estimation
25
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction DVL
‐
ut‐ bias
DVL‐dropout‐ bias
HPR‐ dropout‐ outliers
Current
Model Measurement
Robust Navigation of Underwater RobotExperiment
Estimationfrom time k‐1Estimation
from time k‐1
Prediction
Estimation and
Diagnosis
‐16m ‐2m
‐2m
2m
HPR OutliersFull
Faults
Full‐scale test, ROV MinervaOctober 17‐18, 2012, Trondheimsfjord.
Real disturbance.Real measurement.
In the real‐time control loopFaults were triggered.
measurmentestimationcommandfaultymeasurementKF estimation
measurmentestimationcommandfaultymeasurementKF estimation
26
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Kinetics&
Kinematics
Propulsion‐ reduction DVL
‐
ut‐ bias
DVL‐dropout‐ bias
HPR‐ dropout‐ outliers
Current
Model Measurement
Robust Navigation of Underwater RobotExperiment
Estimationfrom time k‐1Estimation
from time k‐1
Prediction
Estimation and
Diagnosis
‐16m ‐2m
‐2m
2mHPR drop
Full
Faults
Full‐scale test, ROV MinervaOctober 17‐18, 2012, Trondheimsfjord.
Real disturbance.Real measurement.
In the real‐time control loopFaults were triggered.
measurmentestimationcommandfaultymeasurementKF estimation
measurmentestimationcommandfaultymeasurementKF estimation
27
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Experiment
HPR OutliersHPR DropoutDVL Dropout
HPR + DVL
Fault Free
DVL BiasThruster Loss
28
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Experiment
HPR OutliersHPR DropoutDVL Dropout
HPR + DVL
Fault Free
DVL BiasThruster Loss
measurmentestimationcommandfaultymeasurementKF estimation
measurmentestimationcommandfaultymeasurementKF estimation
29
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Experiment
HPR OutliersHPR DropoutDVL Dropout
HPR + DVL
Fault Free
DVL BiasThruster Loss
measurmentestimationcommandfaultymeasurementKF estimation
measurmentestimationcommandfaultymeasurementKF estimation
30
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Principle:• System with faults: SM‐HMM• Particle filter for fault diagnosis
Applications: • Diagnosis of DP position reference system• Underwater robot robust navigation
Future work:• Efficiency issue for particle filter in SM‐HMM• Formal design process for the mode transition• Transient after mode switching
Summary
31
www.cesos.ntnu.no Bo Zhao – Centre for Ships and Ocean Structures
Reference:
Particle filter:
• Zhao, B.; Skjetne, R. & Blanke, M., Particle Filter and for Fault and Diagnosis and Robust Navigation of Underwater Robot, IEEE Transactions on control systems technology (Submitted), IEEE, 2013
Fault diagnosis (regarding marine crafts):
• Blanke, M.; Kinnaert, M.; Lunze, J. & Staroswiecki, M., Diagnosis and Fault‐Tolerant Control, Springer Berlin Heidelberg, 2006
• Blanke, M., Diagnosis and Fault‐Tolerant Control for Ship Station Keeping, Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, MediterreanConference on Control and Automation, 2005, 1379 ‐1384
Others
• The Software Problem ++, Marine Cybernetics, 2004.