Diagnos på distans
GP Rovsing Dynamics
GP Strategies Denmark
Fundamentals of
Condition Monitoring
Ole Dossing
Director of Operations, Technical Director
GP Strategies/Rovsing Dynamics, Denmark
Confidential & Proprietary to GP Strategies Corporation
Diagnos på distans
Enterprise Server
Confidential & Proprietary to GP Strategies Corporation
Confidential & Proprietary to GP Strategies Corporation
Why Condition Monitoring
• Objectives of Condition Monitoring
– Maximize Availability (Reliability)
– Maximize Capacity / Minimize Emission
– Condition Monitoring as a Proactive Equipment
Reliability Improvement Strategy by Risk Based
Maintenance/Condition Based Maintenance
Confidential & Proprietary to GP Strategies Corporation
4
CM-Technology & CBM:
Historical Perspectives
•
5
•1939
•early 1950’s
•mid 1960’s
•1968 (about)
•early 1970’s
•mid 1970’s
•mid 1980’s
•21st Century
— T. C. Rathbone: “Vibration Tolerance”
— Time Based Preventive Maintenance
— Continuous, installed monitoring
— Study on opportunities to correct
maintenance waste in the UK
— US Navy: 1/N octave CM analysis for
“predictability”
— Introduction of the Real Time Analyzer
(FFT) for machinery diagnostics
— Introduction of the concept of
predictive or Condition Based
Maintenance
— Microcomputer based walk around data
collection systems
—?
Confidential & Proprietary to GP Strategies Corporation
The Technologies and Applications of
OPENpredictor™. Copyright 2011
Why Condition Monitoring
• Objectives of Condition Monitoring
– Maximize Availability
– Maximize Capacity / Minimize Emission
– Condition Monitoring as a Proactive Equipment Reliability Improvement
Strategy by Risk Based Maintenance
• Challenges in Condition Monitoring
–
–
–
–
–
–
CM is often used as a stand-alone application
CM is sometime mistaken a for Trouble Shooting
Traditionally CM is simply used for Failure Prediction, little else is asked for or expected
Often CM has been driven from the bottom upward
CM alone does not provide for reliability
CM does not prevent failure – it detects and possibly predicts failures
Confidential & Proprietary to GP Strategies Corporation
6
Allocation of maintenance costs by type:
Standard vs. Goal
100
Eliminated Maintenance
75
A survey disclosed the following potentials:
 Reduce total maintenance by 50%
 Shift the proportion of maintenance:
Current Objective
Reactive
50% 15%
Preventive
35% 30%
Condition Based 15%
55%
Percent
Reactive / Corrective Maintenance
50
50
Preventive Maintenance
25
25
Condition-Based Maintenance
Current
Confidential & Proprietary to GP Strategies Corporation
Objective
7
From Information Flow
to Cashing Benefits
Increase Availability/Production
Reduce Maintenance Costs
Prevent Failures
AutoDiagnosis™: Diagnostics and Predictions
Sensor and Operational Data
Confidential & Proprietary to GP Strategies Corporation
8
What is Condition Monitoring?
Si gnature Spectrum
0
-10
Mag [dB m/s]
-20
Gearbox Signature:
Normal Operation
-30
-40
-50
-60
-70
-80
-90
-100
0
100
200
300
400
500
600
Frequecy [H z]
Si gnature Spectrum
0
Gearbox Signature:
Abnormal tooth mesh
-10
Mag [dB m/s]
-20
-30
-40
-50
-60
-70
-80
-90
-100
0
100
200
300
400
500
600
Frequecy [H z]
Signature Spectrum
0
Gearbox Signature:
Tooth Broken !!
-10
Mag [dB m/s]
-20
-30
-40
-50
-60
-70
-80
-90
0
100
200
300
Frequecy [Hz]
Confidential & Proprietary to GP Strategies Corporation
400
500
600
9
OVERALL LEVELS/SPECTRA
VERSUS SIGNATURES
Protection Systems
or your DCS
Auto Spectrum/FFT
OPENpredictor™ SED
Envelope Spectrum
Healthy
Bearing
SAME
Indication
SAME Indication
Clear DIFFERENT Indication
Worn
Bearing
Confidential & Proprietary to GP Strategies Corporation
The Technologies and Applications of
OPENpredictor™
SELECTIVE SIGNATURE & DOMAINS:
OVERVIEW
FRF: Turbine Blade #11, row #2
(angle)
magnitude [mm/s2/N]
40
(ORDER)
20
0
-20
-40
0
1000
2000
3000
4000
5000
6000
0
1000
2000
3000
4000
5000
6000
Angle [Deg]
200
100
0
-100
-200
Frequecy [Hz]
1/3 Octave Analysis
110
100
STA: Tooth fault: 13 teeth at 138 Hz
Band Level [db]
1.2
1
0.8
0.4
90
80
70
0.2
60
0
-0.2
50
-0.4
-0.8
62.5
125
250
500
Frequency Band [Hz]
-0.6
0
2
4
6
8
10
12
14
16
18
Time [ms]
SED: Envelope Spectrum: 500 - 1500 Hz
0.18
0.16
0.14
magnitude [mm/s2]
amplitude [mm/s2]
0.6
0.12
0.1
0.08
0.06
0.04
0.02
0
0
500
1000
Frequecy [Hz]
Confidential & Proprietary to GP Strategies Corporation
1500
1000
2000
Traditional vs. EtaPRO predictor™ Diagnosis
Event!!
Signal
Acqusition
Signal Processing
Expert Analysis and List of
Possible Faults
Data Acquisition
Advanced
Signal
Processing
Feature
Extraction
Data Acquisition
Advanced
Signal
Processing
Feature
Extraction
Confidential & Proprietary to GP Strategies Corporation
12
EtaPRO predictor™: OVERVIEW
OP File Server
OP/O Client
OP/O Client
Client
OP/O Client
Client
PLC, PI, Oil,
etc
Control
System
vSPU
Wireless Sensors
Confidential & Proprietary to GP Strategies Corporation
Alternative Paths to Diagnosis/Concern
• From sensor to high level operational information
Sensors
DataAqc
Features/ Fault
AutoDiagnosis™
Baselines for
Discrete States + Component Data
Confidential & Proprietary to GP Strategies Corporation
APR
History (Continuous)
of Operational data
14
Machinery Dynamics +APR
Asset Sensors
Signature Feature Extraction
 Power Output
 Reactive Load
 Exhaust Temp
 IGV Position
 Inlet DP
 Bearing Temp
 Bearing Vibration
 Wheel Space Temps
 Etc.
Confidential & Proprietary to GP Strategies Corporation
APR Model
 Signature Features
 Overall
 Unbalance
 Misalignment
 Instability
 Blade Phenomena
 Etc.
 Signature History
15
About Features & Fault Symptoms
Example: diagnosis for unbalance
Feature Trend
1st Harm
6
2nd Harm
Unbalance Fault Symptom Trend
rd
5
3.5
4
3
3
2
1
0
0
Symptom Value [unity]
Feature Value [mm/s]
3
Harm
Fault Symptom
2.5
2
1.5
1
10
0.5
0
20
30
40
50
60
70
Time [days]]
0
10
20
30
40
50
60
70
Time [days]]
Confidential & Proprietary to GP Strategies Corporation
16
Feature Trend
1st Harm
6
2nd Harm
Feature Value [mm/s]
3rd Harm
5
4
3
2
1
0
0
10
20
30
40
50
60
70
Time [days]]
Unbalance Fault Symptom Trend
3.5
Fault Symptom
Symptom Value [unity]
3
2.5
2
1.5
1
0.5
0
0
10
20
30
40
50
60
70
Time [days]]
Confidential & Proprietary to GP Strategies Corporation
17
Case: Steam Turbine Instability
• Suez Gulf & East Port Said
– Each plant is formed of two units rated at 2x341 MW.
The power plant will burn natural gas or heavy fuel oil
as backup fuel
Confidential & Proprietary to GP Strategies Corporation
18
Case 1: Steam Turbine Instability
Instantaneous AutoDiagnosis™
Confidential & Proprietary to GP Strategies Corporation
19
From AD to Root Cause Analysis
• Parameter that caused the alarm and IAD
– In ‘Full Load’ alarm level
– Otherwise normal
Confidential & Proprietary to GP Strategies Corporation
20
From AD to Root Cause Analysis
• Analyze behavior
Confidential & Proprietary to GP Strategies Corporation
21
From AD to Root Cause Analysis
• Analyze behavior
Observe PSD:
rms 
f2
 PSD( f )  9  m
f1
Confidential & Proprietary to GP Strategies Corporation
22
From AD to Root Cause Analysis
• Analyze behavior
Confidential & Proprietary to GP Strategies Corporation
23
Solution
Valve Sequence
• Analyze behavior: TemperatureRe-Schedule
vs. Load
• Shaft Lift->Load release
Confidential & Proprietary to GP Strategies Corporation
24
Summary
• Goals and Objectives
– Condition Monitoring as a Proactive Equipment Reliability Improvement
–
–
–
–
–
–
Strategy by Condition Based Maintenance
Maximize Availability
Maximize Capacity / Minimize Emission
CM must be part of a wider strategy
CM is much more that Failure Prediction, but
• CM alone does not provide for reliability
• CM does not prevent failure – it detects and possibly predicts failures
CM should be a top management strategic decision
CM Systems must be operated by adequately educated staff
Confidential & Proprietary to GP Strategies Corporation
GP Strategies Corporation
Ole Døssing
Director of Operations, Technical Director
GP Strategies Denmark
odossing@gpstrategies.com
+45 23449812
Knowledge. Performance. Impact.
Confidential & Proprietary to GP Strategies Corporation