14/10/2016 1
Design of CBM
based concept
Condition Based Maintenance (CBM)
ENERGY EFFICIENT EMBEDDED SYSTEMS
CBM of equipment and machinery enables higher productivity, optimal
operation and maintenance, improves the reliability of a system and
employees safety, and decreases maintenance costs.
CBM comprises analysis of various condition related features derived from
vibration, temperature, pressure, flow etc. measurements from critical
components such as bearings, gears, electrical devices, or engines and
structure elements. The data is collected at regular intervals or continually
and when necessary wirelessly transmitted to IoT network, and analyzed in
a real-time.
The condition based maintenance (CBM) ensures that maintenance is
performed at the right time and only if necessary. It includes condition
monitoring, automatic diagnosis and prognosis as well as managment of
maintenance information.
Process
Industrial
Internet
Specifying
measurement needs
Measurement data
analysis
Development of
measurement
algorithms
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O&M Analytics - a toolbox for decision support
from condition monitoring data
Automation of diagnostics and prognostics, and more
optimized operation and maintenance.
Increases the knowledge of the operation and behaviour of
machines and processes throughout their entire life-cycles
Supports different phases of condition based maintenance with
tools that extract essential information and automate data
processing. For example,
Fault detection of industrial centrifuges based on measured
electrical current
Centralized monitoring of a fleet of machines that supports
organizational learning
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Building blocks for O&M
Measurement
methods
Data acquisition
and transmission
Signal
processing
Diagnostics
methods
0 0.1 0.2 0.33
2.4
1.8
1.2
0.6
0
0.6
1.21.8
2.4
3
Aika [s]
Värä
hte
lykii
hty
vy
ys [
m/s
2]
0 50 100 150 200 250 300 350 400 450 5000
0.004
0.008
0.012
0.016
Taajuus [Hz]
Värä
hte
lykii
hty
vy
ys [
m/s
2]
Now Time
Interaction of
components
Prognostics
Increased efficiency
Time
Cutting Lifting Moving
PotholeBegining End
Meas.
data Rainflow (tB..tE)
Time at level (tB..tE)
…
Use and load profiles
Spectrometry (SOAP)
Wear particles, etc
Acoustic emission (80 -120 kHz)
Temperature
Vibrations (0 - 10 kHz)
Toolbox features Tolkku toolbox includes modules for:
• Data import
• Data preparation
• Feature extraction
• State recognition
• Load profiles
• Anomaly detection
• Analysis of causality
• Time-frequency analysis
• Analysis of bearings and gearboxes
• Decision support
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General Machine Health Solutions
Our focus
Development of monitoring, analysis and
management systems of machines and structures.
Our competences
Condition monitoring, diagnostics, prognostics
Measuring methods
Tribology (friction, wear, lubrication).
Vibration and shock attenuation
Fatigue and durability of structures.
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Light Remote Solutions for O&M
Fault and usage history of the machine
Operating hours, fuel consumption, fault history of the components
Safety tracking
Load situation, tilting and other wanted alarms concerning safety
The goal is to provide easily exploitable methods and technologies related to operation
and maintenance that can be implemented for lightweight and cost- effective solutions
for a range of services to implement. For Example:
Global Asset Management (GAM): Highlights
The selected Internet-of-Things (IoT) platform for GAM
platform development
Microsoft Azure Intelligent Systems Service
IoT framework consisting of MS products & services
Condition Based Maintenance (CBM) Phase 1, Demo:
Example of E-maintenance Network and Modern
Integrated Control System in Mobile Machinery
Heavy Remote Solutions for CBM
Azure ISS
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Additional information
VTT Technical Research Centre of Finland Ltd
Halme Jari
Senior Scientist
Machine Health
+358 50 5476542
Kalle Määttä
Senior Scientist
Industrial IoT
+358 40 515 9704