Transcript Case: Mining industry condition monitory

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Arrowhead Task 1.6:
Case: Mining industry condition monitoring
Mika Karaila, D.Sc. (Tech.)
Research Manager
[email protected], +358 40 761 2563
www.arrowhead.eu
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WP 1.6 Participants (FINLAND)
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Metso Automation (task leader)
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Outokumpu
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Laurentiu Barna, Veli-Pekka Salo, Pasi Tuominen
Tampere University of Technology
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Erkki Jantunen, Ventä Olli, Määttä Kalle
Wapice Ltd.
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Petri Vuolukka, Pasi Lassuri
VTT Technical Research Centre of Finland
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Mika Karaila, Yiqing Liang
David Hästbacka, Seppo Kuikka
University of Oulu
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Esko Juuso, Antti Koistinen, Jouni Laurila
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Outokumpu
Multiple challenges in mining:
 Optimal and correct system operation
o Reduced risks
o Remote control
 Large number of devices from different vendors
o Cost-effective on-time maintenance
o Maintenance strategy
o Condition monitoring of devices and equipment
 ERP integration
Kemi Mine
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WP 1.6 Demonstration
condition monitoring
data (from the Kemi mine)
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Automation System
 Metso DNA
 Condition monitoring
 Condition and stress indexes
 Vibration analysis
WAPICE REMOTE MANAGEMENT (WRM)
Beckhoff
 OPC UA Server
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Beaglebone Black
 OPC UA Server
OPC UA Servers / Clients
Generic Data Model & Databases
Terminal Communication
REST API
VPN, Security Gateway
WRM TERMINAL (WRM247+)
 Data Acquisition
 Device Control
 Accelerometer, GPS
 RS-232, RS-485, USB
 Digital I/O, Analog Output
 1-Wire, CAN
 Ethernet, GPRS, 3G
OPC UA process and control data
(e.g. from/to the Kemi mine)
STAVANGER
KEMI
OULU
process and control data
(e.g. from/to the Kemi mine)
TAMPERE
WRM Desktop
ESPOO
Information Services for Condition Monitoring
and Maintenance
Data Aggregation and Unified Access
Information Model and Interoperability
Events and Notifications
OPC UA Client/Server Architecture
OPC UA (alarms & events)
Generic Information Model
 VTT Node (Acceleration Sensor)
 Acceleration Data
 MIMOSA
OPC UA process and control data
(e.g. from/to the Kemi mine)
Enterprise Applications and
Mobile Clients
condition monitoring data
(from the Kemi mine)
VAASA
 User Interface (web based)
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Grinding mill (Kemi)
Wear part monitoring
Hoisting rope damage
Fine concentrate machine vision
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Demo session: Metso
Cloud:
Big Data
Windows:
OPC UA client
Beckhoff PLC:
OPC UA server
BeagleBone Black:
OPC UA server
Node-red:
Sensortag
OPC UA client
Raspberry PI:
Camera
Node-red:
Cloud storage
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Demo session: Wapice
Wapice Remote Management (WRM) System, OPC UA
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Demo session: Tampere University of Technology
OPC UA based aggregation of
heterogeneous device data for
maintenance information systems
Consolidating
information model e.g.
for device, segment or
site level services (i.e.
Arrowhead framework)
Adaptation of legacy
system structures for
improved
interoperability
Built-in support for
information security for
a multi-vendor
environment
Dynamic system structure enables
scalability to data gathering and
propagation of event notifications
from a multitude of devices
OPC UA information modeling for
declaring data relations and semantics
as well as views for different purposes
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Demo session: VTT Technical Research Centre of Finland
Cloud:
Big Data
Windows:
Mimosa
Maintenance
centre:
Wear plate
diagnosis
CMMS:
Registry
Work management
VTT Little Node:
Vibration acceleration
data
Wear plate monitoring
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Preliminary results from the first test
NaturalFreq uencyOF_Averag edFTT
kHz
1.08
1.06
1.04
1.02
1.00
0.98
0.96
0.94
0.92
0.90
0.88
0.86
0.84
0.82
0.80
0.78
0.76
0.74
0.72
0.70
0.68
0.0
0.5
1.0
1.5
2.0
2.5
10^3
Change of natural frequency (1050 -> 710 Hz) of a wear plate during a
2 month period 19.4–24.5.2014
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Demo session: VTT Technical Research Centre of Finland
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Wireless data acquisition system using BT-LE sensor nodes, smartphones and
gateway units.
Intelligent distribution of data pre-processing in node, in phone and in gatewaynodes to optimize energy, bandwidth and capacity usage
Use case/next steps: Implementation of distributed data analyzing system for wear
plate analysis utilizing distributed WSN architecture
Distributed analysis in WSN
Smartphone data analysis
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Demo session: University of Oulu, Overview
• On-site data processing
• FFTDerivationIFFTNorms and describing indices
Location and setup
Matlab demonstration
Finding the degrees
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Thank you!
www.arrowhead.eu