BDE SC3.3 Workshop - BDE Pilot case for Wind Turbine condition monitoring research

Big Data Europe
for System Monitoring
BigDataEurope 3rd Workshop Amsterdam 28/11/1725-janv.-18
F. Mouzakis, D. Foussekis
and BDE consortium

BigDataEurope 3rd Workshop in WindEurope Conference & Exhibition, Amsterdam 28/11/17
System Monitoring p.2
Overview
 CRES challenge
 Data acquisition challenge
 Research case in WT monitoring
www.big-data-europe.eu

CRES Wind Department - Testing
 Wind potential measurement campaigns & Lidar
 Power Performance Measurements
 Electrical Power Quality of Wind Turbine Generators
 Mechanical Load measurements
 Blade testing (<30m) and coupon testing
 Research on testing

CRES challenges
 Exploit the capabilities of the new data distributed DAQ with high-throughput
rates for research
 Utilize the open Big Data technology tool
Background:
 Fully instrumented WT in WF with no fiber optic connection (24MBps ADSL,
Upload speeds <1Mbps)
 Cluster of 16 x [ 8core-CPUs, 16GB RAM + 256GB SSD ]
 150TB in 5 x NAS [8 x 4TB in 1disk-redundancy RAID]

General requirements in System monitoring
 Modular distributed system using standard Ethernet network
 Specs compliant with International Standards
 Robust and reliable for 24/7 standalone non-stop operation
 Scalable and reconfigurable
 Time Synchronization across all modules (GPS or Master module)
 Embedded processing capabilities
 Send notifications and alarms
 Data storage

Typical DAQ system core component (1/2)
 NI-CompactRIO platform http://www.ni.com/compactrio/
 Designed for harsh environments
-20º to -55ºC temperature, 5grms vibration, 30g shock
 Low power requirements
~10W at 9-30V for battery powered standalone operation
 Data acquisition based on FPGA hardware offering fast I/O response times
and increased reliability
Source: NI.com

Field-Programmable Gate Array (FPGA)
- Reconfigurable Hardware chip.
- Analogous to a printed circuit board with unconnected components on it.
- Connections in an FPGA circuit are dynamically defined in software.

Benefits of FPGA in wind energy applications
Inline processing:
Reduce the noise of a periodic signal by averaging the samples as acquired on the FPGA
Average 1,024 records, 1 million samples long with 16 bits of resolution

Typical configuration
. . .
Gigabit Local Area Network (LAN)
Network Attached Storage (NAS)System Monitoring PC

Raw Data storage – Existing File Formats
ASCII files
+ Human-readable
+ Portable / MS Excel
- Significantly larger disk footprint
- Slow read and write
Binary
+ Compact file size
+ Fast streaming (read & write)
- Not human-readable
- Not easily exchangeable
XML
+ Stores complex data structures
+ Web browser / text editor
- Even larger disk footprint
- Front-end schema design
- Does not streamDatabase files
+ Store data centrally
+ Organize and query test results with SQL
- Time intensive startup effort
- Requires maintenance
- Potentially high cost

Raw Data storage – Existing File Formats
Binary Structured (TDMS – NI Technical Data Management Technology, Physical Acoustics Format)
Characteristics
• Single streaming binary file
• Three levels of hierarchy for better organization
File, groups, and channels
• Customizable, descriptive properties at each level
• User-defined Meta data for campaign properties
Considerations
• Third party format

System Monitoring – Research pilots p.13
Type: SCADA and CMS data on a Wind Turbine specifically instrumented for BDE
Status: Open
Sensors: Operational parameters, Vibration, Mechanical Loading, Power Quality, AE
Format: Third party (TDMS technical data management streaming) – preprocessing foreseen
Acquisition technology: Field Programmable Gate Arrays (FPGA)
Sampling rate: from 10s/s for operational parameters up to 64ks/s for vibration & power quality
Streaming volume: 3 distributed units yield ~14Gb/hour continuously
Scope: Research on condition monitoring based on long term data
Analytics: engineering signal analysis, research on parametrics, fault identification and loop with
updated methodologies on raw data
Operation of pilot:1 year (on-going)
Primary Content/Data Involved

CRES Wind Farm
Monitored WT
Neg-Micon 750kW

The monitoring system provides indicatively the following data for the condition monitoring
system:
- system operational status/parameters
- wind turbine output electrical power
- nacelle yaw position, yaw motor electrical power
- wind speed from nacelle anemometer (1~10s/s)
and additionally:
- mechanical loads on tower top and base cross section (~100s/s)
- rotor thrust & tower torsion
- HSS torque (on shaft coupling the gearbox with the generator) (64ks/s)
- power quality current & voltage (64ks/s)
- vibration at gearbox various stages (64ks/s)
- acoustic emission signals at gearbox (10Ms/s)
CRES CM system on NegMicon 750kW WT

SC3 Pilot measuring system
Gearbox and Drive train DAQ systems
Operation DAQ
system
Supervising PC
Local storage
unit

Bearing vibration
sensors at
gearbox HSS
(accelerometers)
Power Quality voltage and current probes
SC3 Pilot sample sensors

SC3 Pilot sample sensors
Conventional vibration CMS
(dynamic content ~3kHz)
Acoustic emission CMS
(dynamic content 100~400kHz)

BDE pilot CM module topology
7.2Gb/hour (i2)
0.1Gb/hour (r4)
7.2Gb/hour (i2)
Source: NI.com
15Gb/h
Condition based

Pilot Data Acquisition module
Access through TeamViewer

Bending Moment
signals for
Mechanical Loading
Monitoring

Vibration signal for
Gearbox monitoring

Electrical signals for
Power Quality Monitoring

OPC
An Industrial Interoperability
Standard for Open Platform
Communications
https://opcfoundation.org/
Pilot Data Acquisition module – On line component

OPC Server operating at: opc.tcp://193.92.104.xxx:49580
Object name: PrjBDE.WT.StatAve
Encryption: SHA256
Data type: 1D- float Array- 52 elements
Transferred parameters: On-line statistical properties
Refresh rate: 2Hz
Server: CompactRIO running NI Real-Time Linux OS
Client: Industrial PC running LabVIEW

OPC server monitor on DAQ app

Pilot Data Acquisition module – AE component
◎ 4 AE (R30) sensors were installed
• Main bearing, gearbox (LSS side,
INT & HSS generator side)
◎ DAQ system records data at a
rate of 10~20GB/hour
depending on threshold (research
item)
◎ Data preprocessor module binary-
binary
◎ Additional feature module

◎ Addition of new descriptive
features and optimize
parameters (multiple signal
analysis)
◎ Describe normal operation
signature
Source: Hit Detection and Determination in AE Bursts, InTechOpen
AE module: research aspects

Basic analytics
Raw time series
Statistics and
correlations
Dynamic analysis
Fatigue analysis

Feature scales
1min10 min
10 min
10 min

Feature scales and patterns
~3700 per minute

Pilot concept

Research concluding steps
◎ Conclusion of data collection
◎ Assessment of added features in AE analysis
◎ Define the operational envelope for the current status of the
WT (distribution parameters)
◎ Assessment of timewise distribution changes

Final Remarks – BDE opportunities
 Big Data Europe offers a easy-to-use generic platform to encourage community’s
entrance to big data technologies
You are invited to implement your case with BDE:
https://www.big-data-europe.eu/bdi-components/
https://www.big-data-europe.eu/howto-install-the-bde-platform/
https://github.com/big-data-europe
Getting Started With BDE Platform

Thank you for your
attention
BDE consortium

BDE SC3.3 Workshop - BDE Pilot case for Wind Turbine condition monitoring research

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (20)

Ähnlich wie BDE SC3.3 Workshop - BDE Pilot case for Wind Turbine condition monitoring research

Ähnlich wie BDE SC3.3 Workshop - BDE Pilot case for Wind Turbine condition monitoring research (20)

Mehr von BigData_Europe

Mehr von BigData_Europe (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

BDE SC3.3 Workshop - BDE Pilot case for Wind Turbine condition monitoring research