Asset Health CIM
Common Information Model (CIM) for
Asset Health
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Asset Health CIM
Table of Contents
1
Introduction .......................................................................................................................................... 5
2
Use Cases, Interfaces, and Interactions ................................................................................................ 5
3
Gas in Oil Analysis ................................................................................................................................. 8
3.1
Factory Acceptance Test ............................................................................................................... 9
3.2
Model .......................................................................................................................................... 10
4
Electrical Property Analysis ................................................................................................................. 12
5
Inspections and Surveys ...................................................................................................................... 13
6
Testing Activity .................................................................................................................................... 13
7
61850 Considerations ......................................................................................................................... 13
8
Concepts and Definitions .................................................................................................................... 14
9
References .......................................................................................................................................... 16
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Table of Figures
Figure 1—Asset health use case. .................................................................................................................. 5
Figure 2—Sequence diagram depicting determination of asset health baseline. ........................................ 6
Figure 3—Sequence diagram depicting asset health condition monitoring and escalation. ....................... 7
Figure 4—Sequence diagram depicting asset health triggers. ..................................................................... 7
Figure 5—Sequence diagram depicting asset use optimization. .................................................................. 8
Figure 6—Illustration of a class for asset health assessment. .................................................................... 11
Figure 7—DGA and Oil Quality measurements. ......................................................................................... 12
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Revision History
Date
19 August 2013
2 September 2013
19 September
2013
Reason
Initial Draft.
Illustrative asset health CIM UML additions
& use case descriptions.
Modified asset health use case figure and
added a secondary use case for CIM-61850
harmonization for the measurements to
track the asset.
Asset Health Focus Community
Author
Gowri Rajappan
Gowri Rajappan
Version
0.1
0.2
Gowri Rajappan
0.3
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1 Introduction
2 Use Cases, Interfaces, and Interactions
Figure 1 shows the use case for asset health. The use case narrative is as follows:
1. An asset health Analytics System obtains asset health-related data from various sources
including:
a. Online monitoring devices.
b. Lab test database.
c. Datasheets.
d. EMS/DMS systems and SCADA Historian.
e. Work history from Work and Asset Management System (WAMS).
2. The Analytics System provides assessment to an Asset Engineer.
3. The Asset Engineer uses the assessment to determine actions such as further testing and
maintenance.
4. The Analytics System can send information to the WAMS that can be used to trigger a
preventive or corrective work order.
Figure 1—Asset health use case.
Asset health use case would require a new 61968 Interface Reference Model (IRM) business subfunction to be defined. We are calling this sub-function “Analytics System.” Assuming such a business
sub-function, a number of sequence diagrams can be developed, showing interaction with other IRM
functions. We anticipate the following four interactions:
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1. Asset health baseline (Figure 2) – the baseline health of the asset needs to be determined. This
is the basis of ongoing condition monitoring and assessment.
2. Condition monitoring and escalation (Figure 3) – this is the main interaction.
3. Asset health triggers (Figure 4) – provide asset health-related operational triggers/thresholds.
4. Asset use optimization (Figure 5) – determine optimal operational region/regime for the asset.
Figure 2—Sequence diagram depicting determination of asset health baseline.
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Figure 3—Sequence diagram depicting asset health condition monitoring and escalation.
Figure 4—Sequence diagram depicting asset health triggers.
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Figure 5—Sequence diagram depicting asset use optimization.
3 Gas in Oil Analysis
The following are requirements and pertinent concepts obtained from responses to the AHFC DGA
Survey and subsequent discussions:
1. Tests on oil samples consist of Dissolved Gas Analysis (DGA) and Oil Quality.
a. DGA indicates current-day problem; Oil Quality indicates future problem.
2. Lab vs. online monitoring equipment.
a. Lab is considered more reliable, since controlled environment vs. instrumentation that is
exposed to the elements.
b. One reason to pull samples for lab testing even when real-time monitoring is done is to
verify the sensors are okay.
c. Labs also perform more tests (more data produced) compared to field instrumentation.
d. Other than lab test data being used to verify field instrumentation, the on-line data from
the field instrumentation is treated the same way.
3. Factory Acceptance Test (FAT) vs Site Acceptance Test (SAT) vs Reconditioning Test vs Routine
Tests.
a. Routine tests are less comprehensive than SAT & Reconditioning Test, which in turn are
less comprehensive than FAT.
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b. When a transformer is first energized (or re-energized), it is monitored to detect infant
mortality. For instance, oil samples @ 24 hr intervals at first, then 1 week interval, and
then 1 month interval.
c. As for FAT vs SAT, results from the latter are more important since they represent infield condition. But if there are symptoms like unusual gassing, may refer back to factory
test data.
d. If oil is cleaned, a new baseline is set.
4. Assessment results communicated to other systems, hence need to be modeled.
a. Oil test results are scored, so that those that score badly can then be attended to.
b. Recommendations need to be communicated.
c. Can give rise to further tests/corrective work.
3.1 Factory Acceptance Test
The following figures show typical DGA and Oil Quality FAT for transformer. These tests could be done
multiple times over a period of several days.
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3.2 Model
Figure 6 and Figure 7 illustrate CIM UML modifications to address the requirements detailed earlier. The
model in the figures provides:



Provenance data through Document hierarchy.
DGA and Oil measurements through Measurement & MeasurementValue.
Assessment results through a new class.
Some issues of note to be addressed include:




Though the model can say what asset the DGA tests pertain to, it doesn’t capture the
provenance of the oil samples themselves – e.g., from what valve were they taken, the
conditions under which it was taken, etc.
The association between ProcedureDataSet and MeasurementValue is currently only
informative, not normative.
As for the DGA and Oil measurements, the measurement classes themselves were subject of
extensive discussion.
o Summary by Tanja: There are three approaches in principle for measurementType.
Enumerated is the most explicit, but not easily extensible. String is the most flexible, but
doesn’t interoperate well. Defining a class called MeasurementType is third, but this
could get messy.
o Suggestion by Herb: Define three categories of measurement types – standardized,
industry standardized, and proprietary. Should be able to define and get agreement on
the first two.
The model needs ways to distinguish between various lifecycle stages such as FAT vs. SAT vs.
ongoing testing. One approach is an attribute in ProcedureDataSet.
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Figure 6—Illustration of a class for asset health assessment.
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Figure 7—DGA and Oil Quality measurements.
4 Electrical Property Analysis
Electrical properties pertinent to asset health include:



Bushing insulation power factor.
Winding insulation power factor.
Winding resistance.
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

Sweep frequency response.
5 Inspections and Surveys
Visual inspections are a key part of asset health maintenance regimes.
6 Testing Activity
AHFC discussions have determined that there is value in explicitly modeling testing activity. For instance,
a single trip to the field could result in multiple procedures (Assets::Procedure) being performed and
multiple, disparate data set being collected (Assets::ProcedureDataSet). We need a way of tracking
these multiple procedures and data sets under the single activity.
7 61850 Considerations
The following are some considerations and conclusions reached regarding 61850 for asset health:



CIM should be able to bring in 61850 data without losing any information.
Need only a subset of 61850 data for CIM – i.e., the measurements needed for asset health
assessments.
A CIM-61850 harmonization use case for asset health to be provided to the CIM-61850
Harmonization Task Force.
The following is the primary use case narrative:





A 61850 IED has measurement and status data objects with data pertinent to asset health. The
Measured Value and Status Information objects in the SIML LN are examples.
The asset health analytics system needs to access this data for its analysis.
Other sources, such as non-61850 devices (via SCADA Historian) and lab test databases may also
be providing the same data that is provided by the 61850 IED.
o This data is expected to be available to the asset health analytics system through classes
in the CIM Meas package.
This equivalent data from multiple sources need to be presented to the analytics system with
common semantics.
The pertinent 61850 measurement and status data objects need to be harmonized with the CIM
Meas package classes.
The following is a secondary use case narrative:
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

The CIM-61850 harmonized measurement data should be tied to the asset.
When the asset moves to a different location, the historical asset health-related CIM-61850 data
should be able to move with it.
8 Concepts and Definitions
Factory Acceptance Test (FAT): Tests that are performed on an asset at the factory prior to shipping to
the install site.
Site Acceptance Test (SAT): Tests that are performed on an asset at its site of operation after it has been
received from the factory and installed, but before it has been commissioned.
Reconditioning Test: Tests that are performed after a component/material replacement.
Field Test: Test that is performed on the field.
On-line Test: A type of field test that is performed using attached instrumentation while the asset could
be energized.
Off-line Test: A type of field test that is performed with the asset de-energized.
Lab Test: Test that is performed off-site under controlled settings on sample obtained from the asset.
Infant Mortality: Describes failure of an asset early in its lifecycle.
9 Measurements (measurementType Enumerations)
9.1 Gas in Oil
Enumeration
Hydrogen
Acetylene
Ethane
Ethylene
Methane
CarbonDioxide
CarbonMonoxide
Nitrogen
Oxygen
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Unit
Ppm
Ppm
Ppm
Ppm
Ppm
Ppm
Ppm
Ppm
Ppm
Comment
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OxygenPlusArgon
TotalDissolvedGas
TotalCombustibleDissolvedGas
Ppm
Ppm
Ppm
9.2 Oil Quality
Enumeration
MoistureInOil
InterfacialNumber
AcidNumber
ColorNumber
FreeWater
VisualExamination
SedimentExamination
DielectricBreakdown
PowerFactor
SpecificGravity
OxidationInhibitor
PCB
CorrosiveSulphur
5Hydroxymethyl2Furaldehyde
FurfurylAlcohol
2Furaldehyde
2Acetylfuran
5Methyl2Furaldehyde
Unit
ppm
Dynes/cm
Mg KOH/g
Comment
kV
%
% weight
Ppm
Ppb
Ppb
Ppb
Ppb
Ppb
9.3 Bushing Insulation Power Factor
9.4 Winding Insulation
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9.5 Thermal
From the different measurement points you can get in the part 7 of the Loading guide for oil-immersed
power transformers (IEC 60076-7), the following are some points to build thermal model for the
estimation of top-oil temperature:
Enumeration
Ambient Temperature
Top-oil Temperature
Load Current
HT Hot-Spot Winding
Temperature
BT Hot-Spot Winding
Temperature
Wind Strength
Wind Direction
Unit
Comment
10 References
[1] IEEE Std C57.104, IEEE Guide for the Interpretation of Gases Generated in Oil-immersed
Transformers.
[2] IEEE Std C57.91, IEEE Guide for Loading Mineral-Oil-Immersed Transformers.
[3] Asset Health Focus Community, Dissolved Gas Analysis (DGA) Survey.
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