increased operation reliability through continuous … 4.2 w koltunowicz.pdf · increased operation...

30 June 2017

INCREASED OPERATION RELIABILITY THROUGH CONTINUOUS PD MONITORING OF STATOR WINDING

Laurentiu-Viorel BADICU*, Wojciech KOLTUNOWICZ*, Ulrike BRONIECKI*, Boris BATLLE**

*OMICRON Energy Solutions GmbH, Germany, **OMICRON Technologies, Spain

Agenda

> Introduction

> PD Monitoring System Architecture

> Case study: Turbo generator 180 MVA, 16.6 kV

> Case Study: Turbo generator 100 MVA, 13.2 kV

> Case Study: Hydro generator 126 MVA, 16.5 kV

> Automated Pattern Classification System

> Conclusions

Partial Discharges Monitoring System

A server based monitoring software to:• trend and store significant data for analysis

and comparison of different machines over their operating life;

• be easily accessible remotely for periodical evaluations and/or system tuning.

A synchronous multi-channel data acquisition stage:• ensure high flexibility for different installation

conditions;• provide advanced tools for in-depth analysis.

The crucial characteristics to guarantee the best insulation assessment :

Turbo generator: 180 MVA, 16.5 kV

Maintenance After maintenanceBefore maintenance

Turbo generator: 180 MVA, 16.5 kV

Preventive maintenance based on PD monitoring

Page 7

Turbo generators: 100 MVA, 13.2 kV – air cooled

Combined PD data trend from Gen. 1 and Gen. 2

Both units commissioned in 1981 PD monitoring system installed in 2012

One – year PD data trend PD data trend Sept. – Oct. 2013

Page: 15

Turbo generators: 100 MVA, 13.2 kV – air cooled

PRPD diagrams for central freq. of measurements: 2 MHz and 7 MHz

Page: 6

Hydro generator: 126 MVA, 16.5 kV

UNIT 7 and UNIT 8 were installed in 1997 in one of the largest hydroelectric power plants in Southeast Asia (1008 MW)

The installation of PD Monitoring completed in the 2nd half of 2012

Unit 7 showed a steep increase in the trend of PD activity in phase S, result confirmed by the comparison with the results from Unit 8

• identify and evaluate the reason of the increased PD activity;

• assess the overall conditions of the stator winding.

By means of 3PARD separation technology

and PD Pattern analysis, root cause investigation has been carried out to:


Root cause investigation

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3PARD cluster under investigation

PD Source under investigation

an anomalous activity has been isolated in Phase S and it’s persistence confirmed by the historical data


Overall assessment of the stator

By rejecting only the investigated PD activity, the overall conditions of the stator winding can be assessed

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• root cause of the growing trend: efficiently isolated and analyzed in time;

• conditions of the stator winding: removing the investigated PD, general assessment can be performed.

Results


Diagnosis

• Surface Tracking evolving in time;

Investigated PD activity

Visual Inspection Dissipation Factor test

• Internal PD activity uniformly distributed on the three phases

Overall conditions of the ground-wall insulation


Partial Discharge Monitoring System

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Fiber optic cable

Central computer & monitoring software

Fiber optic cable

Capacitive sensors

1st generator 2nd generator 3rd generator 4th generator

Hardware Architecture

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Web GUI


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Trend Analysis

PD Source Separation

Pattern Classification

Alarm / Warning

Q: Has something happened on

HV asset?

Q: How many problems are

there?

Q: What are the problems – defects

or noise?

Q: How dangerous are the problems?

Analysis Services


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Trend Analysis

PD Source Separation

Threshold


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PD Source Separation(automated OPTICS clustering)

PD Pattern Classification


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Reference Database(examples of PRPD patterns - stator winding PD defects)

Name PRPD illustration

rmS1 Delamination of the

insulation on the copper side

rmS2 Delamination of the insulation layers

rmS3 Delamination of the

insulation on the core side

rmS4 Discharges in micro cavities

rmE1 End-winding surface discharge (tracking)

rmE2 End-winding discharges /

sparking

rmE3

Discharge between corona protection and stress grading

layers

Cause of PD in Stator Winding

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Patterns Features (descriptors)

PRPD

Hq ‐ charge vs. impulse number

Hn – impulse amount vs. phase angle

Hqn – avarage charge vs. phase angle


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Algorithmic Concept

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Report example – PD


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PD Data Evaluation


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Decision Reliability

• The decision is based on separated initial data corresponded to only one PD source (automated clustering)

• Insufficient data is rejected at the early stage of analysis

• Only few approved PD features (attributes) are considered for the decision

• Reliable deterministic decision is provided for clear cases by knowledge-based analysis

• Probabilistic decision is provided for unclear cases with different levels of reliability defined by the distance plot


Conclusions

Continuous PD monitoring of stator windings in large generators has proven to be an essential diagnostic tool for condition-based maintenance in order to increase their reliability.

Based on the PD monitoring results obtained before and after the maintenance of the machine, the effectiveness of the maintenance program can be evaluated and future maintenance can be properly scheduled.

A versatile PD acquisition unit can be used for PD measurements on different types of rotating machines.

A modular, distributed monitoring software system allows reliable long-term storage of monitoring data and provides access via a web interface for detailed data evaluation.

The main key to performing appropriate diagnosis of the insulation state is to accurately separate and identify different PD sources from noise. To achieve this, synchronous multi-channel 3PARD evaluation techniques can be applied.

Thank you for your kind attention

[email protected]

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