automated classification system for polymeric insulation

Automated Classification System for Polymeric

Insulation Surface Condition

A. N. Ramani and A. R. Abdullah Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia

Email: {anisniza, abdulr}@utem.edu.my

N. Norddin

Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka (UTeM), Malaysia

Email: [email protected]

N. Q. Z. Abidin and A. Aman Universiti Teknikal Malaysia Melaka (UTeM), Malaysia

Abstract—Polymeric insulation is commonly used for high

voltage engineering as they are light, easy to fabricate, and

have good dielectric properties. Ageing factors affect the long

term performance of insulating material. Leakage current is

broadly accepted as tools in the determination of surface

condition and level of its severity. Hence, an automated

monitoring system is needed to reduce diagnostic time and

ensure quality of insulators performance. Due to the

limitation fast Fourier transforms (FFT), this research used

spectrogram as time frequency distribution technique that

represents the leakage current signals in the joint time

frequency domains which appropriate to analyze the leakage

current signals that consist of multi-frequency components

and magnitude variations. This technique extract relevant

information from leakage current (LC) signal and then

leakage current (LC) parameters are estimated to identify its

characteristics. Surface condition on High Density

Polyethylene (HDPE) and Polypropylene (PP) are

investigated. The classification of material surface state could

be determined instantaneously using the percentage of total

waveform distortion. Thus, the outcome of this study shows

that the system is very appropriate and reliable to be

implemented for leakage current online monitoring system.

I. INTRODUCTION

In high voltage engineering or its applications,

insulation is the most important part to prevent the flow of

current to undesired paths. Polymeric insulation is widely

accepted [1] compared to conventional ceramic insulation

due to its several advantages as mentioned by Hackam [2].

However, polymeric insulation still has certain limitations

such as difficulty in detecting defective insulation.

Hydrophobicity measurement techniques are mostly

studies on material surface characterization and chemical

Manuscript received December 15, 2014, revised April 30, 2015.

investigation. Besides that, one of the key indicators

widely accepted to determine performance of polymeric

insulation whether in service or accelerated ageing

laboratory test is by investigating the leakage current (LC)

signal. LC signal provides information of polymeric

insulation surface condition and the pollution severity [3].

LC measurement is popular technique because it can be

monitored either online or offline [4], [5]. Measurement of

the peak current, accumulated charge [6] and discharge

duration has been used by some researchers to provide

information on degradation.

However, onwards literatures show, LC harmonic

component analysis will give better information on

insulation surface [7]. As an example, A. H. El Hag, et al.

[8] examined low harmonic components of LC as a

diagnostic tool to study ageing and surface condition.

While N. Bashir, et al. [9] and Kordkheili [10] have

verified the ratios of lower harmonics components as the

major factor in determining the surface condition.

Nevertheless, FFT does not provide temporal

information and is not appropriate for non-stationary signal

[11]. Instead, the analysis using time frequency distribution

(TFD) such as is used. These TFD linear time frequency

distribution approach resolve the limitation of FFT. In this

recent work, TFD is employed to analyze LC components

to identify surface condition of polymer materials.

Fernando and Gubanski [7] in their work had been

separated the surface events into several stages. The stages

are early ageing period (EAP), transition period (TP) and

late ageing period (LAP). These stages determine the level

of surface condition as well as its contamination levels. At

early ageing period (EAP) only capacitive LC existed

which indicated the insulator in hydrophobic condition.

Then, during transition period (TP) the surface of insulator

becomes hydrophilic and LC significantly changes to

resistive condition. Finally, during late ageing period (LAP)

the LC level become higher and become completely

resistive. At this moment, the surface erosion took place as

well as produce non linear LC wave shape.

International Journal of Electrical Energy, Vol. 3, No. 2, June 2015

©2015 International Journal of Electrical Energy 105doi: 10.12720/ijoee.3.2.105-109

Index Terms—time frequency distribution, spectrogram,

insulation, tracking and erosion

Tracking and erosion test complying with BS EN

60587-2007 conducted on High Density Polyethylene

(HDPE) and Polypropylene (PP) as the polymeric

insulation material. A computer-based online LC

monitoring of the insulators surface is found to be more

practical due to the long period of time taken in conducting

the laboratory test. Online performance monitoring can

benefits engineering industries by confirming if the

materials is performing as desired by the user. Monitoring

system gives instantaneously information on LC

parameters such its harmonic components. Normal

performance analyses are usually conducted in offline

mode which the LC data is saved into other files to be

analyzed later.

This paper describes the online LC monitoring system

that classifies LC signals in time domain, frequency

spectrum, time-frequency representation as analysis

method, LC parameters such as root mean square (RMS)

value, fundamental value, total harmonic distortion (THD),

total non-harmonic distortion (TnHD), and total wave

distortion (TWD). These parameters instantaneously is

estimated in order to develop and monitoring state

condition of the materials insulating condition. The

percentage of total waveform distortion TWD% is applied

as rule based value for surface classification purpose. The

results of LC analysis the online monitoring system is

compared with other software that also used to monitor and

analyzed the LC performance. This comparison is certainty

that the online monitoring system is reliable and can be

used in the industry.

II. EXPERIMENTAL SETUP

A. Inclined-Plane Test

Inclined-Plane Test (IPT) is normally used to evaluate

the tracking and erosion resistance of insulating materials

and recommended by BS EN 60587 [12]. In the test

procedure, since it is done in the same place every day,

there are three parameters that are assumed constant;

humidity, pressure, and temperature. As stated in the

standard, the contaminant conductivity level is set to

2.533S/m measured by Hanna Dist 4 conductivity meter

and its flow rate at 0.6ml/min. The system for evaluating

the surface tracking and erosion test along with the online

LC monitoring system is shown in Fig. 1 and Fig. 2. The

whole system is placed inside a separated room to avoid

any outside noise or disturbance that could affect the test

measurement.

Figure 1. Schematic diagram of incline-plane tracking (IPT) test

Figure 2. Schematic diagram of incline-plane tracking (IPT) test

B. Material

The major factors that resolve to the failure of the

insulation are dielectric and electrical field which are the

key properties of insulating materials [6]. High Density

Polyethylene (HDPE) and Polypropylene (PP) are

non-ceramic or polymeric composite refer to hydrophobic

materials. These substances selected based on nature

dielectric strength and dielectric constant that is nearly

identical [7].

High Density Polyethylene (HDPE) is among polymer

that is good to be made as insulating material. Numerous

studies were done towards High Density Polyethylene

(HDPE) [8]. According to Lynn, high density polyethylene

has the capability as insulating material. This is as that

stated inside [9]. Fig. 3 shows discharge condition for

HDPE and during the discharge the spark and smoke exist.

After the test, there are small erosion exist on the surface of

the sample.

Figure 3. Discharge on high density polyethylene (HDPE)

(a) (b)

Figure 4. Discharge on polypropylene (PP)

Polypropylene (PP) has good balance between electrical

and mechanical properties [13]. It also has high dielectric


©2015 International Journal of Electrical Energy 106

strength [14]. Polypropylene has resistance to heat

distortion, have excellent electrical properties and fatigue

strength, chemically inert, relatively inexpensive, but it

have poor resistance to UV light [15]. Their melting

temperature generally range from 170-230°C and due to its

low moisture absorption, it is not necessary to dry its

compound before moulding [16]-[18]. In Fig. 4 the

discharge condition for Polypropylene and the condition

after the test on sample surface are shown.

C. Leakage Current Monitoring System

An LC data acquisition system is developed to analyze

the LC flowing on the sample surface under laboratory

conditions. It consists of three parts; measuring unit, signal

conditioning, and analog-to-digital (ADC) with personal

computer. The graphical results of the LC signal are

developed using Visual Basic (VB) software in the

personal computer. Visual Basic (VB) applies events

driven programming language and allows users to click on

a certain object randomly to make some action. More

specifically, the system is designed for interactive user

interface. The data is entered and then the result is viewed

on the computer screen. The front panel of the graphical

user interface (GUI) of the developed program is shown in

Fig. 5.

Figure 5. Front panel of leakage current monitoring system

III. TIME FREQUENCY DISTRIBUTION

Linear time frequency distribution (TFD) provides the

information about time variation as well as frequency

spectrum of leakage current simultaneously which using

spectrogram. From the time frequency representation

(TFR), characteristics of the signals can be calculated and

used as input for signals classification. The signal

characteristics are total harmonic distortion, total non

harmonic distortion, total waveform distortion and current

root mean square (IRMS).

Spectrogram is one of the time-frequency

representations (TFR) that represents a three-dimensional

of the signal energy with respect to time and frequency.

Spectrogram is squared magnitude of the short time

Fourier transforms (STFT). This technique roughly reflects

how frequency content changes over time. The

spectrogram defined as

2

2( , ) ( ) ( ) j fxS t f h w t e d

(1)

where h(τ) is the input signal and w(t) is the window

observation window. In this study, Hanning window is

selected because of its lower peak side lope [14] which is

narrow effect on other frequencies around fundamental

value (50Hz in this study) and other frequency

components.

IV. PARAMETER ESTIMATION

Parameters of the signal estimated from the time

frequency distribution to recognize the signal information

in time.

A. Instantaneous RMS Current

The instantaneous RMS current is

max

0

[ ] ( , )

f

rms xI t S t f df (2)

B. Instantaneous RMS Fundamental Current (I1rms)

Instantaneous RMS fundamental current I1rms(t) is

defined as the RMS current at power system frequency and

can be calculated as:

(3)

where f1 is the fundamental frequency that corresponds to

the power system frequency and Δf is the bandwidth which

is set to 50Hz.

C. Total Harmonic Distortion (THD)

THD is the relative signal energy present at

non-fundamental frequencies and written as:

2,2

1

( )( )

( )

H

h rmshTHD

rms

I tI t

I t

(4)

where Ih,RMS(t) is RMS harmonic current and H is the

highest measured harmonic component.

D. Total Non-Harmonic Distortion (TnHD)

Non-harmonics or inter harmonic are not multiple

integer signal components frequency of the power system

frequency. Therefore, TnHD is referred as distinguishing

between non-harmonic and noise, and is calculated as:

2 2,0

1

( ) ( )( )

( )

H

rms h rmshTnHD

rms

I t I tI t

I t

(5)

E. Total Waveform Distortion (TWD)

TWD consists of harmonic distortion and non-harmonic

distortion. It can define as:

2 2( ) ( ) ( )TWD THD TnHDI t I t I t

(6)



1

1 1

( ) 2 ( , )

,2 2

hi

lo

f

rms x

f

hi lo

I t S t f df

f ff f f f

V. RESULT

The effectiveness and reliability of the online

monitoring system is tested by conducting an experiment

according to the IPT method. During experiment, it is

observed that at low voltages level between 0-0.5kV, there

is no erosion and arcing activities occurred on the

insulation material. The capacitive state from both

materials shows the same capacitive sinusoidal shape

depicts in Fig. 6. All patterns amplitudes of RMS current

have been normalized by dividing by the RMS value of the

normal signal (resistive signal). This is because at resistive

signal only fundamental frequency exists.

Figure 6. Capacitive pattern

Figure 7. Resistive pattern

At this resistive state only fundamental frequency 50Hz

exist. This condition appeared at voltage stresses 1kV until

1.5kV. The average instantaneous RMS current is

approximately 1.0pu and it has a smallest TWD value that

is below 3% because of low distortion on the signal. In Fig.

7, resistive pattern is shown.

At 1.8kV, waveform of the non linear pattern with

distortion exists depict in Fig. 8 and the sounds of arcing

without spark are produced. At 2.5kV until 4kV arcing

sound and spark exist, this also created nonlinear pattern.

The RMS current pu for this state is higher than 1.0pu.

THD, TnHD and TWD value around 100%. On non linear

pattern there are ‘rest’ times requisite for a full

hydrophobic condition to take place again. It is the

temporary loss of hydrophobicity during discharge.

Hydrophobicity transfer or recovery occurs because of

absorption of low molecular weight to pollution layer. Arc

current dissipated energy large enough to cause rupture in

the polymer chains and is transferred to the surface directly.

The severities because of degradation on the surface

become higher [17], [19]. The non linear pattern during

discharge on polymeric insulation material also indicated

that erosion is occurred on the surface of the insulator.

Figure 8. Nonlinear pattern

VI. SURFACE CONDITION CLASSIFICATION

In order to find out the relation between RMS current pu

and total waveform distortion (TWD) to the surface

condition of the insulator signal classification have been

conducted. Analysis results were made based on leakage

current parameter estimation obtained from spectrogram.

The rules based are used to classify the surface condition

event instanteously are summaries in Table I.

TABLE I. RULED BASED ON SURFACE CONDITION CLASSIFICATION

Pattern Parameter High Density

Polyethylene Polypropylene Condition

Capacitive IRMS <1.0 pu <1.0 pu No arching Harmonic

exist at 500-600Hz TWD 50-3% 50-3%

Resistive

IRMS 1.0 pu 1.0 pu Arching sound and

only fundamental

frequency, 50Hz exist TWD <3% <3%

Nonlinear

IRMS varies

1.0≤x≥1.0 varies Dry band with high

arcing which lead to

erosion and harmonic

exist at 3rd, 150Hz TWD

Percentage

varies around

50 %-200%

Percentage

varies around

50 %-200%



VII. CONCLUSION

This study using new approach to presents analysis of

polymeric insulation leakage current patterns using

parameter estimation to identify the surface condition of

the insulator. In conclusion, it was found that late aging

period state with unsymmetrical discharge pattern on

polymeric insulation material can be use as erosion

indicator occurred on the surface of the insulator. Instead

of using leakage current amplitude, ruled based obtained

from spectrogram can be used to determine the surface

condition of the insulator instantaneously. Moreover, the

classification of surface condition of insulators can be

automatically done by using this new system.

ACKNOWLEDGMENT

The authors gratefully acknowledge the Ministry of

Higher Education (MOHE) and Universiti Teknikal

Malaysia Melaka (UTeM) for providing the research grant

RACE/F1/TK3 /UTEM/10.

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A. N. Ramani was born in Kuala Lumpur,

Malaysia in 1981. She received his B.Eng. from

University Teknikal Malaysia Melaka (UTeM)

in 2006 and Master Degree from University of

Technology Malaysia in 2009.

1979. He received his B. Eng., Master, PhD

Degree from University of Technology

Malaysia in 2001, 2004 and 2011 in Electrical

Engineering and Digital Signal Processing. He

is currently a Senior Lecturer and Coordinator

of Center of Excellent Robotic and Industrial

Automation (CeRiA) in Universiti Teknikal

Malaysia Melaka (UTeM).

Malaysia in 1987. She received her Diploma

and B.Eng from Universiti Teknikal Malaysia

Melaka (UTeM) in 2008 and 2011, respectively,

in electronic power and drives. She is now

pursuing her Master Degree in High Voltage

engineering in Universiti Teknikal Malaysia

Melaka (UTeM).

in Perak, Malaysia, on November 25, 1985. She

received Diploma and B. Eng. degrees with

honours in electrical engineering from the

University Teknikal Malaysia Melaka (UTeM)

in 2006 and 2011, respectively. Currently, she

is master’s degree student researcher in the field

of high voltage engineering.

Malaysia in 1973. He received his B.Eng. and

Master Degree from University of Technology

Malaysia in 1998 and 2007, respectively, in

Control & Instrumentation and High Voltage

engineering. He is now pursuing his PhD in

same university in High Voltage engineering.

He is lecturer in Universiti Teknikal Malaysia

Melaka.



M. S. Naidu and V. Kamaraju, High Voltage Engineering,

McGraw-Hill, 1999.

A. R Abdullah was born in Kedah, Malaysia in

Nurbahirah Binti Norddin was born in Kedah,

Nur Qamarina Binti Zainal Abidin was born

Aminudin Bin Aman was born in Melaka,

automated classification system for polymeric insulation

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