Monitoring power transformers oils deterioration using ...

Measurement 113 (2018) 38–45

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Monitoring power transformers oils deterioration using structured laser illumination planar imaging

MARK

Guy-Oscar Regnimaa, Amidou Betiéa,b, Thomas Koffia, Olivier K. Baguia, Issouf Fofanab, ⁎ Abaka Kouacoua, Jérémie Zoueua, a b

Laboratoire d’Instrumentation, Image et de Spectroscopie (L2IS), INPHB, DFR-GEE, B.P. 1093 Yamoussoukro, Cote d’Ivoire Research Chair on Aging Power Equipment Infrastructure (ViAHT), Université du Québec à Chicoutimi, Chicoutimi, Québec, Canada

A R T I C L E I N F O

A B S T R A C T

Keywords: Extinction coefficient Structured illumination Transformers oil diagnosis Dense turbid media

Reliable quality assessments of oils in power transformers are important as they provide valuable information regarding the proper functioning of transformers. Thus, an early and accurate diagnostic of power transformers oils can prevent potential failures of transformers. In this paper, an imaging technique known as Structured Laser Illumination Planar Imaging (SLIPI) was used to monitor the extinction coefficient μe in various oil samples. The proposed technique offers the advantage of extracting the light intensity contribution from singly scattered photons and rejecting most of the light intensity from photons that have been scattered many times. This leads to more accurate and reliable measurement of the extinction coefficient μe , in optically dense oil samples. The variation of the extinction coefficient was therefore determined as a function of oil aging. The results demonstrate that SLIPI is reliable as a practical measurement method for the diagnosis of power transformer oils and present an attractive solution, alternative to the conventional methods such as Dissolved Decay Products, Interfacial Tension and Turbidity.

1. Introduction Power transformers are key components for electrical energy generation and delivery [1]. Degraded oil in transformers affects the power delivery and can lead to functioning failures. It is therefore critical to control and anticipate the proper functioning of power transformers by monitoring their insulation. The diagnosis of transformers is thus vital for their proper maintenance and to improve their operating conditions, which ensure a reliable and efficient supply of electricity [2]. The oil content and condition tell us about the degradation and the Aging of power transformers; therefore, it serves as diagnostic target as it contains approximately 70% of these diagnostic information [3–5]. Thus, the diagnosis of oils has long been the focus of several research projects, ultimately leading to the development of various diagnostic tools. Among these diagnostic tools, electrical-based methods allow to determining certain properties non-destructively such as the relative permittivity and dissipation factor, the capacitance, polarization index, resistivity, dielectric strength, partial discharges, electrostatic charging tendency, etc [6]. The results of these measurements provide an average value of the whole insulator volume, electrically and geometrically heterogeneous, and they do not characterize the status in a specific point of the material. The role of these methods is nevertheless

⁎

Corresponding author. E-mail addresses: [email protected] (A. Betié), [email protected] (J. Zoueu).

http://dx.doi.org/10.1016/j.measurement.2017.08.019 Received 6 May 2017; Received in revised form 7 August 2017; Accepted 11 August 2017 Available online 23 August 2017 0263-2241/ © 2017 Elsevier Ltd. All rights reserved.

very important to monitor the condition of the transformer by comparison with previous or suggested limit values. Physicochemical methods, such as the water content in oil [7–9], and the analysis of dissolved gas in the insulation oil are also widely used. Various standards/methods have been developed for the interpretation of these dissolved gas analysis. The most commonly used interpretation methods are [10]: the IEEE C57.104–1991, Doernenberg, Rogers, IEC 60599 and the Duval’s triangle. The main problem concerning this technique lies in the determination of the limit values for simple gases. However, gas chromatographs are very expensive. Other techniques such as the total acid number in oil [11], the interfacial tension (IFT) [12] are also widely used. IFT test require experienced user and also, some precautions have to be taken as indicated in the American Society for Testing and Materials (ASTM), ASTM D971 in order to do measurements. Methods based on spectral analysis also exist, including spectrophotometric absorption measurements of the oil samples. In this case, light that passes through the contaminated oil is attenuated by the absorbing elements [13]. The results obtained allow assessing the relative amount of dissolved decay products (DDP) in oil. Furthermore, it should be noted that these different diagnostic methods mentioned above are for the most part time consuming and very expensive. Moreover, regarding the methods based on spectral analysis, not all of

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them provide knowledge about the degree of degradation of the oils namely due to the high density of some of them. For spectrophotometry using the Beer-Lambert-Bouguer within the limits of its application, it is necessary to dilute the solution by a solvent thus modifying the initial state of this solution. Otherwise, there are measurement errors due mainly to multiple scattering of light [14]. In this article, a new assessment technique based on optical imaging called SLIPI (Structured Laser Illumination Planar Imaging) is proposed [14]. This technique could serve as a better alternative approach for the diagnosis of oils in power transformers. The main advantage of the technique is its capability in providing reliable results even within optically dense liquids as recently demonstrated in [14]. Thus, one does not need, for the dense samples, to perform dilution processes,. In addition to being fast and cost-effective, it has a simplified optical setup. No need to shift the lines pattern to record images and it is suitable for recording series of successive images. The most important advantage is its ability to suppress multiple scattering effects on instantaneous imaging in turbid media [14]. The SLIPI method consists in imaging, from the side, a modulated light sheet crossing the turbid sample. Then, the intensity contribution from multiple light is suppressed after post-processing of the recorded image, and an exponential intensity decay is obtained as light crosses the sample. By making a curve fit on this decay and using the BeerLambert law, the extinction coefficient of the sampled liquid is obtained [14]. Note that Bagui et al. [15] have used the SLIPI technique to establish ground coffee classification. In this article, the extinction coefficient of transformer oils is measured using the so-called single-phase SLIPI approach [14,16]. The results are compared with those obtained from the methods commonly used for the diagnosis of power transformer oils, such as Dissolved Decay Products (DDP), Interfacial Tension (IFT) and Turbidity. A description of the equipment and methodologies used is provided, followed by the results and finally the discussion and conclusion are presented.

Fig. 1. Overview of the transformer oil samples. The first range of transformer oils from S1 to S4 are pale yellow and are unaged (0 h). The second range of transformer oils from S5 to S8 are brown and are those aged at 1000 h. Their appearance indicates bad condition. The last range from S9 to S12 are black and are those aged at 2000 h. Their appearance indicates extremely bad condition. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

2.2. Analysis of the oils using Turbidimetry Turbidity defines the disorder of a transformer’s oil caused by suspended solids which are generally invisible to the naked eye. Usually, an oil contains suspended solids, which consist of a large number of particles of different sizes. The suspended particles are responsible of the turbidity of the oil in the transformers. The instrument used to make the measurements is the nephelometer 2100AN of the manufacturer HACH [17]. Measurement of turbidity has been performed according to the ASTM D 6181 [18]. The turbidimeter uses the principle of the interaction between an incident light and the suspended solids in oil leading to several phenomena such as diffusion, reflection, absorption and refraction. These suspended solids in oil, according to their size, kind, shape, refractive index and its intensity cause a dispersion of the incident light in all directions [19]. The optical system consists of a tungsten filament lamp, lenses and apertures for concentrating light, a detector placed at 90 degrees from the light detector, a forward scatter detector, a backscatter detector and a transmitted light detector. The instrument measures the Turbidity using the complete set of detectors (ratio measurement). The microprocessor of the instrument uses a mathematical calculation from the signals ratio of each detector. The advantages of using the ratio for measurements include excellent linearity and stability of calibration and ability to measure turbidity in presence of color. The turbidity is expressed in NTU (Nephelometric Turbidity Unity). As advantages, the Turbidimetry is very accurate and useful for measuring very low turbidity (less than 5 NTU). However, there is a number of limitations: the high cost, high power needed and the fragility of the system [19]. Some guidelines for turbidity values of oils are given in Table 2. The results of turbidity obtained for each sample of transformer oils as a function of aging duration are shown on Fig. 2. In the analysis of the results obtained (Fig. 2), the increase of the values of turbidity reflects the aging of the power transformers oils [19,21]. According to the guidelines suggested for turbidity given in

2. Description of the investigated oils and standard analysis 2.1. Description of the oils The preparation of oil samples of transformer has been made in laboratory, at the University of Quebec in Chicoutimi, Canada. The simulation of the aging of the different oils is made by taking into account the conditions of aging in the power transformers. Aging was carried out in a mechanical convection oven whose temperature was set to 115 °C. To accelerate the aging, catalysts such as the powder of copper (3 g per liter of oil) were used. Several samples were prepared. The list of samples analysed is shown in the Table 1. The paper behaves as a filter and decreases the dissolved decay products (see Fig. 1). Table 1 Description of Transformer oil samples. Name of the samples

Samples description

Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample

0 h before test of stability 0 h with 150 strains and strong electric discharges 0 h with 0% of ratio paper-oil 0 h with 10% of ratio paper-oil 1000 h before test of stability 1000 h with 150 strains and strong electric discharges 1000 h with 0% of ratio paper-oil 1000 h with 10% of ratio paper-oil 2000 h before test of stability 2000 h with 150 strains and strong electric discharges 2000 h with 0% of ratio paper-oil 2000 h with 10% of ratio paper-oil

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12

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Table 2 Guidelines suggested for turbidity [20]. Oil condition

Turbidity (NTU)

Good oils Proposition an oils Marginal oils Bad oils Very bad oils Extremely bad oils

0–1 1–4 4–10 10–30 30–150 > 150

Fig. 3. Interfacial tension of each sample of transformer oils as a function of aging duration. When the aging duration is high, the IFT for each sample of power transformer oil decreases.

some precautions have to be taken as indicated in the ASTM D971 in order to do measurements. Some guidelines for IFT values of oils exist. Good and clean oils have IFT number between 40 to 50 dynes per centimeter. For IFT value below 25 dynes per centimeter, the oil is recommended to be reclaimed because the oil is contaminated by sludge, which begins at around 22 dynes per centimeter [25]. The results of IFT values obtained for each sample of transformer oils are shown on Fig. 3. Fig. 3 shows a decay of the values of IFT. Indeed, for in-service transformer oil, the decrease of the values of IFT indicates the accumulation of contaminants and/or oxidation products in the oil. One may notice that with increasing aging duration, the IFT value decreases [19,21]. This value is constant and is equal to 15 dynes per centimeter from 1500 h. Classification of transformer oils samples has been established by using data reported in [24]. At 0 h, all the oils samples have IFT values higher than 25 dynes per centimeter. They are refereed as “Good oils”. The oils with aging duration at 1000 h and 2000 h have IFT values lower to 22 dynes per centimeter. They are classified as “bad quality oils” and reclamation is recommended .

Fig. 2. Turbidity of each sample of transformer oils as a function of aging duration. When the aging duration is high, the turbidity for each sample of power transformer oil increases.

table 2 [20], classification of the oils samples has been made. At 0 h, all the oil samples are in the range of “Good oils”. the oil ssamples with aging duration equals to 1000 h are “Marginal oils” and those aged at 2000 h correspond to “Marginal or bad oils”. 2.3. Analysis of the oils using interfacial tension The interfacial tension (IFT) allows evaluating the oxidation degree of the mineral oils, by detecting the presence of polar compounds [22]. It represents the force in dynes per centimeter required to rupture a platinum ring at the interface between the oil and distilled water [23]. Measurement of the interfacial tension to assess the condition of the liquid insulation is performed according to the ASTM D971-12 [12] using a surface tensiometer. The instrument used is a DuNouy type from Fisher Scientific brand tensiometer which uses a plane ring of Platinum/iridium alloy. The measurement shall be made within 60 s of formation of the interface. When certain contaminants such as oxidation products are present in the oil, the strength of the oil film is weakened, requiring less tension to break the film. For oils in service, a decreasing value of IFT points out the accumulation of contaminants, oxidation products or both. It is a measurement indicating the presence of oxidation products that can attack the solid insulation and influence the cooling of the transformer. The more the oil degrades, the more this value has a tendency to decrease. The IFT test provides information on polar contaminants and oxidation products. However, due to the high hydrophilic nature of the oil, the interfacial tension test may not be very sensitive to changes in the fluid quality [24]. Moreover, IFT test requires trained person and also,

2.4. Analysis of the oils using dissolved decay products The measurement of the relative quantity of Dissolved Decay Products in oil or DDP is carried out by spectrophotometry UV/VIS (ultraviolet/visible) according to the ASTM 6802. The instrument used for measurements is a Thuramed T60 UV/Vis spectrophotometer. The spectrophotometer sheds a monochromatic incident light I0 through a length L (the length of the cuvette) of the oil sample to test and measures the absorbance A (size linked to the quantity of light absorbed by the solution). From this study one determines the absorbance A and transmittance T defined respectively by the Beer-Lambert-Bouguer law:

A = −logT and T =

I = e−μe L I0

(1)

where I is the intensity transmitted from the light and µe is the extinction coefficient. For each wavelength, the absorbance of each power transformer oil is measured and the data collected are used to plot the absorbance 40

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with respect to those of 0 h (fresh oils).

Table 3 Guidelines for Dissolved Decay Products (DDP) [20]. Oil condition

DDP (a.u)

Good oils Proposition an oils Bad oils Very bad oils Extremely bad oils

0–10 ± 10–25 25–50 50–300 > 550

3. Single-phase SLIPI experiment 3.1. Experimental setup The SLIPI technique has been developed in 2008 by Edouard Berrocal and Elias kristensson [26,27]. This technique, which has been both demonstrated by simulation and by experimentation, possesses a large capacity for the suppression of multiple light scattering in the planar spray imaging, thereby strongly improving the visualization [28–31]. With the conventional method, there is a multitude of scattering in all directions which seriously affect the expected results. The main motivation for developing this new technique is to eliminate blurring effects due to multiple scattering of light in order to obtain qualitative and quantitative information such as the extinction coefficient [32]. While the transmission measurement records the light intensity of a single beam crossing the sample of interest (where the initial and final intensities are recorded), SLIPI makes the imaging of the spatially modulated light sheet. (from 90° angle). In this contribution, the single-phase SLIPI approach [14,16] is used for the measurements of the extinction coefficients. Fig. 2 shows a schematic of the experimental setup. A sample of transformer oil into a silica cuvette, is illuminated by a spatially modulated laser sheet. The light sources consist of two continuous wave (CW) laser beams of 450 nm and 638 nm, which are recombined along the same optical path using a dichroic mirror. One laser is activated at a time and a neutral density wheel is used to adjust the incident irradiance in order to optimize the signal to noise ratio, while avoiding saturation. The laser sheet is performed by means of a succession of spherical and cylindrical lens. Subsequently, a reflecting mirror is placed at 45° which returns the laser sheet on the sample after passing through a Ronchi grating (2 lines pairs/mm) creating intensity modulation. The images are recorded using a 14 bit Electron Multiplying CCD camera, Luca (r) from Andor with 1002 × 1004 pixels and the final image is the results of the accumulation over 200 single-shot images. This camera located at 90°, perpendicular to the direction of propagation of the laser sheet, captures images of the modulation created into the cuvette. The camera objective is set to F# = 5.6 and the exposure time ranges between 0.002 and 0.015 s to optimize the dynamic range for each sample of oils concentration. The camera linked to a computer records the different images obtained. Fig. 5 is the schematic of the experimental set up.

curve A (on the ordinate) as a function of the Wavelength λ (on the abscissa). The graph thus obtained constitutes the UV/visible spectrum. The numerical integration of the surface below the absorbance curve allows determining the relative amount of the Dissolved Decay Products (DDP: peroxides, Aldehydes, ketones and organic acids) in liquid samples. This technique is used routinely for the quantitative study of organic molecules (molecules composed essentially of carbon and hydrogen) and functional groups by measuring the absorbance of the oil samples. While being very useful, these measurements are, unfortunately, no longer valid when applied to optically dense scattering media such as turbid liquids. This limitation is due to both the strong reduction of desired unscattered light and the large increase of unwanted scattered photons reaching the detector. Using more sensitive sensors or brighter light sources can compensate the reduction of the desired signal. However, the effects of multiple light scattering are more challenging to account for [14]. Table 3 highlights the guidelines for DDP values, expressed in arbitrary unit (a.u.). The results of DDP obtained for each sample of transformer oils as a function of aging duration are shown on Fig. 4. Concerning the evolution of the DDP in the power transformer oils seen on Fig. 4, there is a general increase in the values of the areas calculated under the curves as the aging duration increases from 0 h to 2000 h. The increase of the values of DDP reflects the aging of the power transformer oils [19,21]. From the analysis of the results of the physicochemical techniques used, it emerges that power transformer oils undergo a rapid deterioration as aging duration increases. Thus, oils aged at 2000 h are more degraded than those at 1000 h which in their turn are degraded

3.2. Single-phase SLIPI post-processing The single-phase SLIPI approach used in the current study and shown in [14] is based on an analytical tool known as lock-in detection [33]. Lock-in detection is most often associated with analysis of temporally varying signals but it works equally well for spatially modulated signals. To explain the principle of lock-in detection, consider a 1D signal, I(x), with a superimposed periodic variation of an amplitude IS in space:

I (x ) = IS sin(2πνx + ϕ) + IMS (x )

(2) −1

where ν equals the spatial frequency (mm ) of the modulation and ϕ is the spatial phase, which is unknown. The IMS term represents any unwanted non-modulated intensity contribution also being detected, such as, multiple light scattering or any surrounding light background. The purpose of the lock-in analysis is to extract IS and reject IMS. To achieve this end, the signal I is multiplied with two reference signals R1 and R2, created computationally, that have a relative phase shift of π/2 : Fig. 4. Dissolved Decay Products of each sample of transformer oils as a function of aging duration. When the aging duration is high, the quantity of DDP for each sample of power transformer oil increases.

R1 (x ) = sin(2πνx ) and R2 (x ) = cos(2πνx ) Multiplying I with these reference signals yields: 41

(3)

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Fig. 5. SLIPI optical set-up: After expanding the incident laser beam, a light sheet is formed using a cylindrical lens focusing the beam into the cuvette. The light sheet is modulated just prior to enter the cuvette containing the oil sample by a Ronchi grating of 2 lp/mm frequency. The images are recorded using an EM−CCD camera.

I1 (x ) =

1 IS (cos(ϕ)−cos(4πνx + ϕ)) + IMS sin(2πνx ) 2

(4)

I2 (x ) =

1 IS (sin(ϕ) + sin(4πνx + ϕ)) + IMS cos(2πνx ) 2

(5)

The frequency analysis of I1 and I2 reveals three components; (1) a DC component, (2) one modulated with 2ν and (3) one modulated with ν. The two latter components can be suppressed by means of a low-pass filter in the Fourier domain, with a cut-off frequency less than ν, resulting in the following expressions:

1∼ 1∼ ∼ ∼ I1 (x ) = IS cos(ϕ) and I2 (x ) = IS sin(ϕ) 2 2

(6)

where the tilde assignment indicates the applied frequency filtering. ∼ From these, IS can finally be extracted by calculating:

∼ ∼ ∼ IS = 2 (I1)2 + (I2)2

(7)

An illustration of the single-phase SLIPI process is given in Fig. 6. From a modulated image, the amplitude of the modulation is extracted using Eqs. (3–7). The modulated component, IS, corresponds to the single light scattering which reduces exponentially with distance. By applying an exponential fit to IS the extinction coefficient, µe, can be directly extracted as stated in the Beer-Lambert-Bouguer law (see Eq. (1)). 4. Results and discussion The experimental results of SLIPI measurements are presented from Figs. 7–10 for the different samples of power transformers oils. The values of the extinction coefficients obtained at the different wavelengths (450 nm, 638 nm) are reported on Figs. 9 and 10. The results of the extinction coefficients values obtained from the curves on Fig. 9 are reported in the Fig. 11. These curves show how the extinction coefficients of power transformers oils change as a function of aging duration. In regard to the results obtained with SLIPI technique (Fig. 9), for an in-service transformer oil (2000 h and 1000 h), the exponential decay of the light intensity as function of distance through the cuvette (a and b respectively) is more pronounced than the exponential decay of light intensity as function of distance through the cuvette (c) obtained for the fresh oils (0 h). These observations point out the effect of transformers oils aging. In fact, its express the fact that SLIPI technique is able to see the effect of aging on power transformers oils. From the presented results on Fig. 10, one can divide for each power

Fig. 6. Principle of single-phase SLIPI. The example shows the signal from a structured laser sheet, with cross-sections extracted from two different depths, marked as A and B. Notice the decrease in amplitude from column A to B. The 1 D Fourier transforms of curves A and B, shows the reduction in strength of the 1st order peak (modulation frequency). This frequency is then isolated using frequency filtering (red area) after applying the lock-in algorithm. Finally, the exponential decay is revealed, as shown in the SLIPI image and related curve IS. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Fig. 7. Images of the structured light sheet crossing the cuvette containing the samples S5, S6, S7 and S8 of power transformer oils for 450 nm illumination wavelength. The corresponding SLIPI images are compared in the figures below. As these oils are mostly absorbing, the blurring effects due to multiple scattering are less apparent. However there is still some remaining undesired scattered light which must be suppressed using SLIPI. The resulting SLIPI images depict, thus, the correct light extinction where an exponential fitting of the intensity decay provide the corresponding extinction coefficient.

oils (0 h), the extinction coefficients are very low which show that they are not deteriorated. When the oils are in service, they change their appearance with the time and become more and more optically dense. Moreover, there is an increase in the concentration of chromophores in the samples. This aging is reflected in some research works by an increase of the absorbance as a function of the aging duration or wavelength [34,35]. Furthermore, there is a relationship linking the absorbance to the extinction coefficient. This relationship is given by the Eq. (8):

transformer oil samples S9, S10, S11 and S12, the extinction coefficients obtained for 450 nm and 638 nm illumination wavelengths such that R = μe (450 nm)/ μe (638 nm) . R corresponds to the ratio of the extinction cross-sections (σe(450 nm)/σe(638 nm)). This ratio calculated for each sample is more or less equal to R = 26. It value is constant and is, therefore, an optical parameter characterizing the probed liquid. This implies that measurements are reliable. It means that power transformer oil particles diffuse and absorb the blue light 26 times more than the red light. Thus from this experimentation, behave power transformer oil when it is in interaction with a radiation can be assess. It can be observed that it would be better to use red laser at 638 nm illumination wavelength to perform measurements in the case of power transformer oils with aging duration superior or equal to 2000 h. The curves in Fig. 11 show for 450 nm illumination wavelength used, an increase in the values of the extinction coefficients of different power transformers oil samples when the aging duration increases. By comparing curves, the extinction coefficients of the in-service transformer oils (2000 h and 1000 h) are higher compared to the one of fresh oils (0 h). The increase of this optical parameter indicates that power transformers oils are subjected to an aging. In fact, in the case of fresh

μe = A. ln(10)/ L

(8)

where L is equal to 16 mm, corresponding to the length of the cuvette used in the measurements. A is the absorbance value. From Eq. (8), it is clear that if the absorbance increases, the extinction coefficient will increase too. Thus, the values of the IFT, DDP and turbidity measurements agree with the obtained results. The inservice transformer oils (2000 h and 1000 h) have high extinction coefficients than the new oil (0 h). So the SLIPI has the great ability to analyse the oil condition to large scale. Fig. 8. Images of the structured light sheet crossing the cuvette containing the samples S9, S10, S11 and S12 of power transformer oils for 638 nm illumination wavelength. The corresponding SLIPI images are compared in the figures below. As these oils are mostly absorbing, the blurring effects due to multiple scattering are less apparent. However there is still some remaining undesired scattered light which must be suppressed using SLIPI. The resulting SLIPI images depict, thus, the correct light extinction where an exponential fitting of the intensity decay provide the corresponding extinction coefficient.

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1

2000 hours S11 µe = 1.989 mm-1

Normalized intensity [au]

2000 hours S12 µe = 2.011 mm-1

0.8

2000 hours S10 µe = 1.998 mm-1

(c) 0.6

(a) 0.4

0.2

(b) 0

0

2

4

6

8

10

12

2000 hours S9

µe = 1.966 mm-1

1000 hours S7

µe = 0.406 mm-1

1000 hours S8

µe = 0.387 mm-1

1000 hours S6

µe = 0.537 mm-1

1000 hours S5

µe = 0.513 mm-1

0 hour S1

µe = 0.053 mm-1

0 hour S4

µe = 0.064 mm-1

0 hour S3

µe = 0.061 mm-1

0 hour S2

µe = 0.059 mm-1

Fig. 9. Curves obtained by vertically integrating the SLIPI image results of the power transformer oils for 2000 h (a), 1000 h (b) and 0 h (c) for 450 nm illumination wavelength. The exponential decay of the light intensity as function of distance through the cuvette is obtained here and the extinction coefficient has been deduced from those decays.

14

Distance [mm]

For 450 nm illumination wavelength (Fig. 9), the extinction coefficient of fresh oils is between 0.053 mm−1 and 0.064 mm−1. For those at 1000 h, the extinction coefficient is between 0.387 mm−1 and 0.537 mm−1. Finally, at 2000 h, it is between 1.966 mm−1 and 2.011 mm−1. The results of the accuracy measurements have been obtained by performing for the same sample of transformer oil for 450 nm illumination wavelength, about ten measurements of the extinction coefficient. The extinction coefficient measurement for each sample including the deviation of the measurements are given in Table 4. Table 4 summaries also the guidelines for extinction coefficients values at 450 nm wavelength, expressed in mm−1. These different intervals found will constitute therefore, the intervals of decision which gives us the state of good or bad quality of power transformer oils. The increase of the extinction coefficients values determined by means of SLIPI reflecting the level of degradation of oils, justifies the evolution of the different physicochemical parameters determined. By comparing both the different results obtained (SLIPI technique and physicochemical methods), a good agreement was observed. Besides, note that SLIPI technique has been able to detect a change in the value of the extinction coefficient around by 0.1 [14]. In the case of aging oils without color large change, SLIPI has demonstrated its ability in detecting a change in the value of extinction coefficient which approach 0.01. This order of magnitude was obtained by making the subtraction between the extinction coefficients for each aging duration. It is therefore a technique which is able to detect the slightest aging effect of power transformer oils.

Fig. 11. Evolution of the extinction coefficient of each sample of transformer oils as a function of aging duration at λ=450 nm illumination wavelengths.

5. Conclusion In this article, a new technique of optical imaging called SLIPI has been investigated. Since SLIPI technique gives excellent results, it can

1

Normalized intensity [au]

[ 450 nm ] 2000 hours S11 µe = 1.989 mm-1

0.8

2000 hours S12 µe = 2.011 mm-1

(b)

2000 hours S10 µe = 1.998 mm-1

0.6

2000 hours S9

[ 638 nm ] 2000 hours S11 µe = 0.076 mm-1

0.4

(a)

2000 hours S12 µe = 0.079 mm-1

0.2

2000 hours S10 µe = 0.078 mm-1 2000 hours S9

0

µe = 1.966 mm-1

0

2

4

6

8

10

12

14

Distance [mm] 44

µe = 0.075 mm-1

Fig. 10. Curves obtained by vertically integrating the SLIPI image results of the power transformer oils for 2000 h for 450 nm (a) and 638 nm (b) illumination wavelengths. The exponential decay of the light intensity as function of distance through the cuvette is obtained here and the extinction coefficient has been deduced from those decays.

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Table 4 Guidelines for extinction coefficient values at 450 nm. Oil condition

Extinction coefficient (mm−1)

Good oils Proposition an oils Marginal oils Bad oils Very bad oils Extremely bad oils

0–0.0640.006 0.064 ± 0.006–0.387 0.387 ± 0.092–0.537 0.537 ± 0.014–1.996 1.966 ± 0.024–2.011 > 2.011 ± 0.02

± ± ± ±

0.092 0.014 0.024 0.02

be used to serve as a tool for diagnosis of the state of the power transformers oils for their deterioration and aging. It is a non-destructive technique with no need to perform dilution like the UV–visible spectroscopy technique. The results obtained have been compared to existing physicochemical techniques and were found very satisfactory. The technique of SLIPI offers a real opportunity and a better alternative for diagnosis of oils compared to other techniques which are time consuming and expensive. Acknowledgement The authors would like to thank the International Science Program (ISP) of Uppsala University for the donation of equipment and financial support as well as the TWAS. The authors would like to thank Assoc. Prof. Edouard Berrocal for useful discussions and valuable guidance. Conflicts of interest The authors declare no conflict of interest. Appendix A. Supplementary material Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.measurement.2017.08. 019. References [1] H. Boyer, M. Norbert, R. Philippe, Cours de construction du matériel électriqueTome 3, La Capitelle ed., France, 1981. [2] J. Zhang, X. Qian, Y. Zhou, Application of extension neural network in transformer fault diagnosis, J. Comp. Eng. Appl. 47 (7) (2011) 8–11. [3] S.D. Myers, Presentation on transformer oil testing, http://www.slideshare.net/ JoeloRoss/transformer-oil-testing-sd-myers, 2016 (accessed 11.10.16). [4] L.O. Séraphin, Bien-fondé des analyses d’huiles pour le diagnostic d’état des transformateurs immergés. http://www.laboratoireoksman.com/Analyse_ transformateur.pdf, 2016 (accessed 11.10.16). [5] I. Fofana, Insulating oil - another vital part of transformer body, In the IEEE seminar Section DEIS Chapter, Ottawa-Montreal, Canada, June 17th 2010. [6] R. Fournié, Les isolants en électrotechnique: Essais, Mécanisme de dégradation, Applications industrielles, Eyrolles ed., France, Paris, 1990. [7] Y. Du, Moisture equilibrium in transformer paper-oil systems, IEEE Electr. Insul. Mag. 15 (1) (1999) 11–20. [8] T.V. Oommen, On-line moisture sensing in transformers, in: Proceedings of the electrical electronics insulation conference, Boston, USA, 7-10 October 1991. [9] B.K. Gupta, Direct determination of moisture in solid oil-paper insulation, in: Conference record of IEEE international symposium on electrical insulation, Ontario, Canada, 7–10 June 1998. [10] T.K. Saha, Review of modern diagnostic techniques for assessing insulation condition in aged transformers, IEEE Trans. Dielectr. Electr. Insul. 10 (5) (2003) 903–917. [11] American Society for Testing and Materials (ASTM), Annual Book of ASTM Standards, in: Electrical insulation and electronics, 2005, p. 577.

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