A New Diagnosis Method on Insulators with Measuring ... - inass

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microphone to estimates insulator’s performance,and its feasibility has been proved by Lundgaard[12] . The fault location and type of informationcan be obtained [13] through analyzing the amplitude,frequency and phase of acoustic wave. But the effectof the detection is determined by the material ofinsulator.Hydrophobicity detection technology is one of themain detection methods as regards the evaluation ofinsulator’s performance. The traditional methodmeasures the insulators’ hydrophobicity throughmeasuring the contact angle directly by photography[ 14 ] . However, this method can only becarried out in laboratory environment. The restrictionis made up by STRI hydrophobicity classificationmethod [ 15 , 16 ] . But it is dependent on theoperators’ subjective judgment, so the accuracy cannot be high. The method mentioned in the Literature[17][18]estimates the average hydrophobicity usingdigital image processing. It is more objective andprecise, but it bases on the hydrophobicity classificationand can not get the insulator’s partial hydrophobicity.It is obvious that the existing detection methodsare not satisfying and have some disadvantages. Soexperts nationally and internationally keep researching[19] in this field.This paper presents a detection method of insulator’sperformance through measuring the hydrophobicity.The method takes advantage of imageprocessing technology, such as extracting waterdroplets’ image from the background, fitting thewater droplets’ contour using the orthogonalpolynomial and measuring the contact angle, toestimate the insulator’s hydrophobicity. Comparingwith other hydrophobicity detection methods, thismethod can detect the insulators which are stillrunning on the spot without manual interventions,and the measurement results are more objective andprecise.2. Basic principleThe definition of contact angle is shown in Figure1. When the insulator’s surface is horizontal, thecontact angles of water droplet on both sides are thesame, and is called static contact angle . Thedynamic contact angles a(advancing angle) andr(receding angle) can be defined when a droplet ison an inclined surface.The model of contact angle detection method isbased on image processing. Use drip device, dripappropriate water droplets on the insulator surface,then use CCD camera device to acquire images,image processing tools and curve fitting can beadopted to get contact angle.Figure 1 Diagram of contact anglesObviously, in the same water droplet capacity andtimes, the larger the static contact angle, the smallerthe interface that the water droplet contacting withthe insulation material, the better the hydrophobicity.It is generally believed that, when 90 insulatorsurface is hydrophobic. For inclined surface, bymeasuring the advancing angle and the recedingangle, the following formula can be used to researchhydrophobicity [20] .mg sin Lcosa cosr (1)where m is mass of water droplet, g is accelerationof gravity, is incline angle, L is length of waterdroplet, is liquid surface tension, and r and a are the largest advancing angle and recedingangle of water droplet in inclined surface, respectively.Based on the liquid surface tension insulatorhydrophobic can be measured, the smaller thesurface tension, the better the hydrophobic.3. Image processingImage processing includes image preprocessing,image segmentation, image feature extraction andcurve fitting derivative about water droplet, etc.3.1 Water droplet image preprocessing1) Gray value transformingFor the operation in Gray Image is simpler thanColored Image, we often transfer Colored Imageinto Gray Image of 256 colors.2) Image smoothingMost pixels’ gray value of an image is of littledifference with the adjacent, existing large graycorrelation degree, which leads the energy of theimage to concentrate in the low-frequency region.Attenuating high-frequency components andenhancing low-frequency component can retain themain message of the image and filter high-frequencynoise.Image smoothing methods include: neighbor-International Journal of Intelligent Engineering and Systems, Vol.2, No.2,2009 19
hood average, median filter, Gaussian filter, frequencydomain method and so on. Particularly,median filter is suitable for extracting water dropletcontours from the image, which has the followingadvantages: ○1 to preserve edge details while removingthe impulse noise, salt and pepper noise at thesame time. ○2 to eliminate pulse effectively withoutaffecting the step function and the slope function. ○3to avoid fuzziness on image detail resulted by thelinear filter under certain conditions. ○4 computingprocess is convenient without need of the statisticalcharacteristics of images. Experimental results showthat the average templates and Gaussian templateboth blur image, especially the average template,while the median template can preserver edge detailbetter, as shown in Figure 2. So in practice we choosemedian filtering method.Detailed practice: to use a sliding window withodd point to slide on the image, to arrange the oddpixels with the pixel gray value, which are containedin the window, from small to large; then to replacethe pixel gray value of the window centre with themiddle gray value in the order, to move the windowfrom left to right till reaching the border, then tomove to the next row, from left to right again and gothrough the whole image in this way. After themedian filter transformation, some pixel’s grayvalue is equivalent to the middle value of the grayvalues in the neighborhood.(a) original image(c) Gaussian template filter(b) average template filter(d) median template filterFigure 2 Images of three kinds of filtering templates3) Gray stretchSince water is translucent liquid, the contrastbetween water droplet image and its background istoo little to distinguish. In order to highlight dropletand suppress the background, piecewise lineartransformation is adopted here.The gray value of the water droplet in the imageis lower than the background, and the whole imagehas a low gray value. Therefore the high graysection is compressed and the low gray section isstretched.To be simple, we can choose a gray value M,stretch the section where gray value is less than M,and turn the section where gray value is more thanM to the highest gray value totally. If f i, jdenotespixel gray value of the original image, g i,jdenotes the gray value after gray transform, thelinear transformation function would be:M/ Mfi,j 0f i,j gMgi, j(2)MgM f i,jMg4) Image RotationAccording to the need of image processing thatfollowed, we hope that the water droplet in theimage is at the horizontal level on the whole in thepicture. As the incline angle on the insulator surfaceis about 15°, the whole image should be rotated by15°.3.2 Image segmentation1) Edge detectionThe water droplet’s transparency makes theboundary between water droplet and its backgroundless obvious, particularly on the light side of theborder. To detect and highlight the edge of the waterdroplet is the premise of extraction of water dropletcontour accurately.Edges mainly divide into step shape and roofshape. The water droplet image is step edge wherethe edge points’ first-order derivative has extremevalue. So detecting edge points can be achieved bycalculating each pixel's gray gradient.The digital image’s first-order partial derivativeswould approximately be: f x f x1,yf x,y(3)f y f x,y 1f x,yTo simplify the calculation of gradient, thefollowing approximate formula is used frequently:gradxy f x f y, (4)Generally, the gradient operator is sensitive inlevel or vertical direction on the edge, while Robertsacross operator detects the gradient which crossalong with the image coordinate axis 45° and 135°.The Operator is:gradx,y f f x y(5)f x,y f x 1,y 1 f x 1,y f x,y 1 International Journal of Intelligent Engineering and Systems, Vol.2, No.2,2009 20
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