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					Australasian Universities Power Engineering Conference (AUPEC 2004) 26-29 September 2004, Brisbane, Australia

APPLICATION OF A NOVEL PLANAR MAGNETIC SENSOR TO ESTIMATE THE LIFE OF TURBINE
C. Gooneratne and S.C.Mukhopadhyay Institute of Information Sciences and Technology Massey University, Provate bag 11 222 Palmerston North Tel : 06- 350 5799 extn. 2480 Fax : 06- 350 5723 Eamil: S.C.Mukhopadhyay@massey.ac.nz

Abstract The inspection of cracks, defects and damages in metal pipes used in power industries such as cooling tubes of nuclear power plants and the estimation of fatigue of the blade of the turbine system has a great implication from the point of view of catastrophic accident. A novel flexible planar type magnetic sensor has been developed for the purpose of estimating the near-surface material properties and the evaluation of defects, cracks, damages and the remaining life of the system. The sensors being planar type and flexible there is no practical limitation of using it for curved surfaces. Based on the estimation of the near-surface material properties it is possible to predict or estimate the mechanical state of the material and consequently the fatigue and the life. The oldest power station in New Zealand had been commissioned in 1935 and the latest one in 1985. The proper use of this sensor can avoid any catastrophic accident due to fatigue of material.

1. INTRODUCTION NONDESTRUCTIVE TESTING or NDT is defined as the use of noninvasive techniques to determine the integrity of a material, component or structure or quantitatively measure some characteristics of an object. So in short NDT does inspect or measure without doing any harm or damage of the system. In recent times NDT has been applied in many different branches of industry. With the increasing demand for highly reliable and high performance inspection techniques, during both manufacturing, production and use of a system or structure, the demand for the employment of suitable NDT techniques is increasing. The use of NDT is even more indispensable in the case of structures that have to work in severe operating environments. There are NDT applications at almost any stage in the production or the life cycle of a component. Some of the most important areas are: 1. Power stations – nuclear and conventional power plants. 2. Metal industry – steel producers, steam and pressure vessel construction for the inspection of cracks, defects, and any other flaws and their characterization, fatigue estimation, quality assurance, wall thickness and coating thickness testing, determination of hardness etc.

3. Petro-chemical industry. 4. Transportation – railways. 5. Food industry - Quality assurance of food products. 6. Medical sciences. 7. Civil engineering - inspection of concrete structures, bridges, infrastructure due to aging problem. 8. Aircraft - fatigue estimation in aircraft surface and other parts. 9. Pipe inspection - Inspection of pipes and piping systems in industrial plants. The pipes are used for carrying oils, gases, waters, milks etc. 10. Others. There are different NDT techniques available with different characteristics. The following are the most commonly used NDT techniques: 1. Visual 2. Magnetic 3. Ultrasonic 4. Acoustic 5. Radiography 6. Eddy current 7. X-ray. For the last few years the authors have been working on the design, fabrication and employment of planar type electromagnetic sensors which have been

successfully applied in many applications such as the inspection of printed circuit boards, estimation of near-surface material properties, electroplated materials, and saxophone reed inspection. The extension of the use of the sensors for the inspection of dairy products is under investigation. This paper will describe the application of a novel planar magnetic sensor which can be used to estimate of life of turbine in power station. The sensor will be very useful in the New Zealand scenario. The oldest power station in New Zealand had been commissioned in 1935 and the latest one in 1985. This sensor can be used to predict the remaining life of the turbine commissioned a long time back to avoid any catastrophic accident. It has been reported that the mechanical state of a material can alter the electrical properties [1, 2, 3, 4]. In other words by determining the electrical properties such as conductivity, permeability etc. it is possible to predict the mechanical state of the material. Fig. 1 shows a reported result of the relationship between fatigue of stainless steel and aluminum as a function of normalized electrical conductivity [1]. The result shown in Fig. 1 is based on the planar meander type sensor.

Fig. 2. To overcome this problem a novel planar mesh type micro-magnetic sensing technology has been developed to detect existence of any cracks or flaws and to evaluate the degradation of material or some other applications such as the detection of the formation of cavity in electroplated materials etc independent of the alignment of the cracks [9]. The configuration of planar mesh type sensor is shown in Fig. 3.

Fig. 2 Configuration of planar meander type sensor

Fig. 3 Configuration of planar mesh type sensor The sensor consists of two coils: one coil is known as exciting coil and the other coil is known as sensing coil. The exciting coil carries high frequency current and generate high frequency electromagnetic field on the system under test. The induced electromagnetic field in the testing system will generate some eddy current in the system under test. Due to the flow of eddy current the induced field in the testing system will modify the generated field and the resultant field will be detected by the pick-up coil or sensing coil which is placed above the exciting coil. Fig. 4 shows the structure of the planar type sensor. The exciting coil and the sensing coil is separated by a polyimide film of 50 µm thickness. In order to improve the directivity of flux flow a magnetic plate of NiZn is placed on top of the sensing coil. The size of sensor depends on the number of pitches used in that. The optimum pitch size depends on the application [10]. The size used in this application is 14 mm X 14 mm with a pitch size of 1.75 mm. Fig. 5 shows the actual picture of the fabricated sensor used for the experiment.

Fig. 1 Fatigue as a function of normalized conductivity 2. PLANAR MAGNETIC SENSOR

This paper is concerned with the research required to establish a novel technology for the assessment and inspection of the properties of any conducting/nonconducting and or magnetic/non-magnetic materials based on which the remaining life of a turbine can be predicted. This technology is nondestructive and inherently capable of the detection of flaws/imperfection independent of orientation. The author has developed both on the meander type and mesh type sensors [5, 6, 7, 8]. The disadvantage of using meander type sensor is that the performance of the sensor is not independent of the alignment of the cracks or non-homogeneity of the material structure with respect to the sensor configuration as shown in

properties are determined. The material properties are then used to estimate the mechanical state of the system under test.

Fig. 4 The structure of the planar sensor

Fig. 6 The experimental set up 4. PREDICTION OF LIFE The measured transfer impedance is used to determine the near-surface material properties and the change of material properties with time is used to predict the fatigue of the system. The transfer impedance varies in a complex way with different parameters, such as conductivity, permeability of the near-surface of the material, operating frequency, lift-off of the sensor etc. In order to make the inspection possible in real time, the impedance characterization of the sensor has been done at offline. A finite element model formulation has been carried out for the calculation of transfer impedance of the sensor. Fig. 7 shows a part of the model used for the finite element analysis.

Fig. 5 The fabricated sensor 3. PRINCIPLE OF MEASUEMENT The sensor is placed on the system under test as shown in the experimental set-up in Fig. 6. The ratio of the voltage of the pick-up coil to the exciting current, defined as the transfer impedance will be measured by the Network analyzer. The transfer impedance is a function of many parameters such as permittivity, conductivity and permeability of the near-surface material, the thickness of the material under test, operating frequency etc. The separation of the variables by direct method is extremely difficult and even if some solutions is possible it will be impossible to get the result on-line. In order to use this type of inspection system an off-line generated grid system has usually been employed. The generation of grid system and its use for the evaluation of material properties is discussed in the next section. By employing this novel type of sensor it is possible to inspect the quality, flaws/imperfection of the above-mentioned systems independent of their alignment. The sensor being planar type is flexible enough to accommodate the curved surface of the pipe, blades of the turbine system. The main parameter of the measurement is the transfer impedance, from which the material

Fig. 7 Finite element model of the sensor for the calculation of transfer impedance The post-processing from the finite element analysis is used for the calculation of necessary parameters, the main parameter in this case is the transfer impedance. The transfer impedance is calculated for varying operating parameters. For each parameter the

model is run separately. A few results are explained here. Fig. 8 shows the variation of the real part of the transfer impedance with the near-surface conductivity for different values of lift-off. It is seen that with the increase of the conductivity the real part of the transfer impedance is decreased. The operating frequency in this case is kept at 500 kHz.

lower at higher values of conductivities. The operating frequency for this data is the same of 500 kHz as in the earlier case.

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Fig. 10 Variation of the real part of transfer impedance with lift-off at 500 kHz
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Fig. 8 Variation of the real part of transfer impedance with conductivity at 500 kHz
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Fig. 9 shows the variation of the imaginary part of the transfer impedance as a function of the nearsurface conductivity with various values of lift at an operating frequency of 500 kHz. The effect of conductivity on the reactive part of transfer impedance is appreciably less compared to the resistive part.
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Fig. 11 Variation of the imaginary part of transfer impedance with lift-off at 500 kHz There can be many other characteristics depending on the parameters of interest. Since the emphasis of this paper is the estimation of fatigue of metal, the estimation of conductivity and permeability are the most important. While the parameters are measured the distance between the top surface of the metal to the outer surface of the sensor i.e., the lift can change a lot, the measurement of conductivity and permeability should not be affected due to change of lift-off. In order to determine the conductivity from the measured transfer impedance data using the values obtained from the Figs. 8 to 11, the grid system as is shown in Fig. 12 is generated. The grid system is obtained by plotting the reactive part of transfer impedance against the resistive part of it for varying values of conductivities and lift-off. Since the generated grid system is obtained off-line, the correspondence of the calculated data from the finite element model and the experimentally obtained data should be very close. If the calculated values are widely different from than that of measured values a correction factor is to be introduced in the

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Fig. 9 Variation of the imaginary part of transfer impedance with conductivity at 500 kHz. Fig. 10 and 11 show the variation of real and imaginary part of the transfer impedance with lift-off of the sensor for different values of conductivities of the near-surface. It is seen from Fig. 10 that the real part decreases with the increase of lift-off and also the value of the real part of the transfer impedance is less for higher values of conductivity. It is seen from Fig. 11 that the imaginary part of the impedance increases with the lift-off and the value of the imaginary part of the transfer impedance is actually

calculation. In order to get more accurate estimation from the grid system a grid can be generated from the experimentally measured data. Of course a lot of data are required for generating the grid.
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detected. In order to accurately predict the remaining life of the system the measuring system will have a lot of such data obtained from the mechanical testing of the particular materials and stored in the computer. One important parameter for this measurement system is the selection of operating frequency. Since the skin-depth decreases with the increase in frequency, in order to determine the defect in inner surface of the material, the higher value of the operating frequency is restricted. Fig. 14 shows the variation of skin-depths as a function of frequency for a few metals. It is seen from Fig. 14 that for titanium to inspect a defect at a depth of 0.5 mm the operating frequency should not be more than 500 kHz. If the crack lies at a depth of more than 0.5 mm the operating frequency should be lower so that flux enters more than the required depth and an appreciable change of flux takes place due to the defect.

Fig. 12 Conductivity versus lift-off grid system obtained from finite element model output Once the grid system is available and the real transfer impedance is measured, the next step is to plot the transfer impedance on the grid system as is shown in Fig. 13. The plotted data lies inside a small grid with four nodes. The conductivites and lift-off of the four neighboring node points are known. So the output parameters corresponding to measured data are obtained by an interpolation technique. Table 1 shows some calculated values obtained from Fig. 13.
Fig. 14 Variation of skin-depth with frequency
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5. NEW ZEALAND SCENARIO
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A statistics of a few power stations in New Zealand is shown in Table 2. It is seen that the old power station still in operation had been commissioned in 1935. The latest one is in 1985, almost 20 years old. The power station commissioned in 1935, is nearly 70 years old and is prone to any kind of catastrophic accident. It is very important to have a very useful nondestructive evaluation scheme to predict the remaining life of the power station to avoid the gas leakage or any other type of accident. In general the developed sensor will be very useful for the power industry. 6. CONCLUSION

Fig. 13 The estimation of near-surface properties from the grid and measured data Once the system properties are obtained the next task is to correlate this data to obtain the fatigue of the system. The Fig. 1 shown earlier is one such example which shows there is a degradation of the conductivity with the age of the metal. If there is crack or some other kind of damage taken place just inside the metal, there will be sharp drop of the conductivity values which can be very easily

This paper has described a novel planar magnetic sensor for the estimation of life of turbine and any object made up of metal. The sensor is based on the variation of magnetic flux due to the change of electrical parameters. The electrical parameters are measured and are then used to predict the mechanical state of the material. The sensor has the potential to be used in many applications starting from

characterization of new materials to the prediction of the remaining life Table 1 : Calculated results of near-surface properties Experimental condition Aluminum (no lift-off) Copper (no lift-off) Aluminum (0.13 mm lift-off) Copper (0.13 mm lift-off) Actual Conductivity (S/m) 3.78 E7 5.8 E7 3.78 E7 5.8 E7 Calculated Conductivity (S/m) 3.87 E7 5.65 E7 3.81 E7 5.75 E7 Actual lift-off (mm) 0.1 0.1 0.23 0.23

of

used

materials.

Calculated lift-off (mm) 0.097 0.094 0.224 0.217

Table 2 Statistics of power stations in New Zealand Power stations Manapouri Tekapo A Tekapo B Ohau A Ohau B Ohau C Benmore Aviemore Waitaki 7. REFERENCES
1. N. Goldfine, “Near surface material property profiling for determination of SCC susceptibility”, Fourth EPRI Balance-of-Plant Heat Exchanger NDE Symposium, Jackson Hole, WY, June 10-12, 1996, pp 1-11. Y. Bi, M.R. Gobindaraju, and D.C. Jiles, ‘The dependence of magnetic properties on fatigue in A533B nuclear pressure vessel steels,’ IEEE transactions on Magnetics, 1997, 33, (5), pp. 3928-3930. Y.Shi, and D.C.Jiles, ‘Finite element analysis of the influence of a fatigue crack on magnetic properties of steel,’ Journal of Applied Physics, 1998, 83, (11), pp. 6353-6355. Y.Bi, and D.C.Jiles, ‘Dependence of magnetic properties on crack size in steels,’ IEEE transactions on Magnetics, 1998, 34, (4), pp. 2021 – 2023. S.C.Mukhopadhyay, S.Yamada and M.Iwahara, “Investigation of Near-surface Properties Using Planar Type Meander Coils”, JSAEM studies in Applied Electromagnetics and Mechanics, Vol. 11, pp 61-69, 2001.

No. of generators 7 1 2 4 4 4 6 4 6

Generator capacity 105 25 80 66 53 53 90 55 15
6.

Station capacity 735 25 160 264 212 212 540 220 90

Date of commission 1969 (4 generators) 1971 (3 generators) 1951 1977 1979 (2 generators) 1980 (2 generators) 1983/84 1984/85 1965 ( 5 generators) 1966 ( 1 generator) 1968 1935-1954

2.

3.

4.

5.

S.C.Mukhopadhyay, “Quality inspection of electroplated materials using planar type micromagnetic sensors with post processing from neural network model”, IEE Proceedings – Science, Measurement and Technology, Vol. 149, No. 4, pp. 165-171, July 2002. 7. S.C.Mukhopadhyay, “A Novel Planar Mesh Type Micro-electromagnetic Sensor: Part I Model Formulation”, accepted for the publication in IEEE Sensors journal, June 2004 issue. 8. S.C.Mukhopadhyay,, “A Novel Planar Mesh Type Micro-electromagnetic Sensor: Part II – Estimation of System Properties”, accepted for the publication in IEEE Sensors journal, June 2004 issue. 9. S.C.Mukhopadhyay, S.Yamada and M.Iwahara, “Inspection of electroplated materials – performance comparison with planar meander and mesh type magnetic sensor”, International journal of Applied Electromagnetics and Mechanics, vol. 15, pp 323-329, 2002. 10. S. C. Mukhopadhyay, S. Yamada, and M. Iwahara, “Experimental Determination of Optimum Coil Pitch for a Planar Mesh Type Micro-magnetic Sensor”, IEEE Transactions on Magnetics, Vol. 38. N0. 5, pp 3380-3382, Sep. 2002.


				
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