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Design and Optimization of Displacement Measurement Eddy Current Sensor for Mass ProductionGuganeswaran, S January 2014 (has links) (PDF)
Eddy current (EC) based testing and measurement methods are well known in non-destructive testing (NDT) world. EC sensors are extensively studied and used for material health monitoring and its property measurement. Target displacement measurement is one of the well-known applications of EC method. The main advantage of EC sensor is its working capability in harsh environment like humidity, contamination etc. It is non-contact, rugged and requires less maintenance. The range and sensitivity of target displacement is mainly determined by the probe geometry and its construction method. Also displacement measurement depends upon geometry and electromagnetic (EM) properties of the target plate. Any variation of ambient temperature alters the EM properties of the probe as well as EM properties of the target. Thus, many parameters like geometry, EM properties and temperature involved in target displacement measurement. Hence, while using EC sensor for displacement measurement, it demands careful design and measurement procedure to achieve high sensitivity and high precision with low temperature drift. To achieve these, we present the following. 1) A temperature compensation technique 2) Optimization of probe geometry and its construction method to increase the range and sensitivity 3) Selection of suitable probe measurement parameter (Z, R, X) based on target material properties 4) Making the displacement measurement less sensitive to tolerance in probe construction parameter.
A temperature compensation technique for target displacement measurement, using a self-running LC oscillator has been presented. A sensing coil is energized by a Hartley oscillator. The oscillator voltage is maintained at a constant level by a closed loop feedback circuit and the average feedback current to the oscillator is measured for target displacement detection. The temperature drift of the feedback current is compensated by applying temperature compensation function (TCF) and this is verified experimentally. Cold rolled mild steel (carbon steel) is taken as a target material and the sensor is tested over a temperature range of 20 °C – 80 °C. It shows that the temperature drift is less than ±30 ppm/°C over 3 mm target displacement. To match all the sensor modules in mass production, components selection procedure is presented. To avoid mismatch across sensors in manufacturing process, the transistor based oscillator is modified with operational trans-conductance amplifier (OTA). The same temperature compensation formula (TCF) is applied to compensate the temperature drift of feedback current and achieved intended accuracy.
Geometry and construction parameters of the eddy current sensing probe is optimized for target displacement measurement using Ansoft Maxwell, electromagnetic design software. EC probe with
different geometry are analyzed in search of suitable geometry for target displacement measurement. Four shapes of commercially available core have been chosen for probe construction. For each shape of sensing probe, the radius and height of the probe is increased by 0 mm to 9 mm to find the effect of them on sensitivity and range of target displacement measurement. It has been observed that the probe with less height and maximum diameter has shown better performance. In addition to that, the probe geometry is optimized to achieve more sensitivity and range within the space available for probe mounting. It helps to utilize the available space effectively for probe design. Coil winding and mount-ing it inside the core window also important parameter in probe design. It has been observed that de-pressing the sensing coil inside the core window from sensing face by 3 mm decreases the sensitivity by 40 %. Hence, it is recommended to place the coil on the extreme end of the sensing face of the core. To know the effect of core permeability, it is varied from 1000 to 15000. It has been observed that it has no effect on sensitivity and measurement range.
Only optimizing the probe geometry and its construction method is not adequate for target displacement measurement. We know that the EC based displacement measurement is also target material dependent. Generally probe impedance is measured and then the temperature drift of the sensing coil resistance is compensated to know the target displacement. Most of the temperature compensation techniques use this compensation technique and it is shown that those are suitable for high conductivity targets like copper. Choosing Z for displacement measurement may not be only best choice for all target materials. The displacement can be measured also through either R or X of the probe. Choosing the proper probe parameter for a given target material will provide a less temperature drift for target displacement measurement. To know about this, a simulation has been made for target displacement measurement with target metal of μr = 1, relative permittivity εr =1, and temperature coefficient of resistivity ∝ = 0.004 K-1. The conductivity (σ) of the target is varied from 1×106 S/m to 62×106 S/m in the temperature range of 20 ℃ – 80 ℃. Now the simulation has been repeated by fixing as a constant and varying target μr. The metal plate with = 1×106 S/m, εr=1 and ∝ = 0.004 K – 1 is taken as a target and μr is varied from 100 to 10000. For both conductivity and permeability sweep analysis, the target displacement is measured as a function of Z, R and X independently. The temperature drift in displacement measurement is also analysed for the above temperature range. An experiment has been conducted with copper, stainless steel and mild steel as target metal in the temperature range of 20 ℃ – 80 ℃. The temperature drift is calculated when the displacement is measured as function of Z, R and X. Based on the results, we have identified that the target material relative permeability determines the selection of probe measurement parameter for target displacement measurement. Hence, knowing tar-get r alone suffice to select the probe measurement parameter (Z or R or X) for displacement measurement.
Optimizing the probe geometry, selecting the proper probe measurement parameter and temperature compensation technique suffice to provide a good sensitivity, range and low temperature drift for
a single probe. But in general, one of the mass produced probes is selected as a reference probe and it is calibrated against the ambient temperature and target displacement. And the calibration curves are loaded to all the probes. Matching the probe construction parameters to each other across the production patches is not possible in mass production. This makes the temperature compensation function and displacement calibration are different for every individual probes for displacement measurement. This degrades the measurement accuracy. A simulation has been performed with pot core with commercial tolerance. Using this, we have obtained 24 probes due to variations in 1) Individual and few combinational variations in core and coil dimensions 2) Core permeability variation and 3) relative position of the coil with respect to core. Finally, we have quantified the displacement error for each probe. We have identified the important probe dimensional parameters that have to be controlled precisely in mass production to improve the measurement accuracy. It shows error of 0.86 % in the displacement measurement when the relative reactance and relative displacement is used for measurement.
In practice, error in displacement measurement due to both the ambient temperature drift and the tolerance in probe construction parameter exist simultaneously. Hence, the combined error is computed for the target displacement range of 0 mm – 3 mm for the temperature range of 0 °C – 100 °C. The total error of less than 1 % is achieved for commercial standard probe tolerance. Finally, we have provided general factory production procedure and user calibration procedure of probe design to achieve cost effective displacement measurement with sensitivity and range with low temperature drift.
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Capacity and Life Estimation of Flooded Lead Acid Batteries using Eddy Current SensorsReddy, T Mohan January 2016 (has links) (PDF)
Lead acid batteries are widely used in domestic, industrial and automotive applications. Even after lot of advancements in battery technologies, lead acid cells are still in use because of their high capacity and low cost. To use any battery effectively, first we should be able to identify the available capacity or State of Charge (SoC). There are many techniques available to measure SoC of a lead acid battery. One such unique method is to measure the capacity using eddy current sensors. This method is unique because it is non-obtrusive and online. Eddy current sensors (ECS) are wire wound inductors which work on the principle of electromagnetic induction. Eddy currents are the currents generated on a conductive material when it is kept in a varying magnetic. Eddy current sensors generate varying magnetic eldest and will be able to identify the properties of conductive materials like thickness, conductivity, material composition etc. Also they can be used as proximity sensors.
Lead acid batteries use lead metal as cathode. Upon usage(discharge) the lead metal converts to lead sulfate and revert back to lead after charging. These changes in lead electrode can be monitored using eddy current sensors. The impedance of an eddy current sensor will change when it is kept close to the lead electrode when the battery is charging or discharging. These impedance parameters can be monitored to determine the battery SoC. When lead is deposited on cathode, there will be more eddy current loss in the target and the total resistance of coil increases. On the other hand, when lead is deposited on the electrode because of increase in the magnitude of eddy currents which oppose the source magnetic, the total inductance of coil decreases. We can observe exactly opposite behaviour of coil resistance and inductance when the lead electrode is converted to less conductive lead sulfate. There is a lot of research on using ECS to measure SoC of lead acid batteries and there are still many challenges to be addressed.
First we have explained about different circuit designs we have used to monitor the battery capacity using eddy current sensors. After that, we have explained about our complete experimental setup and the procedure to measure the sensor parameters using the setup. Then, we have discussed about different issues involved in the eddy current sensing based state of charge measurement.
Eddy current sensors are affected by temperature variations. We have studied the coil resistance behaviour with temperature at different frequencies using simulations and experiments. We have obtained the conditions for linear variation of coil resistance with temperature. The measured temperature compensation scheme is applied and the results are discussed. We have also modified the measurement system design in order to minimize the lift o errors. We have used a metallic clamp structure to minimize the lift o errors.
We have used finite element analysis based simulations to study different design parameters and their effect on the sensitivity of eddy current sensor. We have created 2D eddy current models and the sensitivity of coil resistance is computed by changing the coil dimensions and the core permeability. We have also performed error analysis and computed the error due to the tilt angle shift between coil and electrode. We have also computed the error due to the internal heating of battery.
We have also studied the effect of acid strati cation on state of charge for both sealed and hooded batteries. We have proposed a multi coil method to minimize the errors in SoC measurement due to acid strati cation for Flooded type batteries. We have used finite element analysis based simulations to compute the error due to acid strati cation by increasing the number of coils.
Finally we have derived the equation for electrode Q factor using the transformer model of eddy current sensor. The derived Q factor equation is then used to study the aging of lead acid batteries both by using experiments and simulations. Finally we have explained a detail procedure to measure the state of charge(SoC) and state of health(SoH) of a hooded lead acid battery using eddy current sensing method.
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