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resources:technical-guides:model_aducm350:validation [16 Aug 2016 20:11] – [RC Impedance Measurement Validation] Tom MacLeod | resources:technical-guides:model_aducm350:validation [17 Aug 2016 10:22] (current) – Dylan Stuart | ||
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The ADuCM350 Matlab model simulates the AFE of the ADuCM350 at a functional block level, allowing voltammetric, | The ADuCM350 Matlab model simulates the AFE of the ADuCM350 at a functional block level, allowing voltammetric, | ||
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===== RC Impedance Measurement Validation ===== | ===== RC Impedance Measurement Validation ===== | ||
A primary use case of the ADuCM350 is the measurement of RC impedance networks in a range of frequencies. Numerous experiments are detailed below which were run to validate the Matlab model’s performance in taking these measurements. | A primary use case of the ADuCM350 is the measurement of RC impedance networks in a range of frequencies. Numerous experiments are detailed below which were run to validate the Matlab model’s performance in taking these measurements. | ||
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==== Current Level Tests ==== | ==== Current Level Tests ==== | ||
The figures below show tests of 4-Wire measurements at different current levels through the sensor. Each test was performed on both the model and the hardware, and is shown below compared to the ideal calculated impedance for this particular impedance network. | The figures below show tests of 4-Wire measurements at different current levels through the sensor. Each test was performed on both the model and the hardware, and is shown below compared to the ideal calculated impedance for this particular impedance network. | ||
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=== 120 nA === | === 120 nA === | ||
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=== 1 uA === | === 1 uA === | ||
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=== 12 uA === | === 12 uA === | ||
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=== 200 uA === | === 200 uA === | ||
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=== Summary === | === Summary === | ||
For most current ranges tested, the Matlab model marginally outperformed the ADuCM350 hardware measurements. However in nearly every case, the difference between the accuracy of the model and the hardware is small (<1% accuracy difference), | For most current ranges tested, the Matlab model marginally outperformed the ADuCM350 hardware measurements. However in nearly every case, the difference between the accuracy of the model and the hardware is small (<1% accuracy difference), | ||
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==== R_ACCESS Tests ==== | ==== R_ACCESS Tests ==== | ||
Tests were run with varying R_ACCESS in order to validate the operation of the 4-Wire measurements, | Tests were run with varying R_ACCESS in order to validate the operation of the 4-Wire measurements, | ||
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These results indicate that the Matlab model very accurately reproduces the ADuCM350’s 4-Wire measurement capabilities, | These results indicate that the Matlab model very accurately reproduces the ADuCM350’s 4-Wire measurement capabilities, | ||
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==== 2-Wire Tests ==== | ==== 2-Wire Tests ==== | ||
The 2-Wire impedance measurement capabilities of the Matlab model are verified against the hardware in the plots below. The sensor impedance for this section is a series resistor and capacitor. | The 2-Wire impedance measurement capabilities of the Matlab model are verified against the hardware in the plots below. The sensor impedance for this section is a series resistor and capacitor. | ||
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The model achieves better accuracy than the hardware in terms of impedance phase measurement error, and performs very similarly to the hardware in terms of impedance magnitude measurement error. | The model achieves better accuracy than the hardware in terms of impedance phase measurement error, and performs very similarly to the hardware in terms of impedance magnitude measurement error. | ||
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===== Noise and Accuracy Validation ===== | ===== Noise and Accuracy Validation ===== | ||
Tests were carried out to determine the ideal noise variance level to accurately model the noise levels and measurement accuracy of the ADuCM350 hardware. These tests were carried out both with the attenuator enabled and disabled. | Tests were carried out to determine the ideal noise variance level to accurately model the noise levels and measurement accuracy of the ADuCM350 hardware. These tests were carried out both with the attenuator enabled and disabled. | ||
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==== Attenuator On ==== | ==== Attenuator On ==== | ||
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==== Attenuator Off ==== | ==== Attenuator Off ==== | ||
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===== Amperometric Measurement Validation ===== | ===== Amperometric Measurement Validation ===== | ||
The amperometric capabilities of the ADuCM350 are available in either Amperometry, | The amperometric capabilities of the ADuCM350 are available in either Amperometry, | ||
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==== Sinc2hf + Sinc2lf Filters Enabled ==== | ==== Sinc2hf + Sinc2lf Filters Enabled ==== | ||
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The model and the hardware track very closely for this measurement. The slow rise time is due to the low pass effect of the Sinc2lf filter. Both measurements settle at ~34uA after the voltage step, which is the expected value for the given impedance and step voltage. | The model and the hardware track very closely for this measurement. The slow rise time is due to the low pass effect of the Sinc2lf filter. Both measurements settle at ~34uA after the voltage step, which is the expected value for the given impedance and step voltage. | ||
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==== Sinc2hf Filter Enabled, Sinc2lf Filter Disabled ==== | ==== Sinc2hf Filter Enabled, Sinc2lf Filter Disabled ==== | ||
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Again the hardware and the model produce a very similar output for the given input, with both step responses having an identical rise time, settling to their final value after 2 samples. | Again the hardware and the model produce a very similar output for the given input, with both step responses having an identical rise time, settling to their final value after 2 samples. | ||
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==== RC Impedance ==== | ==== RC Impedance ==== | ||
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These plots show visually that the current measurement capabilities of the Matlab model closely match that of the hardware – the difference between the measured and modelled current is typically in the nanoampere-range. Further, the sinc2hf and sinc2lf filters have a nearly identical effect on the model as they do on the hardware. | These plots show visually that the current measurement capabilities of the Matlab model closely match that of the hardware – the difference between the measured and modelled current is typically in the nanoampere-range. Further, the sinc2hf and sinc2lf filters have a nearly identical effect on the model as they do on the hardware. | ||
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==== Amperometric Consistency ==== | ==== Amperometric Consistency ==== | ||
All three simulation modes capable of Current Vs. Time measurements should produce the same output, given the same input parameters (The differences between these modes is in the excitation waveforms that are possible with each). The plot below shows the performance of each measurement mode given the same sensor configuration and excitation waveform. | All three simulation modes capable of Current Vs. Time measurements should produce the same output, given the same input parameters (The differences between these modes is in the excitation waveforms that are possible with each). The plot below shows the performance of each measurement mode given the same sensor configuration and excitation waveform. | ||
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====== Footnote ====== | ====== Footnote ====== | ||
All tests were carried out with high-accuracy passive components where possible, however some discrepancies between ideal, measured, and modelled results may be partly due to inaccuracies in the components used in measurements taken on the ADuCM350 evaluation board hardware. | All tests were carried out with high-accuracy passive components where possible, however some discrepancies between ideal, measured, and modelled results may be partly due to inaccuracies in the components used in measurements taken on the ADuCM350 evaluation board hardware. | ||