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IEEE Technical paper based on 1597.1 standard in Electromagnetic compatibility - Lab Report Example

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Availability of empirical evidences relating the shielding effectiveness (SE) of a screen with apertures to the size of the aperture is investigated under the assumption that the actual shielding effectiveness is proportional to the longest dimension of the aperture. However in…
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IEEE Technical paper based on 1597.1 standard in Electromagnetic compatibility
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Download file to see previous pages To achieve this, we performed a series of shielding effectiveness (SE) tests for a board level shielding product with different apertures by means of a reverberation chamber. An analytical shielding effectiveness formulation has been developed in comparison with the shielding effectiveness (SE) measurement results.
When performing tasks related to electromagnetic shielding, Board Level Shielding (BLS) is widely used for isolating electromagnetic interferences. A typically perfect Board Level Shielding (BLS) is deemed to have no apertures and it is fixed to the ground plate of the circuit board all round in order to reach maximum shielding effectiveness (SE). By introducing several apertures, we can be able to make the Board Level Shielding (BLS) lighter weight and increase its convenience. To evaluate the effect of the aperture size and the total number of apertures on the shielding effectiveness, several tests were performed in the lab and a number of apertures of different sizes and the results obtained were compared. The results are processed and used to plot the corresponding shielding effectiveness (SE) data using calculation tools based on the shielding theory.
The IEEE standard 1597.1 demands that we use feature selective (FSV) to compare the level of agreement between the reference and the numerical results. In this method, the data sets are compared by decomposing them into two parts:
This approach involves taking the overlapping portion of the two datasets and interpolating them so that they share a coincident x axis location. A Fourier transformation is then used to transform this data. The two data sets are low (DC), band (L0) and high pass (Hi) filtered. The six elements are then inversely transformed. Comparing the trend data gives the Amplitude Difference Measure (ADM).
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