Several filters, both analog and digital, are commonly applied in systems that work, at some level, with data collection and analysis. Environments such as substations and large industries are known for their incredible capacity to generate noise in these signals.

The moving average digital filter can be a great option to avoid noise, especially surges that can cause the signal to oscillate with large amplitude quickly.

The IED receives an analog signal that will be “discretized,” meaning that the initial continuous signal (infinite points in a given space of time) will be transformed into an X amount of signal values in the same space.

The moving average filter will perform an arithmetic average to consider as a filtered value. That is, a point of this filtered signal will be the average of a defined number of predecessor points.

If we have an incorrect value generated by a surge within 100 points with correct values, the surge effect will be mitigated. However, it is also observed that since the filter needs several samples to calculate the filtered value, in this filter, we will always have a space without measurement at the beginning of the reading, as can be seen in the first graph.

It is worth noting that the greater the number of samples for calculating the moving average, the greater the signal attenuation and the greater the delay of the filtered values in relation to the actual value.

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