Anti Aliasing Filter2

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Anti-aliasing filter used in monitoring systems of

electrical equipment

Abstract - This paper proposes the design of a Butterworthfilter and its use in the electric drive systems to avoid theappearance of the aliasing phenomenon . Anti-aliasing filters arean important element in data acquisition systems. Mountedupstream of the analogue digital converter, they serve to limitthe frequency spectrum of the input signal, to avoid overlappingsignal spectra of the signal resulting from sampling.Measurements and experimental tests were performed in orderto validate the results obtained.The obtained circuit hasadvantages of modularization design, strong transplantation,and has widely use value and application prospect.

I. INTRODUCTION

Generally, the anti-aliasing filters are used for therejection of high-frequency noise affecting the measurementchain. The paper includes a theoretical background on thedata acquisition system, sampling theory and generalconcepts about filters. Based on the required characteristics -cutting frequency, attenuation rate - were designed andsimulated filter topology, components, supply type (bipolar),using a dedicated program (Filter Pro Texas Instruments).Numerical simulations have been made to test the proposedmethod and results are presented as well.

II. GENERALNOTIONSOFDATAACQUISITIONSYSTEMS

Data acquisition is the process of sampling signals thatmeasure real world physical conditions and converting theresulting samples into digital numeric values that can bemanipulated by a computer. Data acquisition systems(abbreviated with the acronym DAS or DAQ) typicallyconvert analog waveforms into digital values for processing.

Therefore a data acquisition system, is designed tomeasure or generate physical signals, and for this purposecontains in its structure a data acquisition board.

Acquisition board is often considered the entiresystem. These include in sensors that convert physicalparameters to electrical signals, their constructionconditioning signal equipment to convert sensor signals into

a form that can be converted to digital values; analog todigital converters and Digital Analogue, inputs and outputs (I/ O) Analog and Digital, count (count, time clock generators)and Direct memory Access memory units to transmit datadirectly to the computer without using microprocessor.

The most important operation is the analog digitalconversion, made with one or more circuits, depending on thetype of application). Another often encountered operations insuch systems are sampling and temporary storing of takensamples.

The sampling frequency is determined by: the frequencyspectrum of the input signals; speed of the A / D converter;accuracy of required processing.

Information processing may consist of simple operations(comparisons) to complicated mathematical processing(integration, differentiation, mediation, Fourier transformcalculation, etc..).

III. SAMPLINGANDALIASINGPHENOMENON. NEEDFORUSINGANTIALIASINGFILTERS

To analyze and synthesize a signal in the digitaldomain, analog signals must be converted into digital signalsthrough the acquisition of "samples" at certain regularintervals.

This process, called sampling is accomplished by

"questioning" the analog signal at regular periods of time,denoted Te (where Te is called the sampling period is theinverse of the sampling frequency, fe (fe = 1/Te)).In mathematical form, a sample of a signal is obtained bymultiplying the signal with a unit step pulse.To avoid loss of information in the process of sampling ananalog signal, the sampling frequency must be at least twotimes the maximum frequency of the sampled signal.

The consequences of sampling at a lower frequency thatthe highest frequency of the signal, generates a phenomenaknown as refolding (aliasing). This concept results frommisidentification of the required frequency for signalreconstruction.

The Shannon sampling theorem introduced restrictions onthe frequency of sampled signal in time, f (t) as follows: Toreconstruct a signal f (t), it is necessary sampling at a ratetwice as high as the maximum signal frequency.

If Shannon's theorem is not respected, it may causeinterference with other frequencies that are not in the band ofinterest regarding the analyzed signal(aliasing, mentionedabove).

The same unwanted phenomenon is met if a digital signalcontains frequencies higher than the Nyquist frequency(where the Nyquist frequency is half the sampling frequencyfN=fe/2 ).

IV. THEORETICALCONCEPTSABOUTFILTERS

In signal processing, a filter is a device or process that

removes from asignalsome unwanted component or feature,this means removing somefrequenciesand not others in order

to suppress interfering signals and reduce background noise.

The main specific size filters are cut off frequency - the

frequency at which the amplitude of the output signal

represents 0.707 of the input signal amplitude, and band pass

- band between zero and cutoff frequency.

Butterworth and Bessel filters are by far the most popular

filters used in electric and electronic circuits. Slow growth

attenuation near the cutoff frequency, provides an excellent

response in the time domain, but this is not very useful in
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In comparison with resistors, close tolerances capacitors

are difficult to achieve and can be more expensive. Choosing

capacitor is very important for high performance filter,

because its behavior may vary significantly from ideal,

introducing resistances and inductances. Also, the non-

linearity of the capacity towards voltage can cause distortion.

Ceramic capacitors with high dielectric constants, such as

the high-K type, can cause errors in the filter circuit.

Recommended capacitors are NPO ceramics, silver, mica,

metallic, polycarbonate, and, for temperatures up to 85 C,

polypropylene or polystyrene.After determining the electrical components of the filter, its

functionality has been simulated using a dedicated program

(Proteus - Texas Instruments), the diagram obtained is shown

in Fig. 1.2.

Figure 1.2 Simulation diagram of the filter - one channel.

VII. NUMERICALSIMULATIONSANDRESULTS

The diagram in Fig.7.1 shows that the next frequencycomponent occurs at 5 kHz, therefore it is necessary at this

frequency to have an attenuation of at least 50dB. If this

condition is satisfied, signal sampling can be performed at

a10 kHz frequency.

Figure 7.1. The frequency spectrum of line voltage

supplied by the inverter at the motor terminals, at the

fundamental frequency of 50 Hz, the switching frequency of

5 kHz

Figure 7.2 Measured input and output signals obtained from

testing the filter at 500 Hz frequency

Figure 7.3 Measured input and output signals obtained

from testing the filter at 5 KHz frequency

After obtaining numerical results, input and output signals

were represented, shown in Fig. 7.2 and 7.3.The input signal

is represented with yellow while the blue one is the output

signal.

It is seen from Fig. 7.2 and that at a500 Hz frequency the

output signal is attenuated within acceptable limits.


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Anti Aliasing Filter2

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