Estimate the total harmonic distortion present

In summary, Total harmonic distortion (THD) is a measure of the amount of distortion present in an electronic signal. It is expressed as a percentage and is calculated by taking the square root of the sum of the squares of all harmonic components divided by the square root of the amplitude of the fundamental frequency squared, multiplied by 100. It is important to estimate THD because high levels can result in distorted sound or images, and it can be caused by non-linearities in electronic components, power supply fluctuations, and interference. THD can be reduced by using high-quality components, proper grounding and shielding techniques, and carefully designing and testing electronic circuits. In audio systems, it can also be reduced by using low-distortion speakers and placing them in
  • #1
Hndstudent
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Thread moved from the technical forums, so no Homework Help Template is shown.
The supply current was sampled 1024 times over a very short time interval. The data so obtained is given in column B of the accompanying Excel worksheet1. This worksheet has been set up to give a graph showing the spectral components of the data.

Question 3

  1. i) Obtain the Fourier Transform for the data using the Fourier Analysis tool of Excel. The transformed data should commence in cell D2.
  2. ii) Identify the principal frequencies in the current waveform.
  3. iii) Estimate the total harmonic distortion [THD] present in the current waveform using the formula:

    n max
    THD(I)=1/I1 SQRT Σ (In)^2 x 100%
    n=2

where I1 is the r.m.s. value of the fundamental current, In the r.m.s value of the nth harmonic and n(max) is the number of the highest measurable or significant harmonic.

[Note the vertical axis of the spectrum graph is scaled in (current)2.]

iv) Attempt to synthesise the shape of the original waveform from its principal harmonics [e.g. sketch the waveforms of the harmonics on the same time axis and add them together].I am struggling with 3iii.

for I1 rms I have SQRT 15.8 + 8.77 + 6.25 = 5.55A

n max I have 15.8 as its the highest magnitude.

But I'm not sure what to do to find In?

any help would be appreciated.
 
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  • #2
Hndstudent said:
But I'm not sure what to do to find In?
In, or ##I_n## to make it clear, should be the rms magnitudes of the individual harmonic components.

Perhaps you could attach the Excel spreadsheet, or even a textfile of the datapoints you were given so that others might duplicate the problem?
 
  • #3
Hi Gneill,

please find attached original worksheet. and a screen shot of the completed waveform.
 

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  • #4
gneill said:
In, or ##I_n## to make it clear, should be the rms magnitudes of the individual harmonic components.

Perhaps you could attach the Excel spreadsheet, or even a textfile of the datapoints you were given so that others might duplicate the problem?
Hi Gneill, I am still struggling to work out ##I_n##. And am I close with my I1 rms and n max answers?

Thanks
 
  • #5
Hndstudent said:
Hi Gneill, I am still struggling to work out ##I_n##. And am I close with my I1 rms and n max answers?

Thanks
##I_1## will be the magnitude of the fundamental alone. That is, the single peak that corresponds to the fundamental frequency associated with the current. In general this is the peak with the lowest frequency. The other peaks should be located at some multiples of that frequency. In your data the fundamental corresponds to the 15.878 at a frequency of about 53 Hz.

##n_{max}## is the number of the frequency component peak with the highest frequency that you intend to deem as "significant". The peaks are numbered from 1 to ##n_{max}##, with "1" being associated with the fundamental. If you plot your FFT values, how many significant peaks can you see over the whole domain? It looks like you've already picked them out and there are three of them. So ##n_{max}## = 3.

As an aside, I have noticed that different implementations of the FFT algorithm tend to apply different normalizing factors to the returned values. You might find, for example, that in order to recover the actual component contributions to your "signal" that you have to multiply the returned values by some constant, typically 2. The "DC" contribution (if any) is usually exempt from this normalization (I don't know why this is).

As an exercise you might try concocting your own "signal" with known components at particular frequencies and see how your Excel FFT handles it. Maybe something like:

##f(t) = 10 sin(ω_o t) + 3 sin(5 ω_o t) + 2 sin(8 ω_o t)##

where you choose the fundamental frequency ##ω_o## in radians/sec as you wish. Also pick a suitable sampling frequency to "sample" the signal generate the raw datapoints. See if you can "recover" the harmonic frequencies and their magnitudes from the FFT data.
 
  • #6
Hi, is this thread still active as I have a question relating to this topic. Please advise or should i start a new thread ?? Thanks
 
  • #7
David J said:
Hi, is this thread still active as I have a question relating to this topic. Please advise or should i start a new thread ?? Thanks
Probably best to start a new thread. It's unlikely that the OP is still interested in pursuing this thread at this time.
 

Related to Estimate the total harmonic distortion present

What is total harmonic distortion (THD)?

Total harmonic distortion (THD) is a measure of the amount of distortion present in an electronic signal. It is expressed as a percentage and represents the ratio of the sum of all harmonic components to the amplitude of the fundamental frequency.

How is THD calculated?

THD is calculated by taking the square root of the sum of the squares of all harmonic components divided by the square root of the amplitude of the fundamental frequency squared. This value is then multiplied by 100 to get a percentage.

Why is it important to estimate THD?

THD is important because it can affect the quality of a signal. High levels of THD can result in distorted sound or images, which can be undesirable in certain applications. Estimating THD allows for the identification and mitigation of potential issues before they impact the overall performance.

What are the sources of THD?

THD can be caused by a variety of factors, including non-linearities in electronic components, power supply fluctuations, and interference from other electronic devices. In audio systems, THD can also be introduced by the speakers themselves.

How can THD be reduced?

THD can be reduced by using high-quality components, proper grounding and shielding techniques, and carefully designing and testing electronic circuits. In audio systems, THD can be reduced by using low-distortion speakers and placing them in an acoustically optimized environment.

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