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I am quite new Digital Signal Processing  .I am trying to implement anti-cogging algortihm for my PMSMpermanent magnet synchronous motor (=PMSM) control algortihm. I follow this documentation

I collected velocity data according to the rotation angle. I have buffer with 1024 byte sizebytes long sampling buffer. Each index meansample is stored when my rotation encoder gave a pulse, so each index actually means mechanical rotation angle. And eachEach stored value is the velocity withat related mechanical angle. 

I transported this buffertransformed the collected samples to frequency domain with FFT. WhatIt's not clear to me what is my Fs (sampling=sampling frequency). When iI examined tothe frequency spectrum  , dominant harmonics are related multiplies of 14 - 27 index numbers which is number of slot(27) and number of pp(14). 

But the last step of the suggested method, Acceleration Based Waveform Analysis  , Itneed calculated derivative of FFT outputs with respect to time. Outputs are in frequency domain, so how could I calculate derivative of FFT outputs with respect to time , and why does it dothe method need this calculation?

I am quite new Digital Signal Processing  .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation

I collected velocity data according to the angle. I have buffer with 1024 byte size. Each index mean encoder pulse so each index actually mechanical angle. And each value is velocity with related mechanical angle. I transported this buffer frequency domain with FFT. What is my Fs (sampling frequency). When i examined to frequency spectrum  , dominant harmonics are related multiplies of 14 - 27 index numbers which is number of slot(27) and number of pp(14). But last step , Acceleration Based Waveform Analysis  , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

I am quite new Digital Signal Processing.I am trying to implement anti-cogging algortihm for my permanent magnet synchronous motor (=PMSM) control algortihm. I follow this documentation

I collected velocity data according to the rotation angle. I have 1024 bytes long sampling buffer. Each sample is stored when my rotation encoder gave a pulse, so each index actually means mechanical rotation angle. Each stored value is the velocity at related angle. 

I transformed the collected samples to frequency domain with FFT. It's not clear to me what is my Fs (=sampling frequency). When I examined the frequency spectrum, dominant harmonics are related multiplies of 14 - 27 index numbers which is number of slot(27) and number of pp(14). 

But the last step of the suggested method, Acceleration Based Waveform Analysis, need calculated derivative of FFT outputs with respect to time. Outputs are in frequency domain, so how could I calculate derivative of FFT outputs with respect to time and why does the method need this calculation?

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I am quite new Digital Signal Processing .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation

I collected velocity data according to the angle. And I translatedhave buffer with 1024 byte size. Each index mean encoder pulse so each index actually mechanical angle. And each value is velocity datas towith related mechanical angle. I transported this buffer frequency domain with FFT. What is my Fs (sampling frequency). When i examined to frequency spectrum , dominant harmonics are related multiplies of 14 - 27 index numbers which is number of slot(27) and number of pp(14). But last step , Acceleration Based Waveform Analysis , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

I am quite new Digital Signal Processing .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation

I collected velocity data according to the angle. And I translated velocity datas to frequency domain with FFT. But last step , Acceleration Based Waveform Analysis , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

I am quite new Digital Signal Processing .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation

I collected velocity data according to the angle. I have buffer with 1024 byte size. Each index mean encoder pulse so each index actually mechanical angle. And each value is velocity with related mechanical angle. I transported this buffer frequency domain with FFT. What is my Fs (sampling frequency). When i examined to frequency spectrum , dominant harmonics are related multiplies of 14 - 27 index numbers which is number of slot(27) and number of pp(14). But last step , Acceleration Based Waveform Analysis , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

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Neil_UK
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I am quite new Digital Signal Processing .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation :this documentation

https://www.modlabupenn.org/wp-content/uploads/piccoli_matthew_anticogging_torque_ripple_suppression_modeling_and_parameter_selection.pdf

I collected velocity data according to the angle. And I translated velocity datas to frequency domain with FFT. But last step , Acceleration Based Waveform Analysis , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

I am quite new Digital Signal Processing .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation :

https://www.modlabupenn.org/wp-content/uploads/piccoli_matthew_anticogging_torque_ripple_suppression_modeling_and_parameter_selection.pdf

I collected velocity data according to the angle. And I translated velocity datas to frequency domain with FFT. But last step , Acceleration Based Waveform Analysis , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

I am quite new Digital Signal Processing .I am trying to implement anti-cogging algortihm my PMSM control algortihm. I follow this documentation

I collected velocity data according to the angle. And I translated velocity datas to frequency domain with FFT. But last step , Acceleration Based Waveform Analysis , It calculated derivative of FFT outputs with respect to time. Outputs are frequency domain how could I calculate derivative of FFT outputs with respect to time , and why does it do this calculation?

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