Using the Raspberry Pi Wobbulator to test the G6LBQ Multiband Bandpass Filter

Finally, I decided to use the Raspberry Pi Wobbulator to test the frequency response characteristics of the G6LBQ multiband bandpass filter which I had built as part of a homebrew transceiver project. The fully assembled filter board is shown below (it is part of a Bitx Transceiver project I'm working on) and it covers the whole HF spectrum in 9 bands, all the way from the 160m band (1.8  – 2.0 Mhz) to the 10m band (28 – 30 MHz). Each bandpass filter uses a 3rd order Butterworth design and built using the “redeveloped” component kit from Spectrum Communications. Please note that there is a revised and improved version of the G6LBQ multiband bandpass filter due out very shortly – see the DX KITS web site for details.

Using the Raspberry Pi Wobbulator to test the G6LBQ Multiband Bandpass FilterPrior to testing with the Raspberry Pi Wobbulator, each bandpasss filter was adjusted to give peak responses at the following frequencies on each band by connecting an RF signal generator to the input of the filter and measuring the output on an Oscillioscope (which is the “normal” way of adjusting such filters).

  • 160m band – adjusted for peak response at 1.9 MHz
  • 80m band – adjusted for peak response at 3.6 MHz
  • 40m band – adjusted for peak response at 7.1 MHz
  • 30m band – adjusted for peak response at 10.1 MHz
  • 20m band – adjusted for peak response at 14.2 MHz
  • 17m band – adjusted for peak response at 18.1 MHz
  • 15m band – adjusted for peak response at 21.2 MHz
  • 12m band – adjusted for peak response at 24.9 MHz
  • 10m band – adjusted for peak response at 29.0 MHz

A screen shot of the results obtained from testing the 160m bandpass filter is shown below. Channel 1 on the ADC Pi module was used and the PGA gain was set to the maximum value of 8x. The wobbulator performed a sweep from 1.8 MHz to 2.0 MHz in increments of 1000 Hz (1 KHz) and the response shows a double peak centered around 1.9 MHz.

A screenshot of the results obtained from testing the 80m bandpass filter is shown below, using channel 1 on the ADC Pi module with PGA gain of 8x. The wobbulator performed a sweep from 3 MHz to 4 MHz in increments of 10 KHz, and the response shows a nice peak around 3.6 MHz.

A screenshot of the results obtained from testing the 40m bandpass filter is shown below, using channel 1 on the ADC Pi module with PGA gain of 8x. The wobbulator performed a sweep from 6.6 MHz to 7.6 MHz in increments of 10 KHz. Although the response of the filter peaks around 7.1 MHz the response curve would suggest that the various filter elements are not well aligned.

Using the Raspberry Pi Wobbulator to test the G6LBQ Multiband Bandpass Filter wave screenshort

A screenshot of the results obtained from testing the 30m bandpass filter is shown below, using channel 1 on the ADC Pi module with PGA gain of 8x. The wobbulator performed a sweep from 9 MHz to 11 MHz in increments of 10 KHz. The response shows a peak around 10.1 MHz, but the response has a “shoulder” around 9.8 MHz which may indicate that the filter is not perfectly aligned.
A screenshot of the results obtained from testing the 20m bandpass filter is shown below, using channel 1 on the ADC Pi module with PGA gain of 8x. The wobbulator performed a sweep from 13 MHz to 15 MHz in increments of 10 KHz. The response shows a peak around 14.2 MHz, and the useable bandwith would be between 14.0 MHz and 14.4 MHz, but again the response has a distinct “shoulder” on the lower side which may indicate that the filter is not well aligned.
A screenshot of the results obtained from testing the 17m bandpass filter is shown below, using channel 1 on the ADC Pi module with PGA gain of 8x. The wobbulator performed a sweep from 17.1 MHz to 19.1 MHz in increments of 10 KHz. The response shows a peak around 18.3 MHz, which is too high, and there is a “shoulder” around 17.9 MHz.

 


About The Author

Ibrar Ayyub

I am an experienced technical writer holding a Master's degree in computer science from BZU Multan, Pakistan University. With a background spanning various industries, particularly in home automation and engineering, I have honed my skills in crafting clear and concise content. Proficient in leveraging infographics and diagrams, I strive to simplify complex concepts for readers. My strength lies in thorough research and presenting information in a structured and logical format.

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