During the process of writing the article Analysis of output matching of a certain 25W 144MHz PA an estimate was made of the characteristic impedance Zo of a section of twisted enamelled 0.71mm copper wires.
Perplexity AI
Let’s ask Perplexity AI for an answer.
Perplexity AI gives approximately 108Ω.
RF Two Wire Transmission Line Loss Calculator
Using TWLLC, we can get a ball park estimate of Zo using a guess of vf=0.7 based on experience.
0.071 ECW twisted pair |
|
| Parameters | |
| Conductivity | 5.800e+7 S/m |
| Rel permeability | 1.000 |
| Diameter | 0.000710 m |
| Spacing | 0.000763 m |
| Velocity factor | 0.700 |
| Loss tangent | 0.000e+0 |
| Frequency | 146.000 MHz |
| Twist rate | 100 t/m |
| Length | 1.000 m |
| Results | |
| Zo | 33.50-j0.68 Ω |
| Velocity Factor | 0.7000 |
| Twist factor | 0.9725 |
So, Zo in the range 30-35Ω is likely.
Measurement
A test section of 255mm length was made and measured with SC and OC terminations using a VNWA3E.
Above are the |s11| measurements for SC and OC.
From that dataset we can calculate Zo.
Calculation of Zo over most of this range looks ok, it has the typical turn up at low frequencies, and there is a problem measuring close to its quarter wave resonance. Around 150MHz, Zo is around 33Ω, quite close to expectation.
We can also calculate vf.
vf is 0.665 around 150MHz, so the earlier guess was not too far off the mark.
So, measurement gives approximately 33Ω.
What went so wrong with Perplexity AI?
- The ln function is not a good approximation for close spacing (even if they solved it correctly, and they didn’t); and
- proximity effect is not considered, again relevant for close spacing.
Conclusions
This problem was not an contrived one designed to trip up Perplexity AI, read the referenced article and it is the solution to a real design problem of a 144MHz RF PA.
Perplexity AI gave a convincing looking result for the naive, but it did not reconcile with measurement, Perplexity AI gave 300% of measurement.
TWLLC based to some extent on an experienced guess of velocity factor gave a much better prediction.
Update: 22/12/2024
Three days later, Perplexity AI gives a value about half that previously, but probably still about twice the correct answer.