"Richard Clark" wrote in message
...
On Mon, 20 Jun 2005 23:17:40 -0400, "Walter Maxwell"
wrote:

I'd like to hear your comments.

Hi Walt,

On first pass, the results are fairly consistent, but with two
exceptions. I am not sure if this is in my translation to file
formats suitable for Mathcad, or if they lie in your process.

Anyway, a general description:

The granularity of 50Khz appears to not be fine enough to find all
peak resonances for the 9 of the 11 within the band. I have rendered
the data into a sequence of 11 curves (one curve for each height) I
call "Q" where that quality factor relates to the ratio of RL to |XL|.
This was merely a survey to glance at all the data at once and to
observe how the Mathcad sheet was taking shape. To this point this
could as easily be accomplished in Excel. Continuing, I noted that
two sets of height data moved retrograde to the general trend.

That general trend revealed a family of peaks that moved up-frequency
as the antenna height was raised. Two of the peaks were out of the
band. One was above the band (the lowest antenna height) and the
second was below the band (the second lowest antenna height). Of
these two, I would suspect that the first, or lowest antenna height,
was a curve rising to peak at the second (anti)resonance - otherwise,
the trend is progressive with two exceptions.

Those exceptions are found in raising the antenna from 8' to 10' and
from 14' to 16'. The peaks in each of these step changes move counter
to the trend: down-frequency when the height is raised. Again, this
may be entirely a transcription error of my own that I need to
investigate further.

The biggest frequency shift comes with (this is a presumption) lifting
the antenna up off the ground to the one foot level. The next biggest
shift comes with the elevation change to the two foot level - and so
on with progressively smaller shifts in frequency shift and
progressively sharpening of the curves as the antenna is hiked higher.

73's
Richard Clark, KB7QHC

Very interesting, Richard. I made a cursury check on the retrograde data, and it
seems that the trend is in the original measured data. I compared readings of
adjacent frequencies for two different heights where the retrograde occurs and
found differences in original R values that I can explain only in the
possibility of different degrees of soil wetness, because the measurements were
not all taken on the same day. The date of each measurement is in the upper left
corner of each page. Since the measurements were taken 22 years ago I can't
remember whether I logged the rain vs non-rain days, and the original data is in
obscure files in Florida. I would not have taken measurements during a rain, but
the day after a rain the soil would still have been wetter than the day before
the rain. Wetness is the only explanation I can think of for the jerk in the
data.

Are your Mathcad graphs in a format suitable for emailing? If so, I'd like to
see them.

Walt

On Wed, 22 Jun 2005 15:31:07 -0400, "Walter Maxwell"
wrote:

Wetness is the only explanation I can think of for the jerk in the
data.

Oh, where that comment might lead. :-)

Are your Mathcad graphs in a format suitable for emailing? If so, I'd like to
see them.

Hi Walt,

Sure, I will kit that up later today.

73's
Richard Clark, KB7QHC

On Wed, 22 Jun 2005 15:31:07 -0400, "Walter Maxwell"
wrote:

I compared readings of
adjacent frequencies for two different heights where the retrograde occurs and
found differences in original R values that I can explain only in the
possibility of different degrees of soil wetness, because the measurements were
not all taken on the same day.

Hi All,

This is a life's lesson in the value of context and measurement, as
well as in the discipline of taking notes. Walt's memory suggests a
reason for the perturbation observed in the data, and it is not
unreasonable. I would suggest that there is some (however slight)
likelihood that the correlations may be backwards in that most of the
days followed rain, and these perturbations were on dry days.

Before or after is not the issue. Before or after is a matter of
separability which is more important. With analysis, Walt's
conjecture can be tested against the data and what it reveals about
the impact the ground's proximity had on the antenna.

His data, either way, already supports that ground is measurable
within the data that falls outside of the spread of noise and error.
Even if Walt slipped an instrument reading or injected statistical
noise, he did it so consistently that he was always in error in the
same direction (this is called systematic error). This may impact the
accuracy of the final answer, but it does not impact the thesis'
general conclusion. What is more, even if such mischance occurred
(and I doubt it), it is recoverable with one or several cardinal
measurements to correct the earlier bias.

This round of discussion also reveals that bad data is as good as good
data. Those who discard results and tailor their reports stand a good
chance of not discovering how to fix their problems when they are
shown to be in serious error (which is to say they probably rejected
good results). I pointed this threat out in another thread that
linked to exhaustive ground data that showed hills composed of fresh
water.

73's
Richard Clark, KB7QHC