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  • in reply to: Energy Compensation and Counting Statistics #1719
    jwet
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    As I said, my intent is only to offer constructive help to improve your design. I won’t make any further comments after this clarification. As I said what you’ve done is very laudable.

    On Energy compensation- your packaging, a few mm of Aluminum, does help with some low energy over response but not very much. You listed a number of high energy isotopes which are generally associated with background. However the assumption is that if there was an accident at a nuclear power plant for example, you would have a completely differnt mix of isotopes (source term as I mentioned before). Some important isotopes would Kr-85, Xe-133, I-131, Cs-137 and perhaps Co-60, if you look at the spectrum of these isotopes, you’ll find a lot of lower energy contributions. The idea of energy compensation is to make a detector that will read some accepted units regardless of the source term.

    On counting statistics, I’m not trying to obfuscate or make things complex but using terms like quantum effects. All this means is that at low rates like background, radiation is quantized, it is not continuous. Imagine measuring very small quantities of rain fall- at some point you get to “drops”, this is the same as counts in radiation. If you measure 100 rain drops in some interval, the statistical standard deviation (one sigma) is the square root of this total count- or 10 drops. This means that 67% of the time if you measure 100 drops, the actual rain fall could be anywhere between 90 and 110 drops. At very low count rates like 5 counts- the one sigma interval is the square root of 5, about 2.2 which is +-40% error. The standard for radiation detection is usually 2 sigma, a 95% confidence interval. This is not complicated but is real.

    A very simple way to implement some control over counting statistics is to just wait for a given number of counts total and let the time vary. A common way to do is to time the overflow of a 10 bit counter. For 1024 counts, the 2 sigma statistics would be about 6% – a reasonable measurement in finite time. At very low count rates, it could take a long time to produce a reading but a reading any sooner would be statistically inaccurate. This is the tradeoff.

    Good luck on your project. I really like it. I think it could be improved with a few changes and don’t want to detract from what you’ve done- its really quite good.

    Constructively,
    John

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