Narked at 90 offers some products that may work for you.I started looking, I'm not terribly handy and can't see myself making a good one quickly. Are there any off the shelf products people can recommend.
Cell Checkers | Narked at 90
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Narked at 90 offers some products that may work for you.I started looking, I'm not terribly handy and can't see myself making a good one quickly. Are there any off the shelf products people can recommend.
He is full of crap
So when one cell goes bad, you'll replace all 4? That seems very risky to replace known good cells with unknown cells
The Liberty has 2 cells per side. If one side "dies", then the voting logic is done and it has to average the two remaining cells, no different to a Shearwater voting one cell out. It won't vote a second one out because it doesn't know how. The difference with the Liberty though is you can manually vote a cell out. Say you're diving EAN32 dil and diving to 30m/100ft. The left O2 board failed and you only have the 2 cells from the right. You do a dil flush to make sure everything is OK like you are supposed to and you get 1.27 on cell 1 and 1.01 on cell 2. Any normal CCR would average those two to 1.15 and try to maintain whatever setpoint you have.
In the other breathers you have to drop the setpoint and run it manually off of cell #1 and ignore cell #2. With the Liberty you go into the menu and tell it to disable cell #2. In the cell menu it will tell you excluded if it was voted out, or disabled if you turned it off.
If you are diving trimix dil, then you can turn it to He mode and it can do some fuzzy logic with the helium sensor to back into the ppO2 and it will fire the solenoid/s based off of that.
This is all made up "hypothetical" data. Revo didn't buy 1000 sensors and look at their failure rates. There's no survey of 200 revo divers and the failure rates of the five cells used by each over a year plus. This whole paper has ZERO science, ZERO data, it's Paul Raymaker making up numbers to fit his preconceived notions of how cells fail - and he even says he is making up the numbers as an example in the text.Thanks @rjack321 is there any off the shelf pressure pots fit for purpose? I have thought about building my own, I'm not the most hands on, and I could see it dragging out longer than it has taken me to build my unfinished o2 analyser.
On the "Zero data", there is a histogram in the paper showing testing of 1,000 cells. Just eyeballing the chart I can see the left skew and I can tell there is a greater than 10% chance that a cell becomes current limited in less than 4 months. SImilarly eyeballing an average of 18 months it means to replicate the results would take (18 x 1000)/12 years = 1,500 years, if you did the test one cell at a time.
There's lots of data in the paper, some peer review would require quite a bit of testing, but its open to anyone to replicate the results. I'll leave that one for someone with access to 1,000 cells to replicate in 2-3 years.
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Do they have to buy 1,000 cells to do the test? They just have to test all the cells on the rEvo's they do a 5 year service on. I'm not trying to argue. When I read the paper that is how I assumed the data would be collected. Most people I know who have put their units into a 5 year service seem to come back with a couple of new cells anyway.This is all made up "hypothetical" data. Revo didn't buy 1000 sensors and look at their failure rates. There's no survey of 200 revo divers and the failure rates of the five cells used by each over a year plus. This whole paper has ZERO science, ZERO data, it's Paul Raymaker making up numbers to fit his preconceived notions of how cells fail - and he even says he is making up the numbers as an example in the text.
It should never have been published or disseminated in the first place. It's unfortunate that he designed the Revo to mitigate for the hypothetical failure rates of cells instead of statistical analysis of actual cell performance.
I read the disclaimerThis is all made up "hypothetical" data. Revo didn't buy 1000 sensors and look at their failure rates. There's no survey of 200 revo divers and the failure rates of the five cells used by each over a year plus. This whole paper has ZERO science, ZERO data, it's Paul Raymaker making up numbers to fit his preconceived notions of how cells fail - and he even says he is making up the numbers as an example in the text.
It should never have been published or disseminated in the first place. It's unfortunate that he designed the Revo to mitigate for the hypothetical failure rates of cells instead of statistical analysis of actual cell performance.
Ever hear about statistics? You don’t need n-100This is all made up "hypothetical" data. Revo didn't buy 1000 sensors and look at their failure rates. There's no survey of 200 revo divers and the failure rates of the five cells used by each over a year plus. This whole paper has ZERO science, ZERO data, it's Paul Raymaker making up numbers to fit his preconceived notions of how cells fail - and he even says he is making up the numbers as an example in the text.
It should never have been published or disseminated in the first place. It's unfortunate that he designed the Revo to mitigate for the hypothetical failure rates of cells instead of statistical analysis of actual cell performance.
Agreed, but if you read on up to just Page 13, the key data that he extrapolates from is the failure modes from an actual batch of 1,000 cells:I read the disclaimer
"Some graphs in the presentation are only shown for didactic purposes and do not reflect real quantities of data."
OMG
Except there is no N at all. We don't know the failure rates at any age beyond anecdotes. If there are actual failure data in that paper the brand, storage, condition, usage, EVERYTHING important is missing or bootstrapped from a completely mysterious dataset. The whole paper is garbageEver hear about statistics? You don’t need n-100
Agreed, but if you read on up to just Page 13, the key data that he extrapolates from is the failure modes from an actual batch of 1,000 cells:
"This type of graph show the number of cell that have failed before or at the moment of reaching a certain age, out of a batch of 1000 sensors. It is this graph we will later use for computer simulation, when we want to estimate the lifetime of a sensor: each time we install a new sensor in our rebreather, we let the computer pick a random number between 1 and 1000, and using the graph we get a lifetime prediction for this particular sensor."
The paper says the data was got from an actual batch of 1,000 cells. As this is a study done by rEvo they would only have used their own cells as they are the only cells that they supply, so the brand dataset would not be relevant. But can you explain what exactly do you mean by 'cell condition'?Except there is no N at all. We don't know the failure rates at any age beyond anecdotes. If there are actual failure data in that paper the brand, storage, condition, usage, EVERYTHING important is missing or bootstrapped from a completely mysterious dataset. The whole paper is garbage