22 jun. 2017

How to check the cooling liquid - NIRS™ DS2500

If for any reasons we have to change the liquid of the liquid circuit, we can see how the liquid is absorbed by the pump. We repeat the process several times looking that the air comes out from the circuit and the tank is filled and purged.


Filter Replacement - NIRS™ DS2500

Lamp Replacement - NIRS™ DS2500

Instrument Calibration - NIRS™ DS2500

Checking Temperatures in DS2500 (Lamp)

In order that the performance of the instrument DS2500 be optimal, we have to attend the temperature of the lamp when running the diagnostics. I consider it is fine around 35ºC.
Sometimes we find high temperatures like the one in the picture, and even seeing that the report says that is OK, this temperature can affect to the instrument itself and the results.
One of the causes that this temperature increase is that the tank of the pump has lost water, so it is a good idea to check the level, and fill it in if necessary.

Checking pump level video
Check that the pump is pumping. We should see some turbulences in the water and a small noise in the pump.
Check if the water is to dirty, or with algae’s.
Check that the fan is working, its mission is to keep cold the water and see if the filter is clean so the fan performs better its mission.

Changing the filter

It is important also the temperature of the room or laboratory where the instrument is. A higher temperature will increase also the lamp temperature.

After checking all this points, and being sure that the lamp is fine, maybe is the moment to run an instrument calibration:

Instrument Calibration


19 jun. 2017

Comparing Residuals, GH and T when validating

When looking to the validation statistics is important to look at the same time to three values: Residual, GH and T value for every sample. From this data (fiber), we can check if our sample is extrapolating badly, it is not robust or any other issues.

In this case, as we can see there are samples with a very high GH and we can see that those samples have in common that the T statistic is negative (in the left tail of the Gaussian Bell) and the value is quite high also for the T.
These samples have also the highest residiual values.
 Something is telling us that this samples have something special and are not well represented by the equation. PCA is warking fine and is detecting these samples as outliers, but we need to know what makes tese samples special.

These samples are soy meal and have  highest fat value as the ones in the calibration so the Model did not learn enough about the interaction between the fiber bands and fat bands. So this samples are very interested to make the calibtration more robust.

After checking this, we can add these samples to the calibration to improve the results of the next validation.

Graphically in Excel we can se the interaction between the Residuals, GHs and T values: