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Removing Faults from Bangladesh Data For Motes 1 and 11

Removing Faults from Bangladesh Data For Motes 1 and 11. Rules. Rule 0: Removing broken sensors Rule 1: Removing shorts Rule 2: Removing sudden drops Rule 3: Removing remaining 0s (why?) Rule 4: Removing potential “low concentration”. Questions. Probability/multiplicative fault?

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Removing Faults from Bangladesh Data For Motes 1 and 11

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  1. Removing Faults from Bangladesh DataFor Motes 1 and 11

  2. Rules • Rule 0: Removing broken sensors • Rule 1: Removing shorts • Rule 2: Removing sudden drops • Rule 3: Removing remaining 0s (why?) • Rule 4: Removing potential “low concentration”

  3. Questions • Probability/multiplicative fault? • Using pre/post when • Shorts: drops from in-range, and then if it goes up a little and goes back to 0, is that still a fault? Should definition be: sharp slope down and sharp slope up and all in between? • What should constants be? • What can I associate with each Rule? • Show graph with shorted chloride attached • What does that mean for pylon 3 • Do you believe remaining data? • Should we remove potentially low concentrations or leave them in?

  4. Next Steps • Validate rules in lab • Try to do rules with just pre-calibration – how much worse does it do?

  5. Terms • MDL: Minimum detection level as defined by our calibration curve’s lower limit • In-range: values above the MDL (using either pre or post calibration equations)

  6. Applying Rules To Explain Faults • Set of slides for mote 1 and for mote 11 for ammonium • Each set contains graphs where 1 rule has been applied to the data (rule described on the slide). • 1 graph has the data left after the rule is applied • 2nd graph has the data removed by the rule • Table quantifies data removed after applying rule and number of points that are below the MDL • So far, all rules only apply to data below MDL because we are more sure that this data is “bad” in some way or another • INTERESTINGLY – all data below MDL is accounted for by some rule • GOAL – associate a “root cause” with each rule that is applied

  7. Rule 0: Removing Broken Sensors • Sensors that never report data > MDL (using pre or post calibration) are considered to be broken: • Calcium for Mote 11 is classified as broken using this rule (validated because it was still broken upon calibration in the field, but is now working in the lab)

  8. Initial Data

  9. Mote 1 - Shorts Rule 1: Shorts Points that are 0mV immediately following an in-range value Explanation of Table: Of 926 total points (of which 162 points were below the MDL), 28 were classified as a short

  10. Mote 11 - Shorts

  11. Mote 1 - Drops Rule 2:Sudden Drops Series of points that are < mdl & have slopes > threshold (1 order of magnitude/hour)

  12. Mote 11 - Drops

  13. Mote 1 – 0s Rule 3:Remaining 0s Remove all remaining 0s. No good explanation for why these should be removed!!

  14. Mote 11 – 0s

  15. Mote 1 – < MDL Rule 4:Potential LowConcentration Points within 1 order of magnitude below the MDL. Reasoning: these are not faults, they are potentially real readings of very low concentrations

  16. Mote 11 – < MDL

  17. Mote 1 – Remaining Out of Range No data left unclassified! Remaining Out Of Range data Goal is to explain all out of range data using preceding faults. Ideally do not remove any data in this step!

  18. Mote 11 Remaining Out of Range No data left unclassified!

  19. For both Mote 1, and 11, all data below MDL is accounted for all sensors EXCEPT calcium (But Rule 0 specifies calcium for mote11 as broken anyways)! DOES THIS MEAN CALCIUM MOTE 1 IS BROKEN??

  20. Original Remaining after Rule 1

  21. Remaining after Rule 2 Remaining after Rule 3

  22. Remaining after Rule 4 MOTE 11 Remaining after Rule 4

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