Advanced Data Editing in Flo-Ware

One of the most powerful features in Flo-Ware is the advanced data editing capabilities offered. The data reconstruction workspace gives you the flexibility to analyze data and, if necessary, repair or reconstruct the data to remove any inherent data in the project you are working with. The example described throughout these topics will relate to removing error from the velocity channel (theme) in a supported flowmeter.

The flow totals show obvious errors in data on 4/28 and 5/2. Each day should be approximately 200,000 gallons higher than reported.

The chart above shows that on 4/28 and 5/1 there is a distinct difference in the pattern of data typically shown before, between and after these sections. In the 2 sections of data described, the velocity and flow themes tend to become erratic and "drop out" for what amounts to about 1 day in each case. This could be the result of rag or debris fouling on the sensor. Whatever the reason, how does one know (in this case) that the recorded wastewater flow was simply low during these periods and that the data is accurate? In our example, it is very simple. First, since flow is a calculated theme, we can ignore it when analyzing data for error. This is simply because the flow will behave relative to the level and velocity themes. We can easily determine that there is an error in the velocity theme because the level continues day after day with a consistent pattern. This is even true during the two events where the dropouts occurred. Both level and velocity follow a distinct and noticeable pattern relative to each other, except on 4/28 and 5/1. Knowing or realizing this pattern combined with the fact that level and velocity are related to each other allows to come to the conclusion that the velocity theme has error in it.

Note: The level and velocity relationship described assumes free flow conditions exist.

The steps described in the following topics will lead you through removing the error shown. The result will be more accurate data, better flow balances and a higher level of statistical confidence in the information presented.