Spectrum Analysis

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The Spectrum Analysis is probably one of the most useful features of Reporter Professional Plus for detecting unexpected or wasteful use of energy.

It works best when you have seven or more days of data, especially when the logger recording period is around 30 minutes, as shorter periods increase the ratio of cell dividing lines to actual data.

The grid shown displays one cell for each period recorded as a single colour (like large pixel).  The vertical axis is the time of day (clarified using the standard Night/Day/Lunch/Peak/Evening colours on the left).  The horizontal axis shows the individual days.

If you look at the picture above you can clearly see that this profile shows only one day of the week when the energy consumption is low all day. You can also see that the Start/End times of electrical use are almost the same for each day.

Moving the mouse cursor across the grid continuously updates the information on the bar at the bottom.  This tells you which day and time period you are currently "over" and what the recorded value is.  The colour is also shown for confirmation.

Please note that due to the interactive nature of the display there is no PDF output for the Spectrum Analysis.

Using this method it's easy to discover that the building's occupied period is usually 07:30 to 18:00 and that it is closed on Sundays only.  If one of those vertical blue lines on a Sunday was a different shade then something was left on!  If something was left on overnight then that would show in the blue zone at the end of the day.

Look at the red cells: it is very obvious when the highest demands were!  The cursor is currently positioned over the highest, as indicated on the bottom bar.

You can filter the data displayed to show only the highest or lowest values by using the Data Filter (the upper of the two drop-down menus).

Data Filter

You can vary the range of colours used to give you finer or more course detail.

Colour Range

If you were interested in when the rest of the high demands occurred then see what happens when you filter the data to Top 50% :-

... and now Top 25% :-

... this clearly show that all the highest demands occurred between 08:00 and 11:00.

One other example worth showing is what happens when you view the same survey as above, but for Power Factor :-

... as you can see the nights during the working week are not the same as the ones when the building is closed after all!