DATA ANALYZER

The Protuner™32 Data Analyzer is designed with the functionality and features to make the complex process of data analysis, trouble shooting, tuning, and system optimization both intuitive and easy.

Data Display Features

Open and closed loop multivariable data collected, following the test procedures outlined in the Protuner™32 Applications Manual, contains a wealth of information about the installed performance of the operating the system being analyzed. The graphical display features provide the Protunertm user with the tools necessary to accurately interpret and document your findings.

 
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Read and export data files in PSA, ASCII, text, and Excel formats
Tab between graphical displays of all data, user selected data channels, and individual graphs
Individual graphs displayed data both percent and EU
Overlay data by defining data channels to be displayed with data offsets
Auto scale data display
Time, relative time, or real time Y-axis
Graphical comment function saves display format and allows for entry of balloon comments
All commented graphic displays are saved and can be recalled
Zoom
Dynamic cursor on all graphical displays
 
Frequency Analysis

Random noise and non-deterministic load disturbances often found in real processes. To optimize the control of a process to achieve minimum variance control the impact and source of the stochastic type disturbances must be understood before can be minimized or eliminated. The frequency and time series analysis routines are a powerful set of analysis functions to understand the disturbance characteristics. Only after disturbances are quantified and understood, can their impact on process variability can be minimized. Each frequency and time series analysis graphic has the following features:

 

Frequency and Time Series Reports

Synopsis - Powerful graphic for displaying both time series and frequency analysis graphics on a single page
Statistics - Documents the statistical variability in the data signal
Histogram - Data points of the time series are sorted into cells and the number of points in each cell is displayed as a percent of the total number of points
Power Spectrum - Describes the frequency content of selected data series
Cumulative Spectrum - Document the percent of variance as a function of cyclic period or frequency
Autocorrelation - Measure of the lack of randomness in the data
Crosscorrelation - Used to determine the correlation and the lag time between variables
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