Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
Next revision		 Previous revision
pa-data-conditioning [2026/01/30 21:16] – reid_go-ci.compa-data-conditioning [2026/01/30 21:21] (current) – reid_go-ci.com
Line 30: Line 30:
 Statistics supports a variety of functions used in data interpretation.  Including several common functions i.e. Min, Max, Mean.  It also supports more specialized operations: Statistics supports a variety of functions used in data interpretation.  Including several common functions i.e. Min, Max, Mean.  It also supports more specialized operations:
 Peak to Peak operator saves the greatest displacement between signal minimum and maximum of oscillation during time block.   Peak to Peak operator saves the greatest displacement between signal minimum and maximum of oscillation during time block.  
-RMS calculates the effective signal strength over a period.   +RMS calculates the effective signal strength over a period.  {{::rms_eqn.png?200|}}
- +
-{{::rms_eqn.png?600|}}+
  
 ===Integration/Differentiation=== ===Integration/Differentiation===
Line 56: Line 54:
 Have a set time duration of response.  FIR filters do not have a feedback loop and feature a constant group delay.  This means that an input signal will have a uniformly delayed output and will have no distortion.  FIR filters are defined by:  Have a set time duration of response.  FIR filters do not have a feedback loop and feature a constant group delay.  This means that an input signal will have a uniformly delayed output and will have no distortion.  FIR filters are defined by: 
  
-{{::fir_filter_eqn.png?600|}}+{{::fir_filter_eqn.png?500|}}
  
 FIR Filter-Window is the simplest method of constructing a FIR filter.  Filters are created by scaling a sinc function.  It begins with a perfect passband filter and is constructed with filter coefficients to generate a desired frequency response. FIR Filter-Window is the simplest method of constructing a FIR filter.  Filters are created by scaling a sinc function.  It begins with a perfect passband filter and is constructed with filter coefficients to generate a desired frequency response.
Line 62: Line 60:
 Infinite Impulse Response (IIR) filters are defined to last forever and decay slowly.  Defined by the equation: Infinite Impulse Response (IIR) filters are defined to last forever and decay slowly.  Defined by the equation:
    
-{{:iir_filter_eqn.png?600|}}+{{:iir_filter_eqn.png?800|}}
  
 There is no set method of creation for IIR filters.  In PA the user defines the decimation filter, filter type, filter order, analog prototype, and cutoff frequencies.   There is no set method of creation for IIR filters.  In PA the user defines the decimation filter, filter type, filter order, analog prototype, and cutoff frequencies.  
Line 74: Line 72:
  
 ====Simple Data Conditioning Demonstration==== ====Simple Data Conditioning Demonstration====
 +
 +Modules can be easily dragged into place and connected to the time stream channel output by click and drag.  Module parameters are opened and modified by right clicking on the parameter and selecting Edit Analysis Parameters 
  
 {{::2026-01-30_11-27-36.gif}} {{::2026-01-30_11-27-36.gif}}