DIAdem Idea Exchange

I would like a tool that would help identify noise spikes in my data, so that they may be set to NO VALUE or carefully interpolated.  In the attached example, I have two torque spikes in my data that are significantly higher than the mean.  If I were only looking at one file, I would simply "Set Flags" in VIEW, then "Flags: Remove Data Points". However, I am reviewing dozens of files with several channels of interest.  

Peak data points are the most damaging to the components under test, so it is important that we keep the real events and reject the noise.  

Concerns with other peak / spike removal options:

• Manual Set Flags -> Flags:  Remove Data Points; time required
• ANALYSIS -> Event Search -> Event = Window -> Upper Limit:  In other data files, I have real events with values higher than the noise in this data file.  
• ANALYSIS -> Digital Filters or Smoothing:  This will change all of the data - it will likely narrow the peak-to-peak of my other data and interpolate my noise spikes, adding damage that is not actually real.  I only want to remove a few data points in the channel data. 

nCode Glyphworks has a nice Spike Detection Tool that uses 6 available algorithms to detect spikes.  Once it identifies them, it allows the user to see them, prior to performing any actions - this is important, because it allows the user to identify if they are real or noise, prior to taking action.  

I want to add a feature of TREWESS into DIAdem. There is a statement in the "Dynamometer Performance Evaluation and Quality Assurance Procedures" that the TREWESS technique (available using DataDesk analysis software:https://datadescription.com/tech-specs/) is a recommended approach. Right now, although OEMs need to adjust standards from "Dynamometer Performance Evaluation and Quality Assurance Procedures" to "40 CFR Part 1066", there is not mentioned about filtering in the responsive assessment so that some OEM customers(especially who have certified Dynamometer benches) request to evaluate with previous TREWESS. Since DataDesk has features of Lowess, TREWESS and Running Median in the Non-Linear Smoothers, they want to use at least TREWESS in the Non-Linear Smoothers.