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How Do I Isolate the Root-Cause of Control Loop Performance Issues?

  • By Control Guru
  • May 21, 2014

Power Spectrum: A Forensic Tool for Advanced Loop Interaction and Root-Cause Analysis

Finding controller performance issues in a typical production facility is not hard, but isolating and correcting their root-cause can present real challenges. Ask around stories abound of production staff who tune a PID control loop or re-pack a valve but ultimately fail to correct their problem. What may seem like the source of a performance problem is often little more than a symptom.

Data from a typical production process is full of valuable information. In fact, the data reveals much about a process and its behavior, including details about the relationships that one control loop shares with others located throughout a production facility. It is those relationships and the general interconnected nature of production processes that can make the isolation of root-causes so challenging. As a result, advanced interaction analysis tools like Power Spectrum have become a staple of control loop performance monitoring (CLPM) solutions due to their ability to provide meaningful insight and to help isolate the source of performance issues.

  • Hidden Clues

Power Spectrum is an effective forensic tool.  Also referred to as Spectral Density, Power Spectrum analyzes the full range of frequencies associated with a given control loop and it depicts the magnitude of those frequencies graphically.  As the magnitude (or power) of a given frequency increases it is displayed as a peak in size relative to the strength of other of the loop’s frequencies. In essence Power Spectrum decomposes control loop data and highlights the frequency (or time period) at which a loop experiences volatility. Just like a crime scene investigator, a CLPM solution equipped with Power Spectrum can use that time period to quickly identify other loops that possess the same variability and to reveal the true source of a performance issue.

  • A Practical Example

Consider a cement mill where engineers identify excessive variability and Output Reversals associated with control of the kiln hood draft pressure. On the merit of that information alone it would be reasonable to suspect that the controller is out of tune.  Indeed a poorly tuned loop would need to work harder in order to achieve the desired level of control. The output would drive variability in the Process Variable.

  • Frequency Matters

Looking at details of the control loop’s frequencies reveals meaningful insights. Further investigation of the process data identifies a clear peak in the Power Spectrum at 19 minutes. A quick search for other loops that share a peak at that frequency identifies several others, including one located upstream in the process a cooler air flow that is cycling. By correlating variability shared by the draft and the cooler air flow, Power Spectrum provides a means for looking beneath the surface and for identifying the root-cause rather than just another symptom.

There is a treasure trove of information buried within a production facility’s process data. Power Spectrum is one of several tools that is increasingly common within CLPM solutions for analyzing the data and uncovering valuable information. Processes within the average production facility are complex and highly interactive. Power Spectrum clarifies the relationships between the many PID loops used to control the means of production. It enables production staff to get to the root-cause of performance issues quickly.