The Process and Equipment Monitoring (PEM) Toolbox is a MATLAB based set of tools that provides a generalized set of functions for use in process and equipment monitoring applications, specifically on-line monitoring systems (OLM).

 

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PEM Toolbox

Description of Software:

PEM Toolbox Architecture

PEM

The Process and Equipment Monitoring (PEM) Toolbox is a MATLAB based set of tools that provides a generalized set of functions for use in process and equipment monitoring applications, specifically on-line monitoring systems (OLM).  The architecture of the PEM Toolbox is organized into six function categories. The first category allows for data to be acquired from multiple sources and conditioned to assure data quality. The next category includes tools to aid in model development including variable grouping and multivariate model optimization. Once a model is developed, functions for parameter prediction and performance analysis may be used for either an auto associative kernel regression (AAKR) model or the auto associative neural network (AANN). The final two function categories provide methods for uncertainty estimation and fault detection.

There is no rapid prototyping tool developed for process and equipment monitoring development that contains this flexibility.  Not only can you develop different architecture types, but you can compare the models and methods using standardized performance metrics.  It is developed on the MATLAB framework, so can easily be integrated with other MATLAB tools for signal processing, statistical analysis, etc.

 

PEP

The Process and Equipment Prognostics (PEP) Toolbox is a set of MATLAB‐based tools that facilitate fast prototyping of empirical‐based prognostic models developed at the University of Tennessee Nuclear Engineering Department. The PEP Toolbox includes functionality to perform algorithms in each of the three prognostic model types: reliability-based, operation-based, and degradation-based. Each of the prognostic algorithms includes methods for estimating the 95% uncertainty interval of the remaining useful life (RUL) estimates. Additional functionality is available to support model development in conjunction with monitoring system results from the PEM Toolbox. 

System Requirements

1) Neural Networks Toolbox release 4.0 or later

2) Signal Processing Toolbox release 6.1 or later

3) Statistics Toolbox release 5.0 or later

4) Wavelet Toolbox release 3.0 or later

 

Other Requirements and Recommendations

  • Microsoft Windows supported graphics accelerator card, printer, and sound card
  • Office 2000, Office XP, or Office 2003 is required to run the MATLAB Notebook, MATLAB Builder for Excel, Excel Link, Database Toolbox, and MATLAB Web Server. (Note that this is not necessary to use the toolbox through the MATLAB command window.)

Supported Platforms

  • Operating systems: Any OS that can run MATLAB 7 will run the PEM Toolbox
  • Windows XP or XP Service Pack 2
  • Windows 2000 (Service Pack 3 or 4) or Windows 2003 Server
  • Windows NT 4.0 (Service Pack 5 or 6a)
  • Apple OSX
  • Windows 7 or later

Materials provided through this license

Source code, user manual, release notes and tutorial are provided in a zipped tar archive and several pdf files

 

Developed by Drs. Dustin Garvey, Wes Hines, Jamie Coble, and Michael Sharp

 

$10,000.00