System for surveillance of spectral signals

A method for testing a process and/or a data set of a system for determining the condition thereof, comprising:

• collecting a first signal from at least a first source of data over a monitoring time period from at least one variable of the process and/or the data set;
• collecting a second signal from at least a second source of data from the process and/or the data set over the monitoring time period for comparison with said first signal from said at least first source of data;
• providing a parametric transformation at a given time for said signals from said at least a first source of data and said at least a second source of data to generate transformed signals for each said first source of data and said at least a second source of data;
• obtaining a difference function characteristic of the difference pairwise at the given time between said parametric transformed signals from said at least a first source of data and said at least a second source of data for the given time in the monitoring time period;
• continuing said parametric transformation for a time increment for a next time in the monitoring time period to provide a three-dimensional surface of data over time and parametric space;
• and
• applying a pattern recognition methodology to determine a three-dimensional spectrum data set characteristic of an operating condition of the at least a first data source and at least a second data source.

A method for testing a process and/or a data set of a system for determining the condition thereof, comprising:

• providing a first signal data from a first source of data over a monitoring time period from at least one variable of the process and/or the data set;
• providing a second signal data from a second source of data from the process and/or the data set over the monitoring time period for comparison with said first signal data from said first source of data;
• providing a frequency domain transformation at a given time for said signal data from said first source of data and said second source of data;
• obtaining a frequency domain difference function characteristic of the difference pairwise at the given time between said frequency domain transformed signals from said first source of data and said second source of data for the given time in the monitoring time period;
• continuing said frequency domain transformation for a time increment for a next time in the monitoring time period to provide a three-dimensional surface of power spectrum data over time and frequency space;
• and
• applying a pattern recognition methodology to determine a three-dimensional spectrum data set characteristic of an operating condition of the first data source and the second data source.