The Stamp method for processing of high noise data from infrared sensor in harsh environment

- A new digital method, called Stamp method, for elimination of undesired noise data from a periodic signal is presented.
- It is a combination of equidistant transversal and differential filters with subtraction of neighboring statistical images.
- Influence of imperfection of data processing is checked by simple shifting of resulting data vector.
- The method was applied on signal from IR sensor in harsh environment of hydroelectric power plant generator.

This article presents a new digital method, called Stamp method, for elimination of undesired noise data from a periodic IR signal. The Stamp method is a useful tool for statistical analysis of changes which appear in a noised input signal. One stamp is a statistical image of several consequence periods from a raw input signal. The Stamp method is a combination of equidistant transversal and differential filters, where useful output data is produced by subtraction of neighboring stamps. The corresponding digital Stamp filter formulation is provided with the Z-transform formalism. An application of the statistical Stamp method is presented on temperature changes extraction from a real noised IR (infra-red) raw signal from turning shaft in a power plant. The moving average and impulse-response filters were applied for final cleaning up of the data. The MATLAB short source code of stamp implementation is in the Appendix A.