In this innovation, a method makes use of a new technique for describing analog information based on the roots of polynomial functions of infinite degree. Monotonic analog signals are transformed into characters that are fused into a two-dimensional composite visualization of the generating signal information. Examples of such signals include those arising from sensors, electronic equipment, or mechanical devices. Traditionally, such information is displayed by indicators, warning lights, or dials that discard the original content and temporal evolution of the source. Hence, they are not invertible back to the original signal for further examination.

Traditional signal sampling methods capture amplitude signal information at regular time points. This method captures information based on when nonmonotonic functions cross zero (real roots), and approximations of imaginary roots based on changes between real root points. This pattern of information is used to create a density distribution describing the behavior of a signal. The description is characterized as a finite alphabet of graphic symbols generated using a custom-designed frame of nodes and arcs called “box codes,” or a second time-frame designed to produce curved figures called “circle codes.” An algorithm then combines these alphabetic characters as they are identified during a signal event and merges them into a composite graphic. The graphic becomes a unique pattern signature of a signal that can be recognized by humans and, when looked at as a dynamic process, can be used to identify changes or faults in a system such as an aircraft missile system.

A second method was developed to deal with monotonic and closed functions such as would occur not from analog signals, but from data such as aircraft trajectories. This method uses another technique called “circuit coding” to turn changes in line slopes into the same sets of box code alphabetic characters. Thus, a wide variety of real-world data can be turned into recognizable graphic structures. The method permits integration of additional data types besides sensor signals or analog information. Text messages can be turned into unique graphic signatures, recognizable by humans, without requiring reading ability. This has likely use for multinational pilot/ ground control communication as well as understanding of text under conditions of high-G or vibration such as occurs on manned spaceflight liftoff.

This work was done by Charles Jorgensen of Ames Research Center.

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