## You need to test, we're here to help.

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## 28 March 2022

### Oscilloscope Basics: When to Use Track to Graph Oscilloscope Measurements

 Figure 1: Pulse Width Modulated waveform (yellow) and Track math operator (blue), where the X-axis scaling is identical for both.
Modern oscilloscopes contain many tools that can be used for analyzing data, including Track and Trend math functions. Both Tracks and Trends graphically display measurement results and locate anomalies. The main similarity between Tracks and Trends is that the Y-axis of both operators is the measurement parameter itself (for example, Pulse Width, Duty Cycle, Rise Time, Slew Rate, etc.). The main difference between the two math operators is their X-axis, in which the Track uses the identical X-axis and synchronous horizontal scaling as the input waveform, whereas the Trend uses units of chronology. A Track, in essence, is a waveform of the measurement values. A Trend is a data logger showing the history of change in measured parameter values, but points are not necessarily synchronous with the measured waveform.

### Use Tracks for Anomaly Detection

The Track provides valuable debugging information by directly pointing to an area of interest.

Notice the negative-going spike in the Track waveform in Figure 1. Figure 1 occurs at the point in time where the input waveform reaches its most narrow pulse width, and the Track instantly finds it, indicating when one measurement deviates from the others in the graph. The Track identifies the exact location in time where the narrowest or widest pulse width has occurred, and fully describes the measurement changes occurring throughout the entire waveform. Since oscilloscopes can acquire thousands or even millions of waveform edges within a single acquisition, the Track allows an engineer to quickly "find the needle in a haystack".

### Use Tracks to Demodulate Waveforms

In addition to locating anomalies, Tracks can synchronously demodulate a waveform, which is useful for uncovering repeating characteristics within signals. When a repeating pattern occurs, the pattern is often not visible to the user because changes in the waveform are quite subtle relative to the repetition time. Consider the case of the same repeating pulse width modulation pattern.

 Figure 2: Measurements on the Track waveform reveal that the modulation pattern repeats once every 45 cycles.
Shown in Figure 2, the Track operator has demodulated a PWM waveform using a much longer time interval. The shape of the pulse width modulation reveals a repeating modulation pattern which would not have been obvious to an engineer if not for the shape of the Track, because at the time scale needed to capture several repetitions of the PWM pattern, there are at least hundreds of pulse widths on the screen. This allows for the user to identify which underlying data patterns exists within the data and their rate of occurrence.

In order to determine how many pulse widths comprise one full repetition of a PWM pattern, the user can measure the frequency of the input waveform and the frequency of the pattern itself, and calculate the ratio of the two frequencies, as shown in Figure 2. By graphing primary measurements, then demodulating the pulse train with the Track operator, secondary measurements on the Track provide a complete description of the underlying pulse width modulation scheme. This type of application is where the Track math operator is at its best, allowing an engineer to combine math and measurement operators in a simple way to learn a great deal about a circuit's behavior.

Download this information in our application note, When to Use Tracks and When to Use Trends to Graph Oscilloscope Measurements.