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08 November 2021

Finding “Unknown” Waveform Anomalies

Figure 1: Width “exclusion” trigger captures
pulse widths outside the range of 980 ns to 1 µs.
The first anomaly captured is a width of 2.99 µs.
Using SmartTriggers® and statistics to find waveform anomalies is easy if you know the characteristics of the anomaly, but how do you find intermittent, anomalous events when you don’t know what you’re looking for? The answer: start with what you do know!  

Look for What’s “Not Normal”

A simple approach is to measure the nominal waveform, then trigger the oscilloscope on waveform elements that differ from nominal. Figure 1 shows a 500 kHz square wave with a roughly 50% duty cycle, so the pulse width is normally about 1 µs (the Width measurement shows a mean of 997 ns). This nominal width does not change significantly with any regularity and gives us a basis on which to begin looking for anomalies.

Most transients manifest themselves by abnormal timing. If you know a signal's nominal timing, set up conditions to trigger the oscilloscope whenever the signal is outside the nominal range of values. This is sometimes referred to as exclusion triggering because it excludes certain trigger values. It is really “lying in wait” for the anomalous event. In this case, by setting up a Width trigger for widths outside the nominal range of 990 ns ±10 ns, the oscilloscope ignores normal width pulses and captures the anomalies.

Looking closer at Figure 1, we can see the abnormal pulse width resulted from the trigger decision level being set below a runt, so the oscilloscope detected only one very wide pulse instead of two. Had it been set higher, the trigger may not have fired, but generally, any anomalies found in repetitive waveforms will point to other irregularities in the signal.

Figure 2: A 10-segment sequence mode acquisition
shows 10 anomalies captured by a
Width trigger with exclusion conditions. 
SmartTriggers, however, are limited by the timing resolution of the oscilloscope’s trigger circuits, which may miss some anomalies in very fast edge signals. By combining SmartTriggers with sequence mode acquisition, you can acquire at rates as high as 1,000,000 times per second, improving your chances of capturing rare, intermittent events. In Figure 2, 10 non-standard pulse widths that were hidden in the waveform were captured in 10 segments. Each segment shows an anomalous width that triggered the oscilloscope, while normal pulses were ignored.

Automate Trigger Creation

Figure 3: TriggerScan training autogenerates
a list of possible SmartTrigger setups
designed to find anomalies.
The TriggerScan® feature automates two key processes in the use of the trigger system to find rare events. First, it automatically trains itself by looking at normal acquired waveforms, from which it generates a list of SmartTrigger setups designed to trigger on abnormal situations likely to occur in that signal. 

Following training, the oscilloscope will suggest a number of SmartTrigger setups in the Trigger List box for you to review and choose which to use. Once the scan is initiated, the oscilloscope tries each selected trigger in turn for the set dwell time. Check Stop on Trigger to stop following an acquisition so that you can evaluate the usefulness of each trigger and refine your TriggerScan trigger list.

Search After the Fact

Figure 4: WaveScan searches a long acquisition
of a 1.5 kHz rectangular signal
to find non-monotonic edges.
WaveScan® makes available up-to-twenty different search criteria that can be used to find a variety of anomalies such as non-monotonic edges and outlier measurements, as well as commonplace anomalies like runts and glitches. It also permits setting up a condition to scan for selected events over multiple acquisitions acquired over hours or even days. Whereas a trigger will acquire only one type of anomaly, WaveScan can find as many types of anomalies within an acquisition as you choose, and it can be applied to existing acquisitions after the fact. Once it finds an anomaly that fits the search criteria, WaveScan opens a zoom of that event for closer inspection—in Figure 4, we see a zoom of a non-monotonic edge. The tabular list of anomalies found can also be used to navigate; touching any row of the table will zoom to that event.

These three techniques can help you find and measure “unknown” transient events with a high level of confidence. 

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