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2017

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Quinton Martins, the leader of the Mountain Lion Project at the Audubon Canyon Ranch (ACR) in Northern California, had a problem.  Mountain lions needed to be trapped and GPS-tagged for research, but traditional trapping methods were just not effective enough.

 

 

Trapping method of the past

 

The traditional technique for trapping mountain lions involves the use of a one-door “single- ended” cage, with bait to lure the cat inside.  A mechanical pressure plate on the cage floor triggers the door-closing mechanism.  There are two significant issues with this approach.

 

  1. Bait isn’t tempting enough. Where food is abundant, mountain lions may not be hungry enough to venture into a cage. It can also be very difficult to source mountain lion munchies, like roadkill deer.
  2. The wrong animals are caught! Often smaller animals like foxes and bobcats end up in the traps instead of mountain lions.

 

 

Catching more mountain lions

 

Mountain lions commonly re-use the same walking paths, so Quinton is able to use bushes and sticks to ‘funnel’ the animal into a walk-through cage that is open at both ends. This works well because it is far easier to convince a mountain lion to walk into a cage if it can see a clear path through the other side. It also eliminates the need for bait by taking advantage of the mountain lion’s natural walking path.

 

The challenge was to develop a reliable electronic system that would simultaneously close both doors of the walk-through cage while the mountain lion was inside.

 

In this new design, the doors operate very simply. They are held vertically in “U” channel guides and drop when actuator rods are pulled (Fig. 1). 

 

 Cage Operation

Fig 1: Mountain Lion Cage Operation

 

 

A single, high-power solenoid pulls a wheel, which is connected to both actuator rods. The electrical system is controlled by an Arduino Uno microcontroller and a high current relay to activate the solenoid (Fig 2).

 

Prototype Actuator Mechanism

Fig 2: The prototype actuator mechanism

 

 

System design

 

The system needed to detect the motion of a mountain lion without trapping smaller animals. I investigated several options for sensing mechanisms including a horizontal light beam sensor and ultrasonic range sensors.  The light beam sensor worked, but it was difficult to set up and align and involved hanging wires over the side of the cage. I ultimately decided to use less intrusive ultrasonic range sensors installed at the top of the cage.

 

The system needed to detect the motion of a mountain lion without trapping smaller animals.

 

By measuring the distance from the top of the cage to the animal, we could set it to trigger on large animals only (mountain lions are typically at least 20 inches tall at their shoulders). The system was designed with two range sensors spaced 14 inches apart that would trigger only when both sensors detected an object at least 20 inches tall.  This double-sensor set-up minimizes the chance of triggering on a smaller animal, such as a fox, that might sniff the top of the cage with its nose.  If that happens, the small animal would only trigger one of the sensors, so the doors would not close.

 

The system was designed with two range sensors spaced 14 inches apart that would trigger only when both sensors detected an object at least 20 inches tall.

Debugging & deployment

 

With the basic design established, the next challenge was to write and debug the code controlling the actuator mechanism, which proved to be challenging. Incorrect timing caused the ultrasonic sensors to interfere with each other.  We needed a way to debug the trap while in the field - the Keysight 1000 X-Series low cost oscilloscope proved to be just the right tool. The 2-channel oscilloscope allows the signals from both sensors to be viewed simultaneously, enabling us to adjust the timing and ensure reliable operation.

We needed a way to debug in the field – the Keysight 1000 X-Series Oscilloscope proved to be just the right tool.

actuator circuitFigure 3:  Keysight EDUX1002A Oscilloscope being used to debug the actuator circuit.

 

 

 Setting up a trap in the field

Figure 4:  Quinton Martins, (Ecologist - in the cage!) and Neil Martin setting up the trap in the field (Picture by Jim Codington)

 

Mountain lions have very large territories, so patience is required when trapping these elusive animals.  After about two weeks, the waiting paid off, and we trapped our first mountain lion with this system, a female, and then caught a male 2 days later!

 

Trapped female mountain lion

Figure 5:  Trapped Female Mountain Lion

 

By Neil Martin 

 

More information about the ACR Mountain Lion project can be found here:

https://www.egret.org/acr-mountain-lion-project

 

 

Neil Martin is Keysight’s Corporate Marketing Director.  He used to be an R&D engineer and he can still remember a little engineering - which he makes use of in his spare time for volunteer projects.

mike1305

How Signal Modulation Works

Posted by mike1305 Employee Jun 20, 2017

Have you ever wondered how radio stations work? What about WiFi, or cell phones? These technologies (and countless others) all use modulation to send data at the same time, without interfering with each other! If electromagnetics wasn’t part of your college coursework, or you haven’t spent hours browsing Wikipedia, modulation of waveforms can be difficult to understand. To understand how wireless data transfer happens, we need knowledge of a handful of topics, which I plan to cover briefly in this blog post. For details, check out the full article.

 

Download the "6 Essentials for Getting the Most Out of Your Oscilloscope" eBook.

 

Sending a signal that is a pure sine wave is called a "tone". It carries no real information, and doesn't sound that great either.

 

Single Tone

Single tone (time domain)

 

How about a signal composed of many tones of varying frequencies? We can see the signal is too complex to understand in the time domain.

 

Multi-tone Signal

Multi-tone signal (time domain)

 

For complex signals, engineers use a different way of graphing a signal in the frequency domain by using something called a Fourier transform. Let's see what our three signals above look like in this representation (skipping to the solution). Instead of plotting a signal’s voltage in time, we are plotting the power of the signal by frequency.

 

Multi-tone Signal of 10 tones

Multi-tone signal (frequency domain) of 10 tones, of varying amplitude

 

Notice the clear spikes? That is the mathematical representation of a sine wave at that particular frequency (x-axis). The multi-tone signal that was unreadable in the time domain has been clearly chopped into small spikes, representing all the frequencies that were summed to create the signal. A final example would be to show an audio signal.

 

Audio Signal

Audio Signal

 

This is how the spectrum of most signals appear, especially analog ones. The human voice and instruments do not play as discreet frequencies, and thus there is frequency content over an entire range. In theory, we can represent this analog signal as the sum of an infinite number of tones added together. That’s a fun one to wrap your head around.

 

Modulation is what takes a signal from low frequencies (we call this the message) and pulls it up to a higher frequency (the carrier). The idea is simple: Multiply your message by a high frequency carrier, such as 680kHz. Let's look at a few mathematical relationships. In this case, theta is the message and phi is the carrier.

The nifty relationships above show us that two signals multiplied can be represented as two signals added together! What does an audio spectrum look like when it's been modulated? We basically shift the signal up and around the carrier frequency.

 

Modulation of a Sound Clip

Modulation of a sound clip to 700 kHz

 

Just as expected, we see two signals. One is carrier + message, one is carrier - message (even notice how it is reversed). We can change the carrier frequency (radio station) to transmit a second, different signal at the same time. This is basically how a transmitter works in a radio tower. Now let's talk about receivers. Fortunately, it’s easy to bring our audio signal back to "baseband" (near 0 Hz instead of the carrier). We simply multiply everything by the carrier again. More math!

 

equation for modulation

 

That's a bunch of cosines, parenthesis, and f's all over the place. But it's correct, and we see that there are four signals that result from it. fC is the carrier frequency, and fM is the message.

 

  • ¼ power signal, (2*carrier + message)
  • ¼ power signal, (message)
  • ¼ power signal, (2*carrier – message)
  • ¼ power signal, (-message)

 

Let’s immediately disregard the last term with a negative frequency. It is a mathematical artifact which occurs quite often when talking about modulation and the math involved, but isn’t really, well… real. The two signals at double the carrier (assuming the carrier is much larger than the message, they are almost the same) can be filtered out with a low pass filter, leaving us with the original message at 25% power. Here's a picture of it, but backwards. Using this process, we can now hear the audio message that was transmitted at the 700 kHz carrier!

 

 

In summary, the purpose of this post was to give a 30,000 foot view of how radio transmission and signal modulation works. By taking multiple audio (or baseband) signals and mathematically multiplying them by different higher frequencies (the carrier), we can successfully transmit multiple signals over the same channel (our atmosphere) without interference. Multiplying it by the carrier again brings the modulated signal back to baseband, and a low pass filter and amplifier clean up and magnify the signal for our listening pleasure! I highly recommend reading the full length article for more details, fun facts about the FCC, as well as more in depth examples of signals being modulated for better understanding.

 

 

Have you ever set up your oscilloscope without a proper trigger? If so, you probably experienced something a little bit like this:

 

In this case, I had an edge trigger and the level was set above my waveform.  The oscilloscope could not find any waveform data at that threshold and therefore, didn’t know what waveform data to display on screen.

When you have a trigger set up, the oscilloscope is looking at the acquisition data to see when your trigger conditions are met. If they are met, the oscilloscope will display the waveform data centered around the trigger event, thus stabilizing your display.  

Triggering

The easiest way to set up a quick trigger and stabilize your display is to hit Auto Scale.  That will take care of your vertical and horizontal scaling, and sets up the most common trigger type (Edge) at an appropriate level. This gets you straight to basic troubleshooting.

 

Below is a trigger diagram showing the conditions for Edge trigger:

Trigger Diagram

Figure 1- edge trigger diagram

 

But triggering isn’t just used to obtain a stable display. It can also help you find events in your waveform. And there are many different triggers to help you find many kinds of events – even the tricky, hard to find events like glitches, runts, patterns, and sequences.  Keysight’s Infiniium oscilloscopes provide both hardware and software triggers.  Hardware triggers are quick and address the most common use cases. They are looking for events happening in real-time acquisition data.  Software triggers are used when the event you want to trigger on is just too complex for hardware alone.  To perform a software trigger, first the oscilloscope triggers in hardware to acquire the waveform data.  Then analysis and event searching happens in software before the waveform is displayed for that trigger. Perhaps a more accurate name for software triggering is event identification software. 

 

Below, you’ll find a quick reference guide for all the hardware and software triggers available on Keysight’s Infiniium oscilloscopes.  This will help you understand what triggers are available and determine what triggers you want to use when.

Hardware Triggers:

Trigger Type

What it Does / When to Use

Edge

looks for slope and voltage level of the selected source - mostly used for general purpose viewing and trouble shooting

Glitch

looks for a pulse that is narrower than other pulses in your source - used to capture infrequent glitches

Pulse Width

looks for a pulse that is either wider or narrower than other pulses in your source based on the pulse width and polarity you set - used to capture pulses that are too short or too long in time

Pattern/State

looks for a user specified pattern - used when you want to find a specific pattern across analog and/or digital channels

Runt

looks for a pulse that is smaller in amplitude than other pulses with low and high thresholds - to find pulses that are too low in voltage

Setup and Hold

looks for violations of setup time, hold time, or both setup and hold time based on a reference clock waveform

Edge Transition

looks for edges that do not rise or fall across two voltage thresholds in the amount of time you specify - used to find violations in rise/fall time

Edge Then Edge

looks for the two events you specify delayed by the number of events or time you set

Timeout

looks for a pulse that is lasting too long either at a high or low level - to find potential timeout errors

Window

looks for an event of the waveform exiting, entering, or remaining outside a voltage range as specified to use when you want to view a waveform either within or without certain thresholds

Protocol

looks for certain packets or patterns in protocol-based data. (Hardware protocol is only available on some Keysight oscilloscopes, the S-Series being one of them, with others performing protocol trigger in software).

Sequence

any two of the above performed in sequence used when you want to capture the signal based on two trigger events

 

Software Triggers (Available with InfiniiScan N5414B):

Trigger Type

What it Does / When to Use

Measurement

After hardware triggering and the waveform data is acquired, the specified measurement is performed, and then if the measurement condition is met, the InfiniiScan trigger condition is set to true and the waveform is displayed on screen

Zone Qualifying

create up to 8 zones and combine them with logic expressions to set triggering conditions

Generic Serial

capture packets of customized protocols or generic patterns

Non-monotonic Edge

capture small glitches or edges that may be hidden by hysteresis

Runt

capture runts that they may be hidden by hysteresis

 

I’m hoping as you advance past Auto Scale and try out a couple of these triggers, you’ll be a wiz and won’t even need this lookup table!

 

So how do you set up these different triggers? Easy.  Here are the two simple steps:

  1. Choose the Trigger Menu, then select Setup
  2. Choose the trigger you want from the list on the left and set your desired conditions

Now you’re rockin’ and rollin’! You’re ready to find all sorts of different anomalies that could exist in your waveforms and find the root causes of your malfunctioning DUT faster.  

 

If you have any interesting test conditions in which you used one of these triggers, we’d love to hear about it in the comments. Happy Triggering!

Oscilloscope users are constantly reviewing the signals of their design in the “normal” time vs voltage display of the scope.  It is easy to overlook the FFT (Fast Fourier Analysis) view of the same signal. It is a completely different way of reviewing the signal characteristics that often reveals clues to some very difficult to solve problems. FFT can be an invaluable tool for identifying noise, crosstalk, and other common problem in many designs that can stall prototype development. In digital designs, it is often used to highlight and pinpoint the source by the frequency content on power rails.

FFT measurement with an input sine wave

By applying the FFT algorithms to the sampled data, you convert the time domain operation of the oscilloscope into a frequency view of the signal. This results in two primary benefits. One, you can easily identify each of the frequency components. Two, it reveals the magnitude of each contributing signal.

Identifying the frequency

By identifying the frequency components, it reveals if there are any signals on that are not expected. For example, a digital signal should only have frequencies that are harmonics of the base signal. If you have a 10 MHz data, there should be only frequencies at 10 MHz (the primary harmonic), 30 MHz (the third harmonic), 50 MHz (the fifth harmonic), and the continuing odd harmonics up to the bandwidth of the source.

Any other frequency is a result of noise, or crosstalk, or some type of coupling on to the signal.

Frequency components of 10MHz clock

Figure 1: In this capture of a 10 MHz clock, we can easily identify the frequency components related to the fundamental frequency, but we can also see a 20 MHz signal that is -55 dB from the fundamental.

 

It’s important to understand how the oscilloscope sampling characteristics play into the quality of this FFT measurement. The oscilloscope analog bandwidth, sample rate, memory depth, and related time capture period all can have a profound effect on the measurement result. The math that is utilized for the calculation is using the data that was sampled at 5 GSa/sec, and it makes it possible to calculate a 10 GHz FFT. However, the front end of this scope is 1 GHz, so the FFT is only valid up to the bandwidth of the oscilloscope.

Identifying the Magnitude

The other key component of the signal is the power of each signal component. When looking at a signal in the time domain, it is only possible to see the very large signal power components. In the spectrum view (or FFT display) the horizontal axis is changed from a linear voltage scale to a logarithmic voltage scale (or dB for decibel).

The display on the right side of the display is listing the power level in dBV (decibel volts, or power relative to 1volt) of each frequency in order with the respective power level.  The first, or fundamental frequency of our signal is at just less than 10 MHz, and a power level of -13.9775 dBV, which is about 200mV rms. Looking at the time display of the signal (in green), you can see that it looks about right. We can also see that the next highest power signal is at 30 MHz and a power level of -30dBV, or about 3 mVrms-- something that cannot be seen in the time display that we are used to looking at.

FFT is just a button away

On Keysight oscilloscopes, the FFT operation is often enabled by simply pressing a button on the front panel. The new 1000X low cost oscilloscopes include this feature standard. The FFT view is a great way to examine a signal to find the frequency and power that you could not normally see any other way. Make sure to take advantage of this powerful tool that next time you are trying to find elusive signals in your design.

Learn other time-saving tips to get more out of your oscilloscope with this new eBook!