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1st harmonic = 12 kHz

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2nd harmonic = 24 kHz

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3rd harmonic = 36 kHz

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4th harmonic = 48 kHz

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5th harmonic = 60 kHz

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6th harmonic = 72 kHz

Notes:
Ask your students to determine the mathematical relationship between harmonic number, harmonic frequency, and fundamental frequency. It isn't difficult to figure out!

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Though it may seem strange to speak of it in such terms, an AC circuit "views" a square wave as an infinite series of sinusoidal harmonics.
Follow-up question: explain how this equivalence between a square wave and a particular series of sine waves is a practical example of the Superposition Theorem at work.

Notes:
If you have access to a graphing calculator or a computer with graphing software installed, and a projector capable of showing the resulting graph(s), you may demonstrate this square-wave synthesis in front of the whole class. It makes an excellent illustration of the concept.
Discuss this with your students: that the relatively simple rules of AC circuit analysis (calculating reactance by wL and [1/(wC)], calculating impedance by the trigonometric sum of reactance and resistance, etc.) can be applied to the analysis of a square wave's effects if we repeat that analysis for every harmonic component of the wave.
This is truly a remarkable principle, that the effects of a complex waveform on a circuit may be determined by considering each of that waveform's harmonics separately, then those effects added together (superimposed) just as the harmonics themselves are superimposed to form the complex wave. Explain to your students how this superposition principle is not limited to the analysis of square waves, either. Any complex waveform whose harmonic constituents are known may be analyzed in this fashion.

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"Any periodic waveform, no matter how complex, is equivalent to a series of sinusoidal waveforms added together at different amplitudes and different frequencies, plus a DC component."

Follow-up question: what does this equation represent?

f(t) = A0 + (A1 sinwt) + (B1 coswt) + (A2 sin2 wt) + (B2 cos2 wt) + ...

Notes:
So far, all the "tools" students have learned about reactance, impedance, Ohm's Law, and such in AC circuits assume sinusoidal waveforms. Being able to equate any non-sinusoidal waveform to a series of sinusoidal waveforms allows us to apply these ßinusoidal-only" tools to any waveform, theoretically.
An important caveat of Fourier's theorem is that the waveform in question must be periodic. That is, it must repeat itself on some fixed period of time. Non-repetitive waveforms do not reduce to a definite series of sinusoidal terms. Fortunately for us, a great many waveforms encountered in electronic circuits are periodic and therefore may be represented by, and analyzed in terms of, definite Fourier series.
It would be good to mention the so-called FFT algorithm in this discussion while you're on this topic: the digital algorithm that computers use to separate any sampled waveform into multiple constituent sinusoidal frequencies. Modern computer hardware is able to easily implement the FFT algorithm, and it finds extensive use in analytical and test equipment.

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A spectrum analyzer.
Challenge questions: two similar instruments are the wave analyzer and the Fourier analyzer. Explain how both these instruments are similar in function to a spectrum analyzer, and also how both differ.

Notes:
Spectrum analyzers capable of analyzing radio-frequency signals are very expensive, but low-cost personal computer hardware and software does a good job of analyzing complex audio signals. It would be a benefit to your class to have a low-frequency spectrum analyzer setup available for student use, and possible demonstration during discussion.

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The input signal is clean: a single peak at the 1 kHz mark. The amplifier's output, on the other hand, is a bit distorted (i.e. no longer a perfect sine-wave shape as the input is).

Notes:
The purpose of this question is to get students to realize the presence of harmonics means a departure from a once-perfect sinusoidal wave-shape. What used to be free of harmonics now contains harmonics, and this indicates distortion of the sine wave somewhere within the amplifier.
By the way, the perfectly flat "noise floor" at -120 dB is highly unusual. There will always be a "rough" floor shown on the display of a spectrum analyzer, but this is not pertinent to the question at hand so I omitted it for simplicity's sake.

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Any feature (or fault) of the circuit causing imperfect signal reproduction will necessarily create harmonics, for it will turn a perfectly sinusoidal input signal into a distorted (non-perfect-sinusoidal) signal.

Notes:
Discuss with your students the nature of harmonics: how multiple sinusoidal waveforms are necessarily contained in any periodic waveform that is not perfectly sinusoidal itself.

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Any feature (or fault) of the amplifier portion of the oscillator circuit causing imperfect signal reproduction will necessarily create harmonics, for it will turn a perfectly sinusoidal input signal (from the LC network) into a distorted (non-perfect-sinusoidal) output signal.
Challenge question: Colpitts oscillators tend to produce "purer" sine-wave outputs than Hartley oscillators, all other factors being equal. Explain why.

Notes:
Discuss with your students the nature of harmonics: how multiple sinusoidal waveforms are necessarily contained in any periodic waveform that is not perfectly sinusoidal itself.

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The LP filter blocks all harmonics of the square wave except the fundamental (1st harmonic), resulting in a sinusoidal output.

Notes:
Ask your students what they think about the rolloff requirement for this LP filter. Will any LP filter work, or do we need something special?

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Nonlinear loads.

Notes:
My answer to this question is intentionally vague. It is correct, but does not reveal anything about the real nature of the cause, or more importantly, why a "nonlinear" load would cause harmonics. Discuss with your students what a "nonlinear" device is, and what it does to a sinusoidal signal to generate harmonics.

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Each series LC section is a resonant band-pass filter, tuned to successive harmonics of a 60 Hz sine wave. The selector switch enables a single voltmeter to measure the RMS amplitude of each harmonic.
Follow-up question: calculate the exact inductance values necessary for precise tuning of the five LC filters, for the first five harmonics of a 60 Hz waveform.
Challenge question: the voltmeter in this circuit would not have to be a true-RMS meter. It could simply be an average-responding (RMS-calibrated) voltmeter and it would work the same. Explain why.

Notes:
This question provides students with some review of passive filter circuit theory, as well as insight into a practical circuit they could conceivably build as a project.
A very important design feature of this circuit is the narrow bandwidth of each harmonic "channel." The filter pass-bands must not come close to overlapping, or else the meter response will not be exclusively indicative of the harmonic it is switched to. High Q values for each filter section ensure that the meter will only register the particular harmonic that is selected for measurement.

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1st harmonic = 60 Hz

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2nd harmonic = 120 Hz

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3rd harmonic = 180 Hz

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4th harmonic = 240 Hz

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5th harmonic = 300 Hz

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6th harmonic = 360 Hz

Notes:
Ask your students to determine the mathematical relationship between harmonic number, harmonic frequency, and fundamental frequency. It isn't difficult to figure out!

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1 octave greater than the fundamental = 2 kHz

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2 octaves greater than the fundamental = 4 kHz

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3 octaves greater than the fundamental = 8 kHz

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4 octaves greater than the fundamental = 16 kHz

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5 octaves greater than the fundamental = 32 kHz

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6 octaves greater than the fundamental = 64 kHz

Notes:
Ask your students if they can determine the mathematical relationship between octave number, octave frequency, and fundamental frequency. This is a bit more difficult to do than for integer harmonics, but not beyond reason if students are familiar with exponents.
Clarify for your students the fact that öctave" is not just a musical term. In electronic circuit analysis (especially filter circuits), the word öctave" is often used to represent multiples of a given frequency, usually in reference to a bandwidth (i.e. "This filter's passband response is essentially flat over two octaves!").

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Notes:
To be honest, the four-harmonic equivalent circuit is a rather poor approximation for a square wave. The real purpose of this question, though, is to have students relate the sinusoidal terms of a common Fourier series (for a square wave) to a schematic diagram, translating between angular velocity and frequency, peak values and RMS values.
Please note that the voltage magnitudes shown in the answer are RMS and not peak! If you were to calculate peak sinusoid source values, you would obtain these results:

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1st harmonic: [40/(p)] volts peak = 12.73 volts peak

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3rd harmonic: [40/(3 p)] volts peak = 4.244 volts peak

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5th harmonic: [40/(5 p)] volts peak = 2.546 volts peak

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7th harmonic: [40/(7 p)] volts peak = 1.819 volts peak

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Notes:
The purpose of this question is to have students relate the sinusoidal terms of a particular Fourier series to a schematic diagram, translating between angular velocity and frequency, peak values and RMS values.

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P_R = 400 watts

Notes:
To calculate this power figure, students have to determine the RMS value of the square wave. Thankfully, this is not difficult.

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P_R(1st) = 1.541 watts
P_R(3rd) = 1.485 watts
P_R(5th) = 1.384 watts
P_R(7th) = 1.255 watts
P_R(1+3+5+7) = 5.665 watts

Notes:
To calculate this power figure, students have to research the Fourier series for a square wave. Many textbooks use square waves to introduce the subject of Fourier series, so this should not be difficult for students to find.
Ask your students how the real power dissipated by this resistor compares with the final figure of 5.665 watts. Is the real power dissipation more, less, or equal to this figure? If not equal, what would we have to do to arrive at a more precise figure?

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I'll let you figure out the answer to this question on your own.

Notes:
The purpose of this question is to get students to think about how a spectrum analyzer would be used in a practical scenario, and what the spectrum would look like for a couple of different scenarios. Really, it focuses more on the harmonic analysis instrument (the spectrum analyzer) more than the oscillator circuit.

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What this pattern means is the power-line voltage waveform is distorted from what should be a perfect sine-wave shape.

Notes:
Note to your students that this is quite typical for modern power systems, due to the prevalence of switching power supply circuits and other "non-linear" electrical loads. The presence of harmonic frequencies in significant quantity can cause severe problems for power systems, including transformer overheating, motor overheating, overloaded neutral conductors (especially in three-phase, four-wire "Wye" systems), and excessive currents through power-factor correction capacitors.

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A pure sine wave is input to the amplifier under test, and a spectrum analyzer is connected to the amplifier's output.

Notes:
The answer given is purposefully vague. All I did is describe what gets connected to the amplifier, not how to interpret the measurements. Ask your students to explain why a pure sine wave is chosen as the test signal, and what sort of response would be considered ideal to see on the spectrum analyzer.

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I'll answer this question with another question: is the "B-H" plot for a ferromagnetic material typically linear or nonlinear? This is the key to understanding how an electromagnetic device can produce harmonics from a "pure" sinusoidal power source.

Notes:
Ask your students what it means for an electrical or electronic device to be "linear." How many devices qualify as linear? And of those devices, are they always linear, or are they capable of nonlinear behavior under special conditions?
Use the discussion time to review B-H curves for ferromagnetic materials with your students, asking them to draw the curves and point out where along those curves inductors and transformers normally operate. What conditions, specifically, would make an iron-core device act nonlinearly?
On a similar note, the (slightly) nonlinear nature of ferromagnetic core transformers is known to permit signals to modulate each other in certain audio amplifier designs, to produce a specific kind of audio signal distortion known as intermodulation distortion. Normally, modulation is a function possible only in nonlinear systems, so the fact that modulation occurs in a transformer is proof positive of (at least some degree of) nonlinearity.

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Filter circuits may be employed to block harmonic frequencies from reaching certain sensitive components.

Notes:
The answer given here is correct, but vague. I did not specify the type of filter or exactly how it might be connected to a load. These are questions to ask your students during discussion.

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The differentiator circuit will output a much more distorted waveshape, because differentiation magnifies harmonics:

d dt ( sint ) = cost

d dt ( sin2t ) = 2 cos2t

d dt ( sin3t ) = 3 cos3t

d dt ( sin4t ) = 4 cos4t

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d dt ( sinnt ) = n cosnt

Notes:
As an interesting footnote, this is precisely why differentiation is rarely performed on real-world signals. Since the frequency of noise often exceeds the frequency of the signal, differentiating a "noisy" signal will only lead to a decreased signal-to-noise ratio.
For a practical example of this, tell your students about vibration measurement, where it is more common to calculate velocity based on time-integration of an acceleration signal than it is to calculate acceleration based on time-differentiation of a velocity signal.

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The addition of an even harmonic introduces asymmetry about the horizontal axis. The addition of odd harmonics does not.
Challenge question: explain why this is the case, any way you can.

Notes:
Although the sequence of images presented in the question by no means constitutes a formal proof, it should lead students to observe a trend: that odd harmonics do not make a waveform unsymmetrical about the horizontal axis, whereas even harmonics do. Given these two facts, we may make qualitative judgments about the harmonic content of a waveform simply by visually checking for symmetry about the horizontal axis.
Incidentally, some students have a difficult time grasping the concept of symmetry about the horizontal axis of a waveform. Take this simple example, which is symmetrical about its horizontal centerline:

Some students will protest that this waveform is not symmetrical about its centerline, because it does not look exactly the same as before after flipping. They must bear in mind, though, that this is just one cycle of a continuous waveform. In reality, the waveform looks like this before and after flipping:


All one needs to do to see that these two waveforms are indeed identical is to do a 180 degree phase shift (shifting either to the left or to the right):


By contrast, a waveform without symmetry about the horizontal axis cannot be made to look the same after flipping, no matter what subsequent phase shift is given to it:


Another way to describe this asymmetry is in terms of the waveform's departure from the centerline, compared to its return to the centerline. Is the rate-of-change ([dv/dt] for a voltage waveform) equal in magnitude and opposite in sign at each of these points, or is there a difference in magnitude as well? Discuss ways to identify this type of asymmetry, and what it means in terms of harmonic content.
Mathematically, this symmetry is defined as such:

f(t) = -f � � t + T 2 � �

Where,
f(t) = Function of waveform with time as the independent variable
t = Time
T = Period of waveform, in same units of time as t

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Nonlinear loads are usually (but not always!) symmetrical in their distortion.

Notes:
I've had electrical power system experts confidently tell me that even-numbered harmonics cannot exist in AC power systems, due to some deep mathematical principle mysteriously beyond their ability to describe or explain. Rubbish! Even-numbered harmonics can and do appear in AC power systems, although they are typically much lower in amplitude than the odd-numbered harmonics due to the nature of most nonlinear loads.
If you ever wish to prove the existence of even-numbered harmonics in a power system, all you have to do is analyze the input current waveform of a half-wave rectifier!

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The following waveforms contain even-numbered harmonics: B, C, D, F, and I. The rest only contain odd harmonics of the fundamental.

Notes:
Ask your students how they were able to discern the presence of even-numbered harmonics by visual inspection. This typically proves difficult for some of my students whose spatial-relations skills are weak. These students need some sort of algorithmic (step-by-step) procedure to see what other students see immediately, and discussion time is a great opportunity for students to share technique.
Mathematically, this symmetry is defined as such:

f(t) = -f � � t + T 2 � �

Where,
f(t) = Function of waveform with time as the independent variable
t = Time
T = Period of waveform, in same units of time as t

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The following waveforms contain even-numbered harmonics: C, D, G, and I. The rest only contain odd harmonics of the fundamental.

Notes:
Ask your students how they were able to discern the presence of even-numbered harmonics by visual inspection. This typically proves difficult for some of my students whose spatial-relations skills are weak. These students need some sort of algorithmic (step-by-step) procedure to see what other students see immediately, and discussion time is a great opportunity for students to share technique.
Mathematically, this symmetry is defined as such:

f(t) = -f � � t + T 2 � �

Where,
f(t) = Function of waveform with time as the independent variable
t = Time
T = Period of waveform, in same units of time as t

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If the signal source is pure (no harmonics), the voltmeter will register nothing (negative infinite decibels) when the switch is flipped to the "test" position.

Notes:
This test circuit relies on the assumption that the notch filter is perfect (i.e. that its attenuation in the stop-band is complete). Since no filter is perfect, it would be a good idea to ask your students what effect they think an imperfect notch filter would have on the validity of the test. In other words, what will a notch filter that lets a little bit of the fundamental frequency through do to the "test" measurement?

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"Sidebands" are sinusoidal frequencies just above and just below the carrier frequency, produced as a result of the modulation process. On a spectrum analyzer, they show up as peaks to either side of the main (carrier) peak. Their quantity, frequencies, and amplitudes are all a function of the data signals modulating the carrier.

Notes:
Be sure to ask your students what ÄM" and "FM" mean, before they present their answers on sidebands.
The answer makes frequent use of the word carrier without defining it. This is another intentional ömission" designed to make students do their research. If they have taken the time to find information on sidebands, they will surely discover what the word "carrier" means. Ask them to define this word, in addition to their description of sidebands.

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The ßuperposition principle" states that when two or more waveforms mix together in a linear network, the result is the sum of the waveforms. That is, the waveforms simply add up to make a total, and are not ïrrevocably affected" by one another. The question, then, is really: what constitutes a linear network?

Notes:
It is no coincidence that the ßuperposition principle" sounds a lot like the ßuperposition theorem" learned as a network analysis technique: consider the effects of all power sources one at a time, and add those effects together to determine the final result.
The matter of ïrrevocable influence" is important to us because it dictates how difficult it would be to separate the mixed signals from each other. When external noise couples to a circuit through capacitive or inductive coupling, can we filter out the noise and obtain the true signal again, or has the signal been corrupted in such a way that restoration is impossible by mere filtering? The key to answering this question is whether or not the "network" formed from parasitic capacitive/inductive coupling is linear. Discuss with your students what determines linearity in a math equation, and apply these criteria to the equations describing resistor, capacitor, and inductor behavior.

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A chord is a mixture of three of more notes. On an oscilloscope, it would appear to be a very complex waveform, very non-sinusoidal.
Note: if you want to see this form yourself without going through the trouble of setting up a musical keyboard (or piano) and oscilloscope, you may simulate it using a graphing calculator or computer program. Simply graph the sum of three waveforms with the following frequencies:

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261.63 Hz (middle "C")

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329.63 Hz (Ë")

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392.00 Hz ("G")

Notes:
Students with a musical background (especially piano) should be able to add substantially to the discussion on this question. The important concept to discuss here is that multiple frequencies of any signal form (AC voltage, current, sound waves, light waves, etc.) are able to exist simultaneously along the same signal path without interference.

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The circuit could be analyzed one harmonic at a time, the results combined via the Superposition Theorem:

Notes:
At first, some students have trouble understanding exactly how Fourier analysis is helpful in any practical way as an analytical tool. The purpose of this question is to have them see how it might be applied to something they are familiar with: an LR circuit.

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