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Time vs Freq Domain

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    Time vs. FrequencySeptember 21, 1999

    Ron Denton

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    What is the Time Domain ?

    How is the Time Domain Measured ? What is the Frequency Domain ?

    How is the Frequency Domain Measured ?

    What does this have to do with Vibration ? How are the two domains related ?

    Time Domain vs. Frequency Domain

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    The Time Domain (for our use) is . . .

    A graphical representation of the change of some valuewith respect to time

    Time moving forward ------>

    V a l u e o

    f s o m e

    v a r i a

    b l e

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    How the Time Domain is Measured

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    The Frequency Domain(for our use) is . . . .

    A graphical representation of the amount of energy presentin a signal at each of many frequencies

    Frequency increasing ----->

    A m p

    l i t u

    d e

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    The Frequency Domain amplitude isusually measured in RMS or Peak

    The frequency domain values are really just a series ofsinusoidal equivalents, so amplitudes are usuallyrepresented the same as in the time domain.

    The frequency domain is usually derived by computing aFast Fourier Transform (FFT) of a time domain signal.

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    What does this have to do withVibration ?

    Transducers, such as accelerometers, convert mechanicalenergy into electrical signals

    The electrical signals are measured with various devices

    Most of these devices record the time data

    The time data is converted to the frequency domain withinthese devices

    Vibration analysts use the time and frequency domain datato interpret machinery condition

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    The Time and Frequency Domainsare related by . . . .

    A m p

    l i t u d e

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    Sinusoidal Signal ExamplesMultiple Sine Waves

    Time

    A m p

    l i t u

    d e 1 cycle

    2 cycle4 cycle8 cycle

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    Sinusoidal Signal ExamplesComplex

    Time

    A m p

    l i t u

    d e

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    Sinusoidal Signal ExamplesComplex Frequency

    0

    0.2

    0.4

    0.6

    0.8

    1

    1.2

    0 0 .

    4 0 .

    8 1 .

    2 1 .

    6 2 2 .

    4 2 .

    8 3 .

    2 3 .

    6 4 4 .

    4 4 . 8

    5 . 2

    5 . 6 6

    6 . 4

    6 . 8

    7 . 2

    7 . 6 8

    8 . 4

    8 . 8

    9 . 2

    9 . 6 1 0

    Frequency

    A m p

    l i t u

    d e

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    Sinusoidal Signal ExamplesSquare from Sines

    Time

    A m p

    l i t u

    d e

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    Sinusoidal Signal Examples"SQUARE" WAVE

    Time

    A m p

    l i t u

    d e

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    Sinusoidal Signal Examples

    "Square" Wave

    0 0 .

    8 1 .

    6 2 .

    4 3 .

    2 4 4 . 8

    5 . 6

    6 . 4

    7 . 2 8

    8 . 8

    9 . 6

    Frequency

    A m p

    l i t u

    d e

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    These examples illustrate that . . .

    The time and frequency domains are related

    A sinusoid in the time domain has a unique value in thefrequency domain

    Complex combinations of time domain sinusoids can beseparated and displayed in the frequency domain

    Signals other than sinusoids can be represented in thefrequency domain accurately

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    A practical example to wrap up

    A customer is using an accelerometer to measuresinusoidal vibration . . . . .

    You receive a phone call . . . . .

    Your accelerometer is all out of whack! I have a simplesignal and your accelerometer is generating all kinds ofharmonics.

    You look around and cant find an application engineer . . .

    (Panic grips you !) What do you do ?

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    A practical example to wrap up

    Tell them to check the gain range (amplifier setting) ontheir equipment !

    Their time domain signal probably looks like this . . .

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    A practical example to wrap up

    If the amplifier range of themeasuring system is not setcorrectly, it will clip the signaland chop off the highest andlowest parts of the signal.

    This is not good !

    It means you are trying to turn asine wave into a square wave.

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    Clipping Time signals will cause apenalty and cost you data

    Just as clipping isillegal in football -

    in data acquisition,clipping the timedata will cost you

    by causing invalid

    data (spurioussignals) in thefrequencyspectrum.

    Clipped vs. Original

    0

    0.2

    0.4

    0.6

    0.8

    1

    1.2

    0 0

    . 3 0

    . 6 0

    . 9 1

    . 2 1

    . 5 1

    . 8 2

    . 1 2

    . 4 2

    . 7 3 3

    . 3 3

    . 6 3

    . 9 4

    . 2 4

    . 5 4

    . 8 5

    . 1 5

    . 4 5

    . 7 6 6

    . 3 6

    . 6 6

    . 9 7

    . 2 7

    . 5 7

    . 8 8

    . 1 8

    . 4 8

    . 7 9 9

    . 3 9

    . 6 9

    . 9

    Frequency

    A m p l i t u d e

    Original SignalAttenuated Signal

    Spurious Signals Added

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    The moral of the example ?

    Dont be a square !

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    Questions ?