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Basics of FFT Signal Analysis

Crystal Instruments Webinar Series

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CI Webinar Schedule

Date Topic

August 18 Basic FFT setup

September 15 Routes for data measurement

October 20 Impact testingNovember 17 Sound Level Measurements

December 15 Order Tracking

See www.go-ci.com/webinars.html for up-to-date schedule

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Basics of FFT Signal Analysis

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FFT Line Response

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FFT Line Response

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Leakage

Frequency centered on FFT line Frequency between FFT lines

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Windowing Functions

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Force and Exponential Windows

Force window: excitation Exponential window: response

Pictures courtesy of University of Massachusetts, Lowell

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Analysis Parameters

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Resolution and Range

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Resolution and Range

Frequency Lines

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Resolution and Range

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Spectrum Type and Scaling

FFT returns complex-valuedamplitudes

Real part represents cosine components,

imaginary part represents sine components

(90 phase difference)

Can be converted to magnitude andphase

Squared magnitude represents signal power

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Spectrum Types

Spectrum Types:

Magnitude: Amplitude Spectrum

Squared magnitude: Power Spectrum

Squared magnitude per unit bandwidth: Power

Spectral Density

Squared magnitude block time length: Energy

Spectrum Squared magnitude block length per unit

bandwidth: Energy Spectral Density

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Spectrum Types

Periodic signals (discrete frequencies):

Amplitude or Power Spectrum

Broadband random signals: Power Spectral

Density

Transient Signals: Energy Spectral Density

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Amplitude Spectrum Scaling

From Wikipedia:

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Averaging

Combine multiple time blocks together to

form one spectral estimate

Random data: higher average number, better

estimate of random characteristics

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Averaging Types

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Averaging Methods

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Averaging

FFT

Average

(Linear/

Exponential/

Peak Hold

|| ||2

Average

(Linear/

Exponential/

Peak Hold

Time SignalData

Complex

FrequencyData

Sx

Magnitude-squared

Frequency Data

Sxx

Linear Spectrum

Average

Gx

Power Spectrum

Average

Gxx

In CoCo: Linear Spectrum:

Time Linear

Time Exponential

Power Spectrum: Linear

Exponential

Peak-Hold

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Overlap Processing

A proportion of each time frame can be reused in

subsequent frames

Faster updating

Better averaging in same time period, only up to 50%

Graphic from Understanding FFT Overlap Processing, Tektronix Corporation

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CoCo Operation

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CSAs

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Windows and Traces

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Signal Display

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Param. Menu

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Analysis Parameters

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Display Parameters

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dB, Mag, Log

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Brought to you by the Crystal Instruments Team

James Zhuge, President

Tim Hsiao

John Holler

Darren Fraser

Justin Tang

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Andrew Snyder

Mike Mu

Crystal Instruments Corporation4699 Old Ironsides Dr., Ste. 100

Santa Clara, CA 95054, USA

Phone: 408-986-8880

Visit us online at http://www.go-ci.com