This video (by request) gives an overview of how to the FFT Math function on the Tektronix TDS2000 series oscilloscope. (same applies to the TDS1000). A brief review of FFT fundamentals is given, followed by a demonstration of using the FFT function and controls, ending with a description of the mathematical relationships between the scope settings and the FFT results. More modern scopes will have different (easier to use) controls for the FFT than this 12+ yr old scope, but it is instructive to understand the operation of this feature.
Basics of using FFT on a Tektronix TDS2000 oscilloscope – [Link]
by mjlorton @ youtube.com
In this video I explain how a spectrum analyser (Tektronix MDO3000) can be used to view signals in the frequency domain vs an oscilloscope’s time domain.
I give an overview of the logarithmic scale and its benefits vs a linear scale.
I explain how compound wave forms like square and triangle are made up of harmonics.
I do a practical demonstration of how the spectrum analyser works with some example signals. I then show how this can also be done on an oscilloscope using the FFT (fast Fourier transform) maths function.
Spectrum Analyzer, Scope and FFT looking at Signals – [Link]
by Arthur Pini @ edn.com:
Modern mid-range oscilloscopes have more features than most engineers ever use. This article summarizes ten oscilloscope applications that may surprise you. In any event, you may find them useful.
Use the oscilloscope’s fast edge feature and math operations to make frequency response measurements
Frequency response measurements require a source signal that has a flat spectrum. By utilizing the fast edge test signal of the oscilloscope as a step source it is possible to derive the impulse response of the device under test using the scopes derivative function. This can then be applied to the FFT (Fast Fourier Transform) function to obtain the frequency response. Figure 1 shows the steps in the process for both the frequency response of the input signal and that of a 37 MHz low pass filter.
10 tricks that extend oscilloscope usefulness – [Link]
This project is an accelerometer data acquisition system for automotive suspension analysis. In other words it’s a low frequency spectrum analyzer based on Lanchpad TIVA Series from Texas Semiconductors. It’ s a spectrum analyzer for mechanical frequencies (max. 50 Hz). In my application I use this analyzer for the signals from a suspension of a car, that contain information about comfort (ride) of a vehicle.
Low Frequency Spectrum Analyzer for Automotive Suspension Analysis – [Link]
New PC adapters offer unprecedented memory size with built-in signal generators
Fairport, NY, USA: Saelig Company, Inc. (www.saelig.com) has introduced the new PicoScope 6000 Series high-performance 4-channel PC oscilloscopes with deep buffer memory and a USB 3.0 SuperSpeed interface. With up to 500 MHz bandwidth on all four channels, and an industry-leading 2 Gsamples of buffer memory, the PS6000 Series has the performance and the advanced analysis capability to speed the debug of todayʼs complex electronic designs. With a real-time sampling rate of up to 5GSa/s, the PicoScope 6000 Series oscilloscopes can display single-shot pulses with 200ps time resolution. Equivalent time sampling (ETS) mode boosts the maximum sampling rate to 50GSa/s, giving an even finer timing resolution of 20ps for repetitive signals.
Each model includes a built-in DC to 20MHz function generator with sine, square, triangle and DC waveforms. Some models also add a built-in 12-bit, 200MSa/s arbitrary waveform generator. PC software features include advanced triggering, automatic measurements with statistics, an FFT spectrum analysis mode, comprehensive waveform math, mask limit testing, and serial decoding for popular serial protocols such as I2C, SPI, UART, CAN, LIN and FlexRay. Another useful feature of the free PicoSoft software is the capability for scaling or modifying the input voltage displayed with a mathematical formula – to correct for gain, attenuation, offsets and non-linearities of probes and transducers, or convert to different measurement units.
Saelig Announces Deepest Memory High Performance PC Oscilloscopes – [Link]
SimpleAVR over at the 430h forum shows off his Educational BoosterPack 8 bit FFT Spectrum Analyzer project:
SimpleAVR comes up with unique Launchpad projects. These include his wire clock and spectrum analyzer projects. This time he wired the CircuitCo Educational BoosterPack to a Launchpad to sample audio and have the LCD display a spectrum.
Educational BoosterPack 8 bit FFT spectrum analyzer – [Link]
Saelig Company, Inc. announces the SDS5032E – a new, low-cost two-channel oscilloscope which is packed with useful features normally only seen on higher-end DSOs, including external and video-capable triggering, auto-measurements, auto-scaling, a large 8″ high resolution full color LCD display, XY mode, auto-set, averaging, math functions, USB output, waveform storage, pass/fail output, and a 3-year warranty. FFT functionality is included for frequency spectrum display, in addition to a built-in 6-digit frequency meter, which can measure frequencies from 2Hz to 30MHz.
SDS5032E 30MHz 250MS/s 2-Ch Oscilloscope – [Link]
Andrew built a DIY GPS receiver with an accuracy of ~25m – [via]
A homemade GPS receiver built from the ground up using discrete components and featuring a limiting IF, followed by 1-bit ADC ahead of DSP signal processing in a Xilinx Spartan 3 FPGA. Fast FFT-based search and navigational solutions are computed by “C” code on a Windows PC
Homemade GPS receiver – [Link]
The Fourier transform is a method for representing an irregular signal as a combination of weighted sine waves or ‘frequencies’. To calculate it quickly the Fast Fourier Transform (FFT) was devised some 50 years ago and ever since people have been searching for methods to make it even faster. At MIT a group of researchers has now developed an algorithm that, in a large range of practically important cases, achieves an up to a tenfold speed increase.
Signals whose Fourier transforms contain a relatively small number of strong frequencies are called ‘sparse’. In nature, most of the normal signals are sparse. The new algorithm determines the weights of the strongest frequency components contained in a signal; the sparser the signal, the greater the speedup the algorithm provides. Indeed, if the signal is sparse enough, the algorithm can simply sample it randomly rather than reading it in its entirety. [via]
EFFT – the Even Faster Fourier Transform – [Link]
The purpose of this project is to make an audio visualizer to demonstrate the use of the Nokia 3310 LCD as a graphical display. By audio visualizer, I mean the visualization like Winamp, XMMS, or Windows Media player. This project utilizes a fixed point FFT (fast fourier transform) algorithm to convert the discrete audio samples in time into frequency. This allows us to graph bars for each frequency as the music is playing. In other words, different bars dance around for the bass, midrange, treble, and all the points in between.
Audio Visualization with Nokia 3310 LCD and FFT – [Link]