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SR770 – FFT Spectrum Analyzer – thinkSRS.com
The SR770 is a single-channel 100 kHz FFT spectrum analyzer with a dynamic range of 90 dB and a real-time bandwth of 100 kHz. Additionally, it includes a low- …
Source: www.thinksrs.com
Date Published: 12/28/2022
View: 9921
Model SR770 – FFT Network Analyzer
User’s Manual. Model SR770. FFT Network Analyzer. 1290-D Reamwood Avenue. Sunnyvale, California 94089. Phone: (408) 744-9040 • Fax: (408) 744-9049.
Source: research.physics.illinois.edu
Date Published: 9/21/2021
View: 3741
Stanford Research SR770 FFT Spectrum Analyzer, 476 µHz to …
The SR770 is a single channel, 100 kHz FFT Spectrum Analyzer with a dynamic range of 90 dB and a real-time bandwth of 100 kHz. The speed and dynamic range of …
Source: www.bellnw.com
Date Published: 1/15/2021
View: 1242
Stanford Research Systems SR770 FFT Spectrum Analyzer SRS
BRIGHT CRT! Fully Tested! Stanford Research SR760 FFT Spectrum Analyzer. Spans: 191 MHz to 100 kHz in a binary sequence. Display: real, imaginary, magnitude …
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Date Published: 5/20/2021
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STANFORD RESEARCH SR770 Datasheet
GPIB and RS-232 interfaces. The SR770 is a single-channel 100 kHz FFT spectrum analyzers with a dynamic range of 90 dB and a real-time bandwth of 100 kHz.
Source: www.testequipmenthq.com
Date Published: 5/21/2021
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Stanford Research Systems SR770 FFT Network Analyzer
The Stanford Research Systems SR770 is a single-channel 100 kHz FFT spectrum analyzer with a dynamic range of 90 dB and a real-time bandwth of 100 kHz.
Source: www.artisantg.com
Date Published: 11/24/2022
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Electrical network analyzer – Stanford Research Systems
Description. SR770 FFT Analyzer The SR770 is a single-channel 100 kHz FFT spectrum analyzer with a dynamic range of 90 dB and a real …
Source: www.directindustry.com
Date Published: 5/9/2022
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SR 770 Spectrum/Network Analyzer – Physics 122
The Stanford Research Systems SR770 FFT (Fast Fourier Transform) Spectrum Analyzer takes a time varying input signal, like you would see on an oscilloscope …
Source: 122.physics.ucdavis.edu
Date Published: 5/26/2022
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Stanford SR770 FFT spectrum analyzer (476 µHz – 100 kHz)
Distributor of Stanford SR770 FFT spectrum analyzer (476 µHz – 100 kHz) BKPRECISION, TTI, Stanford, OMICRON, Lisun, SIGLENT, PROTEK, YOKOGAWA, AARONIA, …
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Date Published: 8/21/2022
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What does an FFT analyzer do?
The FFT spectrum analyzer samples the input signal, computes the magnitude of its sine and cosine components, and displays the spectrum of these measured frequency components.
What is the difference between FFT and spectrum analyzer?
Spectrum Analyzers measure Spectral Density and Digital SA’s use FFT to calculate the spectrum whereas RF SA’s use dual or triple conversion swept scanning like a TV tuner but with very precise preamps, filters and Log converters since measurements are more convenient to display a wide dynamic range such as 100 dB.
Does a spectrum analyzer use FFT?
In many instances superheterodyne and FFT techniques are used in single spectrum analyzer. This enables the best of both techniques to be adopted to provide a truly versatile and high performance test instrument.
What is the difference between signal analyzer and spectrum analyzer?
While the terms spectrum analyzer and signal analyzer are used interchangeably, signal analyzer is a more accurate term for today’s analyzers that combine the superior dynamic range of a swept tuned spectrum analyzer with vector signal analyzer (VSA) capabilities and enable in-channel measurements such as error vector …
Why is FFT used?
The FFT algorithm is used to convert a digital signal (x) with length (N) from the time domain into a signal in the frequency domain (X), since the amplitude of vibration is recorded on the basis of its evolution versus the frequency at that the signal appears [40].
What does FFT stand for?
What Does Fast Fourier Transform (FFT) Mean? A fast Fourier transform (FFT) is an algorithm that calculates the discrete Fourier transform (DFT) of some sequence – the discrete Fourier transform is a tool to convert specific types of sequences of functions into other types of representations.
How many types of analyzers are there?
Analyzers come in two types: analog and digital.
What is FFT of a signal?
As the name implies, the Fast Fourier Transform (FFT) is an algorithm that determines Discrete Fourier Transform of an input significantly faster than computing it directly. In computer science lingo, the FFT reduces the number of computations needed for a problem of size N from O(N^2) to O(NlogN) .
What are the types of spectrum analyzers?
Today, there are three basic types of analyzer: the swept-tuned spectrum analyzer, the vector signal analyzer, and the real-time spectrum analyzer.
What is FFT test?
The Friends and Family Test (FFT) is an important feedback tool that supports the fundamental principle that people who use NHS services should have the opportunity to provide feedback on their experience. Listening to the views of patients and staff helps identify what is working well, what can be improved and how.
Which machine is used for fastest and accurate analysis?
- The fastest and most accurate signal and spectrum ana.
- The R&S®FSV is superior to established instruments of its class in almost every. …
- GENERAL PURPOSE | Signal analyzers.
- te signal and spectrum analyzer in the medium class.
Can I use a network analyzer as a spectrum analyzer?
In some cases, a VNA receiver can be used for the purposes of simplified spectrum analysis, which might include detection of self-excitation, determination of signal power and harmonic level, or spectrum deviation from an expected reference spectrum, among other parameters.
What are the types of network analyzer?
The two main types of network analyzers are Scalar Network Analyzer (SNA) which measures amplitude properties only and Vector Network Analyzer (VNA) which measures both amplitude and phase properties. A VNA may also be called a gain-phase meter or an Automatic Network Analyzer.
What is the purpose of a network analyzer?
Network analyzers can: Provide detailed packet capture data that specifies who specific devices are communicating with — source and destination — and which protocol or port is being used. Identify devices or parts of the network that are causing traffic flow bottlenecks. Detect unusual levels of network traffic.
What is FFT test?
The Friends and Family Test (FFT) is an important feedback tool that supports the fundamental principle that people who use NHS services should have the opportunity to provide feedback on their experience. Listening to the views of patients and staff helps identify what is working well, what can be improved and how.
What does a spectrum analyzer display?
A spectrum analyzer displays a spectrum of signal amplitudes on different frequencies. It enables analysis that determines whether signals fall within required limits. It displays spurious signals, complex waveforms, rare short-duration events and noise.
What is FFT in vibration analysis?
The fast Fourier transform (FFT) is a computational algorithm that efficiently implements a mathematical operation called the discrete-time Fourier transform. It transforms time-domain data into the frequency domain by taking apart a signal into sine and cosine waves.
FFT Spectrum Analyzer
SR770 FFT Analyzer
The SR770 is a single-channel 100 kHz FFT spectrum analyzer with a dynamic range of 90 dB and a real-time bandwidth of 100 kHz. Additionally, it includes a low-distortion source which allows you to measure the transfer functions of electronic and mechanical systems. The speed and dynamic range of these instruments, coupled with their flexibility and many analysis modes, makes them the ideal choice for a variety of applications including acoustics, vibration, noise measurement and general electronic use.
High Dynamic Range
The SR770 has a dynamic range of 90 B. This means that for a full-scale input signal, the instruments have no spurious responses larger than -90 dBc (1 part in 30,000). Even signals as small as -114 dBc (1 part in 500,000) may be observed by using averaging. The low front-end noise and low harmonic distortion of the SR770 allows you to see signals that would be buried in the noise of other analyzers.
Powerful Processing
The SR770 uses a pair of high-speed, 24-bit digital signal processors (DSPs) to filter, heterodyne and transform sampled data from its 16-bit analog-to-digital converter. This computing capability allows the analyzers to operate at a real-time bandwidth of 100 kHz. In other words, the SR770 processes the input signal with no dead time. Your measurements will be done in as little as a tenth of the time of other analyzers, which typically have a real-time bandwidth of about 10 kHz.
Easy To Use
The SR770 is easy to use. The simple, menu-oriented interface logically groups related instrument functions. Context-sensitive help is available for all keys and menus, and entire instrument setups can be saved to disk and recalled with a single keystroke.
Spectrum Measurements
The spectrum, power spectral density, and input time record can be displayed in a variety of convenient linear and logarithmic units including Vp, Vrms, dBVp, dBVrms or user-defined engineering units (EUs). The magnitude, phase and real and imaginary parts of complex signals can all be displayed. Several window functions including Hanning, Flat-Top , Uniform and Blackman-Harris can be chosen to optimize in-band amplitude accuracy or minimize out-of-band side lobes.
Octave Measurements
The SR770 also computes both the 15 and 30 band 1/3 octave spectra, commonly used in acoustics and noise measurement applications. A-weighting compensation is available for octave measurements. Amplitudes are computed for band -2 (630 mHz) through band 49 (80 kHz).
Triggering and Averaging
Flexible triggering and averaging modes let you see signals as low as 114 dB below full scale. RMS averaging provides an excellent estimate of the true signal and noise levels in the input signal, while vector averaging can be used with a triggered input signal to actually reduce the measured noise level. Both rms and vector averaging can be performed exponentially, where the analyzer computes a running average (weighting new data more heavily than older data), or linearly, where the analyzer computes an equally weighted average of a specified number of records. Triggering can be used to capture transient events or to preserve spectral phase information. Both internal and external triggering are available with adjustable pre-trigger and post-trigger delays .
Synthesized Source
The SR770 includes a low-distortion (-80 dB) , synthesized source which can be used to make frequency response measurements. It generates single frequency sine waves, two-tone signals for intermodulation distortion (IMD) testing, pink and white noise for audio and electronic applications, and frequency chirp for transfer function analysis. This direct digital synthesis (DDS) source provides an output level from 100 µV to 1 V, and delivers up to 50 mA of current.
Transfer Function X Transfer Function SR770 FFT Analyzer
Frequency Response
With its low-distortion DDS source, the SR770 is capable of performing accurate frequency response measurements. The source is synchronized with the instrument’s input allowing transfer functions to be measured with 0.05 dB precision. The SR770 measures the magnitude and phase response of control systems, amplifiers, and electromechanical systems, and displays the resulting Bode plot.
Limit and Data Tables
Sometimes it is important to keep track of a few key portions of a spectrum. Data tables allow up to 200 selected frequencies to be displayed in tabular format. Automated entry makes it easy to set up data tables for harmonic or sideband analysis. Convenient limit tables allow the entry of up to 100 separate upper or lower limit segments for pass-fail testing . On exceeding a limit, the analyzers can be configured to generate a screen message, an audio alarm, or a GPIB service request.
Analysis Modes
Three built-in analysis modes simplify common measurements. Harmonic analysis computes both harmonic power and THD (Total Harmonic Distortion) relative to a specified fundamental. Sideband analysis lets you compute power in a set of sidebands relative to the carrier power. And band analysis lets you easily integrate the power in a selected frequency band. All three analysis modes provide clear, on-screen markers which make it easy to pick out frequencies of special interest, such as harmonics or sidebands.
Markers
The SR770 has a marker that is designed to be fast, responsive and flexible. The marker can be configured to read the maximum, minimum or mean of a selected width of display, or can be set to tracking mode to lock on to a moving peak. Delta-mode readouts let you easily view frequency or amplitude differences between two peaks. Automated peak-find lets you quickly move between the peaks in a spectrum. And the markers for the upper and lower displays can be linked to display similarities or differences in the two spectra.
Math Functions
Data taken with the SR770 can be processed with the built-in trace calculator. Basic arithmetic functions such as addition, subtraction, multiplication, division, square roots and logarithms can be performed on traces. Traces can be combined with other on-screen traces, or with traces stored on disks. These calculator functions are quite useful for performing background subtraction or normalization of data.
Flexible Storage and Output
All traces, data tables and limit tables can be stored using the USB drive. Data can be saved in a space-saving binary format, or an easy-to-access ASCII format for off-line analysis. A variety of hardcopy options let you easily print data from the instruments. The screen can be dumped to a dot-matrix printer or a LaserJet compatible laser printer via the standard rear-panel Centronics printer interface. Complete limit and data tables, as well as a summary of the instrument settings, can be printed. Data can be plotted to any HP-GL compatible plotter with an RS-232 or GPIB interface.
Easy to Interface
Stanford Research SR770 FFT Spectrum Analyzer, 476 µHz to 100 kHz, with Low-Distortion, Synthesized Source, Single Channel
The SR770 is a single channel, 100 kHz FFT Spectrum Analyzer with a dynamic range of 90 dB and a real-time bandwidth of 100 kHz. The speed and dynamic range of the SR770, coupled with its’ flexibility and many analysis modes, makes it the ideal choice for a variety of applications including acoustics, vibration, noise measurement, and general electronic use. The SR770 includes a low-distortion source which allows you to measure the transfer functions of electronic and mechanical systems.
Measurement range: 476 µHz to 100 kHz
Spans: 191 MHz to 100 kHz in a binary sequence
Real-time bandwidth: 100 kHz
Channels: 1
Input impedance: 1 M Ohm + 15 pF
Amplitude range: 0.1 mVp to 1.0 Vp
Dynamic range: 90 dB typical
Display Real, imaginary, magnitude or phase
Measurements: Spectrum, power spectral density, time record and 1/3 octave
Hardcopy output to printers and plotters
3.5 inch disk drive
GPIB (IEEE-488) and RS-232 interfaces
Monitor: CRT Monochrome, 640 x 480 resolution
Connectors: BNC(f)
100, 120/220, 240 Vac; 50/60 Hz operation
Weight: 36 lb; Size: 159 mm (6.25 in)H x 432 mm (17.0 in)W x 470 mm (18.5 in)D
Please see Datasheet for complete details and specifications.
Stanford Research Systems SR770 FFT Spectrum Analyzer SRS for sale online
The lowest-priced item that has been refurbished by the manufacturer or a manufacturer-approved vendor (‘certified refurbished condition’), or an eBay seller or a third party not approved by the manufacturer (‘seller refurbished condition’).This means the item has been inspected, cleaned, and repaired to full working order and is in excellent condition.This item may or may not be in original packaging. See details for full description.
Oscilloscope with FFT or a Spectrum Analyzer?
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To answer simply – an oscilloscope is an essential tool for any electronics lab, whilst an SA is generally not (unless you are an RF engineer, and even then you need a good scope) and for a good quality one much more expensive in comparison (though Rigol have just brought out some pretty powerful SAs at decent scope type prices)
The FFT function on your average DSO will do for most work, so unless your frequency range of interest is e.g. > 500MHz or so (if it is let us know), then the DSO is the tool of choice.
Basically one does amplitude versus time (scope), and the other does amplitude versus frequency (SA)
Scope example:
Say you have a digital signal that is intermittently working, you could check on the scope and look for over/undershoot, ringing, noise, gltiches, etc.
(simple) SA example: Say you have a signal and you want to check the harmonic components of it, you can look on the SA screen and check for harmonics (e.g. a pure sine wave should just be one single spike on the screen, at it’s frequency, a square wave would be a decreasing series of odd harmonics)
Square wave on a Spectrum Analyser:
The same signal on a scope would look like this:
FFT Spectrum Analyzer: Fast Fourier Transform
FFT Spectrum Analyzer Fast Fourier Transform spectrum analyzers are a type of RF test equipment using digital signal processing for improved performance in RF design, test, service & repair.
Spectrum Analyzer Tutorial Includes:
What is a spectrum analyzer Spectrum analyzer types and technologies Superheterodyne / sweep spectrum analyzer FFT spectrum analyzer Realtime spectrum analyzer USB spectrum analyzer Spectrum analyzer tracking generator Specifications Spectrum analyzer operation Noise figure measurements Phase noise measurements Pulsed signal spectrum analysis
The FFT or Fast Fourier Transform spectrum analyser is now being used increasingly to improve performance reduce costs in RF design, electronics manufacturing test, service, repair. With increasing use of wireless technology used in the electronic circuit design of electronic devices, improved performance from spectrum analyzers is growing in importance.
As the name suggests the FFT spectrum analyzer is an item of RF test equipment that uses Fourier analysis and digital signal processing techniques to provide spectrum analysis.
Using Fourier analysis any waveform in the time domain can be represented by the weighted sum of sine and cosine signals. Using this concept, the FFT spectrum analyzer samples the input signal. It then computes the magnitude of its sine and cosine components of the overall signal, and finally it displays the spectrum of the signal.
The FFT spectrum analyzer is able to provide facilities that cannot be provided by swept frequency analyzers. They can provide fast capture and analysis of waveforms in a way that cannot be achieved with sweep / superheterodyne techniques alone. The signals can be displayed, stored, and processed to provide more insight into the signal and its characteristics, enabling the engineers undertaking RF design of the electronic devices to understand the signals in more depth.
As many test instruments use a digital approach to signal processing and control, it is hardly surprising to see that spectrum analysers also use this technology, reaping significant benefits in terms of performance and convenience.
Typical spectrum analyzer that uses FFT technology
Fast Fourier Transform – FFT analyser basics
The concept of the FFT spectrum analyzer is built around the Fast Fourier Transform which is based on a technique called Fourier analysis, developed by Joseph Fourier (1768 – 1830). Using his transform it is possible for one value in, for example, the continuous time domain to be converted into the continuous frequency domain, in which both magnitude and phase information are included.
To capture a waveform digitally it is necessary to capture a series of successive discrete values at regular intervals in the test equipment. As the time domain waveform is taken at time intervals, it is not possible for the data to be converted into the frequency domain using the standard Fourier transform. Instead a variant of the Fourier transform known as the Discrete Fourier Transform, DFT must be used.
As the DFT uses discrete samples for the time domain waveform, this reflects into the frequency domain and results in the frequency domain being split into discrete frequency components or “bins.”
The number of frequency bins over a frequency band is the frequency resolution. To achieve greater resolution, a greater number of bins is needed, and hence in the time domain a large number of samples is required.
As can be imagined, this results in a much greater level of computation, and therefore methods of reducing the amount of computation required is needed to ensure that the results are displayed in a timely fashion, although with today’s vastly increased level of processing power, this is less of a problem.
To ease the processing required, a Fast Fourier Transform, FFT is used. This requires that the time domain waveform has a the number of samples equal to a number which is an integral power of two.
Within the test instrument, the input signal is digitized at a high sampling rate. The Nyquist theorem states that as long as the sampling rate is greater than twice the highest frequency component of the signal, the sampled data will accurately represent the input signal.
FFT spectrum analyzer basics
The block diagram and topology of the FFT analyzer test equipment are different to that of the more usual superheterodyne or sweep spectrum analyzer. In particular circuitry is required to enable the digital to analogue conversion to be made, and then for processing the signal as a Fast Fourier Transform.
Nevertheless, analogue preconditioning is still enquired to ensure that the signal reaching the analogue to digits conversion is within the correct range and any other analogue processing that may be required has been undertaken.
The FFT spectrum analyzer can be considered to comprise of a number of circuit different blocks:
FFT Spectrum Analyser Block Diagram
Analogue front end attenuators / gain: The test instrument requires stages at the input of the FFT analyser to ensure that the signal is at the required level for the analogue to digital conversion. These stages may provide either gain or attenuation. If the signal level is too high, then clipping and distortion will occur, too low and the resolution of the ADC and noise become a problems. Matching the signal level to the analogue to digital converter, ADC range ensures the optimum performance and maximises the resolution of the ADC. Often the control of the gain will be controlled by the test instrument control processor.
Analogue low pass anti-aliasing filter: The signal is passed through an anti-aliasing filter. This is required because the rate at which points are taken by the sampling system within the FFT analyzer is particularly important. The waveform must be sampled at a sufficiently high rate. According to the Nyquist theorem a signal must be sampled at a rate equal to twice that of the highest frequency, and also any component whose frequency is higher than the Nyquist rate will appear in the measurement as a lower frequency component – a factor known as “aliasing”. This results from the where the actual values of the higher rate fall when the samples are taken. To avoid aliasing a low pass filter is placed ahead of the sampler to remove any unwanted high frequency elements. This filter must have a cut-off frequency which is less than half the sampling rate, although typically to provide some margin, the low pass filter cut-off frequency is at highest 2.5 times less than the sampling rate of the analyzer. In turn this determines the maximum frequency of operation of the overall FFT spectrum analyzer.
Sampling and analogue to digital conversion: In order to perform the analogue to digital conversion, two elements are required. The first is a sampler. This takes samples at discrete time intervals: this is called the sampling rate. The importance of this rate has been discussed above. The samples are then passed to an analogue to digital converter, ADC which produces the digital format for the samples that is required for the FFT analysis.
FFT analyzer: The data from the sampler is in the time domain but it is converted into the frequency domain by the FFT analyzer. This is then able to further process the data using digital signal processing techniques to analyze and process the data so that it can then be passed to the display to give the required display.
Display: With the power of processing it is possible to present the information for display in a variety of ways. Displays are very flexible and enable the information to be presented in formats that are easy to comprehend and reveal a variety of facets of the signal. The display elements of the FFT spectrum analyzer are therefore very important so that the information captured and processed can be suitably presented for the user. In addition to actually displaying the signal, the display often has many controls around to to provide a considerable degree of flexibility and additional soft-functions.
In operation the test instrument will take a sample at set times, and then this will be processed before passing it to the display.
There will be a given amount of time between samples, and this can be likened to the time between scans of a traditional swept superheterodyne spectrum analyzer.
It should be noted that the time interval between successive samples is likely to be very much shorter than that experienced by a swept analyzer passing the same frequency again.
Sampling and display of a basic FFT spectrum analyzer
In view of the amount of processing required to achieve the required signal processing, most FFT spectrum analyzers will use FPGAs (field programmable gate arrays) as they are able to be configured to provide very fast signal processing.
Advantages and disadvantages of FFT analyzer technology
As with any form of technology, FFT analysers have their advantages and disadvantages:
Advantages of FFT spectrum analyzer technology
Fast capture of waveform: In view of the fact that the waveform is analysed digitally, the waveform can be captured in a relatively short time, and then the subsequently analysed. This short capture time can have many advantages – it can allow for the capture of transients or short lived waveforms. The fast capture of waveforms by this type of test instrument can be used in many areas: characterising a new RF design, be it an integrated circuit, or an electronics circuit design using many components. The higher speed can enable a far greater number of measurements to be taken in a short time, and computer controlled. It can also be used within electronics manufacturing, where measurement speed is important to ensure a high production rate.
Able to capture non-repetitive events: The short capture time means that the FFT analyzer can capture non-repetitive waveforms, giving them a capability not possible with other spectrum analyzers.
The short capture time means that the FFT analyzer can capture non-repetitive waveforms, giving them a capability not possible with other spectrum analyzers. Able to analyse signal phase: As part of the signal capture process, data is gained which can be processed to reveal the phase of signals. With various forms of phase based modulation schemes being used for digital communications, the ability to capture phase information in this test instrument can be particularly useful.
As part of the signal capture process, data is gained which can be processed to reveal the phase of signals. With various forms of phase based modulation schemes being used for digital communications, the ability to capture phase information in this test instrument can be particularly useful. Waveforms can be stored Using FFT technology, it is possible to capture the waveform and analyse it later should this be required. For storing waveforms, considerable amounts of memory may be required, especially if repeated waveforms are to be stored. However with memory being relatively cheap, this is not a major problem – the real issue is to ensure that the system has sufficient memory available, either within the test equipment itself, or within any associated computer.
Disadvantages of the FFT spectrum analyzer technology
Frequency limitations: The main limit of the frequency and bandwidth of FFT spectrum analyzers is the analogue to digital converter, ADC that is used to convert the analogue signal into a digital format. It is this component that places the major limitation on the bandwidth as a result of the ADC top frequency. Also ADCs with more bits tend to have lower frequency limits. As a result of this superheterodyne techniques are often combined with the FFT approach to obtain a more versatile instrument with higher frequency and bandwidth limits.
Cost: Cost used to be an issue, but is not a problem these days. Initially FFT analysers were far more expansive than their analogue counterparts. However with processing technology now being cheaper, FFT analysers are now commonplace and virtually all new spectrum analysers use a digital approach with FFT technology.
In many instances superheterodyne and FFT techniques are used in single spectrum analyzer. This enables the best of both techniques to be adopted to provide a truly versatile and high performance test instrument.
Essentially the superheterodyne technique may be used to convert the frequency down to an intermediate frequency where the analogue to digital conversion can take place. The RF test instrument then uses FFT signal processing techniques in the normal way.
However, with analogue to digital conversion technology improving significantly in speed, the the need for conversion of the signals is being confined to the very much higher frequencies.
In view of the low cost of processing circuitry, most new RF spectrum analyzers these days adopt the FFT approach along with a significant amount of control processing to enable the test instrument to have a high degree of RF performance along with many capabilities.
These spectrum analyzers are used in many areas from general electronics circuit design, RF design, electronics manufacturing, service and repair, etc. These test instruments offer a much higher level of performance than the older swept or superheterodyne spectrum analyzers, and as a result FFT spectrum analyzers are now used in most applications.
More Test Topics:
Data network analyzer Digital Multimeter Frequency counter Oscilloscope Signal generators Spectrum analyzer LCR meter Dip meter, GDO Logic analyzer RF power meter RF signal generator Logic probe PAT testing & testers Time domain reflectometer Vector network analyzer PXI GPIB Boundary scan / JTAG Data acquisition
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Electrical network analyzer
SR770 FFT Analyzer The SR770 is a single-channel 100 kHz FFT spectrum analyzer with a dynamic range of 90 dB and a real-time bandwidth of 100 kHz. Additionally, it includes a low-distortion source which allows you to measure the transfer functions of electronic and mechanical systems. The speed and dynamic range of these instruments, coupled with their flexibility and many analysis modes, makes them the ideal choice for a variety of applications including acoustics, vibration, noise measurement and general electronic use. High Dynamic Range The SR770 has a dynamic range of 90 B. This means that for a full-scale input signal, the instruments have no spurious responses larger than -90 dBc (1 part in 30,000). Even signals as small as -114 dBc (1 part in 500,000) may be observed by using averaging. The low front-end noise and low harmonic distortion of the SR770 allows you to see signals that would be buried in the noise of other analyzers. Powerful Processing The SR770 uses a pair of high-speed, 24-bit digital signal processors (DSPs) to filter, heterodyne and transform sampled data from its 16-bit analog-to-digital converter. This computing capability allows the analyzers to operate at a real-time bandwidth of 100 kHz. In other words, the SR770 processes the input signal with no dead time. Your measurements will be done in as little as a tenth of the time of other analyzers, which typically have a real-time bandwidth of about 10 kHz.
Stanford SR770 FFT spectrum analyzer (476 µHz – 100 kHz)
Frequency:
Measurement range: 476 µHz to 100 kHz
Spans: 191 mHz to 100 kHz in a binary sequence
Center frequency: Anywhere within the 0 to 100 kHz measurement range
Accuracy: 25 ppm from 20 °C to 40 °C
Resolution: Span/400
Window functions: Blackman-Harris, Hanning, Flat-Top and Uniform
Real-time bandwidth: 100 kHz
Signal Input:
Number of channels: 1
Input: Single-ended or differential
Input impedance: 1 MΩ, 15 pF
Coupling: AC or DC
CMRR (at 1 kHz):
90 dB (input range <-6 dBV) 80 dB (input range <14 dBV) 50 dB (input range ≥14 dBV) Noise: Typ. 5 nVrms/√Hz at 1 kHz (-162 dBVrms/√Hz) Max. 10 nVrms/√Hz (-155 dBVrms/√Hz) Amplitude: Full-scale input range: -60 dBV (1.0 mVp) to +34 dBV (50 Vp) in 2 dB steps Dynamic range: 90 dB (typ.) Harmonic distortion: No greater than -80 dB from DC to 100 kHz (input range 0 dBV) Spurious: No greater than -85 dB below full scale (<200 Hz). No greater than -90 dB below full scale to 100 kHz (-50 dBV input range). Trigger Input: Modes: Continuous, internal, external, TTL Internal level: Adjustable to ±100 % of input scale. Positive or negative slope. Min. trigger amplitude: 10 % of input range External level: ±5 V in 40 mV steps. Positive or negative slope. 10 kΩ Impedance Min. trigger amplitude: 100 mV Source: Amplitude range: 0.1 mVp to 1.0 Vp Amplitude resolution: 1 mVp (output >100 mVp), 0.1 mVp (output <100 mVp) DC offset: <10.0 mV (typ.) Output impedance: <5 Ω, 50 mA peak output current General: Data storage: USB drive Power: 60 W, 100/120/220/240 VAC, 50/60 Hz Dimensions: 17" × 6.25" × 18.5" (WHL) Weight: 36 lbs.
키워드에 대한 정보 sr770 fft network analyzer
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- Spectrum Analyzer
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- Android (Operating System)
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- RTL2832U
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