This section provides overview, applications, and principles of fast fourier transform (fft) analyzers. Also, please take a look at the list of 11 fast fourier transform (fft) analyzer manufacturers and their company rankings.
An FTT (Fast Fourier Transform) analyzer is an analytical instrument that performs a Fast Fourier Transform (FFT). The waveform of the measured signal can be observed on an oscilloscope with time as the horizontal axis.
On the other hand, a frequency analyzer is needed when one wants to observe the frequency components (sine and cosine waves) in the signal.
This device handles waveform conversion and has some points in common with spectrum analyzers and memory recorders but is selected according to the purpose of use. The points where it differs from a spectrum analyzer are as follows.
While conventional spectrum analyzers are composed of analog circuits, FFT analyzers used AD converters to digitize the obtained waveforms and then perform high-speed Fourier transform processing to calculate the frequency intensity distribution.
FFT analyzers are mainly used to observe the frequency components of low-frequency signals.
One of the main features of the FFT analyzer is its ability to represent complex waveforms as a combination of simple waveforms, allowing the analysis of signal components. There are many seemingly irregular waveforms measured from actual equipment, and the more complex the equipment system, the more pronounced this tendency is.
For example, oscilloscopes, which are often used for waveform observation, can show changes in waveforms over time, but it is difficult to identify which factors are responsible for the changes in waveforms over time.
Therefore, by conducting frequency analysis using FFT, it is possible to estimate the cause of the abnormality and its location by examining which frequency and to what extent the frequency has changed and from which system the frequency is thought to originate.
In this way, the use of FFT makes it possible to detect minute abnormalities in addition to the conventional detection of macroscopic waveforms.
Recently, in addition to equipment management and abnormality diagnosis through vibration analysis, frequency analysis has been used in various fields, such as noise analysis, to evaluate the quietness of office machines and home appliances and to study the cause of noise and its countermeasures. For example, one of the frequency analyses using an FFT analyzer is to investigate the vibration of machinery.
Similarly, it can be used to identify noise sources in low-frequency signals and thus is also used and applied in noise control for products that handle frequency signals
The Fast Fourier Transform (FFT) is based on the theory of the Fourier series proposed by the French mathematician Fourier.
The theory states that any complex waveform with periodicity can be represented by a series of simple sine (sin wave) and cosine (con wave) waves, and the Fourier transform is an extension of this series concept.
Since it is not known how much of the signal to be measured is periodic, the Fourier transform is generally performed by cutting off an appropriate amount of time from the observed waveform and assuming that the cut waveform is an infinitely repeating signal.
In the early days of the Fourier transform, the calculation of the Fourier transform required an enormous number of multiplications. However, J.W. Turkey and J.W. Cooley proposed a method to reduce the number of calculations by taking the number of data to the nth power of 2. For example, if the number of data is 1024, the number of calculations is reduced from 1024 × 1024 = 1048576 times to 10240 times.
This method is what is known as the Fast Fourier Transform (FFT) and is commonly referred to by its acronym FFT.
A waveform can be represented by three parameters: amplitude, frequency (or period), and phase (time difference).
The FFT analyzer then finds the coefficients of the Fourier series for the input signal. The specific transformation can be observed as a decomposition by frequency.
As a result, the input waveform signal with time as the horizontal axis is transformed into a waveform signal with frequency as the horizontal axis. The vertical axis represents the amplitude of the waveform at each frequency.
The FFT allows us to decompose signals caused by a combination of multiple sources, such as sound and vibration, into their components of frequency. By examining which frequencies have changed in level and by how much, and by examining where the frequencies are thought to originate from, important information can be obtained to identify the causative factor.
The price of an FFT analyzer varies depending on the frequency range it can handle and the processing functions, but a simple handheld type starts at around 50,000 yen.
For high-precision measurement, we recommend a stationary type for stable measurement. The main unit price is approximately 2,000,000 yen. Adding measurement probes, microphones, and measurement units to the main unit will cost 3,000,000 yen for the whole set
The input signal is generally connected to the FFT analyzer with a single cable using the BNC terminal.
Commonly used for vibration analysis of machines, equipment, and buildings. Acceleration pickups are attached to the object to be measured, converted into electrical signals, input to the FFT analyzer, and the frequency components are analyzed through arithmetic processing. The vibration and resonance frequencies emitted by machines and buildings are checked, and used to reinforce structures to prevent fatigue failures and to suppress vibration.
Another use is to detect uneven rotation of motors. Drive waveforms or monitor signals can be extracted from the motor and analyzed by FFT to check for variations in rotational speed and wobble.
It is also widely used for sound analysis. It can be used to check the area of sound emitted by a person or musical instrument, or to analyze the frequency of noise to see what kind of place or facility it is emitted from. In this case, a microphone is used to pass the sound through an amplifier, which converts and amplifies the signal for FFT analysis.
Both FFT analyzers and spectrum analyzers are instruments used to break down a signal into frequencies and analyze the strength of the signal at each frequency
Typically, an FFT analyzer is used when it is not known what frequency components a signal has, while a spectrum analyzer is used to analyze the frequency components of a known high-frequency signal (for example, a cell phone or WiFi transmitter).
FFT analyzers handle low-frequency signals from DC to 100 kHz. It takes an input signal and frequency decomposes it using the Fast Fourier Transform to analyze the fundamental frequency, 2nd overtone, and 3rd overtone strengths. It is also used to analyze the wobble width of the fundamental frequency.
Spectrum analyzers, on the other hand, differ from FFT analyzers in that they have an extremely wide frequency range of 10 kHz to 10 GHz. Some recent models can handle DC to 50 GHz.
*Including some distributors, etc.
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