Contents
How do you Upsample in Matlab?
y = upsample( x , n ) increases the sample rate of x by inserting n – 1 zeros between samples. If x is a matrix, the function treats each column as a separate sequence. y = upsample( x , n , phase ) specifies the number of samples by which to offset the upsampled sequence.
What is 1X 2X in vibration analysis?
A 1X and 2X vibration signal predominant in the axial direction is generally the indicator of a misalignment between two coupled shafts. These signals may be also visible in the radial direction at a lower amplitude and in phase.
When should I upsample?
Upsampling. The purpose of upsampling is to add samples to a signal, whilst maintaining its length with respect to time. Consider again a time signal of 10 seconds length with a sample rate of 1024Hz or samples per second that will have 10 x 1024 or 10240 samples.
When to upsample and when to downsample a signal?
So, in order to downsample the signal we must first low pass filter the data to remove the content between 256Hz and 512Hz before it can be resampled. The purpose of upsampling is to add samples to a signal, whilst maintaining its length with respect to time.
What should be the factor for upsample and downsample?
However, that is the very minimum required. Generally, in the real world, a factor of at least 2.5 is used. Some will even go as high as 4 to allow an adequate margin. It will depend on your application. What happens if we ignore the Nyquist rate?
How is the amplitude of a upsample related to the sampling rate?
This is no coincidence and is carefully selected by DATS. The frequency which corresponds to half the sampling rate is known as the Nyquist Rate. [Note also that the amplitude is 0.5, exactly half the amplitude of the signal in Figure 1. This half amplitude is an effect of the type of frequency transform that has been used.
Which is the most common Fourier transform for time domain data?
The Fourier Transform (FFT) is the most common analysis to take time domain data and create frequency domain data. The following figure shows the signal from Figure 1 in the frequency domain as the result of an FFT transform. Note the range of the data on the x-axis in Figure 3.