You are here : matlab → Signal Processing → rpmfreqmap
# rpmfreqmap() - Signal Processing

### Syntax

### Example

### Output / Return Value

### Limitations

### Alternatives / See Also

### Reference

examplemap = rpmfreqmap(x,fs,rpm) returns the frequency-RPM map matrix, map, that results from performing frequency analysis on the input vector, x. x is measured at a set rpm of rotational speeds expressed in revolutions per minute. fs is the sample rate in Hz. Each column of map contains root-mean-square (RMS) amplitude estimates of the spectral content present at each value of rpm. rpmfreqmap uses the short-time Fourier transform to analyze the spectral content of x. examplemap = rpmfreqmap(x,fs,rpm,res) specifies the resolution bandwidth of the map in Hz. examplemap = rpmfreqmap(___,Name,Value) specifies options using Name,Value pairs in addition to the input arguments in previous syntaxes. [map,freq,rpm,time,res] = rpmfreqmap(___) returns vectors with the frequencies, rotational speeds, and time instants at which the frequency map is computed. It also returns the resolution bandwidth used. examplerpmfreqmap(___) with no output arguments plots the frequency map as a function of rotational speed and time on an interactive figure.

map = rpmfreqmap(x,fs,rpm) examplemap = rpmfreqmap(x,fs,rpm,res) examplemap = rpmfreqmap(___,Name,Value) example[map,freq,rpm,time,res] = rpmfreqmap(___)rpmfreqmap(___) example

Frequency-RPM Map of Chirp with 4 OrdersOpen This Example Create a simulated signal sampled at 600 Hz for 5 seconds. The system that is being tested increases its rotational speed from 10 to 40 revolutions per second during the observation period. Generate the tachometer readings.fs = 600; t1 = 5; t = 0:1/fs:t1; f0 = 10; f1 = 40; rpm = 60*linspace(f0,f1,length(t)); The signal consists of four harmonically related chirps with orders 1, 0.5, 4, and 6. The order-4 chirp has twice the amplitude of the others. To generate the chirps, use the trapezoidal rule to express the phase as the integral of the rotational speed.o1 = 1; o2 = 0.5; o3 = 4; o4 = 6; ph = 2*pi*cumtrapz(rpm/60)/fs; x = [1 1 2 1]*cos([o1 o2 o3 o4]'*ph); Visualize the frequency-RPM map of the signal.rpmfreqmap(x,fs,rpm) Frequency-RPM Map of Helicopter Vibration DataOpen This Example Analyze simulated data from an accelerometer placed in the cockpit of a helicopter. Load the helicopter data. The vibrational measurements, vib, are sampled at a rate of 500 Hz for 10 seconds. Inspection of the data reveals that it has a linear trend. Remove the trend to prevent it from degrading the quality of the frequency estimation.load('helidata.mat') vib = detrend(vib); Plot the nonlinear RPM profile. The rotor runs up until it reaches a maximum rotational speed of about 27,600 revolutions per minute and then coasts down.plot(t,rpm) xlabel('Time (s)') ylabel('RPM') Compute the frequency-RPM map. Specify a resolution bandwidth of 2.5 Hz.[map,freq,rpmOut,time] = rpmfreqmap(vib,fs,rpm,2.5); Visualize the map.imagesc(time,freq,map) ax = gca; ax.YDir = 'normal'; xlabel('Time (s)') ylabel('Frequency (Hz)') Repeat the computation using a finer resolution bandwidth. Plot the map using the built-in functionality of rpmfreqmap. The gain in frequency resolution comes at the expense of time resolution.rpmfreqmap(vib,fs,rpm,1.5); Waterfall Plot of Frequency-RPM MapOpen This Example Generate a signal that consists of two linear chirps and a quadratic chirp, all sampled at 600 Hz for 15 seconds. The system that produces the signal increases its rotational speed from 10 to 40 revolutions per second during the testing period. Generate the tachometer readings.fs = 600; t1 = 15; t = 0:1/fs:t1; f0 = 10; f1 = 40; rpm = 60*linspace(f0,f1,length(t)); The linear chirps have orders 1 and 2.5. The component with order 1 has half the amplitude of the other. The quadratic chirp starts at order 6 and returns to this order at the end of the measurement. Its amplitude is 0.8. Create the signal using this information.o1 = 1; o2 = 2.5; o6 = 6; x = 0.5*chirp(t,o1*f0,t1,o1*f1)+chirp(t,o2*f0,t1,o2*f1) + ... 0.8*chirp(t,o6*f0,t1,o6*f1,'quadratic'); Compute the frequency-RPM map of the signal. Use the peak amplitude at each measurement cell. Specify a resolution of 6 Hz. Window the data with a flat top window.[map,fr,rp] = rpmfreqmap(x,fs,rpm,6, ... 'Amplitude','peak','Window','flattopwin'); Draw the frequency-RPM map as a waterfall plot.[FR,RP] = meshgrid(fr,rp); waterfall(FR,RP,map') view(-6,60) xlabel('Frequency (Hz)') ylabel('RPM') zlabel('Amplitude') Interactive Frequency-RPM Map Plot an interactive frequency-RPM map by calling rpmfreqmap without output arguments. Load a file containing simulated vibrational data from an accelerometer placed in the cockpit of a helicopter. The data are sampled at a rate of 500 Hz for 10 seconds. Remove the linear trend in the data. Call rpmfreqmap to generate an interactive plot of the frequency-RPM map. Specify a frequency resolution of 2 Hz.load('helidata.mat') rpmfreqmap(detrend(vib),fs,rpm,2) Move the crosshair cursors in the figure to determine the RPM and the RMS amplitude at a frequency of 25 Hz after 5 seconds. Click the Zoom X button in the toolbar to zoom into the time region between 2 and 4 seconds. A panner appears in the bottom plot. Click the Waterfall Plot button in the toolbar to display the frequency-RPM map as a waterfall plot. For improved visibility, rotate the plot clockwise using the Rotate Left button three times. Move the panner to the interval between 4 and 6 seconds.