Envelope spectrum for machinery diagnosis

specifies additional options for any of the previous syntaxes using name-value
pair arguments. Options include the algorithm used to compute the envelope
signal and the frequency band over which to estimate the spectrum.`es`

= envspectrum(___,`Name,Value`

)

`envspectrum(___)`

with no output arguments
plots the envelope signal and the envelope spectrum in the current
figure.

`envspectrum`

initially removes the DC bias from the input signal,
`x`

, and then computes the envelope signal.

If

`'Method'`

is set to`'hilbert'`

, the function:Bandpass-filters the signal. The FIR filter has an order specified by

`'FilterOrder'`

and cutoff frequencies at`ba(1)`

and`ba(2)`

, where`ba`

is a frequency band specified using`'Band'`

.Computes the analytic signal using the

`hilbert`

function.Computes the envelope signal as the absolute value of the analytic signal.

If

`'Method'`

is set to`'demod'`

, the function:Performs complex demodulation of the signal. The signal is multiplied by exp(

*j*2*π**f*_{0}*t*), where*f*_{0}= (`ba(1)`

+`ba(2)`

)/2.Lowpass-filters the demodulated signal to compute the analytic signal. The FIR filter has an order specified by

`'FilterOrder'`

and a cutoff frequency of (`ba(2)`

–`ba(1)`

)/2.Computes the envelope signal as twice the absolute value of the analytic signal.

After computing the envelope signal, the function removes the DC bias from the envelope and computes the envelope spectrum using the FFT.

[1] Randall, Robert Bond. *Vibration-Based Condition
Monitoring*. Chichester, UK: John Wiley & Sons, 2011.

`envelope`

| `hilbert`

| `orderspectrum`

- Vibration Analysis of Rotating Machinery
- Rolling Element Bearing Fault Diagnosis (Predictive Maintenance Toolbox)