qlibs::rms Class Reference

RMS calculator object. More...

#include <rms.hpp>

Inheritance diagram for qlibs::rms:

Public Member Functions
virtual	~rms ()
	rms ()=default
real_t	update (const real_t x) noexcept
	Computes the moving root mean square (RMS) of the input signal. The object uses both the exponential weighting method and the sliding window method to compute the moving RMS.
bool	setup (real_t *const window, const size_t wsize) noexcept
	Initialize the RMS instance by setting the default optimal parameters.
template<size_t windowSize>
bool	setup (real_t(&win)[windowSize]) noexcept
	Initialize the RMS instance by setting the default optimal parameters.
bool	setParams (const real_t l, const real_t a) noexcept
	Change the recursive parameters for the moving RMS estimator.
Public Member Functions inherited from qlibs::smootherEXPW
virtual	~smootherEXPW ()
bool	setup (const real_t lam=0.8_re)
	Setup an initialize the Exponential weighting filter.
real_t	smooth (const real_t x) override
	Perform the smooth operation recursively for the input signal x.
Public Member Functions inherited from qlibs::smoother
virtual	~smoother ()
bool	isInitialized (void) const
	Check if the smoother filter is initialized.
bool	reset (void)
	Reset the the smoother filter.
Public Member Functions inherited from qlibs::smootherMWM2
virtual	~smootherMWM2 ()
bool	setup (real_t *window, const size_t w_size)
	Setup an initialize the Moving Window Median filter.
template<size_t windowSize>
bool	setup (real_t(&window)[windowSize])
	Setup an initialize the Moving Window Median filter.
real_t	smooth (const real_t x) override
	Perform the smooth operation recursively for the input signal x.
Public Member Functions inherited from qlibs::tdl
virtual	~tdl ()
	tdl ()=default
	tdl (real_t *const area, const size_t n, const real_t initVal=0.0_re)
	Constructor for the Tapped Delay Line (TDL) instance.
template<size_t numberOfDelays>
	tdl (real_t(&area)[numberOfDelays], const real_t initVal=0.0_re) noexcept
	Constructor for the Tapped Delay Line (TDL) instance.
void	setup (real_t *const area, const size_t n, const real_t initVal=0.0_re) noexcept
	Setup and initialize a Tapped Delay Line (TDL) instance by setting the default optimal parameters.
template<size_t numberOfDelays>
void	setup (real_t(&area)[numberOfDelays], const real_t initVal=0.0_re) noexcept
	Setup and initialize a Tapped Delay Line (TDL) instance by setting the default optimal parameters.
void	flush (const real_t initVal=0.0_re) noexcept
	Clears all delays from the TDL and sets them to the specified value.
real_t	getOldest (void) const noexcept
	Get the oldest sample from the TDL x(k-n)
real_t	getRecent (void) const noexcept
	Get the most recent sample from the TDL x(k)
real_t	getAtIndex (const size_t i) const noexcept
	Get the specified delayed sample from the TDL x(k-i)
void	insertSample (const real_t sample) noexcept
	Insert a new sample to the TDL removing the oldest sample.
const real_t &	operator[] (int index) noexcept
	Get the specified delayed sample from the TDL x(k-i)
void	operator() (const real_t sample) noexcept
	Insert a new sample to the TDL removing the oldest sample.
bool	isInitialized (void) const
	Check if the TDL has been initialized.
Public Member Functions inherited from qlibs::smootherLPF1
virtual	~smootherLPF1 ()
bool	setup (const real_t a=0.9_re)
	Setup an initialize the 1st order Low-Pass Filter.
real_t	smooth (const real_t x) override
	Perform the smooth operation recursively for the input signal x.

Detailed Description

RMS calculator object.

Constructor & Destructor Documentation

~rms()

virtual qlibs::rms::~rms ( )

inlinevirtual

rms()

qlibs::rms::rms ( )

default

Member Function Documentation

setParams()

bool rms::setParams ( const real_t l, const real_t a )

noexcept

Change the recursive parameters for the moving RMS estimator.

Parameters

[in]	l	Exponential weighting factor, specified as a positive real scalar in the range [0,1]. A forgetting factor of 0.9 gives more weight to the older data than does a forgetting factor of 0.1. A forgetting factor of 1.0 indicates infinite memory. All the past samples are given an equal weight.
[in]	a	A parameter to tune the 2nd stage filter. Should be a value between [ 0 < a < 1 ]. A higher value will result in a smoother output but also increasing the convergence time.

Returns

true on success, otherwise returns false.

setup() [1/2]

bool rms::setup ( real_t *const window, const size_t wsize )

noexcept

Initialize the RMS instance by setting the default optimal parameters.

Parameters

[in]	window	A pointer to the window storage, an array of wsize elements.
[in]	wsize	The window size.

Returns

true on success, otherwise returns false.

setup() [2/2]

template<size_t windowSize>

bool qlibs::rms::setup ( real_t(&) win[windowSize] )

inlinenoexcept

Initialize the RMS instance by setting the default optimal parameters.

Parameters

[in]

win

The array for the window storage

Returns

true on success, otherwise returns false.

update()

real_t rms::update ( const real_t x )

noexcept

Computes the moving root mean square (RMS) of the input signal. The object uses both the exponential weighting method and the sliding window method to compute the moving RMS.

Note

For a 50-60Hz sine waveform leave default parameters, use a window of 8 samples and make sure you call the this method at a rate of 1mS. In this configuration you will obtain an optimal estimate that converges in a cycle of the wave

Parameters

[in]

x

The raw signal.

Returns

A recursive estimation of the RMS for the incoming signal x.