qRMS

API for the qRMS Recursive Root Mean Square calculator. More...

Data Structures
struct	qRMS_t
	RMS calculator instance. More...

Functions
int	qRMS_Setup (qRMS_t *const q, float *const window, const size_t wsize)
	Initialize the RMS instance by setting the default optimal parameters.
float	qRMS_Update (qRMS_t *const q, const float x)
	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.
int	qRMS_SetParams (qRMS_t *const q, const float lambda, const float alpha)
	Change the recursive parameters for the moving RMS estimator.

Detailed Description

API for the qRMS Recursive Root Mean Square calculator.

For a brief description of this module, please read Recursive Root Mean Square estimator

Function Documentation

qRMS_SetParams()

int qRMS_SetParams	(	qRMS_t *const	q,
		const float	lambda,
		const float	alpha )

Change the recursive parameters for the moving RMS estimator.

Parameters

[in]	q	A pointer to the RMS instance.
[in]	lambda	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]	alpha	A parameter to tune the 2nd stage filter. Should be a value between [ 0 < alpha < 1 ]. A higher value will result in a smoother output but also increasing the convergence time.

Returns

1 on success, otherwise returns 0.

qRMS_Setup()

int qRMS_Setup	(	qRMS_t *const	q,
		float *const	window,
		const size_t	wsize )

Initialize the RMS instance by setting the default optimal parameters.

Parameters

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

Returns

1 on success, otherwise returns 0.

qRMS_Update()

float qRMS_Update	(	qRMS_t *const	q,
		const float	x )

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 qRMS_Update() at a rate of 1mS. In this configuration you will obtain an optimal estimate that converges in a cycle of the wave

Parameters

[in]	q	A pointer to the RMS instance.
[in]	x	The raw signal.

Returns

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