CN117932315A - Transient response power frequency interference suppression method and system - Google Patents
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Abstract
The invention relates to the technical field of power frequency interference suppression in sensor output signals, and provides a transient response power frequency interference suppression method and a transient response power frequency interference suppression system, wherein the method comprises the following steps: preprocessing the acquired sensor transient response signals; EMD (empirical mode decomposition) is carried out on the transient response signal to obtain imf components; constructing an observation signal matrix according to imf components, and performing iterative ICA separation; and LEVKOV, filtering the signal subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression. The invention combines the iteration EMD-ICA with LEVKOV, adopts the method of iteration EMD-ICA to reduce the frequency-moving power frequency interference in transient response by constructing a power frequency reference signal, and further weakens the power frequency interference and harmonic interference thereof by linear section mean filtering and nonlinear section noise template filtering by LEVKOV method, thereby improving the filtering precision of the power frequency interference in the transient response signal.
Description
Technical Field
The invention relates to the technical field of power frequency interference suppression in sensor output signals, in particular to a transient response power frequency interference suppression method and system.
Background
With the rapid development of science and technology and the continuous improvement of industrial automation, more and more application occasions need to realize the measurement of dynamic signals, which requires that the used sensor has good dynamic characteristics. The dynamic characteristics of the sensor are generally analyzed and evaluated by acquiring transient response signals through a dynamic experiment method. However, in the experimental process, due to the experimental field or experimental equipment, power frequency interference is inevitably introduced into the weak signal output by the sensor, so that the time-frequency analysis of the dynamic characteristics of the sensor is affected. In the face of power frequency interference, researchers have proposed a plurality of methods for suppressing the power frequency interference, and the methods can be mainly divided into three categories of time domain filtering, frequency domain filtering and time-frequency analysis. The time domain filtering method includes Independent Component Analysis (ICA), LEVKOV method, smoothing filtering, etc. The ICA is used for separating the power frequency interference irrelevant to the useful signal by searching for components meeting statistical independence and non-Gaussian, but the method is used for carrying out interference separation by independently measuring the power frequency interference or constructing the power frequency interference as a reference signal; the LEVKOV method is proposed for solving the problem of power frequency interference in the electrocardiosignal, and by manually segmenting the electrocardiosignal, different filtering methods are respectively adopted, so that the power frequency interference in the electrocardiosignal can be effectively inhibited, but the filtering effect on other signals with different signal characteristics is poor; the smoothing filter has simple operation and good real-time performance, but is substantially equivalent to a frequency domain low-pass filter, and can weaken useful signals while suppressing interference. The frequency domain filtering method is commonly used as a wave trap filter for filtering, and can eliminate interference of a specific frequency. The window-based FIR filter, the variable step length Least Mean Square (LMS) adaptive wave trap, the Least Mean Square (LMS) filter, the Normalized Least Mean Square (NLMS) filter and the wave trap remove power frequency interference in electrocardiosignals, although good effects are achieved. However, it is difficult to control the notch coefficients of either a fixed or an adaptive notch filter so that it does not affect the useful signal of the band aliasing. Wavelet filtering is commonly used in time-frequency analysis methods. The wavelet filtering has good time-frequency localization characteristics, and the wavelet coefficients controlled by the noise are found and removed by reserving the wavelet coefficients controlled by the useful signals, so that the noise is filtered; however, due to the wide frequency window of the wavelet filtering, effective signals of power frequency and other frequencies nearby the power frequency are filtered simultaneously, the noise elimination coefficient is not easy to control, and the filtering and the underfilting are easy to cause, so that the signals are severely distorted.
Disclosure of Invention
The invention aims to solve at least one technical problem in the background art and provides a transient response power frequency interference suppression method and system.
In order to achieve the above object, the present invention provides a transient response power frequency interference suppression method, including:
Preprocessing the acquired sensor transient response signals;
EMD decomposition is carried out on the transient response signals after pretreatment, so that imf components representing power frequency reference signals are obtained;
Constructing an observation signal matrix according to imf components, and performing iterative ICA separation until the number of iterations is reached;
and LEVKOV, filtering the signal subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression.
According to one aspect of the invention, the preprocessing of the acquired transient response signal comprises: de-biasing and low pass filtering.
According to one aspect of the invention, the constructing an observation signal matrix from imf components is:
And carrying out FFT on IMF components obtained by EMD decomposition, observing amplitude spectrums of the components, selecting the IMF component with the maximum amplitude of about 50Hz, and forming an observation signal matrix with the preprocessed transient response signal.
According to one aspect of the invention, the iterative ICA separation is performed until an iteration number is reached that is:
ICA separation is carried out according to the obtained observation signal matrix to obtain a separated signal, EMD decomposition is carried out on the separated signal, IMF components are selected to construct the observation signal matrix, ICA separation is carried out again, and iteration is carried out until the maximum iteration times are reached.
According to one aspect of the invention, the LEVKOV filtering divides the signal into a linear section and a nonlinear section according to the amplitude and slope characteristics of the signal filtered by the EMD-ICA in different sections, then removes the power frequency noise of the linear section by using a noise whole period mean value filtering method, and removes the power frequency noise of the nonlinear section by using a noise template of the linear section.
According to one aspect of the invention, the LEVKOV filters include:
① The slope D n of the current sample point is calculated according to the following equation:
Dn＝yn+N-yn
Where y is the transient response signal after iterative EMD-ICA filtering, n represents the current sampling point, and the signal y can be expressed as a matrix of 1 xT: y [ y 1,y2,y3,...,yT ], then y n represents the nth sample point; n is the number of sampling points in the whole period of the power frequency interference signal, n=f s/f,fs is the sampling frequency, and f is the power frequency;
② Let d n＝|Dn-Dn-1 |, if d n at all of the q consecutive sampling points starting from the current sampling point is smaller than M, then filtering by using a linear segment method; otherwise, filtering by a nonlinear segment method;
Aiming at the linear section, a power frequency whole period average filtering method is adopted to remove power frequency interference:
calculating the linear offset of the average value of one power frequency periodic signal and the current sampling point, thereby obtaining the filtering result of the current signal, wherein the specific filtering calculation formula is as follows:
Wherein z is a transient response signal after LEVKOV filtering;
aiming at the nonlinear section, the power frequency interference signal of the previous power frequency period is taken as a template to eliminate the power frequency interference in the signal in the current power frequency period:
Calculating a power frequency interference value of a corresponding point in a previous power frequency interference period according to a formula temp n-N＝yn-N-zn-N, taking the power frequency interference value as a power frequency noise template value, and then calculating a filtering result of a current point according to a formula z n＝yn-tempn-N; wherein temp n-N represents the noise at y n-N;
the next N-1 sampling points are all filtered by adopting a nonlinear segment method.
In order to achieve the above object, the present invention further provides a transient response power frequency interference suppression system, which is characterized by comprising:
The signal preprocessing module is used for preprocessing the acquired transient response signals of the sensor;
The EMD decomposition module is used for carrying out EMD decomposition on the preprocessed transient response signal to obtain imf components representing the power frequency reference signal;
The iterative ICA separation module constructs an observation signal matrix according to imf components and performs iterative ICA separation until the number of iterations is reached;
And LEVKOV the filtering module is used for LEVKOV filtering the signals subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression.
In order to achieve the above object, the present invention further provides an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the computer program when executed by the processor implements the transient response power frequency interference suppression method as described above.
To achieve the above object, the present invention further provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the transient response power frequency interference suppression method as described above.
According to the scheme of the invention, the power frequency interference suppression method of the joint iteration ICA and LEVKOV method is provided by combining the characteristics of the transient response signal of the sensor and the characteristics of actual power frequency interference aiming at the problem that the existing power frequency interference suppression method is difficult to be used for power frequency noise elimination of the transient response of the sensor. The basic idea is that the ICA method is firstly used for reducing the power frequency interference of frequency play in transient response by constructing a power frequency interference reference signal through cyclic iteration, and then LEVKOV method is used for further eliminating the power frequency and harmonic interference thereof, so that the filtering effect on the power frequency interference in the transient response of the sensor is improved.
According to the scheme of the invention, for the power frequency interference of the power frequency play in the transient response signal, the iterative EMD-ICA method flow is adopted to carry out iterative filtering for a plurality of times, and the input signal of each EMD-ICA filtering is the output signal of the last EMD-ICA filtering, so that the power frequency interference in the signal is gradually reduced; aiming at the problems of residual power frequency interference and harmonic interference thereof after iterative EMD-ICA filtering, LEVKOV method is utilized to carry out secondary filtering through linear section mean filtering and nonlinear section noise template filtering, thereby improving the filtering precision of the power frequency interference in transient response signals. In addition, since the EMD-ICA method and LEVKOV method are both time domain methods, the proposed method is also time domain filtering method, and the signal filtering does not generate problems such as delay, phase lag, etc.
According to the scheme of the invention, the iterative EMD-ICA method is combined with LEVKOV method, the industrial frequency reference signal is constructed, the iterative EMD-ICA method is adopted to reduce the industrial frequency interference of frequency play in transient response, and the LEVKOV method is utilized to further weaken the industrial frequency interference and harmonic interference thereof through linear section mean filtering and nonlinear section noise template filtering, so that the filtering precision of the industrial frequency interference in the transient response signal is improved.
Drawings
FIG. 1 schematically illustrates a flow chart of a transient response power frequency interference suppression method in accordance with the present invention;
FIG. 2 schematically illustrates a flow chart of a transient response power frequency interference suppression method according to one embodiment of the invention;
FIG. 3 schematically shows an iterative EMD-ICA schematic diagram according to embodiment 1 of the present invention;
Fig. 4 schematically shows an actual power frequency interference suppression time domain effect diagram according to embodiment 1 of the present invention.
Fig. 5 schematically shows an actual power frequency interference suppression frequency domain effect diagram according to embodiment 1 of the present invention.
Detailed Description
The present disclosure will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are merely to enable those of ordinary skill in the art to better understand and thus practice the teachings of the present invention and do not imply any limitation on the scope of the invention.
As used herein, the term "comprising" and variants thereof are to be interpreted as meaning "including but not limited to" open-ended terms. The term "based on" is to be interpreted as "based at least in part on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment.
FIG. 1 schematically illustrates a flow chart of a transient response power frequency interference suppression method in accordance with the present invention; fig. 2 schematically illustrates a flow chart of a transient response power frequency interference suppression method according to an embodiment of the invention. Referring to fig. 1 and fig. 2, according to an embodiment of the present invention, a transient response power frequency interference suppression method includes:
a. Preprocessing the acquired sensor transient response signals;
b. EMD decomposition is carried out on the transient response signals after pretreatment, so that imf components representing power frequency reference signals are obtained;
c. Constructing an observation signal matrix according to imf components, and performing iterative ICA separation until the number of iterations is reached;
d. And LEVKOV, filtering the signal subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression.
Based on the scheme, the invention provides the power frequency interference suppression method of the joint iteration ICA and LEVKOV method by combining the characteristics of the transient response signal of the sensor and the characteristics of actual power frequency interference aiming at the problem that the existing power frequency interference suppression method is difficult to be used for power frequency noise elimination of the transient response of the sensor. The basic idea is that the ICA method is firstly used for reducing the power frequency interference of frequency play in transient response by constructing a power frequency interference reference signal through cyclic iteration, and then LEVKOV method is used for further eliminating the power frequency and harmonic interference thereof, so that the filtering effect on the power frequency interference in the transient response of the sensor is improved.
As shown in fig. 2, according to an embodiment of the present invention, in the step a, preprocessing the acquired transient response signal includes: de-biasing and low pass filtering. The unbiasing is to avoid the output of the force sensor from shifting, and the unbiasing needs to be performed before the data processing. The low-pass filtering is to avoid the influence of high-frequency noise on the subsequent analysis, and a Butterworth low-pass filter is used for filtering the source signal, wherein the order of the filter is 2, and the cut-off frequency is 1000Hz.
Further, according to an embodiment of the present invention, in the step c, the observation signal matrix is constructed according to imf components as follows:
And carrying out FFT on IMF components obtained by EMD decomposition, observing amplitude spectrums of the components, selecting the IMF component with the maximum amplitude of about 50Hz, and forming an observation signal matrix with the preprocessed transient response signal.
Further, according to an embodiment of the present invention, in the step c, iterative ICA separation is performed until the number of iterations is reached:
ICA separation is carried out according to the obtained observation signal matrix to obtain a separated signal, EMD decomposition is carried out on the separated signal, IMF components are selected to construct the observation signal matrix, ICA separation is carried out again, and iteration is carried out until the maximum iteration times are reached.
Further, according to an embodiment of the present invention, in the step d, LEVKOV filtering divides the signal into a linear section and a nonlinear section according to the amplitude and slope characteristics of the signal filtered by the EMD-ICA in different sections, and then removes the power frequency noise of the linear section by using a noise whole period mean value filtering method, and removes the power frequency noise of the nonlinear section by using a noise template of the linear section.
In this embodiment, LEVKOV filtering includes:
① The slope D n of the current sample point is calculated according to the following equation:
Dn＝yn+N-yn
Where y is the transient response signal after iterative EMD-ICA filtering, n represents the current sampling point, and the signal y can be expressed as a matrix of 1 xT: y [ y 1,y2,y3,...,yT ], then y n represents the nth sample point; n is the number of sampling points in the whole period of the power frequency interference signal, n=f s/f,fs is the sampling frequency, and f is the power frequency;
② Let d n＝|Dn-Dn-1 |, if d n at all of the q consecutive sampling points starting from the current sampling point is smaller than M, then filtering by using a linear segment method; otherwise, filtering by a nonlinear segment method;
Aiming at the linear section, a power frequency whole period average filtering method is adopted to remove power frequency interference:
calculating the linear offset of the average value of one power frequency periodic signal and the current sampling point, thereby obtaining the filtering result of the current signal, wherein the specific filtering calculation formula is as follows:
Wherein z is a transient response signal after LEVKOV filtering;
aiming at the nonlinear section, the power frequency interference signal of the previous power frequency period is taken as a template to eliminate the power frequency interference in the signal in the current power frequency period:
Calculating a power frequency interference value of a corresponding point in a previous power frequency interference period according to a formula temp n-N＝yn-N-zn-N, taking the power frequency interference value as a power frequency noise template value, and then calculating a filtering result of a current point according to a formula z n＝yn-tempn-N; wherein temp n-N represents the noise at y n-N; ( For example, if the current sampling point is y n, the current sampling point is a few power frequency cycles forward, the corresponding sampling point is y n-N,yn-N, which is not filtered by LEVKOV, and z n-N is filtered by LEVKOV, so Temp n-N represents the noise of the point y n-N. Then, y n is filtered using this as a template. )
The next N-1 sampling points are all filtered by adopting a nonlinear segment method.
According to the scheme, the method and the device for eliminating offset and high-frequency noise in the transient response signals are used for preprocessing the collected transient response signals to eliminate offset and high-frequency noise in the signals; filtering the power frequency interference of the swimming in the signal by iterative EMD-ICA filtering; and finally, carrying out LEVKOV filtering to inhibit residual power frequency interference and harmonic interference in the signals, thus obtaining a final filtering result.
According to the scheme, the method is used for carrying out repeated iterative filtering on the power frequency swimming power frequency interference in the transient response signal by adopting an iterative EMD-ICA method flow, and the input signal of each EMD-ICA filtering is the output signal of the last EMD-ICA filtering so as to gradually reduce the power frequency interference in the signal; aiming at the problems of residual power frequency interference and harmonic interference thereof after iterative EMD-ICA filtering, LEVKOV method is utilized to carry out secondary filtering through linear section mean filtering and nonlinear section noise template filtering, thereby improving the filtering precision of the power frequency interference in transient response signals. In addition, since the EMD-ICA method and LEVKOV method are both time domain methods, the proposed method is also time domain filtering method, and the signal filtering does not generate problems such as delay, phase lag, etc.
According to the scheme, the iterative EMD-ICA method is combined with LEVKOV method, the industrial frequency reference signal is constructed, the iterative EMD-ICA method is adopted to reduce industrial frequency interference of frequency play in transient response, and the LEVKOV method is utilized to further weaken industrial frequency interference and harmonic interference thereof through linear section mean filtering and nonlinear section noise template filtering, so that filtering precision of the industrial frequency interference in the transient response signal is improved.
Further, in order to achieve the above object, the present invention further provides a transient response power frequency interference suppression system, including:
The signal preprocessing module is used for preprocessing the acquired transient response signals of the sensor;
The EMD decomposition module is used for carrying out EMD decomposition on the preprocessed transient response signal to obtain imf components representing the power frequency reference signal;
The iterative ICA separation module constructs an observation signal matrix according to imf components and performs iterative ICA separation until the number of iterations is reached;
And LEVKOV the filtering module is used for LEVKOV filtering the signals subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression.
Based on the scheme, the invention provides the power frequency interference suppression system by the joint iteration ICA and LEVKOV method, which aims at solving the problem that the existing power frequency interference suppression method is difficult to be used for power frequency noise elimination of the transient response of the sensor and combines the characteristics of the transient response signal of the sensor and the characteristics of actual power frequency interference. The basic idea is that the ICA method is firstly used for reducing the power frequency interference of frequency play in transient response by constructing a power frequency interference reference signal through cyclic iteration, and then LEVKOV method is used for further eliminating the power frequency and harmonic interference thereof, so that the filtering effect on the power frequency interference in the transient response of the sensor is improved.
As shown in fig. 2, in the signal preprocessing module, preprocessing the acquired transient response signal according to an embodiment of the present invention includes: de-biasing and low pass filtering. The unbiasing is to avoid the output of the force sensor from shifting, and the unbiasing needs to be performed before the data processing. The low-pass filtering is to avoid the influence of high-frequency noise on the subsequent analysis, and a Butterworth low-pass filter is used for filtering the source signal, wherein the order of the filter is 2, and the cut-off frequency is 1000Hz.
Further, according to an embodiment of the present invention, in the above iterative ICA separation module, the observed signal matrix is configured according to imf components as follows:
And carrying out FFT on IMF components obtained by EMD decomposition, observing amplitude spectrums of the components, selecting the IMF component with the maximum amplitude of about 50Hz, and forming an observation signal matrix with the preprocessed transient response signal.
Further, according to an embodiment of the present invention, in the above-mentioned iterative ICA separation module, iterative ICA separation is performed until the number of iterations is reached:
ICA separation is carried out according to the obtained observation signal matrix to obtain a separated signal, EMD decomposition is carried out on the separated signal, IMF components are selected to construct the observation signal matrix, ICA separation is carried out again, and iteration is carried out until the maximum iteration times are reached.
Further, according to an embodiment of the present invention, in the LEVKOV filtering module, LEVKOV filtering divides the signal into a linear section and a nonlinear section according to the amplitude and slope characteristics of the signal filtered by the EMD-ICA in different sections, and then removes the power frequency noise of the linear section by using a noise whole period mean filtering method, and removes the power frequency noise of the nonlinear section by using a noise template of the linear section.
In this embodiment, LEVKOV filtering includes:
① The slope D n of the current sample point is calculated according to the following equation:
Dn＝yn+N-yn
Where y is the transient response signal after iterative EMD-ICA filtering, n represents the current sampling point, and the signal y can be expressed as a matrix of 1 xT: y [ y 1,y2,y3,...,yT ], then y n represents the nth sample point; n is the number of sampling points in the whole period of the power frequency interference signal, n=f s/f,fs is the sampling frequency, and f is the power frequency;
② Let d n＝|Dn-Dn-1 |, if d n at the continuous q sampling points from the current sampling point is smaller than M, filtering by using a linear segment method; otherwise, filtering by a nonlinear segment method;
Aiming at the linear section, a power frequency whole period average filtering method is adopted to remove power frequency interference:
calculating the linear offset of the average value of one power frequency periodic signal and the current sampling point, thereby obtaining the filtering result of the current signal, wherein the specific filtering calculation formula is as follows:
Wherein z is a transient response signal after LEVKOV filtering;
aiming at the nonlinear section, the power frequency interference signal of the previous power frequency period is taken as a template to eliminate the power frequency interference in the signal in the current power frequency period:
Calculating a power frequency interference value of a corresponding point in a previous power frequency interference period according to a formula temp n-N＝yn-N-zn-N, taking the power frequency interference value as a power frequency noise template value, and then calculating a filtering result of a current point according to a formula z n＝yn-tempn-N; wherein temp n-N represents the noise at y n-N; ( For example, if the current sampling point is y n, the current sampling point is a few power frequency cycles forward, the corresponding sampling point is y n-N,yn-N, which is not filtered by LEVKOV, and z n-N is filtered by LEVKOV, so Temp n-N represents the noise of the point y n-N. Then, y n is filtered using this as a template. )
The next N-1 sampling points are all filtered by adopting a nonlinear segment method.
According to the scheme, the method and the device for eliminating offset and high-frequency noise in the transient response signals are used for preprocessing the collected transient response signals to eliminate offset and high-frequency noise in the signals; filtering the power frequency interference of the swimming in the signal by iterative EMD-ICA filtering; and finally, carrying out LEVKOV filtering to inhibit residual power frequency interference and harmonic interference in the signals, thus obtaining a final filtering result.
According to the scheme, the method is used for carrying out repeated iterative filtering on the power frequency swimming power frequency interference in the transient response signal by adopting an iterative EMD-ICA method flow, and the input signal of each EMD-ICA filtering is the output signal of the last EMD-ICA filtering so as to gradually reduce the power frequency interference in the signal; aiming at the problems of residual power frequency interference and harmonic interference thereof after iterative EMD-ICA filtering, LEVKOV method is utilized to carry out secondary filtering through linear section mean filtering and nonlinear section noise template filtering, thereby improving the filtering precision of the power frequency interference in transient response signals. In addition, since the EMD-ICA method and LEVKOV method are both time domain methods, the proposed method is also time domain filtering method, and the signal filtering does not generate problems such as delay, phase lag, etc.
According to the scheme, the iterative EMD-ICA method is combined with LEVKOV method, the industrial frequency reference signal is constructed, the iterative EMD-ICA method is adopted to reduce industrial frequency interference of frequency play in transient response, and the LEVKOV method is utilized to further weaken industrial frequency interference and harmonic interference thereof through linear section mean filtering and nonlinear section noise template filtering, so that filtering precision of the industrial frequency interference in the transient response signal is improved.
Further, in order to achieve the above object, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, where the computer program when executed by the processor implements the transient response power frequency interference suppression method as described above.
Further, in order to achieve the above object, the present invention further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the transient response power frequency interference suppression method as described above.
Based on the above-described aspects of the present invention, the aspects of the present invention will be described in detail below by way of one specific embodiment with reference to the accompanying drawings.
Example 1
As shown in FIG. 2, firstly, preprocessing the acquired transient response signal to eliminate offset and high-frequency noise in the signal; then, filtering the power frequency interference of the swimming in the signal by iterative EMD-ICA filtering; and finally, carrying out LEVKOV filtering to inhibit residual power frequency interference and harmonic interference in the signals, thus obtaining a final filtering result.
The transient response signal preprocessing is to perform bias removal and low-pass filtering on the acquired transient response signal s so as to eliminate the influence caused by self bias and high-frequency noise of the sensor in the process of acquiring the signal, and obtain a preprocessed signal x.
The specific method for unbiasing comprises the following steps: and observing and analyzing the acquired transient response signals, intercepting steady-state part data of the signals, calculating an average value, and then subtracting the average value from the whole transient response signals to obtain the unbiased signals.
And the low-pass filtering is to filter the unbiased signal by adopting a Butterworth low-pass filter with the low-pass cut-off frequency of 1000Hz to obtain a filtered signal x.
As shown in fig. 3, iterative EMD-ICA filtering, that is, EMD decomposition is performed on the transient response signal x after pretreatment, the IMF component obtained by the decomposition is analyzed, then a suitable IMF component is selected to construct an observation signal matrix, and iterative ICA separation is performed until the number of iterations is reached. The iterative EMD-ICA filtering process is as follows: EMD decomposition, constructing an observation signal matrix, and iterative ICA separation.
EMD decomposition: EMD decomposition is carried out on the preprocessed signal x, and each IMF component is obtained.
Constructing an observation signal matrix: the IMF components obtained by EMD decomposition are subjected to FFT, the amplitude spectrum of each component is observed, the IMF component r with the maximum amplitude near 50Hz is selected, and an observation signal matrix X= [ X, r ] T is formed by the IMF component r and the transient response signal after pretreatment.
Iterative ICA separation: the ICA separation is carried out according to the obtained observation signal matrix X= [ X, r ] T to obtain a separated signal y temp, EMD decomposition is carried out on the separated signal, then a proper IMF component is selected to construct an observation signal matrix, ICA separation is carried out again, and the iteration is carried out until the maximum iteration times are reached, so that a filtered signal y is obtained.
LEVKOV filtering: the filtering result y obtained by the iteration ICA is filtered again LEVKOV, and is divided into a linear section (a stable section) and a nonlinear section (a pulsation section) according to the amplitude and slope characteristics of the signal in different sections, the power frequency noise of the linear section is eliminated by using a noise whole period mean value filtering method, and the power frequency noise of the nonlinear section is eliminated by using a noise template of the linear section. The conditions for determining the nonlinear segment are: if d n at the continuous q sampling points from the current sampling point is smaller than M, filtering by using a linear segment method, wherein d n is the difference value between two adjacent sampling points; otherwise filtering by a nonlinear segment method. Assuming that the signal to be LEVKOV filtered is y, the specific filtering steps of LEVKOV method are as follows:
① The slope (differential value) of the current sampling point is calculated according to the following equation,
Dn＝yn+N-yn
Wherein y is a transient response signal subjected to EMD-ICA filtering, N is the number of sampling points of the whole period of the power frequency interference signal, namely N=f s/f,fs is the sampling frequency, and f is the power frequency.
② Let d n＝|Dn-Dn-1 |, if d n at the continuous q sampling points from the current sampling point is smaller than M, filtering by using a linear segment method; otherwise filtering by a nonlinear segment method.
For the linear section, a power frequency whole period mean value filtering method is adopted to remove power frequency interference, namely, the linear offset of the average value of a power frequency periodic signal and a current point is calculated, so that a filtering result of the current signal is obtained, and a specific filtering calculation formula is as follows:
Wherein z is a transient response signal after LEVKOV filtering;
Aiming at the nonlinear section, the power frequency interference signal in the previous power frequency period is taken as a template to eliminate the power frequency interference in the signal in the current power frequency period; that is, the power frequency interference value of the corresponding point in the previous power frequency interference period is calculated according to the formula temp n-N＝yn-N-zn-N, the power frequency interference value is taken as the power frequency noise template value, and then the filtering result of the current point is calculated according to the formula z n＝yn-tempn-N. The next N-1 sampling points are all filtered by adopting a nonlinear segment method.
The filtering result LEVKOV is the final filtering result of the transient response.
As can be seen from fig. 4 and 5, the power frequency and harmonic interference thereof in the sensor step response signal are greatly reduced, and the effective signal is not obviously distorted. As can be seen from the time domain waveforms before and after filtering shown in fig. 4, in the initial section and the stationary section of the sensor step response signal, the fluctuation caused by the power frequency interference is almost completely eliminated, the power frequency interference in the transient process is effectively suppressed, the waveform is not obviously distorted, and no time delay exists; also, as can be seen from the spectrum diagrams before and after the filtering shown in fig. 5, the interference amplitude of the frequency spectrum curve of the sensor step response at the power frequency and the harmonic frequency thereof is greatly attenuated, the curve at the corresponding frequency point becomes smoother, the transient response spectrum in the sensor step response is kept better, and the condition of excessively inhibiting the interference amplitude at the power frequency and the harmonic frequency thereof does not occur.
Those of ordinary skill in the art will appreciate that the modules and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and device described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment of the invention.
In addition, each functional module in the embodiment of the present invention may be integrated in one processing module, or each module may exist alone physically, or two or more modules may be integrated in one module.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method for energy saving signal transmission/reception of the various embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application referred to in the present application is not limited to the specific combinations of the technical features described above, but also covers other technical features formed by any combination of the technical features described above or their equivalents without departing from the inventive concept. Such as the above-mentioned features and the technical features disclosed in the present application (but not limited to) having similar functions are replaced with each other.
It should be understood that, the sequence numbers of the steps in the summary and the embodiments of the present invention do not necessarily mean the order of execution, and the execution order of the processes should be determined by the functions and the internal logic, and should not be construed as limiting the implementation process of the embodiments of the present invention.
Claims (9)
1. The transient response power frequency interference suppression method is characterized by comprising the following steps of:
Preprocessing the acquired sensor transient response signals;
EMD decomposition is carried out on the transient response signals after pretreatment, so that imf components representing power frequency reference signals are obtained;
Constructing an observation signal matrix according to imf components, and performing iterative ICA separation until the number of iterations is reached;
and LEVKOV, filtering the signal subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression.
2. The method for suppressing transient response power frequency interference according to claim 1, wherein the preprocessing the collected transient response signal comprises: de-biasing and low pass filtering.
3. The method of claim 1, wherein the constructing an observation signal matrix according to imf components is:
And carrying out FFT on IMF components obtained by EMD decomposition, observing amplitude spectrums of the components, selecting the IMF component with the maximum amplitude of about 50Hz, and forming an observation signal matrix with the preprocessed transient response signal.
4. The method for suppressing transient response power frequency interference according to claim 1, wherein the iterative ICA separation is performed until the number of iterations is reached:
ICA separation is carried out according to the obtained observation signal matrix to obtain a separated signal, EMD decomposition is carried out on the separated signal, IMF components are selected to construct the observation signal matrix, ICA separation is carried out again, and iteration is carried out until the maximum iteration times are reached.
5. The transient response power frequency interference suppression method according to claim 1, wherein the LEVKOV filtering divides the signal into a linear section and a nonlinear section according to the amplitude and slope characteristics of the signal filtered by the EMD-ICA in different sections, then removes power frequency noise of the linear section by using a noise whole period mean value filtering method, and removes power frequency noise of the nonlinear section by using a noise template of the linear section.
6. The method of any one of claims 1-5, wherein the LEVKOV filtering includes:
① The slope D n of the current sample point is calculated according to the following equation:
Dn＝yn+N-yn
Where y is the transient response signal after iterative EMD-ICA filtering, n represents the current sampling point, and the signal y can be expressed as a matrix of 1 xT: y [ y 1,y2,y3,...,yT ], then y n represents the nth sample point; n is the number of sampling points in the whole period of the power frequency interference signal, n=f s/f,fs is the sampling frequency, and f is the power frequency;
② Let d n＝|Dn-Dn-1 |, if d n at all of the q consecutive sampling points starting from the current sampling point is smaller than M, then filtering by using a linear segment method; otherwise, filtering by a nonlinear segment method;
Aiming at the linear section, a power frequency whole period average filtering method is adopted to remove power frequency interference:
calculating the linear offset of the average value of one power frequency periodic signal and the current sampling point, thereby obtaining the filtering result of the current signal, wherein the specific filtering calculation formula is as follows:
Wherein z is a transient response signal after LEVKOV filtering;
aiming at the nonlinear section, the power frequency interference signal of the previous power frequency period is taken as a template to eliminate the power frequency interference in the signal in the current power frequency period:
Calculating a power frequency interference value of a corresponding point in a previous power frequency interference period according to a formula temp n-N＝yn-N-zn-N, taking the power frequency interference value as a power frequency noise template value, and then calculating a filtering result of a current point according to a formula z n＝yn-tempn-N; wherein temp n-N represents the noise at y n-N;
the next N-1 sampling points are all filtered by adopting a nonlinear segment method.
7. The transient response power frequency interference suppression system is characterized by comprising:
The signal preprocessing module is used for preprocessing the acquired transient response signals of the sensor;
The EMD decomposition module is used for carrying out EMD decomposition on the preprocessed transient response signal to obtain imf components representing the power frequency reference signal;
The iterative ICA separation module constructs an observation signal matrix according to imf components and performs iterative ICA separation until the number of iterations is reached;
And LEVKOV the filtering module is used for LEVKOV filtering the signals subjected to the filtering of the EMD-ICA to complete the transient response power frequency interference suppression.
8. An electronic device comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the transient response power frequency interference suppression method of any one of claims 1 to 6.
9. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when executed by a processor, the computer program implements the transient response power frequency interference suppression method according to any one of claims 1 to 6.
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