CN110601722B - Carrier signal-based active identification method and device for electric appliance - Google Patents

Carrier signal-based active identification method and device for electric appliance Download PDF

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CN110601722B
CN110601722B CN201910758980.4A CN201910758980A CN110601722B CN 110601722 B CN110601722 B CN 110601722B CN 201910758980 A CN201910758980 A CN 201910758980A CN 110601722 B CN110601722 B CN 110601722B
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electric appliance
original signal
inductor
resistor
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CN110601722A (en
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吴晓薇
陈建文
张前进
陈广义
陈康划
叶大贵
许仁俊
王秋虹
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Foshan University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
    • H04B3/54—Systems for transmission via power distribution lines
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B3/00—Line transmission systems
    • H04B3/54—Systems for transmission via power distribution lines
    • H04B3/546—Combination of signalling, telemetering, protection
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Abstract

The invention discloses an electrical appliance active identification method based on a carrier signal and a device thereof, the identification method transmits the carrier signal to an electrical appliance to be detected through a power line, the carrier signal can generate an original signal after passing through the electrical appliance to be detected, then clutter elimination processing is carried out on the original signal to obtain a signal to be detected, the signal to be detected and a reference signal are compared to obtain an error value, the type of the electrical appliance to be detected is judged according to the comparison between the error value and a first threshold value, the type of the electrical appliance stored in a database is updated, the detection accuracy is high, and the method is suitable for detection of various types of electrical appliances.

Description

Carrier signal-based active identification method and device for electric appliance
Technical Field
The invention relates to the technical field of electrical appliance identification, in particular to an electrical appliance active identification method and device based on carrier signals.
Background
In recent years, the use of illegal electrical appliances in students' dormitories of colleges and universities in China causes a plurality of safety accidents, and simultaneously, the following data are displayed according to the ministry of public security: in the fire occurrence proportion of China, the number of electric appliance fires is ranked at the head, people in dormitories are dense, and once a fire occurs, the consequences are unimaginable. Therefore, in order to practically strengthen the safe power utilization management and eliminate potential safety hazards, the use of high-power electric appliances in the Ming dynasty student dormitories of multiple institutes is strictly forbidden. But some students can use the students in a dormitory in a stealing way, and great hidden danger is brought to the safety of the students. However, in the examination process, due to different school students of different specialties in high schools, the examination time of the host tube and the cadres of the students is not fixed, which brings great inconvenience to both parties.
The method comprises the steps of firstly, acquiring the current value of an unknown electric appliance, forming a current value sequence chart of the electric appliance, applying fast Fourier transform to convert data, preprocessing the data, fitting a function through a least square method, comparing the data in a database, and matching to obtain the electric appliance. But the calculated signal parameters are inaccurate, the precision is low, and the database cannot be automatically updated; secondly, the load recognizer is used for directly recognizing the electric appliances, but the cost is relatively high, and some special electric appliances cannot be recognized; thirdly, the APP is used for collecting electric signals, electric fingerprint information of the electric appliance is determined, the electric fingerprint information is matched with the working state of the electric appliance according to fingerprints in a database, and the electric fingerprint information is not suitable for analyzing nonlinear and non-stationary signals due to large phase difference. In summary, the existing appliance identification schemes have the defects of low detection accuracy and low applicability.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: an electrical appliance active identification method based on carrier signals and a device thereof are provided.
The solution of the invention for solving the technical problem is as follows:
an electrical appliance active identification method based on carrier signals comprises the following steps:
step 100, generating a carrier signal, and coupling the carrier signal to a power line;
step 200, after a carrier signal passes through an electric appliance to be tested, generating an original signal and collecting the original signal;
step 300, performing clutter elimination processing on the original signal to obtain a signal to be detected;
step 400, extracting the existing electric appliance types in the database one by one, extracting the corresponding LRC value according to the electric appliance types, and generating a reference circuit according to the extracted LRC value;
step 500, inputting the carrier signal into a reference circuit according to the reference circuit generated by the type of the electric appliance and the coupled carrier signal, simulating an output signal generated by the reference circuit, and defining the obtained output signal as a reference signal;
step 600, comparing the signal to be detected with a reference signal to obtain an error value between the signal to be detected and the reference signal;
step 700, determining whether the error value is smaller than a set first threshold, if so, outputting the corresponding appliance type, if not, updating the database, and adding a new appliance type and the corresponding LRC value in the database.
As a further improvement of the above technical solution, in step 100, the carrier signal is one of a sine function signal, an exponential function signal, an exponentially decaying oscillation function signal, a sampling function signal, and a bell-shaped function signal.
As a further improvement of the above technical solution, in step 400, the reference circuit is one of a resistor-inductor-capacitor parallel resonant circuit, a resistor-inductor-capacitor series resonant circuit, a resistor-inductor series resonant circuit, a resistor-capacitor series resonant circuit, an inductor-capacitor series resonant circuit, a resistor-inductor parallel resonant circuit, a resistor-capacitor parallel resonant circuit, and an inductor-capacitor parallel resonant circuit.
As a further improvement of the above technical solution, step 200 includes the following steps:
step 210, performing signal attenuation operation on the original signal;
step 220, performing pre-amplification operation on the original signal;
step 230, performing dispersion, tracking and sampling operations on the original signal;
step 240, performing post-amplification operation on the original signal;
step 250, performing digital operation on the original signal;
and step 260, translating the digitized original signal into a waveform and outputting the waveform.
As a further improvement of the above technical solution, step 300 includes the following steps:
step 310, for the primitiveSampling the signal to obtain non-periodic sequence x [ k ] satisfying certain constraint condition]，
Figure BDA0002169678750000031
Step 320, performing Fourier transform on the original signal to obtain a non-periodic sequence x [ k ]]The frequency spectrum of (a) is,
Figure BDA0002169678750000032
step 330, adaptively segmenting the aperiodic sequence x [ k ]]Of the non-periodic sequence x [ k ]]Support [0, π ] in the spectrum of]Divided into N successive parts by ωnRepresenting the boundaries between the parts, N being [0, N]，ωnSelecting the maximum point as a middle point between two adjacent maximum points in the frequency spectrum;
step 340, construct an empirical wavelet for each ωnIs a center and has a width Tn＝2τnDefining transition sections and respectively obtaining empirical wavelet function psin(t) Fourier transform
Figure BDA0002169678750000041
And empirical scale function
Figure BDA0002169678750000042
Fourier transform of
Figure BDA0002169678750000043
Wherein
Figure BDA0002169678750000044
Figure BDA0002169678750000045
β(x)＝x4(35-84x+70x2-20x3)，τn＝γωn；
Step 350, detecting the amplitude of the maximum value point in the frequency domain range of the frequency spectrum of the non-periodic sequence xk, arranging the obtained amplitudes of the maximum value points according to a decreasing rule, carrying out normalization operation, setting a second threshold value, setting the number of the maximum value points lower than the second threshold value as M, and solving a boundary by taking the first M maximum value points;
step 360, solving empirical mode, defining empirical wavelet transform
Figure BDA0002169678750000046
The detail coefficients are defined by empirical wavelet function psin(t) inner product with the original signal f (t),
Figure BDA0002169678750000047
approximation coefficient passing through scale function
Figure BDA0002169678750000048
Inner product with the original signal f (t),
Figure BDA0002169678750000049
wherein
Figure BDA00021696787500000410
Respectively represent psin(t) and
Figure BDA00021696787500000411
f (ω) represents the complex conjugate of the inverse of F (t), F-1[·]Representing an inverse fourier transform operation;
step 370, reconstructing the original signal to obtain a signal to be measured,
Figure BDA0002169678750000051
wherein x represents the operation of convolution,
Figure BDA0002169678750000052
and
Figure BDA0002169678750000053
respectively represent
Figure BDA0002169678750000054
And
Figure BDA0002169678750000055
fourier transform of (1);
step 380, solving modal experience fk(t), and f0(t) represents fk(t) an initial state, defining the relationship,
Figure BDA0002169678750000056
step 390, after obtaining the empirical mode of the signal to be measured, performing hilbert transform on each empirical mode function to obtain a hilbert spectrum of the function to be measured.
The invention also discloses a device for actively identifying the electrical appliance based on the carrier signal, which comprises the following components:
a signal generator for generating a carrier signal;
a coupler coupling the carrier signal to the power line;
the signal acquisition module is used for acquiring an original signal generated after the carrier signal passes through the electric appliance to be tested;
the signal processing module is used for performing clutter elimination processing on the original signal to obtain a signal to be detected;
the database stores a plurality of electric appliance types and LRC values corresponding to the electric appliance types;
the extraction module is used for extracting the existing electric appliance types in the database, extracting the corresponding LRC values according to the electric appliance types, and generating a reference circuit according to the extracted LRC values;
the simulation module is used for inputting the carrier signal into the reference circuit and simulating an output signal generated by the reference circuit according to the reference circuit generated by the type of the electric appliance and the coupled carrier signal, and defining the obtained output signal as the reference signal;
the difference making module is used for comparing and making a difference between the signal to be detected and the reference signal to obtain an error value between the signal to be detected and the reference signal;
the comparison module is used for judging whether the error value is smaller than a set first threshold value or not;
the output module is used for outputting the corresponding type of the electric appliance when the error value is smaller than a first threshold value;
and the updating module is used for updating the database when the error value is larger than the first threshold value, and adding a new electric appliance type and the LRC value corresponding to the new electric appliance type in the database.
As a further improvement of the above technical solution, the carrier signal output by the signal generator is one of a sine function signal, an exponential function signal, an exponentially decaying oscillation function signal, a sampling function signal, and a bell-shaped function signal.
As a further improvement of the above technical solution, the reference circuit generated in the extraction module is one of a resistance inductance capacitance parallel resonance circuit, a resistance inductance capacitance series resonance circuit, a resistance capacitance series resonance circuit, an inductance capacitance series resonance circuit, a resistance inductance parallel resonance circuit, a resistance capacitance parallel resonance circuit, and an inductance capacitance parallel resonance circuit.
As a further improvement of the above technical solution, the signal acquisition module includes:
the attenuation unit is used for carrying out signal attenuation operation on the original signal;
the pre-amplification unit is used for carrying out pre-amplification operation on the original signal;
the preprocessing unit is used for performing dispersion, tracking and sampling operations on the original signal;
the post-amplification unit is used for carrying out post-amplification operation on the original signal;
the signal conversion unit is used for carrying out digital operation on the original signal;
the translation unit is used for translating the digitized original signal into a waveform;
and the display unit is used for outputting the waveform obtained by translating the original signal.
The invention has the beneficial effects that: the invention transmits a carrier signal to the electric appliance to be detected through the power line, the carrier signal can generate an original signal after passing through the electric appliance to be detected, then clutter elimination processing is carried out on the original signal to obtain a signal to be detected, the signal to be detected is compared with the reference signal to obtain an error value, the type of the electric appliance to be detected is judged according to the comparison between the error value and the first threshold value, the type of the electric appliance stored in the database is updated, the detection accuracy is high, and the method is suitable for detection of various types of electric appliances.
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In order to more clearly illustrate the technical solution in the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly described below. It is clear that the described figures are only some embodiments of the invention, not all embodiments, and that a person skilled in the art can also derive other designs and figures from them without inventive effort.
FIG. 1 is a schematic flow chart of the identification method of the present invention;
fig. 2 is a schematic structural diagram of the identification device of the present invention.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the features and the effects of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all embodiments, and other embodiments obtained by those skilled in the art without inventive efforts based on the embodiments of the present application belong to the protection scope of the present application. In addition, all the connection relations mentioned herein do not mean that the components are directly connected, but mean that a better connection structure can be formed by adding or reducing connection accessories according to the specific implementation situation. All technical characteristics in the invention can be interactively combined on the premise of not conflicting with each other. Finally, it should be noted that the terms "center, upper, lower, left, right, vertical, horizontal, inner, outer" and the like as used herein refer to an orientation or positional relationship based on the drawings, which is only for convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application.
Referring to fig. 1, the present application discloses a method for actively identifying an electrical appliance based on a carrier signal, wherein a first embodiment of the method comprises the following steps:
step 100, generating a carrier signal, and coupling the carrier signal to a power line;
step 200, after a carrier signal passes through an electric appliance to be tested, generating an original signal and collecting the original signal;
step 300, performing clutter elimination processing on the original signal to obtain a signal to be detected;
step 400, extracting the existing electric appliance types in the database one by one, extracting the corresponding LRC (inductance, resistance, capacitance) values according to the electric appliance types, and generating a reference circuit according to the extracted LRC values;
step 500, inputting the carrier signal into a reference circuit according to the reference circuit generated by the type of the electric appliance and the coupled carrier signal, simulating an output signal generated by the reference circuit, and defining the obtained output signal as a reference signal;
step 600, comparing the signal to be detected with a reference signal to obtain an error value between the signal to be detected and the reference signal;
step 700, determining whether the error value is smaller than a set first threshold, if so, outputting the corresponding appliance type, if not, updating the database, and adding a new appliance type and the corresponding LRC value in the database.
The so-called appliance type includes two contents, one is the model of the appliance, and the other is one or more operation modes corresponding to the appliances of each model, that is, the final result of this embodiment is to output the determined appliance model and its corresponding operation mode, or to update the appliance model and its corresponding operation module and LRC value in the database.
Specifically, in the embodiment, a carrier signal is transmitted to the electrical appliance to be detected through the power line, the carrier signal can generate an original signal after passing through the electrical appliance to be detected, then the clutter cancellation processing is performed on the original signal to obtain a signal to be detected, an error value obtained by comparing the signal to be detected with the reference signal is compared with a first threshold value, the type of the electrical appliance to be detected is judged according to the comparison result, the type of the electrical appliance stored in the database is updated, the detection accuracy is high, and the method is suitable for detection of various types of electrical appliances.
Of course, after the step 700 is completed, that is, after the database updating operation is completed, the method needs to return to the step 400, and the operations from the step 400 to the step 700 are executed again, and the comparison with the set first threshold is performed again, so as to determine whether the updated appliance type in the database and the LRC value corresponding to the updated appliance type in the database are accurate.
Further preferably, in step 100 of this embodiment, the carrier signal is one of a sine function signal, an exponential function signal, an exponentially decaying oscillation function signal, a sampling function signal, and a bell function signal.
Further preferably, in step 400 of this embodiment, the reference circuit is one of a resistor-inductor-capacitor parallel resonant circuit, a resistor-inductor-capacitor series resonant circuit, a resistor-inductor series resonant circuit, a resistor-capacitor series resonant circuit, an inductor-capacitor series resonant circuit, a resistor-inductor parallel resonant circuit, a resistor-capacitor parallel resonant circuit, and an inductor-capacitor parallel resonant circuit.
Further as a preferred implementation manner, in this embodiment, the step 200 is mainly used for processing, identifying, digitizing and outputting the original signal, and includes the following steps:
step 210, performing signal attenuation operation on the original signal;
step 220, performing pre-amplification operation on the original signal;
step 230, performing dispersion, tracking and sampling operations on the original signal;
step 240, performing post-amplification operation on the original signal;
step 250, performing digital operation on the original signal;
and step 260, translating the digitized original signal into a waveform and outputting the waveform.
The steps 210, 220 and 240 are mainly used to artificially modify the amplitude of the original signal to prevent the collected original signal from being too large or too small, so that the attenuation operation is preferentially performed, mainly to improve the resolution of the original signal to improve the accuracy of outputting the original signal waveform.
Further as a preferred implementation, in this embodiment, the step 300 includes the following steps:
step 310, sampling the original signal to obtain a non-periodic sequence x [ k ] satisfying a certain constraint condition]，
Figure BDA0002169678750000101
Step 320, performing Fourier transform on the original signal to obtain a non-periodic sequence x [ k ]]The frequency spectrum of (a) is,
Figure BDA0002169678750000102
step 330, adaptively segmenting the aperiodic sequence x [ k ]]Of the non-periodic sequence x [ k ]]Support [0, π ] in the spectrum of]Divided into N successive parts by ωnRepresenting the boundaries between the parts, N being [0, N]，ωnSelecting the maximum point as a middle point between two adjacent maximum points in the frequency spectrum;
step 340, construct an empirical wavelet for each ωnIs a center and has a width Tn＝2τnDefining transition sections and respectively obtaining empirical wavelet function psin(t) Fourier transform
Figure BDA0002169678750000111
And empirical scale function
Figure BDA0002169678750000112
Fourier transform of
Figure BDA0002169678750000113
Wherein
Figure BDA0002169678750000114
Figure BDA0002169678750000115
β(x)＝x4(35-84x+70x2-20x3)，τn＝γωn；
Step 350, detecting the amplitude of the maximum value point in the frequency domain range of the frequency spectrum of the non-periodic sequence xk, arranging the obtained amplitudes of the maximum value points according to a decreasing rule, carrying out normalization operation, setting a second threshold value, setting the number of the maximum value points lower than the second threshold value as M, and solving a boundary by taking the first M maximum value points;
step 360, solving empirical mode, defining empirical wavelet transform
Figure BDA0002169678750000116
The detail coefficients are defined by empirical wavelet function psin(t) inner product with the original signal f (t),
Figure BDA0002169678750000117
approximation coefficient passing through scale function
Figure BDA0002169678750000118
Inner product with the original signal f (t),
Figure BDA0002169678750000119
wherein
Figure BDA00021696787500001110
Respectively represent psin(t) and
Figure BDA00021696787500001111
f (ω) denotes the inverse of f (t)Transformed complex conjugate, F-1[·]Representing an inverse fourier transform operation;
step 370, reconstructing the original signal to obtain a signal to be measured,
Figure BDA0002169678750000121
wherein x represents the operation of convolution,
Figure BDA0002169678750000122
and
Figure BDA0002169678750000123
respectively represent
Figure BDA0002169678750000124
And
Figure BDA0002169678750000125
fourier transform of (1);
step 380, solving modal experience fk(t), and f0(t) represents fk(t) an initial state, defining the relationship,
Figure BDA0002169678750000126
step 390, after obtaining the empirical mode of the signal to be measured, performing hilbert transform on each empirical mode function to obtain a hilbert spectrum of the function to be measured.
Referring to fig. 2, the present application also discloses an electrical appliance identification apparatus based on carrier signals, and a first embodiment of the apparatus includes:
a signal generator for generating a carrier signal;
a coupler coupling the carrier signal to the power line;
the signal acquisition module is used for acquiring an original signal generated after the carrier signal passes through the electric appliance to be tested;
the signal processing module is used for performing clutter elimination processing on the original signal to obtain a signal to be detected;
the database stores a plurality of electric appliance types and LRC values corresponding to the electric appliance types;
the extraction module is used for extracting the existing electric appliance types in the database, extracting the corresponding LRC values according to the electric appliance types, and generating a reference circuit according to the extracted LRC values;
the simulation module is used for inputting the carrier signal into the reference circuit and simulating an output signal generated by the reference circuit according to the reference circuit generated by the type of the electric appliance and the coupled carrier signal, and defining the obtained output signal as the reference signal;
the difference making module is used for comparing and making a difference between the signal to be detected and the reference signal to obtain an error value between the signal to be detected and the reference signal;
the comparison module is used for judging whether the error value is smaller than a set first threshold value or not;
the output module is used for outputting the corresponding type of the electric appliance when the error value is smaller than a first threshold value;
and the updating module is used for updating the database when the error value is larger than the first threshold value, and adding a new electric appliance type and the LRC value corresponding to the new electric appliance type in the database.
Further preferably, in this embodiment, the carrier signal output by the signal generator is one of a sine function signal, an exponential function signal, an exponentially decaying oscillation function signal, a sampling function signal, and a bell function signal.
Further preferably, in this embodiment, the reference circuit generated in the extracting module is one of a resistor-inductor-capacitor parallel resonant circuit, a resistor-inductor-capacitor series resonant circuit, a resistor-inductor series resonant circuit, a resistor-capacitor series resonant circuit, an inductor-capacitor series resonant circuit, a resistor-inductor parallel resonant circuit, a resistor-capacitor parallel resonant circuit, and an inductor-capacitor parallel resonant circuit.
Further as a preferred implementation manner, in this embodiment, the signal acquisition module includes:
the attenuation unit is used for carrying out signal attenuation operation on the original signal;
the pre-amplification unit is used for carrying out pre-amplification operation on the original signal;
the preprocessing unit is used for performing dispersion, tracking and sampling operations on the original signal;
the post-amplification unit is used for carrying out post-amplification operation on the original signal;
the signal conversion unit is used for carrying out digital operation on the original signal;
the translation unit is used for translating the digitized original signal into a waveform;
and the display unit is used for outputting the waveform obtained by translating the original signal.
While the preferred embodiments of the present invention have been described in detail, it should be understood that the invention is not limited to those precise embodiments, and that various changes and modifications may be effected therein by one skilled in the art without departing from the scope or spirit of the invention as defined in the appended claims.

Claims (8)

1. An electrical appliance active identification method based on carrier signals is characterized by comprising the following steps:
step 100, generating a carrier signal, and coupling the carrier signal to a power line;
step 200, after a carrier signal passes through an electric appliance to be tested, generating an original signal and collecting the original signal;
step 300, performing clutter elimination processing on the original signal to obtain a signal to be detected;
step 400, extracting the existing electric appliance types in the database one by one, extracting the corresponding LRC value according to the electric appliance types, and generating a reference circuit according to the extracted LRC value;
in step 400, the reference circuit is one of a resistor-inductor-capacitor parallel resonance circuit, a resistor-inductor-capacitor series resonance circuit, a resistor-inductor series resonance circuit, a resistor-capacitor series resonance circuit, an inductor-capacitor series resonance circuit, a resistor-inductor parallel resonance circuit, a resistor-capacitor parallel resonance circuit, and an inductor-capacitor parallel resonance circuit;
step 500, inputting the carrier signal into a reference circuit according to the reference circuit generated by the type of the electric appliance and the coupled carrier signal, simulating an output signal generated by the reference circuit, and defining the obtained output signal as a reference signal;
step 600, comparing the signal to be detected with a reference signal to obtain an error value between the signal to be detected and the reference signal;
step 700, determining whether the error value is smaller than a set first threshold, if so, outputting the corresponding appliance type, if not, updating the database, and adding a new appliance type and the corresponding LRC value in the database.
2. The method for actively identifying an electric appliance according to claim 1, wherein in step 100, the carrier signal is one of a sine function signal, an exponential function signal, an exponentially decaying oscillation function signal, a sampling function signal and a bell function signal.
3. The active identification method for an electric appliance based on a carrier signal as claimed in claim 1, wherein the step 200 comprises the following steps:
step 210, performing signal attenuation operation on the original signal;
step 220, performing pre-amplification operation on the original signal;
step 230, performing dispersion, tracking and sampling operations on the original signal;
step 240, performing post-amplification operation on the original signal;
step 250, performing digital operation on the original signal;
and step 260, translating the digitized original signal into a waveform and outputting the waveform.
4. A method for actively identifying an electrical appliance based on a carrier wave signal as claimed in claim 1 or 3, wherein the step 300 comprises the steps of:
step 310, sampling the original signal to obtain a non-periodic sequence x [ k ] satisfying a certain constraint condition]，
Figure FDA0003230724960000021
Step 320, performing Fourier transform on the original signal to obtain a non-periodic sequence x [ k ]]The frequency spectrum of (a) is,
Figure FDA0003230724960000022
step 330, adaptively segmenting the aperiodic sequence x [ k ]]Of the non-periodic sequence x [ k ]]Support [0, π ] in the spectrum of]Divided into N successive parts by ωnRepresenting the boundaries between the parts, N being [0, N]，ωnSelecting the maximum point as a middle point between two adjacent maximum points in the frequency spectrum;
step 340, construct an empirical wavelet for each ωnIs a center and has a width Tn＝2τnDefining transition sections and respectively obtaining empirical wavelet function psin(t) Fourier transform
Figure FDA0003230724960000023
And empirical scale function
Figure FDA0003230724960000031
Fourier transform of
Figure FDA0003230724960000032
Wherein
Figure FDA0003230724960000033
Figure FDA0003230724960000034
(1-γ)ωn≤|ω|≤(1+γ)ωnWherein β (x) ═ x4(35-84x+70x2-20x3)，τn＝γωn；
Step 350, detecting the amplitude of the maximum value point in the frequency domain range of the frequency spectrum of the non-periodic sequence xk, arranging the obtained amplitudes of the maximum value points according to a decreasing rule, carrying out normalization operation, setting a second threshold value, setting the number of the maximum value points lower than the second threshold value as M, and solving a boundary by taking the first M maximum value points;
step 360, solving empirical mode, defining empirical wavelet transform
Figure FDA0003230724960000035
The detail coefficients are defined by empirical wavelet function psin(t) inner product with the original signal f (t),
Figure FDA0003230724960000036
approximation coefficient passing through scale function
Figure FDA0003230724960000037
Inner product with the original signal f (t),
Figure FDA0003230724960000038
wherein
Figure FDA0003230724960000039
Respectively represent psin(t) and
Figure FDA00032307249600000310
f (ω) represents the complex conjugate of the inverse of F (t), F-1[·]Representing an inverse fourier transform operation;
step 370, reconstructing the original signal to obtain a signal to be measured,
Figure FDA00032307249600000311
wherein x represents the operation of convolution,
Figure FDA00032307249600000312
and
Figure FDA00032307249600000313
respectively represent
Figure FDA00032307249600000314
And
Figure FDA00032307249600000315
fourier transform of (1);
step 380, solving modal experience fk(t), and f0(t) represents fk(t) an initial state, defining the relationship,
Figure FDA0003230724960000041
step 390, after obtaining the empirical mode of the signal to be measured, performing hilbert transform on each empirical mode function to obtain a hilbert spectrum of the function to be measured.
5. An active appliance identification device based on carrier signals, comprising:
a signal generator for generating a carrier signal;
a coupler coupling the carrier signal to the power line;
the signal acquisition module is used for acquiring an original signal generated after the carrier signal passes through the electric appliance to be tested;
the signal processing module is used for performing clutter elimination processing on the original signal to obtain a signal to be detected;
the database stores a plurality of electric appliance types and LRC values corresponding to the electric appliance types;
the extraction module is used for extracting the existing electric appliance types in the database, extracting the corresponding LRC values according to the electric appliance types, and generating a reference circuit according to the extracted LRC values;
the simulation module is used for inputting the carrier signal into the reference circuit and simulating an output signal generated by the reference circuit according to the reference circuit generated by the type of the electric appliance and the coupled carrier signal, and defining the obtained output signal as the reference signal;
the difference making module is used for comparing and making a difference between the signal to be detected and the reference signal to obtain an error value between the signal to be detected and the reference signal;
the comparison module is used for judging whether the error value is smaller than a set first threshold value or not;
the output module is used for outputting the corresponding type of the electric appliance when the error value is smaller than a first threshold value;
and the updating module is used for updating the database when the error value is larger than the first threshold value, and adding a new electric appliance type and the LRC value corresponding to the new electric appliance type in the database.
6. The active appliance identification device based on the carrier signal as claimed in claim 5, wherein the carrier signal outputted from the signal generator is one of a sine function signal, an exponential function signal, an exponentially decaying oscillation function signal, a sampling function signal and a bell function signal.
7. The active identification device of an electrical appliance based on a carrier signal according to claim 5, wherein the reference circuit generated in the extraction module is one of a resistor-inductor-capacitor parallel resonant circuit, a resistor-inductor-capacitor series resonant circuit, a resistor-inductor series resonant circuit, a resistor-capacitor series resonant circuit, an inductor-capacitor series resonant circuit, a resistor-inductor parallel resonant circuit, a resistor-capacitor parallel resonant circuit, and an inductor-capacitor parallel resonant circuit.
8. The active identification device of an electrical appliance based on a carrier signal as claimed in claim 5, wherein the signal acquisition module comprises:
the attenuation unit is used for carrying out signal attenuation operation on the original signal;
the pre-amplification unit is used for carrying out pre-amplification operation on the original signal;
the preprocessing unit is used for performing dispersion, tracking and sampling operations on the original signal;
the post-amplification unit is used for carrying out post-amplification operation on the original signal;
the signal conversion unit is used for carrying out digital operation on the original signal;
the translation unit is used for translating the digitized original signal into a waveform;
and the display unit is used for outputting the waveform obtained by translating the original signal.
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