CN113884758A - Direct current electric energy metering method, device, equipment and storage medium - Google Patents
Direct current electric energy metering method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for direct current electric energy metering, and relates to the technical field of electric energy metering. The method comprises the steps of obtaining original sampling data of an electric energy signal; performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer; setting a threshold value and a threshold value function for the wavelet coefficient corresponding to each decomposition layer, and quantizing the wavelet coefficient corresponding to each decomposition layer to obtain a quantized wavelet coefficient; reconstructing the quantized wavelet coefficient to obtain a de-noising signal; performing ripple error correction on the de-noised signal to obtain corrected data; and performing integral calculation on the corrected data by adopting a composite trapezoidal integral method to obtain target electric energy data. The invention can overcome the defect that the window size changes along with the frequency, filter in the whole frequency range and improve the accuracy of output measurement.
Description
Technical Field
The invention relates to the technical field of electric energy metering, in particular to a method, a device, equipment and a storage medium for direct current electric energy metering.
Background
The direct current electric energy can be measured by adopting a direct current voltmeter and a direct current ammeter to respectively measure the effective values of voltage and current, then multiplying the effective values of the voltage and the current to obtain direct current power, and finally calculating the direct current electric energy value, or synchronously sampling the voltage and the current and then calculating the direct current electric energy value by using instantaneous power integration.
The existing direct current metering module uses an electronic type intelligent ammeter, and the metering accuracy mainly depends on a multiplier. When the electric energy is actually measured, because the direct current signal is mixed with noise signals containing ripples and various pulses, an ideal metering result cannot be achieved, and therefore, denoising processing on the sampling signal is an essential link before electric energy calculation.
The traditional frequency domain denoising method converts the analysis domain of the signal from the time domain to the frequency domain by fourier transform, and reduces or eliminates the high frequency component of the signal in the frequency spectrum to reduce the influence of noise on the useful signal. However, in real life, the received signals are not all stationary signals, and although the fourier transform can distinguish the frequency components of the signals, the time when the components with different frequencies appear in the signals cannot be known. The short-time fourier transform segments the signal to be analyzed into a plurality of time windows of equal length, and then performs fourier transform, so that the signal is a stable signal within a limited time width, but the selection of the time windows causes the contradiction between time resolution and frequency resolution. Therefore, the traditional denoising method can suppress signal noise and easily lose edge details in a local time range.
Disclosure of Invention
The invention aims to provide a method, a device, equipment and a storage medium for direct current electric energy metering, which are used for filtering and denoising original sampling data of an electric energy signal so as to solve the problem of poor signal noise suppression effect of the traditional denoising method.
In order to achieve the above object, the present invention provides a method for measuring dc power, comprising:
acquiring original sampling data of the electric energy signal;
performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer;
setting a threshold value and a threshold value function for the wavelet coefficient corresponding to each decomposition layer, and quantizing the wavelet coefficient corresponding to each decomposition layer to obtain a quantized wavelet coefficient;
reconstructing the quantized wavelet coefficient to obtain a de-noising signal;
performing ripple error correction on the de-noised signal to obtain corrected data;
and performing integral calculation on the corrected data by adopting a composite trapezoidal integral method to obtain target electric energy data.
Preferably, the expression of the threshold function is:
where y is the wavelet coefficient after hard thresholding, ωj,kIs the kth wavelet coefficient on the jth scale, TjIs the critical threshold.
Preferably, the original sampling data is obtained by sampling a direct current voltage signal and a direct current signal by using a fixed frequency.
Preferably, the performing wavelet transform on the original sample data according to a preset wavelet basis and a preset number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer includes:
and selecting db3 type wavelets, and performing wavelet transformation on the original sampling data by using 3-layer or 4-layer decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer.
The present invention also provides a dc power metering device, comprising:
the data acquisition module is used for acquiring original sampling data of the electric energy signal;
the de-noising module is used for performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer;
the de-noising module is also used for setting a threshold value and a threshold value function for the wavelet coefficients corresponding to each decomposition layer, and quantizing the wavelet coefficients corresponding to each decomposition layer to obtain quantized wavelet coefficients; reconstructing the quantized wavelet coefficient to obtain a de-noising signal;
the error correction module is used for performing ripple error correction on the de-noised signal to obtain corrected data;
and the integral module is used for carrying out integral calculation on the corrected data by adopting a composite trapezoid integral method to obtain target electric energy data.
Preferably, the expression of the threshold function is:
where y is the wavelet coefficient after hard thresholding, ωj,kIs the kth wavelet coefficient on the jth scale, TjIs the critical threshold.
Preferably, the original sampling data is obtained by sampling a direct current voltage signal and a direct current signal by using a fixed frequency.
Preferably, the denoising module is further configured to select a db3 type wavelet, and perform wavelet transformation on the original sample data by using 3-layer or 4-layer decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer.
The invention also provides a computer terminal device comprising one or more processors and a memory. A memory coupled to the processor for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement the method for direct current power metering as described in any of the embodiments above.
The present invention also provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the method for dc power metering as defined in any one of the above embodiments.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses a direct current electric energy metering method, which comprises the following steps: acquiring original sampling data of the electric energy signal; performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer; setting a threshold value and a threshold value function for the wavelet coefficient corresponding to each decomposition layer, and quantizing the wavelet coefficient corresponding to each decomposition layer to obtain a quantized wavelet coefficient; reconstructing the quantized wavelet coefficient to obtain a de-noising signal; performing ripple error correction on the de-noised signal to obtain corrected data; and performing integral calculation on the corrected data by adopting a composite trapezoidal integral method to obtain target electric energy data. The invention introduces a wavelet threshold denoising method in a modern filtering method to filter the direct current signal, can overcome the defect that the window size changes along with the frequency, can filter in the whole frequency range and improve the accuracy of output measurement.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a dc power metering method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a dc power metering device according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer terminal device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not used as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a schematic flow chart of a dc power metering method according to an embodiment of the present invention. In this embodiment, the method for metering dc power includes the following steps:
s110, acquiring original sampling data of the electric energy signal;
it can be understood that, when the electric energy is actually measured, since the load is constantly changing, the voltage, the current and the phase difference thereof also change in real time, and thus a real-time sampling process is required. In order to make the data more stable and accurate, the original sampling data is obtained by sampling direct current voltage and current signals by using a fixed frequency.
S120, performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer;
s130, setting a threshold value and a threshold function for the wavelet coefficients corresponding to each decomposition layer, and quantizing the wavelet coefficients corresponding to each decomposition layer to obtain quantized wavelet coefficients;
s140, reconstructing the quantized wavelet coefficient to obtain a denoising signal;
s150, performing ripple error correction on the de-noised signal to obtain corrected data;
and S160, performing integral calculation on the corrected data by adopting a composite trapezoidal integral method to obtain target electric energy data.
In this embodiment, the definition of wavelet transform is that after a certain function Ψ (t) called basic wavelet is shifted by b, it is further inner-integrated with the signal f (t) to be analyzed at different scales a, and the wavelet of the signal f (t) is defined as:
wherein, WTfAnd (a, b) is the coefficient of the wavelet transform, and psi (t) is the complex conjugate complex number of psi (t).
Get
a0＞1，b0E.g. R, the corresponding discrete wavelet transform can be obtained:
the data processing steps of the discrete wavelet denoising method comprise: (1) the original sampled data with noise is decomposed with wavelets. The decomposition level and wavelet type are selected, and then the decomposition actual signal is calculated. (2) And performing threshold quantization processing on the high-frequency coefficient of the wavelet decomposition. The threshold is calculated and used to subject the high frequency coefficients of the different decomposition metrics to a soft threshold quantization process. (3) And (5) reconstructing the wavelet. And performing wavelet reconstruction by using the low-frequency coefficient of the bottom layer and the high-frequency coefficient of each layer obtained by the previous decomposition.
The embodiment of the invention improves on the basis of the traditional soft and hard threshold function to overcome the problems of the traditional soft and hard threshold, and the expression of the adopted threshold function is as follows:
where y is the wavelet coefficient after hard thresholding, ωj,kIs the kth wavelet coefficient on the jth scale, TjIs the critical threshold.
Further, to prove the continuity, deviation and progressiveness of the threshold function, the following method may be used for verification:
(1) continuity of the threshold function:
order to
To obtain
And when ω isj,k→Tj +When the temperature of the water is higher than the set temperature,
then
I.e. the function is at TjHas continuity when omegaj,k→-Tj -When the temperature of the water is higher than the set temperature,
then
I.e. the function is at-TjHaving continuity, i.e. improved threshold function at ± TjAll have continuity, i.e. the hard threshold function can be overcome at TjIs not present.
(2) Deviance of threshold function:
when ω isj,kThe time → ∞ of the time,
all the same as omegaj,kThe time is → -infinity,
therefore, it is
I.e. soft thresholds at y and omega can be overcomej,kA constant deviation therebetween.
(3) Asymptotic of threshold function:
when ω isj,kThe time → ∞ of the time,
all the same as omegaj,kThe time is → -infinity,
therefore, it is
In summary, the wavelet threshold function follows | ωj,kThe increase in the value of l is increased,
the value of (d) is decreasing, i.e. the deviation is decreasing, the function is given by y- ωj,kBeing an asymptote, y approaches ω infinitelyj,k. The forensic function may overcome the bias problem of the soft threshold.
In one embodiment, discrete wavelet noise cancellation is used to process the voltage and current signals during the charging of the load. Selecting db3 type wavelet according to load charging characteristics and filtering effect, selecting 3 or 4 layers of decomposition layers, and performing inverse wavelet transform by using the scale coefficient and the wavelet coefficient processed by the threshold value to obtain a normal signal after noise filtering.
In this embodiment, during dc measurement, a voltage signal and a current signal that are generally input into the electric energy meter are not constant and unchangeable dc, and a certain ac component may be included therein, and for this kind of dc electric energy with ripple waves, multiplication by using an effective value may cause multi-measurement of active power, and through derivation, a relative error that the active power is calculated by using the effective value for multiplication may be obtained, and when calculating electric energy, the error is removed to improve accuracy.
In this embodiment, a complex trapezoidal integration method is used to perform integral calculation on the corrected data, and in consideration of the currently used dc metering principle, the method is essentially a rectangular integration method, that is, a power curve is divided into a plurality of rectangles within a period of time, and the integration result of the area of the plurality of rectangles and the equivalent power with respect to time is used. In ac metering, the total area of the separating rectangles is substantially equal to the actual integral value of the power curve due to the periodicity of the power variation, and the error of the front and back offsets is negligible. However, the output direct current signal under the complex working condition is a non-periodic function, and the generated errors are accumulated. In order to improve the accuracy of direct current measurement, a composite trapezoidal integration method with higher accuracy than a rectangular integration method can be adopted, and when the ammeter is in a dynamic measurement condition, the advantage of measurement by using the method is more obvious.
On the basis of analyzing the direct current metering algorithm, aiming at the problem that ripples in direct current electric energy influence the accuracy of electric energy metering, the embodiment of the invention introduces the improved wavelet threshold denoising algorithm, can effectively filter the ripples in direct current signals while keeping the charging characteristics of the original signals, and improves the accuracy of direct current electric energy metering accuracy.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a dc power metering device according to an embodiment of the present invention. In this embodiment, the dc power metering device includes:
a data obtaining module 210, configured to obtain original sampling data of the electrical energy signal;
the denoising module 220 is configured to perform wavelet transformation on the original sample data according to a preset wavelet basis and a preset number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer;
the denoising module 220 is further configured to set a threshold value and a threshold function for the wavelet coefficients corresponding to each decomposition layer, and quantize the wavelet coefficients corresponding to each decomposition layer to obtain quantized wavelet coefficients; reconstructing the quantized wavelet coefficient to obtain a de-noising signal;
an error correction module 230, configured to perform ripple error correction on the denoised signal to obtain corrected data;
and the integral module 240 is configured to perform integral calculation on the corrected data by using a composite trapezoidal integration method to obtain target electric energy data.
The embodiment of the invention improves on the basis of the traditional soft and hard threshold function to overcome the problems of the traditional soft and hard threshold, and the expression of the adopted threshold function is as follows:
where y is the wavelet coefficient after hard thresholding, ωj,kIs the kth wavelet coefficient on the jth scale, TjIs the critical threshold.
Further, to prove the continuity, deviation and progressiveness of the threshold function, the following method may be used for verification:
(1) continuity of the threshold function:
order to
To obtain
And when ω isj,k→Tj +When the temperature of the water is higher than the set temperature,
then
I.e. the function is at TjHas continuity when omegaj,k→-Tj -When the temperature of the water is higher than the set temperature,
then
I.e. the function is at-TjHaving continuity, i.e. improved threshold function at ± TjAll have continuity, i.e. the hard threshold function can be overcome at TjIs not present.
(2) Deviance of threshold function:
when ω isj,kThe time → ∞ of the time,
all the same as omegaj,kThe time is → -infinity,
therefore, it is
I.e. soft thresholds at y and omega can be overcomej,kA constant deviation therebetween.
(3) Asymptotic of threshold function:
when ω isj,kThe time → ∞ of the time,
all the same as omegaj,kThe time is → -infinity,
therefore, it is
In summary, the wavelet threshold function follows | ωj,kThe increase in the value of l is increased,
the value of (d) is decreasing, i.e. the deviation is decreasing, the function is given by y- ωj,kBeing an asymptote, y approaches ω infinitelyj,k. The forensic function may overcome the bias problem of the soft threshold.
In one embodiment, discrete wavelet noise cancellation is used to process the voltage and current signals during the charging of the load. Selecting db3 type wavelet according to load charging characteristics and filtering effect, selecting 3 or 4 layers of decomposition layers, and performing inverse wavelet transform by using the scale coefficient and the wavelet coefficient processed by the threshold value to obtain a normal signal after noise filtering.
In this embodiment, during dc measurement, a voltage signal and a current signal that are generally input into the electric energy meter are not constant and unchangeable dc, and a certain ac component may be included therein, and for this kind of dc electric energy with ripple waves, multiplication by using an effective value may cause multi-measurement of active power, and through derivation, a relative error that the active power is calculated by using the effective value for multiplication may be obtained, and when calculating electric energy, the error is removed to improve accuracy.
In this embodiment, a complex trapezoidal integration method is used to perform integral calculation on the corrected data, and in consideration of the currently used dc metering principle, the method is essentially a rectangular integration method, that is, a power curve is divided into a plurality of rectangles within a period of time, and the integration result of the area of the plurality of rectangles and the equivalent power with respect to time is used. In ac metering, the total area of the separating rectangles is substantially equal to the actual integral value of the power curve due to the periodicity of the power variation, and the error of the front and back offsets is negligible. However, the output direct current signal under the complex working condition is a non-periodic function, and the generated errors are accumulated. In order to improve the accuracy of direct current measurement, a composite trapezoidal integration method with higher accuracy than a rectangular integration method can be adopted, and when the ammeter is in a dynamic measurement condition, the advantage of measurement by using the method is more obvious.
On the basis of analyzing the direct current metering algorithm, aiming at the problem that ripples in direct current electric energy influence the accuracy of electric energy metering, the embodiment of the invention introduces the improved wavelet threshold denoising algorithm, can effectively filter the ripples in direct current signals while keeping the charging characteristics of the original signals, and improves the accuracy of direct current electric energy metering accuracy.
Referring to fig. 3, an embodiment of the invention provides a computer terminal device, which includes one or more processors and a memory. The memory is coupled to the processor for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the method of direct current energy metering as in any one of the embodiments described above.
The processor is used for controlling the overall operation of the computer terminal equipment so as to complete all or part of the steps of the direct current electric energy metering method. The memory is used to store various types of data to support the operation at the computer terminal device, which data may include, for example, instructions for any application or method operating on the computer terminal device, as well as application-related data. The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
In an exemplary embodiment, the computer terminal Device may be implemented by one or more Application Specific 1 integrated circuits (AS 1C), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is configured to perform the above dc power metering method and achieve the same technical effects AS the above methods.
In another exemplary embodiment, a computer-readable storage medium comprising a computer program is also provided, which when executed by a processor implements the steps of the method of direct current energy metering in any of the above embodiments. For example, the computer readable storage medium may be the above-mentioned memory including a computer program, which is executable by a processor of a computer terminal device to perform the above-mentioned dc power metering method, and achieve the technical effects consistent with the above-mentioned method.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. A method of direct current electrical energy metering, comprising:
acquiring original sampling data of the electric energy signal;
performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer;
setting a threshold value and a threshold value function for the wavelet coefficient corresponding to each decomposition layer, and quantizing the wavelet coefficient corresponding to each decomposition layer to obtain a quantized wavelet coefficient;
reconstructing the quantized wavelet coefficient to obtain a de-noising signal;
performing ripple error correction on the de-noised signal to obtain corrected data;
and performing integral calculation on the corrected data by adopting a composite trapezoidal integral method to obtain target electric energy data.
2. Method for direct current electrical energy metering according to claim 1, characterized in that the expression of the threshold function is:
where y is the wavelet coefficient after hard thresholding, ωj,kIs the kth wavelet coefficient on the jth scale, TjIs the critical threshold.
3. The method of claim 1, wherein the raw sampling data is obtained by sampling a dc voltage and current signal using a fixed frequency.
4. The direct current electric energy metering method according to claim 1, wherein the performing wavelet transform on the original sampling data according to a preset wavelet basis and a preset number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer comprises:
and selecting db3 type wavelets, and performing wavelet transformation on the original sampling data by using 3-layer or 4-layer decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer.
5. A direct current electric energy metering device, comprising:
the data acquisition module is used for acquiring original sampling data of the electric energy signal;
the de-noising module is used for performing wavelet transformation on the original sampling data according to a preset wavelet basis and the number of decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer;
the de-noising module is also used for setting a threshold value and a threshold value function for the wavelet coefficients corresponding to each decomposition layer, and quantizing the wavelet coefficients corresponding to each decomposition layer to obtain quantized wavelet coefficients; reconstructing the quantized wavelet coefficient to obtain a de-noising signal;
the error correction module is used for performing ripple error correction on the de-noised signal to obtain corrected data;
and the integral module is used for carrying out integral calculation on the corrected data by adopting a composite trapezoid integral method to obtain target electric energy data.
6. The direct current energy metering device of claim 5, wherein the threshold function is expressed by:
where y is the wavelet coefficient after hard thresholding, ωj,kIs the kth wavelet coefficient on the jth scale, TjIs the critical threshold.
7. The direct current energy metering device of claim 5, wherein the raw sampling data is obtained by sampling direct current voltage and current signals using a fixed frequency.
8. The direct current energy metering device of claim 5, wherein the de-noising module is further configured to select a db3 type wavelet, and perform wavelet transformation on the original sampled data by using 3-layer or 4-layer decomposition layers to obtain wavelet coefficients corresponding to each decomposition layer.
9. A computer terminal device, comprising:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method of direct current electrical energy metering of any one of claims 1 to 4.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method for direct current energy metering according to any one of claims 1 to 4.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117076823A (en) * | 2023-09-25 | 2023-11-17 | 国网四川省电力公司营销服务中心 | Ripple component analysis method, system, equipment and medium based on Gaussian integration method |
| CN117353856A (en) * | 2023-09-28 | 2024-01-05 | 辽宁天衡智通防务科技有限公司 | Signal processing method and signal transmission system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104880592A (en) * | 2015-06-24 | 2015-09-02 | 国网浙江省电力公司电力科学研究院 | Electric energy calculating method and system under harmonic wave condition |
| CN108169553A (en) * | 2018-01-10 | 2018-06-15 | 长沙理工大学 | Electric energy gauging method under the conditions of distorted signal based on wavelet transformation and curve matching |
| CN108649573A (en) * | 2018-06-13 | 2018-10-12 | 国网河北省电力有限公司 | A kind of computational methods for causing grid net loss to change by power transmission and transforming equipment maintenance |
| CN111537789A (en) * | 2020-05-09 | 2020-08-14 | 湖南省计量检测研究院 | Direct current electric energy metering device and method based on signal separation and accurate integration |
| CN112395992A (en) * | 2020-11-18 | 2021-02-23 | 云南电网有限责任公司电力科学研究院 | Electric power harmonic signal denoising method based on improved wavelet threshold |
| CN113205022A (en) * | 2021-04-23 | 2021-08-03 | 湖南万脉医疗科技有限公司 | Respiratory anomaly monitoring method and system based on wavelet analysis |
| CN113281673A (en) * | 2021-05-21 | 2021-08-20 | 深圳市虹鹏能源科技有限责任公司 | Direct current electric quantity calculation device and method |
| CN113378661A (en) * | 2021-05-25 | 2021-09-10 | 浙江工业大学 | Direct current electric energy signal denoising method based on improved wavelet threshold and related detection |
-
2021
- 2021-09-29 CN CN202111152492.2A patent/CN113884758B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104880592A (en) * | 2015-06-24 | 2015-09-02 | 国网浙江省电力公司电力科学研究院 | Electric energy calculating method and system under harmonic wave condition |
| CN108169553A (en) * | 2018-01-10 | 2018-06-15 | 长沙理工大学 | Electric energy gauging method under the conditions of distorted signal based on wavelet transformation and curve matching |
| CN108649573A (en) * | 2018-06-13 | 2018-10-12 | 国网河北省电力有限公司 | A kind of computational methods for causing grid net loss to change by power transmission and transforming equipment maintenance |
| CN111537789A (en) * | 2020-05-09 | 2020-08-14 | 湖南省计量检测研究院 | Direct current electric energy metering device and method based on signal separation and accurate integration |
| CN112395992A (en) * | 2020-11-18 | 2021-02-23 | 云南电网有限责任公司电力科学研究院 | Electric power harmonic signal denoising method based on improved wavelet threshold |
| CN113205022A (en) * | 2021-04-23 | 2021-08-03 | 湖南万脉医疗科技有限公司 | Respiratory anomaly monitoring method and system based on wavelet analysis |
| CN113281673A (en) * | 2021-05-21 | 2021-08-20 | 深圳市虹鹏能源科技有限责任公司 | Direct current electric quantity calculation device and method |
| CN113378661A (en) * | 2021-05-25 | 2021-09-10 | 浙江工业大学 | Direct current electric energy signal denoising method based on improved wavelet threshold and related detection |
Non-Patent Citations (1)
| Title |
|---|
| 傅成豪等: "基 于 改 进 阈 值 的 风 机 齿 轮 箱 故 障 信 号小 波 去 噪 方 法 研 究" * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117076823A (en) * | 2023-09-25 | 2023-11-17 | 国网四川省电力公司营销服务中心 | Ripple component analysis method, system, equipment and medium based on Gaussian integration method |
| CN117353856A (en) * | 2023-09-28 | 2024-01-05 | 辽宁天衡智通防务科技有限公司 | Signal processing method and signal transmission system |
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