CN110572087B - Motor device based on electric power harmonic state control - Google Patents
Motor device based on electric power harmonic state control Download PDFInfo
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
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Abstract
An electric machine apparatus based on power harmonic state control, comprising: the device comprises a power supply module, a wireless receiving module, a communication interface, a controller, a driving circuit and a harmonic detection module; the harmonic detection module for detecting the harmonic content output by the wireless receiving module is connected with the controller through the communication interface, the wireless module outputs a signal to the controller, and the power supply module is connected with the communication interface, the controller and the driving circuit. According to the invention, a column of vectors is selected from the state estimation matrix in the detection method, so that the harmonic component can be reflected best, a plurality of measurement quantities are calculated only once, the control method is simple, and the system cost is reduced; in addition, the invention also utilizes wavelet denoising to reconstruct the denoised signal, thereby eliminating residual noise and greatly improving the accuracy of harmonic state evaluation.
Description
Technical Field
The invention relates to the field of power systems, in particular to a motor device based on power harmonic state control.
Background
With the rapid development of modern power electronic technology, various power electronic devices are widely applied to various fields such as power systems, industry, traffic and the like, but because the power electronic devices are nonlinear time-varying topological loads, generated harmonics and reactive power are injected into a power grid, the equipment capacity and line loss can be increased, the utilization rate of power generation and distribution equipment is reduced, the power supply quality is influenced, and the potential threat to the safe and stable operation of the power systems is formed. At present, harmonic pollution, electromagnetic interference and power factor reduction become three major public hazards of an electric power system, so that the reasons for harmonic generation are researched and analyzed, a good detection method is provided for inhibiting harmonic interference of the electric power system, and the method has important practical significance for improving the operation quality of a power grid and meeting the requirements of users.
Because the harmonic waves of the power system are influenced by various factors such as randomness, non-stationarity, distributivity and the like, the real-time and accurate detection is not easy. The existing detection method has poor real-time performance, inaccurate sampling process, high requirements on devices and complex control method.
In addition, multipath cancellation is performed by a time domain equalization technique commonly used in harmonic vector data transmission in the prior art, which may result in excessive tap coefficients and excessive implementation complexity, and generally, OFDM (orthogonal frequency division multiplexing) may also effectively combat multipath interference, but because it employs a multi-carrier modulation method, the peak-to-average ratio is high and is sensitive to frequency offset, these two disadvantages become main factors that limit the application of OFDM in short-wave communication. Commonly used channel estimation criteria are LS (least squares) criterion, MMSE (minimum mean square error) criterion, and the like. The MMSE algorithm utilizes the correlation characteristics of the channel, the estimation accuracy is high, but the operation is too complex, and the short wave channel is changed in real time, so that the correlation characteristics of the channel are difficult to obtain, and the MMSE algorithm is not practical in actual engineering. The LS algorithm has a simple structure and small calculation amount, does not need to know channel information in advance, is practical, and does not consider the influence of noise.
Therefore, how to solve the influence of the harmonic and the noise thereof on the motor device becomes an important technical problem to be solved by those skilled in the art.
Disclosure of Invention
In order to overcome the above drawbacks and deficiencies of the prior art, the present invention provides a motor apparatus based on power harmonic state, comprising: the device comprises a power supply module, a wireless receiving module, a communication interface, a controller, a driving circuit and a harmonic detection module;
the harmonic detection module for detecting the harmonic content output by the wireless receiving module is connected with the controller through the communication interface, the wireless module outputs a signal to the controller, and the power supply module is connected with the communication interface, the controller and the driving circuit.
The detection method of the harmonic detection module comprises the following steps:
step (1), presetting the maximum dimension D of a state vector of the measurement data, so that the dimension D of the state vector is 2,3 … …, D;
step (2) according to i, d(i)Obtaining a state vector x of measurement data(i)Wherein the measurement data is representative of current and voltage of the system;
and (3) acquiring a state estimation matrix W according to the state estimator and the state vector of the measured data(i)；
Step (4), estimating the matrix W in the state(i)In which a column of vectors w is selected(i)To best reflect harmonic components;
the vector pair w in the step (5)(i)Performing wavelet denoising, comprising:
for vector data w(i)Partitioning, periodically inserting pilot frequency between data blocks, extracting information at a pilot frequency position at a receiving end, estimating channel frequency response at a pilot frequency sequence by adopting an LS algorithm, and performing channel estimation by utilizing the information at the pilot frequency position to obtain an estimated value;
performing IDFT inverse discrete Fourier transform on the estimated value to transform the estimated value to a time domain, decomposing the estimated value in a wavelet domain according to a Mallat algorithm, filtering noise by adopting a threshold denoising method, and reconstructing a denoised signal;
and carrying out interpolation zero filling on the reconstructed signal, and carrying out DFT on the reconstructed signal to transform the reconstructed signal to a frequency domain so as to obtain the frequency response of the whole channel and finish channel estimation.
Step (6) of obtaining a vector
Calculating a harmonic component;
step (7), calculating the closeness between the harmonic component obtained in the step (6) and the original harmonic component;
step (8), for d(i)< D such that i ═ i +1, then return to step (2);
step (9), for d(i)D, selecting w with the best closenesscAs the final correction vector.
The state vector x of the measurement data in step (2)(i)Comprises the following steps:
x(i)[n]＝[xi[n],[xi[n-1],…,[xi[n-D+1]]T
where x [ n ] is the discretized state vector of the continuous signal x (T), and T represents the transpose of the matrix.
The state estimation matrix W in step (3)(i)Is obtained from the following formula:
y(i)[n]＝W(i)x(i)[n]
wherein, y(i)[n]Is a state estimator.
Estimating the matrix W in the state in the step (4)(i)In which a column of vectors w is selected(i)The harmonic components that can be best reflected by the method are specifically:
calculating deviation value, and selecting column vector w with minimum deviation value(i)Wherein the deviation value is a difference between the obtained harmonic component and the original harmonic component.
The formula for calculating the deviation value in the step (4) is as follows:
wherein, PiRepresenting the original harmonic components of the wave,
is the resulting harmonic component.
Vector obtained according to step (6)
The harmonic component is calculated as follows:
the closeness between the harmonic component obtained by the calculation in the step (7) and the original harmonic component is obtained by calculating the mean square error between the harmonic component obtained by the calculation and the original harmonic component.
The driving circuit comprises a human-computer interface, a power supply sub-circuit, a power driving sub-circuit, a driving signal processing sub-circuit, a control signal processing sub-circuit and a direct current brushless motor;
one end of the control signal processing sub-circuit is connected with the human-computer interface, the other end of the control signal processing sub-circuit is connected with one end of the driving signal processing sub-circuit through an optical coupler, the other end of the driving signal sub-circuit is connected with one end of the power driving sub-circuit, the other end of the power driving circuit is connected with the direct current brushless motor, and the power supply circuit provides working voltage for the direct current brushless motor driving circuit.
Compared with the closest prior art, the technical scheme provided by the invention has the following beneficial effects:
according to the invention, a column of vectors is selected from the state estimation matrix in the detection method, so that the harmonic component can be reflected best, a plurality of measurement quantities are calculated only once, the control method is simple, and the system cost is reduced; in addition, the invention also utilizes wavelet denoising to reconstruct the denoised signal, thereby eliminating residual noise and greatly improving the accuracy of harmonic state evaluation.
Drawings
FIG. 1 is an overall architecture diagram of the present invention;
FIG. 2 is a control block diagram of the present invention;
FIG. 3 is a flow chart of a method for estimating a state based on power harmonic detection according to the present invention;
fig. 4 shows a driving circuit in the motor apparatus of the present invention.
Detailed Description
The technical solution of the present invention is further described in detail below with reference to the accompanying drawings.
The motor device shown in fig. 1 includes a power module, a wireless receiving module, a communication interface, a controller, a driving circuit, and a harmonic detection module;
the harmonic detection module for detecting the harmonic content output by the wireless receiving module is connected with the controller through the communication interface, the wireless module outputs a signal to the controller, and the power supply module is connected with the communication interface, the controller and the driving circuit.
Referring to the control block diagram of fig. 2 and the flow chart of the state estimation method of fig. 3, the control steps are as follows:
and (1) presetting the maximum dimension D of the state vector of the measurement data, so that the dimension D of the state vector is 2,3 … … and D. Wherein, the selection of D has a great relationship with the control accuracy of the system. If D is too small, the selection is too small in the process of finally selecting the column vector capable of reflecting the harmonic component best, and the accuracy of the system is reduced. However, if D is selected too much, it will bring too much burden to the control system, increase the amount of calculation, and unnecessarily increase the complexity of the system. Therefore, D is selected as moderately as possible, such as 64 or 128.
Step (2) according to i, d(i)Obtaining a state vector x of a measurement quantity(i)Wherein the measured quantities represent the current and voltage of the system.
State vector x of the measurement quantities in step (2)(i)Expressed as:
x(i)[n]＝[xi[n],[xi[n-1],…,[xi[n-D+1]]T
where x [ n ] is the discretized state vector of the continuous signal x (T), and T represents the transpose of the matrix.
And (3) acquiring a state estimation matrix W according to the state estimator and the state vector of the measured data(i). State estimation matrix W(i)Is obtained from the following formula:
y(i)[n]＝W(i)x(i)[n]
wherein, y(i)[n]Is a state estimator.
Step (4), estimating the matrix W in the state(i)In which a column of vectors w is selected(i)So that it can best reflect the harmonic components. The method specifically comprises the following steps:
calculating deviation value, and selecting column vector w with minimum deviation value(i)Wherein the deviation value is a difference between the obtained harmonic component and the original harmonic component.
The formula for calculating the deviation value in the step (4) is as follows:
wherein, PiRepresenting the original harmonic components of the wave,
is the resulting harmonic component.
Step (5), the vector w(i)Performing wavelet denoising to obtain a vector
The method specifically comprises the following steps:
partitioning the transmitted data, periodically inserting pilot frequency between data blocks, extracting information at a pilot frequency position at a receiving end, estimating channel frequency response at a pilot frequency sequence by adopting an LS algorithm, and performing channel estimation by utilizing the information at the pilot frequency position to obtain an estimated value;
performing IDFT (inverse discrete Fourier transform) on the obtained estimated value to transform the estimated value into a time domain, decomposing the estimated value in a wavelet domain according to a Mallat algorithm, filtering noise by adopting a threshold denoising method, and reconstructing a denoised signal;
interpolating and zero-filling the reconstructed signal, and performing DFT (discrete Fourier transform) on the signal to transform the signal to a frequency domain, thereby obtaining the frequency response of the whole channel, finishing channel estimation and obtaining a vector
Step (6) of obtaining a vector
Calculating a harmonic component; the method specifically comprises the following steps:
and (7) calculating the closeness between the harmonic component obtained in the step (6) and the original harmonic component. The closeness between the harmonic component obtained by the calculation in the step (7) and the original harmonic component is obtained by calculating the mean square error between the harmonic component obtained by the calculation and the original harmonic component.
Step (8), for d(i)< D such that i ═ i +1, then return to step (2);
step (9), for d(i)D, selecting w with the best closenesscAs the final correction vector.
In practical applications, those skilled in the art can determine whether the harmonic occurs or exceeds a predetermined limit by comparing the output harmonic content with a threshold based on the above state estimation method based on power harmonic detection. By the method, the accuracy of harmonic state evaluation is greatly improved, a plurality of measurement data can be calculated at one time, and the control method is simple, so that the system cost is reduced.
The driving circuit shown in fig. 4 includes a human-machine interface, a power driving sub-circuit, a driving signal processing sub-circuit, a control signal processing sub-circuit, and a dc brushless motor.
The control signal processing sub-circuit is connected with a human-computer interface, a serial port communication interface of the control signal processing sub-circuit is connected with a serial port communication interface of the driving signal processing sub-circuit through an optical coupler, the driving signal sub-circuit is further connected with a power driving sub-circuit, and the power driving sub-circuit is connected with the direct-current brushless motor. The power supply electronic circuit comprises a power module input port and a rectification filter sub-circuit, and the commercial power input port is connected with the rectification filter circuit.
The human-computer interface comprises a display and a control key, and the display and the control key are respectively connected with the driving signal processing sub-circuit. The display adopts an LCD display screen. The driving signal processing sub-circuit is also provided with an external signal input port.
The processing chips of the driving signal processing sub-circuit and the control signal processing sub-circuit of the embodiment can be single-chip microcomputers.
The working principle of the embodiment is as follows:
after the power supply is connected, the power supply is converted into direct current through the filter rectification circuit, and working voltage is provided for each working circuit. The driving signal processing sub-circuit is responsible for processing a motor reversing signal transmitted by the direct current brushless motor and information transmitted from an external signal input port or the control signal processing circuit, and can also output the rotating speed, the temperature and the working state information of the direct current brushless motor to the display; the control signal processing sub-circuit is responsible for external control signals or local control signals. The controller may adjust the output speed according to the PWM or analog voltage.
The drive signal processing sub-circuit and the control signal processing sub-circuit realize isolation effect through the serial port communication interface and the optical coupler, and a circuit on one side of the optical coupler is a safe cold circuit which can be directly connected with a computer control or other control units, so that the damage or electric shock danger of an electric appliance cannot be caused, and the safety is very high.
While the embodiments of the present invention have been disclosed above, it is not limited to the applications listed in the description and embodiments, but is fully applicable to various fields suitable for the present invention, and it will be apparent to those skilled in the art that various changes, modifications, substitutions and alterations can be made in the embodiments without departing from the principle and spirit of the present invention, and therefore the present invention is not limited to the specific details without departing from the general concept defined in the claims and the scope of equivalents thereof.
Claims (5)
1. An electric machine apparatus based on power harmonic state control, comprising: the device comprises a power supply module, a wireless receiving module, a communication interface, a controller, a driving circuit and a harmonic detection module;
the harmonic detection module for detecting the harmonic content output by the wireless receiving module is connected with the controller through the communication interface, the wireless module outputs a signal to the controller, and the power supply module is connected with the communication interface, the controller and the driving circuit;
the detection method of the harmonic detection module comprises the following steps:
step (1), presetting the maximum dimension D of a state vector of measurement data, so that the dimension D of the state vector is 2,3 … …, D;
step (2) according to i, d(i)Obtaining a state vector x of measurement data(i)Wherein the measurement data is representative of current and voltage of the system;
step (3) obtaining a state estimation matrix W according to the state estimator and the state vector of the measured data(i)；
Step (4) estimating the matrix W in the state(i)In which a column of vectors w is selected(i)To best reflect harmonic components;
step (5) for vector w(i)Performing wavelet denoising to obtain a vector
Step (6) according to the obtained vector
Calculating a harmonic component;
step (7) obtaining the closeness by calculating the mean square error between the obtained harmonic component and the original harmonic component;
step (8) for d(i)< D such that i ═ i +1, then return to step (2);
step (9) for d(i)D, selecting w with the best closenesscAs the final correction vector;
the state vector x of the measurement data in step (2)(i)Comprises the following steps:
x(i)[n]＝[xi[n],[xi[n-1],…,[xi[n-D+1]]T
wherein x [ n ] is the discretized state vector of the continuous signal x (T), and T represents the transpose of the matrix;
the state estimation matrix W in step (3)(i)Is obtained from the following formula:
y(i)[n]＝W(i)x(i)[n]
wherein, y(i)[n]Is a state estimator;
the formula for calculating the deviation value in the step (4) is as follows:
wherein, PiRepresenting the original harmonic components of the wave,
harmonic components obtained after denoising;
vector obtained according to step (6)
The harmonic component is calculated as follows:
2. the electromechanical machine of claim 1, wherein the state estimation matrix W in step (4)(i)In which a column of vectors w is selected(i)The harmonic components that can be best reflected by the method are specifically:
calculating deviation value, and selecting column vector w with minimum deviation value(i)Wherein the deviation value is a difference between the obtained harmonic component and the original harmonic component.
3. The motor apparatus of claim 1, wherein the correction vector obtained in step (5)
Is obtained by aligning the vector w(i)And carrying out wavelet denoising to obtain the wavelet denoising filter.
4. The electromechanical device according to claim 3, wherein the vector pair w in step (5) is(i)Performing wavelet denoising, comprising:
for vector data w(i)Partitioning, periodically inserting pilot frequency between data blocks, extracting information at a pilot frequency position at a receiving end, estimating channel frequency response at a pilot frequency sequence by adopting an LS algorithm, and performing channel estimation by utilizing the information at the pilot frequency position to obtain an estimated value;
performing IDFT inverse discrete Fourier transform on the estimated value to transform the estimated value to a time domain, decomposing the estimated value in a wavelet domain according to a Mallat algorithm, filtering noise by adopting a threshold denoising method, and reconstructing a denoised signal;
and carrying out interpolation zero filling on the reconstructed signal, and carrying out DFT on the reconstructed signal to transform the reconstructed signal to a frequency domain so as to obtain the frequency response of the whole channel and finish channel estimation.
5. The electromechanical device according to claim 1, wherein the driving circuit comprises a human-machine interface, a power supply sub-circuit, a power driving sub-circuit, a driving signal processing sub-circuit, a control signal processing sub-circuit and a dc brushless motor;
one end of the control signal processing sub-circuit is connected with the human-computer interface, the other end of the control signal processing sub-circuit is connected with one end of the driving signal processing sub-circuit through an optical coupler, the other end of the driving signal sub-circuit is connected with one end of the power driving sub-circuit, the other end of the power driving circuit is connected with the direct current brushless motor, and the power supply circuit provides working voltage for the direct current brushless motor driving circuit.
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