CN113567788A - Application method, device, equipment and medium of mixed base FFT (fast Fourier transform) in power system - Google Patents
Application method, device, equipment and medium of mixed base FFT (fast Fourier transform) in power system Download PDFInfo
- Publication number
- CN113567788A CN113567788A CN202110869980.9A CN202110869980A CN113567788A CN 113567788 A CN113567788 A CN 113567788A CN 202110869980 A CN202110869980 A CN 202110869980A CN 113567788 A CN113567788 A CN 113567788A
- Authority
- CN
- China
- Prior art keywords
- sampling points
- power
- fourier transform
- calculating
- transform algorithm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000005070 sampling Methods 0.000 claims abstract description 94
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 66
- 238000004364 calculation method Methods 0.000 claims abstract description 31
- 238000004590 computer program Methods 0.000 claims description 5
- 230000000694 effects Effects 0.000 abstract description 4
- 238000007792 addition Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000012356 Product development Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000000205 computational method Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
Abstract
The embodiment of the application provides an application method, device, equipment and medium of a mixed base FFT in a power system. The method comprises the following steps: when the electric energy quality data in the power system is sampled, the number of total sampling points is determined according to the sampling frequency and the number of preset sampling points of single cycle waves in harmonic waves, and the number of the total sampling points is expressed as a positive integer of a power of 2 multiplied by a power of non-2; and calculating data acquired by sampling points with the power of 2 by adopting a mixed-basis fast Fourier transform algorithm, and calculating data acquired by sampling points with the positive integer number which is not the power of 2 by adopting a discrete Fourier transform algorithm. The method and the device can solve the problems that the existing processor is low in calculation speed and cannot meet the real-time requirement in a calculation power system, and achieve the effect of reducing the calculation pressure of the processor.
Description
Technical Field
Embodiments of the present application relate to the technical field of data processing, and more particularly, to an application method, an application device, an application apparatus, and a medium of a hybrid-base FFT in a power system.
Background
In an electric power system, when electric parameters such as current, voltage, power and the like need to be calculated, sampling 2 within one cycle of time is generally adoptednA number of sample points are sampled at the time of sampling,for calculation with the FFT algorithm. FFT, Fast Fourier Transform (FFT), a generic term for an efficient, fast computational method that utilizes a computer to compute the Discrete Fourier Transform (DFT). If the 5Hz resolution inter-harmonic needs to be calculated, 10 cycles of data are needed, since each cycle is 2nSampling points with 10 cycles of 2nX 10, since it is not 2nAnd (3) each sampling point cannot be directly calculated by using fast Fourier transform, and only a discrete Fourier transform algorithm is used.
In view of the above-mentioned related technologies, the inventor believes that, in actual product development, when calculating 8 channels of inter-harmonics, a power quality analyzer needs 1.6 seconds to complete calculation, and the data updating speed is slow.
Disclosure of Invention
The embodiment of the application provides an application method, device, equipment and medium of a mixed-base FFT in a power system, and can solve the problems that an existing processor is low in calculation speed and cannot meet the real-time requirement in a calculation power system.
In a first aspect of the present application, a method for applying a hybrid-based FFT in a power system is provided, including:
when the electric energy quality data in the power system is sampled, the number of total sampling points is determined according to the sampling frequency and the number of preset sampling points of single cycle waves in harmonic waves, and the number of the total sampling points is expressed as a positive integer of a power of 2 multiplied by a power of non-2;
and calculating data acquired by sampling points with the power of 2 by adopting a mixed-basis fast Fourier transform algorithm, and calculating data acquired by sampling points with the positive integer number which is not the power of 2 by adopting a discrete Fourier transform algorithm.
By adopting the technical scheme, in the application method, the device, the equipment and the medium of the mixed-base FFT provided by the embodiment of the application, the mixed-base fast Fourier transform algorithm is adopted to calculate the data collected by the sampling points with the power number of 2, and the discrete Fourier transform algorithm is adopted to calculate the data collected by the sampling points with the positive integer number which is not the power number of 2, so that the problems that the existing processor is low in calculation speed and cannot meet the real-time requirement in the calculation of the power system can be solved, and the effect of reducing the calculation pressure of the processor is achieved.
In one possible implementation, the number of total sampling points is represented by the following equation:
N＝2·A·B＝2·2n·(2X+1)，X＝0，1，2，……
wherein, N is the number of total sampling points, A is the number of preset sampling points of the single-cycle wave, and B is the sampling frequency.
In a possible implementation manner, the number of times C of calculation required for calculating the data acquired by the power-of-2 number of sampling points by using the mixed-basis fast fourier transform algorithm is as follows:
the number D of times required for calculating the data collected by the sampling points of the number of positive integers which are not the power of 2 by adopting the discrete Fourier transform algorithm is as follows: D-8B2；
The number of times of calculating the electric energy quality data in the electric power system is expressed as M:
in one possible implementation, the harmonics are sub-harmonics.
In a second aspect of the present application, there is provided an apparatus for applying a hybrid-based FFT to a power system, including: the determining module is used for determining the number of total sampling points according to the sampling frequency and the number of preset sampling points of a single cycle in a harmonic wave when sampling the power quality data in the power system, and expressing the number of the total sampling points as a positive integer which cannot be divided by 2 multiplied by a power of 2;
and the calculating module calculates data acquired by the sampling points with the power of 2 by adopting a mixed-base fast Fourier transform algorithm, and calculates data acquired by the sampling points with the positive integer number which is not the power of 2 by adopting a discrete Fourier transform algorithm.
In a possible implementation manner, the determining module is specifically configured to:
the number of the total sampling points is represented by the following formula:
N＝2·A·B＝2·2n·(2X+1)，X＝0，1，2，……
wherein, N is the number of total sampling points, A is the number of preset sampling points of the single-cycle wave, and B is the sampling frequency.
In a possible implementation manner, the calculation module is specifically configured to:
the calculation times C required by the data acquired by the sampling points with the power number of 2 calculated by adopting the mixed-basis fast Fourier transform algorithm are as follows:
the number D of times required for calculating the data collected by the sampling points of the number of positive integers which are not the power of 2 by adopting the discrete Fourier transform algorithm is as follows: D-8B2；
The number of times of calculating the electric energy quality data in the electric power system is expressed as M:
in one possible implementation, the harmonics are sub-harmonics.
In a third aspect of the present application, an electronic device is provided. The electronic device includes: a memory having a computer program stored thereon and a processor implementing the method as described above when executing the program.
In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the method as according to the first aspect of the present application.
It should be understood that what is described in this summary section is not intended to limit key or critical features of the embodiments of the application, nor is it intended to limit the scope of the application. Other features of the present application will become apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present application will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
fig. 1 shows a flow chart of a method of applying a hybrid-based FFT in a power system according to an embodiment of the present application;
fig. 2 shows a block diagram of an application device of a hybrid-based FFT in a power system according to an embodiment of the present application;
fig. 3 shows a schematic structural diagram of an electronic device suitable for implementing embodiments of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
The application method of the mixed-basis FFT in the power system provided by the embodiment of the application can be applied to the technical field of data processing, for example, scenes such as calculating power quality data by a power quality analyzer in actual product development and the like. However, in the above scenario, the most important and time-consuming application is to calculate the power quality data. Therefore, how to accurately and quickly calculate the power quality data is an important technical problem. To solve the technical problem, embodiments of the present application provide an application method of a mixed-radix FFT in a power system. In some embodiments, the method of applying the hybrid-based FFT in the power system may be performed by an electronic device.
Fig. 1 shows a flowchart of a method for applying a hybrid-based FFT in a power system according to an embodiment of the present application. Referring to fig. 1, the method for applying the mixed-base FFT to the power system includes the following steps:
In the embodiment of the application, the electric energy quality data in the power system for sampling are electric parameters such as current, voltage and power, the harmonic waves comprise inter-harmonic waves and sub-harmonic waves, and the sampling frequency and the number of preset sampling points of single-cycle waves in the harmonic waves are determined according to actual calculation requirements.
The number of total sampling points is represented by the following equation:
N＝2·A·B＝2·2n·(2X+1)，X＝0，1，2，……
wherein, N is the number of total sampling points, A is the number of preset sampling points of the single-cycle wave, and B is the sampling frequency.
For example:
if 5Hz resolution of the inter-harmonics is calculated, 10 cycles are taken:
assuming that the sampling point of a single period is 512,
the total of 10 cycles to be calculated is N512 × 10,
according to the formula N2. A. B2. 2n·(2X+1)，X＝0，1，2，……，
Then A is 2n＝512，B＝5；
If the sub-harmonic of 1Hz resolution is calculated, 50 cycles are taken:
assuming that the sampling point of a single period is 512,
the total of 10 cycles to be calculated is N512 × 50,
according to the formula N2. A. B2. 2n·(2X+1)，X＝0，1，2，……，
Then A is 2n＝512，B＝25。
And step 120, calculating data collected by the sampling points with the power of 2 by adopting a mixed-basis fast Fourier transform algorithm, and calculating data collected by the sampling points with the positive integer number which is not the power of 2 by adopting a discrete Fourier transform algorithm.
In the embodiment of the application, the number of times of calculating the power quality data in the power system is the number of times of calculating the power of 2 by adopting a mixed-basis fast fourier transform algorithm and the number of times of calculating the positive integer of the power of non-2 by adopting a discrete fourier transform algorithm.
In the embodiment of the present application, a mixed-radix (radix x) fast fourier transform algorithm is defined, wherein x is an even number and is equal to 2y (y is a positive integer), the total points calculated by the mixed-radix (radix x) fast fourier transform algorithm are required to satisfy the logarithm of the total points based on x, and the logarithm of the total points based on x is a positive integer. The calculation formula in the mixed-basis (radix x) fast fourier transform algorithm is not uniform but unique.
For example:
the calculation times C required for calculating the data collected by the sampling points with the power number of 2 by adopting the base 2 fast Fourier transform algorithm are as follows:
the number D of times required for calculating the data collected by the sampling points of the number of positive integers which are not the power of 2 by adopting the discrete Fourier transform algorithm is as follows: D-8B2；
The number of times of calculating the electric energy quality data in the electric power system is expressed as M:
the calculation times C required for calculating the data collected by the sampling points with the power number of 2 by adopting the base 4 fast Fourier transform algorithm are as follows:
the number D of times required for calculating the data collected by the sampling points of the number of positive integers which are not the power of 2 by adopting the discrete Fourier transform algorithm is as follows: D-8B2；
The number of times of calculating the electric energy quality data in the electric power system is expressed as M:
in the embodiment of the present application, if the number of samples is not 2nWhen sampling points are sampled, discrete Fourier transform is adopted, if the calculated amount of a sine function and a cosine function is not considered, the calculation times during calculation of a discrete Fourier transform algorithm are as follows:
complex multiplication operation N2；
Complex addition is equal to N (N-1).
The fast fourier transform algorithm calculates the number of calculations when calculating in base 2 as follows:
complex multiplication (N/2 × log)2N；
Complex addition operation N × log2N。
Given that z1 is a + bi and z2 is c + di is any two complex numbers, z1+ z2 is (a + bi) + (c + di) is (a + c) + (b + d) i, so that 1 complex addition is 2 real additions.
Given that z1 is a + bi and z2 is c + di is any two complex numbers, z1 × z2 is (a + bi) (c + di) (ac-bd) + (bc + ad) i, so 1 complex multiplication is 4 real multiplications +2 real additions.
Since the CPU with a hardware multiplier calculates one multiplication time equal to one addition time.
Inference can be understood, in the discrete Fourier transform algorithm, N2Complex multiplication by N2×(4+2)＝6N2Real number addition; n (N-1) complex addition ═ N (N-1) × 2 ≈ 2N2And (4) real number addition.
Therefore, 6N needs to be calculated when calculating the N-point DFT2+2N2＝8N2The second real number addition.
For example, when calculating the 5Hz resolution of the inter-harmonics, 10 cycles are taken:
setting the sampling point of the single period as 512
The total number of the 10 cycles to be calculated is N512 × 10
The first algorithm:
using discrete Fourier transform algorithm
M＝8N2＝209715200
The second algorithm:
adopting a base 2 fast Fourier transform algorithm:
according to the formula N-2. A. B and A-2n，B＝2X+1，X＝0，1，2，……
Then A is 2n＝512，B＝5
Substituting A, B the formula for calculating the number M of power quality data in the power system according to the 2-based fast Fourier transform algorithm
And obtaining M-10240000.
The third algorithm:
adopting a base 4 fast Fourier transform algorithm:
according to the formula N-2. A. B and A-2n，B＝2X+1，X＝0，1，2，……
Then A is 2n＝512，B＝5
Substituting A, B the formula for calculating the number M of power quality data in the power system according to the 4-based fast Fourier transform algorithm
And obtaining M-6656000.
Therefore, when the inter-harmonics are calculated, compared with a discrete Fourier transform algorithm, the mixed-basis fast Fourier transform algorithm is faster, the mixed basis of the mixed-basis fast Fourier transform algorithm is different, and the advantages of the mixed-basis FFT are larger.
For example, when calculating the sub-harmonic of 1Hz resolution, 50 cycles are taken:
setting the sampling point of the single period as 512
The total number of sampling points to be calculated for 10 cycles is N512 × 50
The first algorithm:
using discrete Fourier transform algorithm
M＝8N2＝5242880000
The second algorithm:
adopting a base 2 fast Fourier transform algorithm:
according to the formula N-2. A. B and A-2n，B＝2X+1，X＝0，1，2，……
Then A is 2n＝512，B＝25
Substituting A, B the formula for calculating the number M of power quality data in the power system according to the 2-based fast Fourier transform algorithm
And obtaining M-256000000.
The third algorithm:
adopting a base 4 fast Fourier transform algorithm:
according to the formula N-2. A. B and A-2n，B＝2X+1，X＝0，1，2，……
Then A is 2n＝512，B＝25
Substituting A, B the formula for calculating the number M of power quality data in the power system according to the 4-based fast Fourier transform algorithm
And obtaining M-166400000.
Therefore, when the subharmonic is calculated, compared with a discrete Fourier transform algorithm, the mixed-basis fast Fourier transform algorithm is faster, the mixed basis of the mixed-basis fast Fourier transform algorithm is different, and the advantages of the mixed-basis FFT are larger.
The reasoning can also be obtained according to the formula, when the inter-harmonic wave or the sub-harmonic wave is calculated, compared with the discrete Fourier transform algorithm, the speed of the mixed-base fast Fourier transform algorithm is higher, and the mixed bases of the mixed-base fast Fourier transform algorithm are different, so that the advantages of the mixed-base FFT are higher. Therefore, the calculation speed of the power quality data in the power system is greatly increased, and the effect of reducing the calculation pressure of the processor is achieved.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required in this application.
The above is a description of method embodiments, and the embodiments of the present application are further described below by way of apparatus embodiments.
Fig. 2 shows a block diagram of an application apparatus of a mixed-base FFT in a power system according to an embodiment of the present application. Referring to fig. 2, the apparatus for applying the hybrid-based FFT to the power system includes a determination module 210 and a calculation module 220.
The determining module 210 is configured to determine the number of total sampling points according to the sampling frequency and the number of preset sampling points of a single cycle in a harmonic, and represent the number of total sampling points as a positive integer which is not divided by 2 multiplied by a power of 2.
The calculating module 220 is configured to calculate the power of 2 by using a mixed-basis fast fourier transform algorithm, and calculate a positive integer that cannot be divided by 2 by using a discrete fourier transform algorithm.
In some embodiments, the determining module 210 is specifically configured to:
when the harmonic is inter-harmonic, the number of preset sampling points of a single cycle is represented as A, and the A is calculated by adopting the following formula:
A＝2n
the sampling frequency is denoted as B, which is calculated using the following equation:
B＝2X+1，X＝0，1，2，……
the number of total sampling points is denoted as N, which is calculated using the following equation:
N＝2·A·B＝2·2n·(2X+1)，X＝0，1，2，……
in some embodiments, the calculation module is specifically configured to:
when the harmonic is inter-harmonic, the calculation frequency obtained by calculating the power of 2 by adopting a mixed-basis fast Fourier transform algorithm is represented as C, and the C is calculated by adopting the following formula:
the number of calculations by which a positive integer that is not a power of 2 is calculated using the discrete fourier transform algorithm is denoted as D, which is calculated using the following equation:
D＝8B2
the number of times of calculating the power quality data in the power system is represented as M, and M is calculated by adopting the following formula:
it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
Fig. 3 shows a schematic structural diagram of an electronic device suitable for implementing embodiments of the present application. As shown in fig. 3, the electronic device 300 shown in fig. 3 includes: a processor 301 and a memory 303. Wherein the processor 301 is coupled to the memory 303, such as via bus 5002. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that the transceiver 304 is not limited to one in practical applications, and the structure of the electronic device 300 is not limited to the embodiment of the present application.
The Processor 301 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 301 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
The Memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
The memory 303 is used for storing application program codes for executing the scheme of the application, and the processor 301 controls the execution. The processor 301 is configured to execute application program code stored in the memory 303 to implement the aspects illustrated in the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
The present application provides a computer-readable storage medium, on which a computer program is stored, which, when running on a computer, enables the computer to execute the corresponding content in the foregoing method embodiments. Compared with the prior art, in the embodiment of the application, the mixed-base fast Fourier transform algorithm is adopted to calculate the data collected by the sampling points with the power number of 2, and the discrete Fourier transform algorithm is adopted to calculate the data collected by the sampling points with the positive integer number which is not the power number of 2, so that the problems that the existing processor is low in calculation speed and cannot meet the real-time requirement in a calculation power system can be solved, and the effect of reducing the calculation pressure of the processor is achieved.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a partial embodiment of the present application, and it should be noted that, for those skilled in the art, several modifications and decorations can be made without departing from the principle of the present application, and these modifications and decorations should also be regarded as the protection scope of the present application.
Claims (10)
1. A method for applying a mixed-base FFT in a power system is characterized by comprising the following steps:
when the electric energy quality data in the power system is sampled, the number of total sampling points is determined according to the sampling frequency and the number of preset sampling points of single cycle waves in harmonic waves, and the number of the total sampling points is expressed as a positive integer of a power of 2 multiplied by a power of non-2;
and calculating data acquired by sampling points with the power of 2 by adopting a mixed-basis fast Fourier transform algorithm, and calculating data acquired by sampling points with the positive integer number which is not the power of 2 by adopting a discrete Fourier transform algorithm.
2. The method of claim 1,
the number of the total sampling points is represented by the following formula:
N＝2·A·B＝2·2n·(2X+1)，X＝0，1，2，……
wherein, N is the number of total sampling points, A is the number of preset sampling points of the single-cycle wave, and B is the sampling frequency.
3. The method of claim 2,
the calculation times C required by the data acquired by the sampling points with the power number of 2 calculated by adopting the mixed-basis fast Fourier transform algorithm are as follows:
the number of positive integers not being power of 2 being calculated by discrete Fourier transform algorithmThe number of times D required for the data collected at the sampling points is as follows: D-8B2；
The number of times of calculating the electric energy quality data in the electric power system is expressed as M:
4. the method of claim 1, wherein the harmonic is a subharmonic.
5. An apparatus for applying a hybrid-based FFT to a power system, comprising:
the determining module is used for determining the number of total sampling points according to the sampling frequency and the number of preset sampling points of a single cycle in a harmonic wave when sampling the power quality data in the power system, and expressing the number of the total sampling points as a positive integer which cannot be divided by 2 multiplied by a power of 2;
and the calculating module is used for calculating data acquired by the sampling points with the power number of 2 by adopting a mixed-base fast Fourier transform algorithm and calculating data acquired by the sampling points with the positive integer number which is not the power of 2 by adopting a discrete Fourier transform algorithm.
6. The apparatus of claim 5, wherein the determining module is specifically configured to:
the number of the total sampling points is represented by the following formula:
N＝2·A·B＝2·2n·(2X+1)，X＝0，1，2，……
wherein, N is the number of total sampling points, A is the number of preset sampling points of the single-cycle wave, and B is the sampling frequency.
7. The apparatus of claim 5, wherein the computing module is specifically configured to:
said adoption ofThe calculation times C required by the mixed-basis fast Fourier transform algorithm for calculating the data collected by the sampling points with the power number of 2 are as follows:
the number D of times required for calculating the data collected by the sampling points of the number of positive integers which are not the power of 2 by adopting the discrete Fourier transform algorithm is as follows: D-8B2；
The number of times of calculating the electric energy quality data in the electric power system is expressed as M:
8. the apparatus of claim 5, wherein the harmonic is a subharmonic.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program, wherein the processor, when executing the program, implements the method of any of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110869980.9A CN113567788A (en) | 2021-07-30 | 2021-07-30 | Application method, device, equipment and medium of mixed base FFT (fast Fourier transform) in power system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110869980.9A CN113567788A (en) | 2021-07-30 | 2021-07-30 | Application method, device, equipment and medium of mixed base FFT (fast Fourier transform) in power system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113567788A true CN113567788A (en) | 2021-10-29 |
Family
ID=78169362
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110869980.9A Pending CN113567788A (en) | 2021-07-30 | 2021-07-30 | Application method, device, equipment and medium of mixed base FFT (fast Fourier transform) in power system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113567788A (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030185316A1 (en) * | 2001-07-04 | 2003-10-02 | Katsuyuki Tanaka | Frequency analysis method and apparatus, and spectrum spread demodulation method and appratus |
| CN101937424A (en) * | 2010-09-10 | 2011-01-05 | 南京航空航天大学 | FPGA (Field Programmable Gate Array) based method for realizing high-speed FFT (Fast Fourier Transform) processing |
| CN102830282A (en) * | 2012-09-04 | 2012-12-19 | 国电南京自动化股份有限公司 | 2560-point grouping 2-based rapid fast Fourier transform method |
| CN104459315A (en) * | 2014-11-06 | 2015-03-25 | 电子科技大学 | Inter-harmonic detection method based on non-base 2FFT transformation |
| CN105137176A (en) * | 2015-08-12 | 2015-12-09 | 吕锦柏 | Signal harmonic analysis method for using fast triangular-form Fourier transform |
| CN111308197A (en) * | 2019-12-10 | 2020-06-19 | 国网江苏省电力有限公司扬州供电分公司 | Harmonic measurement method and device based on block FFT |
| CN111398814A (en) * | 2020-04-17 | 2020-07-10 | 中铁隧道局集团有限公司 | Motor fault detection and intelligent rapid diagnosis method controlled by soft starter |
| CN112051446A (en) * | 2020-08-18 | 2020-12-08 | 许继集团有限公司 | Mixed base FFT implementation method and device for broadband measurement of power system |
-
2021
- 2021-07-30 CN CN202110869980.9A patent/CN113567788A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030185316A1 (en) * | 2001-07-04 | 2003-10-02 | Katsuyuki Tanaka | Frequency analysis method and apparatus, and spectrum spread demodulation method and appratus |
| CN101937424A (en) * | 2010-09-10 | 2011-01-05 | 南京航空航天大学 | FPGA (Field Programmable Gate Array) based method for realizing high-speed FFT (Fast Fourier Transform) processing |
| CN102830282A (en) * | 2012-09-04 | 2012-12-19 | 国电南京自动化股份有限公司 | 2560-point grouping 2-based rapid fast Fourier transform method |
| CN104459315A (en) * | 2014-11-06 | 2015-03-25 | 电子科技大学 | Inter-harmonic detection method based on non-base 2FFT transformation |
| CN105137176A (en) * | 2015-08-12 | 2015-12-09 | 吕锦柏 | Signal harmonic analysis method for using fast triangular-form Fourier transform |
| CN111308197A (en) * | 2019-12-10 | 2020-06-19 | 国网江苏省电力有限公司扬州供电分公司 | Harmonic measurement method and device based on block FFT |
| CN111398814A (en) * | 2020-04-17 | 2020-07-10 | 中铁隧道局集团有限公司 | Motor fault detection and intelligent rapid diagnosis method controlled by soft starter |
| CN112051446A (en) * | 2020-08-18 | 2020-12-08 | 许继集团有限公司 | Mixed base FFT implementation method and device for broadband measurement of power system |
Non-Patent Citations (2)
| Title |
|---|
| ANDREW N.SLOSS等: "ARM嵌入式系统开发 软件设计与优化", vol. 7, 31 May 2005, 北京：北京航空航天大学出版社, pages: 293 - 295 * |
| 肖湘宁: "电能质量分析与控制", vol. 7, 29 February 2004, 北京：中国电力出版社, pages: 29 - 32 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Xiao et al. | Increasing the order of convergence for iterative methods to solve nonlinear systems | |
| Karmouni et al. | Fast reconstruction of 3D images using Charlier discrete orthogonal moments | |
| CN107315564B (en) | Device and method for executing vector transcendental function operation | |
| CN109444515B (en) | Reactive power, imbalance and harmonic detection method based on SDFT algorithm | |
| Cetin et al. | An integrated 256-point complex FFT processor for real-time spectrum analysis and measurement | |
| Chandra Inguva et al. | Implementation of FPGA design of FFT architecture based on CORDIC algorithm | |
| CN113567788A (en) | Application method, device, equipment and medium of mixed base FFT (fast Fourier transform) in power system | |
| Thomas et al. | Fixed-point implementation of discrete Hirschman transform | |
| Jothin et al. | High performance modified static segment approximate multiplier based on significance probability | |
| Papakostas et al. | Numerical stability of fast computation algorithms of Zernike moments | |
| RU2003100794A (en) | METHOD AND DEVICE FOR QUICK CALCULATION OF A DISCRETE WAVELET TRANSFORMING A SIGNAL WITH AN ARBITRARY STEP OF DISCRETIZATION OF SCALE SCALES | |
| Murillo et al. | PLAUs: Posit Logarithmic Approximate Units to implement low-cost operations with real numbers | |
| JP2022024080A (en) | Neural network product-sum calculation method and device | |
| Slavchev et al. | Performance study of hierarchical semi-separable compression solver for parabolic problems with space-fractional diffusion | |
| CN108229668B (en) | Operation implementation method and device based on deep learning and electronic equipment | |
| Banerjee et al. | A Novel Paradigm of CORDIC-Based FFT Architecture Framed on the Optimality of High-Radix Computation | |
| Kovács et al. | Software implementation of the recursive discrete Fourier transform | |
| Singh et al. | Reduced cost numerical methods of sixth-order convergence for systems of nonlinear models | |
| TW201423438A (en) | Digital signal processing apparatus and processing method thereof | |
| Yasodai et al. | An efficient implementation of rotational radix-4 CORDIC based FFT processor | |
| Chouhan et al. | FPGA Implementation of High Performance and Energy Efficient Radix-4 based FFT | |
| Chen et al. | Numerical approximations of highly oscillatory Hilbert transforms | |
| JP3872724B2 (en) | Rotation factor table for fast Fourier transform and fast Fourier transform device using the same | |
| CN113114119B (en) | Method and system for judging noise interference level of novel feedback controller on line | |
| US20100106761A1 (en) | Method, Apparatus, and Computer Program Product for Identifying Techniques for Solving Functions |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |