CN102680838B - Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform - Google Patents
Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform Download PDFInfo
- Publication number
- CN102680838B CN102680838B CN201210177935.8A CN201210177935A CN102680838B CN 102680838 B CN102680838 B CN 102680838B CN 201210177935 A CN201210177935 A CN 201210177935A CN 102680838 B CN102680838 B CN 102680838B
- Authority
- CN
- China
- Prior art keywords
- data
- electric energy
- dual
- energy quality
- programmable logic
- 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.)
- Expired - Fee Related
Links
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
Abstract
The invention discloses an electric energy quality monitoring and distinguishing method based on dual-tree complex wavelet transform and relates to the technical field of data acquisition, signal processing and mode distinguishing. The monitoring system controls a data acquisition state machine in an on-site programmable logic controller through a digital signal processor, a high-precision 8-channel 16-bit symmetrical analog to digital (AD) converter is controlled through the data acquisition state machine in the programmable logic controller so as to complete synchronous acquisition of electric energy quality signals, the digital signal processor reads acquired electric energy liquid data from a first in first out (FIFO) memory in the programmable logic controller, the dual-tree complex wavelet transform is performed on the acquired electric energy liquid data, wavelet coefficient Shannon entropy of the acquired electric energy liquid data is calculated, and finally a wavelet support vector machine classifier based on a binary tree is used for classifying and distinguishing disturbing signals so as to achieve continuous real-time accurate electric energy quality monitoring of three-phase voltage and current. In addition, the invention further provides an electric energy quality monitoring and distinguishing system.
Description
Technical field
The invention belongs to the technical field of electric energy quality monitoring and identification, be specifically related to data acquisition, signal processing and mode identification technology, particularly a kind of electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform also relates to a kind of system simultaneously.
Background technology
In recent years, power quality problem has become one of major issue of power department and user's common concern.It is to find power quality problem the precondition of administering and improving that the quality of power supply is carried out to determination and analysis.The quality of power supply in short-term perturbation analysis accounts for critical role in power quality analysis, and its Classification and Identification is a complicated problem, because the disturbance type that it comprises numerous complicated, and various undesired signal itself also has very large scrambling.
Disturbing signal is carried out to the key that feature extraction is electrical energy power quality disturbance identification, and wherein main feature extracting method has: Fourier transform, wavelet transformation, Atomic Decomposition method, S conversion etc.Because existing method cannot be accomplished real-time continuous monitoring to the quality of power supply, and not high to the discrimination of Power Quality Disturbance.
Summary of the invention
In view of this, one of object of the present invention is to provide a kind of electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform, by 3 phase voltage current signals are accurately gathered, then carry out analyzing and processing, realize the real-time continuous monitoring of the 3 phase qualities of power supply, and can effectively identify common various undesired signals, for the improvement of electric network pollution provides technical guarantee; Two of object of the present invention is to provide a kind of electric energy quality monitoring recognition system based on dual-tree complex wavelet transform.
One of object of the present invention is achieved through the following technical solutions:
Electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform, comprises the following steps:
1) 3 phase voltages, 3 phase current signals are carried out to signal extraction through corresponding voltage current transformer respectively, then through second order Butterworth low-pass filtering, be input to multi-channel synchronous AD converter, the data acquisition state machine of field programmable logic controller inside produces the control sequential of multi-channel synchronous AD converter, complete collection and the buffer memory of 3 phase voltages and 3 phase current signals, and with the mode number of notifications word signal processor of look-at-me;
2) digital signal processor receive interruption responds, and reads 3 phase voltages and 3 phase current signals of Real-time Collection in the FIFO from field programmable logic controller;
3) digital signal processor carries out 3 layers of dual-tree complex wavelets decomposition to 3 phase voltages that read and 3 phase current signals, and calculates its wavelet coefficient Shannon entropy, as the proper vector of disturbing signal;
4) adopt the wavelet support vector machines sorter based on binary tree to identify the proper vector of disturbing signal;
5) recognition result is sent to detection system main frame through wireless communication module.
6) monitoring recognition system holds on a correspondence by " encoding and decoding heartbeat packet " and monitoring central server.
Further, described step 1) comprises the steps:
11) the data acquisition state machine of field programmable logic controller inside is as a peripheral hardware of digital signal processor, independently take a sector address addressing space, first digital signal processor stops the work of data acquisition state machine, then write the relevant control parameter of multi-channel synchronous AD converter to it, comprise sample frequency and control sequential, finally by the order of digital signal processor write-enable, the work of log-on data acquisition state machine;
12) field programmable logic controller is integrated with a data acquisition state machine in inside, only in the time quitting work, just receives writing of the relevant control parameters such as sample frequency, starts working receiving after the startup command of digital signal processor;
13) field programmable logic controller internal configurations push-up storage SCFIFO, for 3 phase voltages that gather and the buffer-stored of 3 phase current signal data, the data acquisition state machine of field programmable logic controller inside is according to correlation parameters such as sample frequency, at the scene under the effect of programmable logic controller (PLC) internal clocking, count time delay by counter, the control sequential correlation parameter of the multi-channel synchronous AD converter writing according to digital signal processor, produce the conversion starting signal of multi-channel synchronous AD converter, and read the status signal of multi-channel synchronous AD converter, guarantee after the success of multi-channel synchronous AD converter data-switching, producing sheet selects CS control signal and data to read RD control signal, from multi-channel synchronous AD converter, read the power quality data of collection,
14) data acquisition state machine reads after the power quality data of collection, produce the written allowance signal of reading of buffer memory SCFIFO, at the scene under the effect of programmable logic controller (PLC) internal clocking, 3 phase voltages and 3 phase current data are write successively to the SCFIFO module of field programmable logic controller inside.
Further, in step 13), described field programmable logic controller to inner SCFIFO block configuration Almost_full and Almost_empty function, in the time that the image data number of SCFIFO buffer memory is greater than 8000, the Almost_full signal of SCFIFO output triggers look-at-me, when the image data number of SCFIFO buffer memory is lower than 192 time, SCFIFO output Almost_empty signal.
Further, described step 2) comprise the steps:
21) INT5 that the Almost_full signal of exporting as SCFIFO triggers TMS320DM642 interrupts, in interrupt routine, DSP starts EDMA data-moving program, the disposable power quality data of moving 8000 3 phase voltages and 3 phase currents from the SCFIFO module of EP2C8QF208I8 inside;
22) from the power quality data of 8000 3 phase voltages and 3 phase currents, order is isolated the electric current and voltage data of each phase successively, and analyzes identification for disturbance program.
Further, described step 3) comprises the steps:
31) electric energy quality signal is carried out to dual-tree complex wavelet transform:
Dual-tree complex wavelet has adopted the two-way wavelet transform of binary tree structure, and a tree generates the real part of conversion, and a tree generates the imaginary part of conversion, and dual-tree complex wavelet transform relation can be expressed as:
W
c(t)＝W
h(t)+jW
g(t)
W
c(t) represent wavelet coefficient, W
hand W (t)
g(t) form Hilbert transfer pair.Dual-tree complex wavelet transform is realized by low-pass filter and the Hi-pass filter of corresponding real number structure.
32) the dual-tree complex wavelet coefficient of dissociation obtaining is carried out to the calculating of wavelet coefficient Shannon entropy: establish X
j,krepresent a sub-frequency bands wavelet coefficient S of wavelet decomposition
j, ktime domain reconstruction discrete signal, S
j,krepresent k node coefficient of wavelet decomposition of j layer,
First electric energy quality signal is carried out to 3 layers of dual-tree complex wavelet and decompose, press
formula calculates the E (X of each node
j,k) value, and with the E (X of the whole nodes of this one deck
j,k) formation Shannon entropy proper vector E
p=[E (X
j, 1), E (X
j, 2) ..., E (X
j, k)].
Further, described step 4) comprises the steps:
41) adopt the wavelet support vector machines sorter structure based on binary tree, its kernel function is selected Morlet small echo, and its wavelet function is:
Utilize the proper vector of various disturbing signals to train the sorter based on small echo support vector; Wherein K (x, x') represents core mapping function, and support vector machine core mapping function can meet translation invariance, i.e. K (x, x')=K (x-x'), and X represents translational movement, in above formula, d represents small echo dimension; a
i>0, represents small echo contraction-expansion factor; x
irepresent i dimension small echo variable, x
i' represent that i ties up the translational movement of small echo.
42) disturbing signal to be identified is utilized to step 51) in the sorter that obtains of training carry out Classification and Identification.
Further, described step 5) comprises the steps:
51), according to recognition result, the quality of power supply relevant information of 3 phase voltages that obtain and 3 phase currents is sent to detection system main frame through wireless communication module, and provide corresponding alerting signal and voice message by system;
52) digital signal processor carries out data communication by extending out the realization of a slice serial control core with Serial Peripheral Interface (SPI) chip, the serial ports UART0 of Serial Peripheral Interface (SPI) chip is for carrying out exchanges data with digital signal processor, and data are encapsulated to packing, pass to MC323 module by serial ports UART1, recognition result is sent to Surveillance center.
Further, in step 6), in order to ensure the reliability of radio communication, " encoding and decoding heartbeat packet " data have been carried out to special encoding and decoding processing, monitoring terminal sends " encoding and decoding heartbeat packet " data layout and is:
| Frame head | Terminal number | Data length | Random data | Cumulative sum |
Monitoring central server is received after " encoding and decoding heartbeat packet ", the decode operation that " random data " of " encoding and decoding heartbeat packet " carried out to step-by-step negate, recalculate cumulative sum, then arrive corresponding monitor terminal according to " encoding and decoding heartbeat packet " data layout passback data, thereby guarantee reliability and the uniqueness of data communication;
Two of object of the present invention is achieved through the following technical solutions:
Be somebody's turn to do electric energy quality monitoring and recognition system based on dual-tree complex wavelet transform, comprise
Signal extraction and converting unit, comprise for 3 phase currents, voltage signal being carried out to the mutual inductor of signal extraction, signal carried out to wave filter and the multi-channel synchronous AD converter of second order Butterworth low-pass filtering, also comprise field programmable logic controller, the data acquisition state machine of described programmable logic controller (PLC) inside produces the control sequential of multi-channel synchronous AD converter, complete collection and the buffer memory of 3 phase voltages and 3 phase current signals, and with the mode number of notifications word signal processor of look-at-me;
Digital signal processor, for receive interruption response, in the FIFO from field programmable logic controller, read 3 phase voltages and 3 phase current signals of Real-time Collection, carry out after 3 layers of dual-tree complex wavelets decomposition, calculate its wavelet coefficient Shannon entropy, as the proper vector of disturbing signal;
Wavelet support vector machines sorter, as a program module in digital signal processor, identifies the proper vector of disturbing signal based on binary tree;
Wireless communication module, for being sent to recognition result in detection system main frame.
The invention has the beneficial effects as follows:
The present invention adopts the data acquisition control state machine control AD converter AD7606 data acquisition and the buffer memory that utilize field programmable logic controller inside, pass through the efficient reading out data of EDMA mode at high speed digital signal processor, and electric energy quality signal is decomposed by dual-tree complex wavelet transform in inside, and calculate the proper vector of Shannon entropy as disturbing signal, then use the wavelet support vector machines sorter based on binary tree to classify and identification to disturbing signal, finally recognition result is sent to electric energy quality monitoring center; The present invention is in design of electronic circuits, part of data acquisition is by data acquisition state machine control AD converter data acquisition and the buffer memory of programmable logic controller (PLC) inside, high speed digital signal processor carries out analyzing and processing, this design architecture can guarantee that data acquisition carries out with synchronizeing of data analysis, has ensured the continuity of power quality data and the real-time of analysis; Although the present invention slightly increases the operation time than traditional recognition method in calculated amount, has improved more than 11% for the average recognition rate of disturbing signal, and the robustness of noise has been improved to approximately 15%.Along with the continuous lifting of CPU arithmetic speed, consider discrimination and feature extraction time, patent of the present invention has obvious technical advantage.
Other advantages of the present invention, target and feature will be set forth to a certain extent in the following description, and to a certain extent, based on will be apparent to those skilled in the art to investigating below, or can be instructed from the practice of the present invention.Target of the present invention and other advantages can be realized and be obtained by instructions and claims below.
Brief description of the drawings
In order to make the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing, the present invention is described in further detail, wherein:
Fig. 1: realize the inventive method overall block-diagram;
Fig. 2: data acquisition module theory diagram of the present invention;
Fig. 3: wireless data transmission module theory diagram of the present invention;
Fig. 4: the wavelet vectors machine sort tree structure based on binary tree in the present invention;
Fig. 5: the feature vector chart of 8 kinds of common disturbing signals in the present invention.
Embodiment
Hereinafter with reference to accompanying drawing, the preferred embodiments of the present invention are described in detail.Should be appreciated that preferred embodiment is only for the present invention is described, instead of in order to limit the scope of the invention.
Fig. 1 is the general frame that realizes the inventive method, and a kind of dual-tree complex wavelet electric energy quality monitoring of the present invention and recognition methods and system, comprise the steps:
1) 3 phase voltages, 3 phase current signals are carried out to signal extraction through corresponding voltage current transformer respectively, then through second order Butterworth low-pass filtering, be input to multi-channel synchronous AD converter, the data acquisition state machine of field programmable logic controller inside produces the control sequential of multi-channel synchronous AD converter, complete collection and the buffer memory of 3 phase voltages and 3 phase current signals, and with the mode number of notifications word signal processor of look-at-me;
2) digital signal processor receive interruption responds, and reads 3 phase voltages and 3 phase current signals of Real-time Collection in the SCFIFO from field programmable logic controller;
3) digital signal processor carries out 3 layers of dual-tree complex wavelets decomposition to 3 phase voltages that read and 3 phase current signals, and calculates its wavelet coefficient Shannon entropy, as the proper vector of disturbing signal; In the present embodiment, adopt the multiple wavelet decomposition of 3 layers of even numbers, through evidence, respond well;
4) adopt the wavelet support vector machines sorter based on binary tree to identify the proper vector of disturbing signal;
5) recognition result is sent to detection system main frame through wireless communication module.
6) monitoring identification terminal system holds on a correspondence by " encoding and decoding heartbeat packet " and monitoring central server.
In the present embodiment, multi-channel synchronous AD converter adopts the AD7606 with 8 passages, and field programmable logic controller adopts EP2C8QF208I8, and digital signal processor adopts TMS320DM642, and wireless communication module adopts cdma communication module MC323.
Below the concrete implementation step to each step is described further:
A. in step 1), comprise the steps:
11) for 1) signal that obtains adopts second order Butterworth LPF to carry out filtering processing, and cutoff frequency is 1KHz;
12) field programmable logic controller EP2C8QF208I8 adopts data acquisition state machine to produce the control sequential of AD7606 in its inside, completes the controlling of sampling to AD7606, and produces the written allowance signal of reading of buffer memory SCFIFO;
13) correlation parameter of the data acquisition state machine of field programmable logic controller EP2C8QF208I8 inside is directly imported according to the control sequential correlation parameter of sample frequency and AD7606 by TMS320DM642;
14) buffer memory of 3 phase voltage current signals of field programmable logic controller EP2C8QF208I8 inside adopts 16 8K(8192) SCFIFO of the buffer memory degree of depth; To SCFIFO block configuration Almost_full and the Almost_empty function of SCFIFO.In the time that the image data number of SCFIFO buffer memory is greater than 8000, the Almost_full signal of SCFIFO output triggers look-at-me, when the image data number of SCFIFO buffer memory is lower than 192 time, and SCFIFO output Almost_empty signal;
B. step 2) in, comprise the steps:
21) INT5 that the Almost_full signal of exporting as SCFIFO triggers TMS320DM642 interrupts.In interrupt response program, DSP starts EDMA data-moving program, adopts that EDMA mode is disposable moves 8000 power quality datas from the SCFIFO buffer memory of FPGA;
22) isolate 3 phase voltage current data from 8000 power quality datas successively order, and identify for the analysis of disturbance program.
C. in described step 3), comprise the steps:
31) electric energy quality signal is carried out to dual-tree complex wavelet transform
Dual-tree complex wavelet has adopted the two-way wavelet transform of binary tree structure, and a tree generates the real part of conversion, and a tree generates the imaginary part of conversion.Dual-tree complex wavelet transform relation can be expressed as:
W
c(t)＝W
h(t)+jW
g(t)
W
c(t) represent wavelet coefficient, W
hand W (t)
g(t) form Hilbert transfer pair.Dual-tree complex wavelet transform is realized by low-pass filter and the Hi-pass filter of corresponding real number structure.
32) to 31) obtain coefficient of wavelet decomposition carry out the calculating of wavelet coefficient Shannon entropy.If X
j,krepresent a sub-frequency bands wavelet coefficient S of wavelet decomposition
j,ktime domain reconstruction discrete signal, S
j,krepresent k node coefficient of wavelet decomposition of j layer.
First electric energy quality signal is carried out to 3 layers of dual-tree complex wavelet and decompose, press
formula calculates the E (X of each node
j,k) value, and with the E (X of the whole nodes of this one deck
j,k) formation Shannon entropy proper vector E
p=[E (X
j, 1), E (X
j, 2) ..., E (X
j, k)].
D. in described step 4), comprise the steps:
41) utilize the proper vector of various disturbing signals to train the sorter of the small echo support vector based on binary tree.
Wavelet support vector machines combines wavelet theory and SVM method, complementary the two advantage, and introducing wavelet basis function is constructed the kernel function of SVM, and it,, except having all advantages of SVM, can also eliminate the high frequency interference of data, possesses good anti-noise ability.Can be used for constructing Wavelet Kernel Function as long as can generate female small echo of wavelet frame.Patent of the present invention adopts the kernel function of Morlet small echo as support vector machine, should illustrate, is not restricted to this kind of wavelet function.
The form of Morlet small echo is:
Its wavelet function is:
Electrical energy power quality disturbance identification is multi-class identification problem, and the many sorting techniques of conventional SVM have two kinds, and one is " one against one ", and another kind is " one against rest ".First method classification performance is good, but along with the increase operand of training classification number increases greatly.And the latter's degree of accuracy is slightly poor, training sample is large, promote error and do not restrain, and real-time is poor.In view of the deficiency of above-mentioned two kinds of sorting techniques, in conjunction with the actual characteristic of Power Quality Disturbance, select binary tree structural support vector machine to identify various disturbing signals.WSVM classifier methods based on binary tree as shown in Figure 4, for a k class problem, need to be trained k-1 sorter.In the present invention, common 8 kinds of disturbing signals and hybrid perturbation signal are identified, k=9 need to design 8 sorters in the time of design category device.
Every kind of disturbing signal selects respectively 100 proper vectors as training sample, and the WSVM sorter based on binary tree is trained.The wavelet support vector machines that is met requirement through training can be used as the effective ways of power disturbance identification, in actual power quality monitoring, is effectively applied.
42) proper vector of disturbing signal to be identified is utilized to 41) in the WSVM sorter based on binary tree that obtains of training carry out Classification and Identification.
E. in step 5), comprise the steps:
51) according to recognition result, draw the relevant information of the quality of power supply, send to detection system main frame through radio CDMA communication module, and provide corresponding alerting signal and voice message by system.
52) TMS320DM642 carries out data communication by extending out the realization of a slice TL16C752 serial port chip with LPC2134.The inner integrated two serial ports of LPC2134, are mainly responsible for the parsing of data command, set up the UART serial-port of " transparent " between monitoring terminal and server.The serial ports UART0 of LPC2134 is used for and DSP carries out exchanges data, and data are encapsulated to packing, passes to CDMA module by serial ports UART1, and recognition result is sent to Surveillance center through radio CDMA communication module.
Can be online for a long time in order to ensure CDMA module, in LPC2134 program code, also increase every 5 minutes " encoding and decoding heartbeat packet " data once, guarantee reliability and the uniqueness of data communication, effectively avoid the generation of lost line.
In step 6), in order to ensure the reliability of radio communication, " encoding and decoding heartbeat packet " data are carried out to special encoding and decoding processing, monitoring terminal sends " encoding and decoding heartbeat packet " data layout and is:
| Frame head | Terminal number | Data length | Random data | Cumulative sum |
Monitoring central server is received after " encoding and decoding heartbeat packet ", the decode operation that " random data " of " encoding and decoding heartbeat packet " carried out to step-by-step negate, recalculate cumulative sum, then arrive corresponding monitor terminal according to " encoding and decoding heartbeat packet " data layout passback data, guarantee reliability and the uniqueness of data communication.
Based on the design philosophy of said method, electric energy quality monitoring and the recognition system based on dual-tree complex wavelet transform of the present invention comprises:
(1) signal extraction and converting unit, comprise for 3 phase currents, voltage signal being carried out to the mutual inductor of signal extraction, signal carried out to wave filter and the multi-channel synchronous AD converter of second order Butterworth low-pass filtering, also comprise field programmable logic controller, the data acquisition state machine of described programmable logic controller (PLC) inside produces the control sequential of multi-channel synchronous AD converter, complete collection and the buffer memory of 3 phase voltages and 3 phase current signals, and with the mode number of notifications word signal processor of look-at-me;
(2) digital signal processor, for receive interruption response, in the FIFO from field programmable logic controller, read 3 phase voltages and 3 phase current signals of Real-time Collection, carry out after 3 layers of dual-tree complex wavelets decomposition, calculate its wavelet coefficient Shannon entropy, as the proper vector of disturbing signal;
(3) wavelet support vector machines sorter, as a program module in digital signal processor, identifies the proper vector of disturbing signal based on binary tree, and this recognizer mainly realizes in digital signal processor;
(4) wireless communication module, for being sent to recognition result in detection system main frame.
Fig. 2 in accompanying drawing is data acquisition module theory diagram, has provided respectively the annexation figure of AD7606, field programmable logic controller EP2C8QF208I8 and digital signal processor TMS320DM642, Fig. 3 is wireless data transmission module theory diagram, has provided respectively the annexation figure between digital signal processor TMS320DM642, serialization controller TL16C752,32 ARM controller LPC2134 and CDMA module MC323, Fig. 4 is the wavelet support vector machines structure based on binary tree structure, 8 types of common disturbances have: voltage die (voltage sag), voltage jump (voltage swell), voltage interruption (interruption), vibration transient state (oscillatory transients), pulse transient state (impulse transients), due to voltage spikes (spike), Voltage notches (notch) and harmonic wave (harmonics), increase in addition a class hybrid perturbation (Complex Disturbances), totally 9 class disturbing signals, 8 sorters in the present invention, are designed, Fig. 5 is that disturbance in short-term has common 8 types to carry out respectively 3 layers of dual-tree complex wavelet and decompose to the quality of power supply, and calculates respectively wavelet coefficient Shannon entropy as proper vector.
The present invention adopts a kind of electrical energy power quality disturbance recognition methods and system based on dual-tree complex wavelet transform, utilize field programmable logic controller EP2C8QF208I8 to control AD converter AD7606 data acquisition and buffer memory, pass through the efficient reading out data of EDMA mode at high speed digital signal processor TMS320DM642, and electric energy quality signal is decomposed by dual-tree complex wavelet transform in inside, and calculate the proper vector of Shannon entropy as disturbing signal, then use the wavelet support vector machines based on binary tree to carry out classification and the identification of disturbing signal.Finally, recognition result is sent to electric energy quality monitoring center.
Finally explanation is, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that, can modify or be equal to replacement technical scheme of the present invention, and not departing from aim and the scope of the technical program, it all should be encompassed in the middle of claim scope of the present invention.
Claims (9)
1. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform, is characterized in that: said method comprising the steps of:
1) 3 phase voltages, 3 phase current signals are carried out to signal extraction through corresponding voltage, current transformer respectively, then through second order Butterworth low-pass filtering, be input to multi-channel synchronous AD converter, the data acquisition state machine of field programmable logic controller inside produces the control sequential of multi-channel synchronous AD converter, complete collection and the buffer memory of 3 phase voltages and 3 phase current signals, and with the mode number of notifications word signal processor of look-at-me;
2) digital signal processor receive interruption responds, and reads 3 phase voltages and 3 phase current signals of Real-time Collection in the FIFO from field programmable logic controller;
3) digital signal processor carries out 3 layers of dual-tree complex wavelets decomposition to 3 phase voltages that read and 3 phase current signals, and calculates its wavelet coefficient Shannon entropy, as the proper vector of disturbing signal;
4) adopt the wavelet support vector machines sorter based on binary tree to identify the proper vector of disturbing signal;
5) recognition result is sent to detection system main frame through wireless communication module;
6) monitoring recognition system holds on a correspondence by " encoding and decoding heartbeat packet " and monitoring central server.
2. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 1, is characterized in that: described step 1) comprises the steps:
11) the data acquisition state machine of field programmable logic controller inside is as a peripheral hardware of digital signal processor, independently take a sector address addressing space, first digital signal processor writes and ceases and desist order, stop the work of data acquisition state machine, then write the relevant control parameter of multi-channel synchronous AD converter to it, comprise sample frequency and control sequential, finally by the order of digital signal processor write-enable, the work of log-on data acquisition state machine;
12) field programmable logic controller is integrated with a data acquisition state machine in inside, only in the time quitting work, just receives writing of the relevant control parameters such as sample frequency, starts working receiving after the startup command of digital signal processor;
13) field programmable logic controller internal configurations push-up storage SCFIFO, for 3 phase voltages that gather and the buffer-stored of 3 phase current signal data, the data acquisition state machine of field programmable logic controller inside is according to correlation parameters such as sample frequency, at the scene under the effect of programmable logic controller (PLC) internal clocking, count time delay by counter, the control sequential correlation parameter of the multi-channel synchronous AD converter writing according to digital signal processor, produce the conversion starting signal of multi-channel synchronous AD converter, and read the status signal of multi-channel synchronous AD converter, guarantee after the success of multi-channel synchronous AD converter data-switching, producing sheet selects CS control signal and data to read RD control signal, from multi-channel synchronous AD converter, read the power quality data of collection,
14) data acquisition state machine reads after the power quality data of collection, produce the written allowance signal of buffer memory SCFIFO, under the effect of programmable logic controller (PLC) internal clocking, 3 phase voltages and 3 phase current data are write in the SCFIFO module of field programmable logic controller inside successively at the scene.
3. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 2, it is characterized in that: in step 13), described field programmable logic controller to inner SCFIFO block configuration Almost_full and Almost_empty function, in the time that the image data number of SCFIFO buffer memory is greater than 8000, the Almost_full signal of SCFIFO output triggers look-at-me, when the image data number of SCFIFO buffer memory is lower than 192 time, SCFIFO output Almost_empty signal.
4. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 3, is characterized in that: described step 2) comprise the steps:
21) when the INT5 of the Almost_full signal triggered digital signal processor of SCFIFO output interrupts, in interrupt routine, DSP starts EDMA data-moving program, the disposable power quality data of moving 8000 3 phase voltages and 3 phase currents from the SCFIFO module of EP2C8QF208I8 inside;
22) from the power quality data of 8000 3 phase voltages and 3 phase currents, order is isolated the electric current and voltage data of each phase successively, and analyzes identification for disturbance program.
5. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 1, is characterized in that: described step 3) comprises the steps:
31) electric energy quality signal is carried out to dual-tree complex wavelet transform:
Dual-tree complex wavelet has adopted the two-way wavelet transform of binary tree structure, and a tree generates the real part of conversion, and a tree generates the imaginary part of conversion, and dual-tree complex wavelet transform relation can be expressed as:
W
c(t)＝W
h(t)+jW
g(t)
W
c(t) represent wavelet coefficient, W
hand W (t)
g(t) form Hilbert transfer pair, dual-tree complex wavelet transform can be realized by the low-pass filter of corresponding real number structure and Hi-pass filter;
32) coefficient of wavelet decomposition obtaining is carried out to the calculating of wavelet coefficient Shannon entropy: establish X
j,krepresent a sub-frequency bands wavelet coefficient S of wavelet decomposition
j,ktime domain reconstruction discrete signal, S
j,krepresent k node coefficient of wavelet decomposition of j layer,
First electric energy quality signal is carried out to 3 layers of dual-tree complex wavelet and decompose, press
formula calculates the E (X of each node
j,k) value, and with the E (X of the whole nodes of this one deck
j,k) formation Shannon entropy proper vector E
p=[E (X
j, 1), E (X
j, 2) ..., E (X
j,k)].
6. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 1, is characterized in that: described step 4) comprises the steps:
41) adopt the wavelet support vector machines sorter structure based on binary tree, its kernel function is selected Morlet small echo, and its wavelet function is:
Utilize the proper vector of various disturbing signals to train the sorter based on small echo support vector, wherein K (x, x') represent core mapping function, support vector machine core mapping function meets translation invariance, be K (x, x')=K (x-x'), x ' expression translational movement, in above formula, d represents small echo dimension; a
i>0, represents small echo contraction-expansion factor; x
irepresent i dimension small echo variable, x '
irepresent the translational movement of i dimension small echo;
42) disturbing signal to be identified is utilized to step 51) in the binary tree sorter that obtains of training carry out Classification and Identification.
7. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 1, is characterized in that: described step 5) comprises the steps:
51), according to recognition result, the quality of power supply relevant information of 3 phase voltages that obtain and 3 phase currents is sent to detection system main frame through wireless communication module, and provide corresponding alerting signal and voice message by system;
52) digital signal processor carries out data communication by extending out the realization of a slice serial control core with Serial Peripheral Interface (SPI) chip, the serial ports UART0 of Serial Peripheral Interface (SPI) chip is for carrying out exchanges data with digital signal processor, and data are encapsulated to packing, pass to MC323 module by serial ports UART1, recognition result is sent to Surveillance center.
8. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 1, it is characterized in that: in step 6), can be online for a long time in order to ensure radio communication CDMA module, in the program code of Serial Peripheral Interface (SPI) chip, also increase every a time period and triggered " encoding and decoding heartbeat packet " data once, be that per minute and monitoring central server keep shaking hands once writing to each other, when not having realization and monitoring central server to keep shaking hands contact in continuous a period of time, Serial Peripheral Interface (SPI) chip resets to MC323 module, thereby avoid the generation of CDMA module lost line.
9. the electric energy quality monitoring recognition methods based on dual-tree complex wavelet transform according to claim 1, it is characterized in that: in step 6), in order to ensure the reliability of radio communication, " encoding and decoding heartbeat packet " data have been carried out to special encoding and decoding processing, and monitoring terminal sends " encoding and decoding heartbeat packet " data layout and is:
Monitoring central server is received after " encoding and decoding heartbeat packet ", the decode operation that " random data " of " encoding and decoding heartbeat packet " carried out to step-by-step negate, recalculate cumulative sum, then arrive corresponding monitor terminal according to " encoding and decoding heartbeat packet " data layout passback data, thereby guarantee reliability and the uniqueness of data communication.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210177935.8A CN102680838B (en) | 2012-05-31 | 2012-05-31 | Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210177935.8A CN102680838B (en) | 2012-05-31 | 2012-05-31 | Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102680838A CN102680838A (en) | 2012-09-19 |
| CN102680838B true CN102680838B (en) | 2014-08-13 |
Family
ID=46813069
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210177935.8A Expired - Fee Related CN102680838B (en) | 2012-05-31 | 2012-05-31 | Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102680838B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103454537A (en) * | 2013-09-16 | 2013-12-18 | 国家电网公司 | Wind power generation low-voltage ride-through detection equipment and method based on wavelet analysis |
| CN104459364A (en) * | 2013-09-23 | 2015-03-25 | 上海达实联欣科技发展有限公司 | Electric energy monitoring equipment |
| CN103605757B (en) * | 2013-11-25 | 2017-02-08 | 国家电网公司 | High-speed rail power quality data sorting method based on SVM (support vector machine) |
| CN113361427B (en) * | 2021-06-11 | 2024-03-15 | 温州大学 | Composite electric energy quality disturbance classification method based on WT and GA-PNN |
| CN113484654B (en) * | 2021-08-24 | 2023-10-10 | 南京协胜智能科技有限公司 | Power quality monitoring and identifying method based on double-tree complex wavelet transformation |
| CN115792377B (en) * | 2023-01-29 | 2023-05-19 | 国网山西省电力公司营销服务中心 | Harmonic detection method and device based on dual-tree complex wavelet transformation algorithm |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7188276B2 (en) * | 2002-06-17 | 2007-03-06 | Samsung Electronics, Co., Ltd. | Apparatus and method for testing a computer system by utilizing FPGA and programmable memory module |
| CN201173949Y (en) * | 2008-03-26 | 2008-12-31 | 首都师范大学 | Three phase electrical energy meter based on NIOS IImicroprocessor |
| CN102288843A (en) * | 2011-05-16 | 2011-12-21 | 湖南大学 | Power quality disturbance signal detection method |
-
2012
- 2012-05-31 CN CN201210177935.8A patent/CN102680838B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7188276B2 (en) * | 2002-06-17 | 2007-03-06 | Samsung Electronics, Co., Ltd. | Apparatus and method for testing a computer system by utilizing FPGA and programmable memory module |
| CN201173949Y (en) * | 2008-03-26 | 2008-12-31 | 首都师范大学 | Three phase electrical energy meter based on NIOS IImicroprocessor |
| CN102288843A (en) * | 2011-05-16 | 2011-12-21 | 湖南大学 | Power quality disturbance signal detection method |
Non-Patent Citations (6)
| Title |
|---|
| Ivan W. Selesnick.The Double-Density Dual-Tree DWT.《IEEE TRANSACTIONS ON SIGNAL PROCESSING》.2004,第52卷(第5期),全文. |
| The Double-Density Dual-Tree DWT;Ivan W. Selesnick;《IEEE TRANSACTIONS ON SIGNAL PROCESSING》;20040531;第52卷(第5期);全文 * |
| 基于DSP与FPGA的实时电能质量监测终端系统;王平等;《电力系统保护与控制》;20120616;第40卷(第12期);全文 * |
| 基于改进小波能熵和支持向量机的短时电能质量扰动识别;李庚银等;《电工技术学报》;20090430;第24卷(第4期);全文 * |
| 李庚银等.基于改进小波能熵和支持向量机的短时电能质量扰动识别.《电工技术学报》.2009,第24卷(第4期),全文. |
| 王平等.基于DSP与FPGA的实时电能质量监测终端系统.《电力系统保护与控制》.2012,第40卷(第12期),全文. |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102680838A (en) | 2012-09-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102680838B (en) | Electric energy quality monitoring and distinguishing method and electric energy quality monitoring and distinguishing system based on dual-tree complex wavelet transform | |
| CN104483011B (en) | A kind of on-line checking of rotating machinery multi-channel Vibration Signal and analysis system and method | |
| Wang et al. | Synchrophasor data compression under disturbance conditions via cross-entropy-based singular value decomposition | |
| CN108872743A (en) | A kind of electric energy quality real-time monitoring analysis system and method based on wavelet transformation | |
| CN105045391A (en) | Smart watch gesture input method and smart watch | |
| TWI752486B (en) | Training method, feature extraction method, device and electronic device | |
| CN108538290A (en) | A kind of intelligent home furnishing control method based on audio signal detection | |
| CN107315809A (en) | A kind of group's news data preprocess method based on Spark platforms | |
| CN107437967A (en) | Data transmission method based on sound wave, send equipment and receiving device | |
| CN205583839U (en) | Computer integrated protection measurement and control device of transformer substation | |
| CN202748417U (en) | Parameter monitoring system of frequency converter in wind generating set | |
| CN103135488B (en) | Based on the vehicle-mounted comprehensive exploitation platform of FlexRay | |
| CN115733780B (en) | Dynamic self-adaption method, system, equipment and medium based on flexible Ethernet | |
| CN203720258U (en) | Voltage and current transient signal high-speed synchronous data sampling device | |
| Lai | Compression of power system signals with wavelets | |
| CN109451254A (en) | A kind of smart television digital receiver | |
| CN104507107B (en) | A kind of preprocess method of signaling data | |
| CN102750126A (en) | Speech input method and terminal | |
| Karthikeyan et al. | Wavelet-support vector machine approach for classification of power quality disturbances | |
| CN113342820A (en) | Method for storing big data of energy storage industrial equipment | |
| Xu et al. | Effective context inconsistency elimination algorithm based on feedback and reliability distribution for IOV | |
| CN105005245A (en) | Data processing method | |
| CN204480660U (en) | A kind of Computer Distance Education system | |
| Wang et al. | A General Dataset Generator for Industrial Internet of Things Using Multi-sensor Information Fusion | |
| CN104765777B (en) | All-purpose card RFID data is converted into the method and system of process event daily record |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20140813 Termination date: 20150531 |
|
| EXPY | Termination of patent right or utility model |