CN108152584A - A kind of high ferro tractive power supply system harmonic wave Multi-path synchronous rapid detection method - Google Patents
A kind of high ferro tractive power supply system harmonic wave Multi-path synchronous rapid detection method Download PDFInfo
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Abstract
The invention discloses a kind of high ferro tractive power supply system harmonic wave Multi-path synchronous rapid detection methods.The purpose of the present invention is to solve high ferro tractive power supply system harmonic detecting method accuracy of detection of the prior art is inadequate, multi-way detecting real-time is bad, is tested the incomplete problem of harmonic spectrum.The additional function that a kind of high ferro tractive power supply system harmonic wave Multi-path synchronous rapid detection method of the present invention is realized including Multi-path synchronous sampling, unified artificial neural network's reference input benchmark, the weighed value adjusting method of artificial neural network, Multi-path synchronous parallel processing, multichannel artificial neuron synchronous study and algorithm based on shared knowledge base.The present invention is completed synchronizes quick detection to the multichannel harmonic wave in high ferro tractive power supply system, not only ensure that the high accuracy of comparison, it is ensured that the real-time of multi-way detecting, synchronism and rapidity.
Description
Technical field
The present invention relates to a kind of high ferro tractive power supply system harmonic wave Multi-path synchronous rapid detection methods.
Background technology
With the rapid development of high ferro, each circuit train operation density increasingly increases, and high-power reconnection even occurs in part circuit
Motor-car or polytypic motor-car mix race phenomenon, in addition the aliasing effect and its transmission characteristic of each harmonic so that originally not very prominent
Harmonic problem become increasingly conspicuous on the influence of the normal operation of tractive power supply system, part traction is caused to become the irregular jump of feeder line
Lock presses phenomena such as mutual booster.
China to the system evaluation of tractive power supply system power quality and administers shortage ganged systems, particularly harmonic wave at present
Quick context of detection have certain shortcoming, and railway terminal tractive power supply system is complicated, feeder assembly is more, to this type
The harmonic detecting of traction substation certainly will want Multi-path synchronous to carry out, to complete quickly to detect the Multi-path synchronous of each road feeder line harmonic wave
It is required that.
However, current harmonic detecting method in high ferro tractive power supply system there are many problems, such as：Based on FFT
Harmonic detection there are spectral leakages and fence effect, time-domain analysis can not be carried out, it is difficult to realize harmonic wave in-situ analysis
Demand；Harmonic detection based on wavelet transformation can only decompose low-frequency range, can not to high band carry out accuracy compared with
High analysis, and aliasing is serious；Harmonic detection based on instantaneous reactive power is mainly used for the harmonic wave inspection of three phase network
It surveys, it is big for the detection algorithm complexity and testing result error of single-phase circuit, time domain transformation is only carried out, is unfavorable for spectrum analysis,
It is not suitable for the harmonic detecting of tractive power supply system.
Invention content
The purpose of the present invention is to solve high ferro tractive power supply system harmonic detecting method of the prior art detections to imitate
The problem of fruit is poor, and accuracy of detection is low, and multi-way detecting real-time is poor.
The technical scheme is that：
A kind of harmonic wave multichannel Fast synchronization detection method of high ferro tractive power supply system, including Multi-path synchronous sampling, uniformly
Artificial neural network's reference input benchmark, artificial neural network weighed value adjusting method, Multi-path synchronous parallel processing, be based on
The additional function that the multichannel artificial neuron synchronous study and algorithm of shared knowledge base are realized.
The Multi-path synchronous is sampled as using multiple branches to be measured the synchronized sampling method of equal interval sampling, in harmonic wave
N point of sampling, sampling interval T in signal period TS, i.e. T=nTS。
Unified artificial neural network's reference input benchmark is to select the same group of lockin signal Jing Guo process of frequency multiplication,
This is because multichannel feeder line is connected directly with traction substation 27.5kV busbares in high ferro tractive power supply system, voltage signal phase
Position is identical with frequency.The voltage signal for sampling low-pressure side is only needed to carry out process of frequency multiplication, generates a reference signal Xn, make
The synchronization process of harmonic detecting process is realized in its input of artificial neural network's collective reference as each test point with this.
The weighed value adjusting method of the artificial neural network is least fibre method, is error function in weights spatially
Smallest point is searched on curved surface, is with the optimization process of the minimum target of error.
Consistency of the Multi-path synchronous parallel processing for detection algorithm between setting each branch in algorithm design level, journey
Multichannel data parallel processing is carried out in program process, makes the synchronization on the multichannel harmonic detecting result retention time.
Multichannel artificial neuron's synchronous study based on shared knowledge base is to sum up spy by largely detecting sample
Levy characteristic harmonics, the Optimal learning efficiency η of vehiclesWith best Inertia αsCombination forms knowledge base, and follow-up each branch carries out harmonic wave inspection
Record is directly transferred during survey from knowledge base and carries out weighed value adjusting, reduces a large amount of interative computations during weighed value adjusting.
The additional function that the algorithm is realized include according to each harmonic virtual value within weight computing 100 times, phase and
Relative harmonic content information provides above- mentioned information and the super-limit prewarning and writing function after harmonic standard comparison, while provides record
Inquiry and data display function.
The present invention has the following effects that compared with prior art：
Harmonic detecting method of the present invention in high ferro tractive power supply system not only solves fast Fourier
The problem of converting the spectral leakage and fence effect when being used for harmonic detecting, when also solving wavelet transformation for harmonic detecting
Aliasing problem.The present invention's is calculated for the harmonic detecting method in high ferro tractive power supply system using artificial neural network
Method is used to handle the unique advantage of nonlinear problem and mass data problem, to the multichannel harmonic wave in high ferro tractive power supply system into
Row simultaneously and rapidly detects, and not only ensure that the high accuracy of comparison in this way, it is ensured that the real-time of multi-way detecting, synchronism and
Rapidity.
Specific embodiment
Below in conjunction with the specific embodiment of the description of the drawings present invention, it should be understood that the implementation for showing and describing in attached drawing
Mode is only exemplary, it is intended that is illustrated the principle of the present invention and method, and is not intended to limit the scope of the invention.
Harmonic wave Multi-path synchronous fast algorithm of detecting in a kind of high ferro tractive power supply system of the present invention includes single prop up
The Harmonic detection on road and the Harmonic detection of Multi-path synchronous.Fig. 1 is shown in high ferro tractive power supply system of the present invention
Single spur track artificial neural network's algorithm harmonic detecting principle, detection harmonic current can use Fourier expansion shape
Formula is expressed as：
Sin ω t, cos ω t are according to obtained by lockin signal, and sinn ω t, cosn ω t are according to the process of frequency multiplication institute of lockin signal
It obtains, collectively constitutes reference input X (nt)=[sin ω t, cos ω t ... sinn ω t, cosn ω t of artificial neural network
]T。
In order to adapt to the form of artificial neural network, the harmonic current detected is rewritten as：
N be harmonic detecting number, wni、wnjFor artificial neural network's connection weight, θ is neuron threshold value.
The adjusting weights learning process of the algorithm is to search for smallest point on weights error function curved surface spatially, is
With the optimization process that error function e (t) is target, weights and neuron adjusting thresholds, error letter are carried out using least fibre method
Number is：iLIt is practical input signal,It is the output signal of artificial neural network.
The wherein foundation of weighed value adjusting and neuron adjusting thresholds is respectively：
Fig. 2 shows the flow charts of the weights adjusting method in the detection method.It is appreciated that flow shown in Fig. 2
Figure is only illustrative, wherein the step of can be omitted and/or increase other steps.As shown in Fig. 2, in artificial neural network
Start to assign learning rate η and Inertia α a reference values in algorithm, the weights of artificial neural network are adjusted, by new
Weights synthesize harmonic current signal and compare to form error signal with input signal, the precision of error in judgement signal, if error exists
In the range of setting accuracy allows, then export each value information w, learning rate η and Inertia α, and determine learning rate at this time and
Inertia has learnt and Inertia to be best；If error signal is unsatisfactory for required precision, to learning rate η and Inertia α into
Capable assignment again, repeats above-mentioned flow.
The harmonic detecting result of the algorithm can represent that nth harmonic current amplitude can be expressed as with weights
Nth harmonic current phase angle can be expressed as
Nth harmonic containing ratio is expressed as
Harmonic wave synchronous detecting algorithm of the present invention includes Multi-path synchronous sampling, unified artificial neural network's ginseng
Examine input reference, the processing of multichannel program parallelization, multichannel artificial neuron's synchronous study based on shared knowledge base.The multichannel is same
Step is sampled as equal interval sampling mode, sampling interval TS, it is n per cycle sampling number, is brought to reduce systematic sampling
Error, using synchronized sampling method carry out signal sampling, i.e., to ensure T=nTS(T is the signal period in Traction networks), this
Kind signal sampling mechanism ensure that there is higher signal-to-noise ratio at signal detection end.Unified artificial neural network's reference input base
To select the same group of lockin signal Jing Guo process of frequency multiplication, this is because multichannel feeder line side and transformation in high ferro tractive power supply system
Device low-pressure side is connected directly, and phase and frequency is identical in voltage signal.Only need sample low-pressure side voltage signal into
Row process of frequency multiplication generates a reference signal, inputs its artificial neural network's collective reference as each test point, with
This realizes the synchronization process of harmonic detecting process, reduces a plurality of harmonic detecting branch and carries out lockin signal process of frequency multiplication respectively
Time, realize during multichannel harmonic detecting that the effect of fully synchronizedization, unified reference input benchmark represent in time
For：
Xn=[sin ω t, cos ω t, sin2 ω t, cos2 ω t ... sinn ω t, cosn ω t]T。
Consistency of the multichannel program parallelization processing to set detection algorithm between each branch in algorithm design level,
Program, which performs, carries out multichannel data parallel processing in design, make the synchronization on the multichannel harmonic detecting result retention time.The base
In multichannel artificial neuron's synchronous study of shared knowledge base be by largely detect sample sum up feature vehicle feature it is humorous
Wave, Optimal learning efficiency ηsWith best Inertia αsCombination forms knowledge base, in harmonic detecting in subsequently carrying out branch, only needs to adjust
Fast Convergent during artificial neural network's harmonic detecting can be realized with the unit in single or combination knowledge base, subtract
A large amount of interative computations during few weighed value adjusting, accelerate the harmonic detecting speed between multiple branch circuit.Fig. 3 shows the multichannel
Artificial neuron's synchronous study block diagram.It is appreciated that block diagram shown in Fig. 3 is only illustrative, wherein the step of can be omitted
And/or increase other steps.According to the synchronism of signal processing, the unit that will be called during harmonic detecting in different branch
It synchronizes and passes to low-pressure side, pass through the η in above-mentioned unitsAnd αsIt is overlapped the harmonic data that low-pressure side is realized after combining
Quick detection.On high-tension side characteristic harmonics and the characteristic harmonics of low-pressure side have very big relevance, but have some differences, these are poor
The different mainly no-load voltage ratio of transformer and structure are brought, therefore when being detected on high-tension side harmonic data, it is only necessary to by these shadows
The factor of sound is converted to the learning rate η influenced by transformeriWith the Inertia α influenced by transformeri, then stack combinations low-pressure side
ηsAnd αsLearnt, you can realize that on high-tension side harmonic wave quickly detects.
Fig. 4 shows the additional function schematic diagram that the Harmonic Detecting Algorithm of the present invention is realized, it will be understood that shown in fig. 5
Schematic diagram is only illustrative, and part therein can be omitted and/or increase other functions.Fig. 4 shows that additional function specifically wraps
It includes according to each harmonic virtual value, phase and relative harmonic content information within weight computing 100 times, above- mentioned information and harmonic wave is provided
Super-limit prewarning and writing function after Comparison of standards, while record queries and data display function are provided.
Fig. 5 shows that a kind of high ferro tractive power supply system multichannel harmonic synchronous fast algorithm of detecting realizes schematic diagram,
It is appreciated that schematic diagram shown in fig. 5 is only illustrative, structure therein can be omitted and/or increase other functions.Fig. 5
In the sensor loop access system by high-pressure side, low-pressure side and feeder line side shown, electric current, voltage are realized by hardware circuit
The acquisition of signal and lock phase, are input to through AD conversion in PC.PC carries out process of frequency multiplication to lockin signal first, makes it as people
The reference input of work neuroid, CPU is humorous to the progress of collected data by artificial neural network's algorithm routine later
Wave analysis, obtains the harmonic wave weight matrix within 100 times, calculates individual harmonic current virtual value and phase by formula, so
Harmonic wave weight matrix, harmonic current virtual value and phase data are stored into database afterwards, are formed simultaneously feature vehicle
It practises knowledge base to be stored, completes the detection of harmonic wave.
Harmonic detecting method in a kind of high ferro tractive power supply system of the present invention is using at artificial neural network's algorithm
The advantage of nonlinear problem and mass data problem is managed, quick inspection is synchronized to multichannel harmonic wave in high ferro tractive power supply system
It surveys, not only ensure that the high accuracy of comparison, it is ensured that the real-time of multi-way detecting, synchronism and rapidity.
In addition, although the operation of the method for the present invention is described with particular order in the accompanying drawings, this do not require that or
Hint must could realize expected knot according to the particular order to perform these operations or must have gone through all operationss
Fruit.It on the contrary, can be by omitting certain steps, multiple steps are combined into a step or a step being decomposed into multiple steps
It is rapid to realize original function.
Description of the drawings
Fig. 1, single spur track artificial neural network's algorithm harmonic detecting principle in high ferro tractive power supply system of the invention
Figure
Fig. 2, artificial neural network's weights adjusting method flow chart in Harmonic Detecting Algorithm of the invention
Fig. 3, multichannel artificial neuron's synchronous study block diagram in high ferro tractive power supply system of the invention
Fig. 4, the additional function schematic diagram that Harmonic Detecting Algorithm of the invention is realized
Fig. 5, high ferro tractive power supply system multichannel harmonic synchronous fast algorithm of detecting of the invention realize schematic diagram.
Claims (7)
1. a kind of high ferro tractive power supply system harmonic wave Multi-path synchronous rapid detection method, including：
Multi-path synchronous sampling, unified artificial neural network's reference input benchmark, artificial neural network weighed value adjusting method,
The additional function that multidiameter delay processing, multichannel artificial neuron synchronous study and algorithm based on shared knowledge base are realized.
2. according to the method described in claim 1, wherein, artificial neural network's algorithm is selected to carry out harmonic detecting, is passed through
The synchronized sampling method of interval sampling is sampled, to sampling n point, sampling interval T in harmonic current signal period TS, i.e.,
T=nTS。
3. according to the method described in claim 1, wherein, the voltage signal for sampling low-pressure side carries out process of frequency multiplication, generates one
Reference signal Xn, its artificial neural network's collective reference as each test point is inputted, harmonic detecting mistake is realized with this
The synchronization process of journey.
4. according to the method described in claim 1, wherein, weights and neuron adjusting thresholds are carried out using least fibre method, in fact
Error smallest point is searched on the error function curved surface in present weights space, exports learning rate η, Inertia α and connection weight at this time
Value wni、wnj, and pass through connection weight wni、wnjHarmonic current signal is synthesized with neuron threshold θ：
5. according to the method described in claim 1, wherein, one of detection algorithm between each branch is set in algorithm design level
Cause property, program, which performs, carries out multichannel data parallel processing in design, make the synchronization on the multichannel harmonic detecting result retention time.
It, will be from a large amount of in order to accelerate the pace of learning of artificial neural network 6. according to the method described in claim 1, wherein
Detection sample sums up the characteristic harmonics of feature vehicle, Optimal learning efficiency ηsWith best Inertia αsCombination forms knowledge base, subsequently
Each branch carries out only transferring record progress weighed value adjusting during harmonic detecting from knowledge base, avoids a large amount of interative computations while adds
Fast harmonic detecting speed.
7. according to the method described in claim 1, wherein, additional function that algorithm is realized include according to weight computing 100 times with
Interior each harmonic virtual value, phase and relative harmonic content information provide above- mentioned information and the super-limit prewarning after harmonic standard comparison
And writing function, while record queries and data display function are provided.
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