CN109542089A - A kind of industrial process nonlinear detection method of oscillations based on improvement variation mode decomposition - Google Patents
A kind of industrial process nonlinear detection method of oscillations based on improvement variation mode decomposition Download PDFInfo
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Abstract
A kind of industrial process nonlinear detection method of oscillations based on improvement variation mode decomposition, comprising: (1) acquire the loop output signal of one group of industrial process to be detected；(2) frequency spectrum and phase correction signal mean spectrum for calculating the loop output signal, determine mode quantity and centre frequency initial value；(3) search range and step-length of penalty coefficient are set；(4) different penalty coefficients are calculated and correspond to the summation arrangement entropy that VMD is decomposed, and determine optimal penalty coefficient；(5) VMD decomposition is carried out with the mode quantity of above-mentioned determination, centre frequency initial value and penalty coefficient, and picks out effective mode；(6) calculating whether there is multiple proportion between the centre frequency of effective mode, judge whether there is Non-Linear Ocsillation.Using the present invention, the non-linear detection accuracy and reliability of the control loop of industrial process can be improved, data are provided and are supported for Performance Evaluation and fault diagnosis, work is positioned for subsequent multiloop Non-Linear Ocsillation source and lays the foundation.
Description
Technical field
The invention belongs to the Performance Evaluations and fault diagnosis field in industrial control system, are based on changing more particularly, to one kind
Into the industrial process nonlinear detection method of oscillations of variation mode decomposition.
Background technique
With the rapid development of the fault diagnosis and Performance Evaluation technology of process control loops, oscillation test becomes control
One of the main task of fault diagnosis in circuit.Due between control system circuit connection with couple, in some circuit
The oscillation of generation would generally travel to other circuits.These oscillations will cause energy loss, waste of raw materials and product quality
The problems such as decline.Valve is viscid, controller is lacked of proper care and external disturbance is three main causes for causing oscillation.
There is document to point out, the nonlinear element in control system, such as valve are viscid, it may be possible to which control loop oscillation is most main
The reason of wanting.The tight demand of safety and product profit for production process has greatly pushed nonlinear control element oscillation inspection
The development of survey technology.Non-Linear Ocsillation detection method can generally be divided into two aspects, one is based on data-driven, this
Kind method does not need the priori knowledge of the dynamic characteristic of research object；Another kind is that method is then or detailed process is needed to know
Know, user's interaction or the fairly precise procedure structure of understanding.
Non-Linear Ocsillation detection method based on data-driven has the viscid detection based on shape, such as is schemed using MV-OP
Phase property method, bicoherence and substituted plane using PV-OP figure；There are also based on cross-correlation, histogram, areal calculation,
The methods of curve matching goes the technology of detection Non-Linear Ocsillation.Need the non-of detailed procedural knowledge or accurate procedure structure
Linear osccilation detection method has the detection method based on model, based on detection method known to output signal frequency etc..
In recent years, the development of signal decomposition technology is swift and violent, these new signal processing technologies for handling Industry Control system
The research for data of uniting is in the ascendant.Bahji et al. using HHT change detection and has diagnosed industrial process control system data first
It is non-linear.Nonlinear degree is measured in Aftab et al. proposition using a kind of nonlinear exponent.Nearest Aftab et al. is more
Dimension empirical mode decomposition introduces Non-Linear Ocsillation detection field.These Non-Linear Ocsillation detection sides based on signal decomposition technology
Method is to include the characteristic of higher hamonic wave based on Non-Linear Ocsillation and carry out.If after a signal decomposition, by non-linear
Detection algorithm is able to detect that higher hamonic wave, then this signal there is Non-Linear Ocsillation.
Variation mode decomposition (VMD) is a kind of new adaptive signal decomposition technology, can input a multi -components
Signal decomposition obtains the centre frequency of these mode at K mode.Compared with the methods of traditional EMD, LMD, variation mode
Decomposition method is with Fundamentals of Mathematics are complete, are not easy to be influenced by end effect and modal overlap, can directly obtain each mode
Frequency and the advantages such as Decomposition Accuracy height.But basic variation mode there are discomposing effect depend critically upon mode quantity, in
The problem of frequency of heart initialization value and penalty coefficient, it is method using iteration or swarm intelligence optimizing that current research is more
Go selection parameter.
Based on background above, for the nonlinear oscillation signals in industrial control system, finds and overcome basic variation mould
State decomposes the improved method to parameter Dependence Problem, using variation mode decomposition feature with high accuracy, by analyzing variation mode
The multiple proportion of the centre frequency of gained effective model is decomposed to detect Non-Linear Ocsillation, for accurately whether vibrating industrial process
There are Non-Linear Ocsillations very important practical value.
Summary of the invention
The present invention provides a kind of based on the industrial process nonlinear detection method of oscillations for improving variation mode decomposition, detection
Precision is high, it is only necessary to obtain conventional operation data, be not necessarily to process mechanism knowledge.
A kind of industrial process nonlinear detection method of oscillations based on improvement variation mode decomposition, comprising the following steps:
(1) loop output signal of one group of industrial process to be detected is acquired；
(2) frequency spectrum and phase correction signal mean spectrum for calculating the loop output signal, determine mode quantity and center
Frequency initial value；
(3) search range and step-length for setting penalty coefficient, calculate different penalty coefficients and correspond to VMD and decompose to obtain each mould
The sum of normalization arrangement entropy of state obtains summation arrangement entropy；
(4) penalty coefficient corresponding to minimum summation arrangement entropy is chosen as optimal penalty coefficient；
(5) penalty coefficient of mode quantity, centre frequency initial value and selection is used to carry out VMD decomposition as parameter, according to
Normalization arrangement entropy and related coefficient obtain effective mode；
(6) centre frequency of these effective mode is calculated with the presence or absence of multiple proportion, and then is judged whether there is non-linear
Oscillation.
Method of the invention overcomes basic variation mode decomposition in signal of the processing by harmonic and reactive detection, and discomposing effect is tight
Again dependent on mode quantity, centre frequency initialization value and penalty coefficient the problem of, and pass through detection improvement variation mode decomposition
The centre frequency of resulting effective mode infers whether that there are Non-Linear Ocsillations.The control of industrial process can be improved in the present invention
The non-linear detection accuracy in circuit and reliability provide data and support, be subsequent more times for Performance Evaluation and fault diagnosis
Non-Linear Ocsillation detection work in road lays the foundation.
The present invention directlys adopt the measurable variable of chemical process as the output of process signal, all the output of process letters to be detected
Number pass through field real-time acquisition to obtain.
Detailed process is as follows for step (2):
The Fourier spectrum and the frequency after phase correction signal average value processing of (2-1) calculating process output signal x (t)
Spectrum；
(2-2) determines mode quantity K according to the following formula
K=max { Kfft,KPRSA}+1
Wherein, KfftIndicate the peak value number in Fourier spectrum, KPRSAIt indicates after phase correction signal average value processing
Frequency spectrum peak value number；
(2-3) is by frequency initialization value ω centered on the frequency values of all peak valuesinit。
In step (3), the search range of penalty coefficient is 100 to 10000, and step-length value is 500 to 1000.
The detailed process of step (3) are as follows:
(3-1) is limited to the upper limit from the value of penalty coefficient under search range, is spaced a step-length and takes a value；
(3-2) calculates VMD corresponding to each penalty coefficient and decomposes the normalization arrangement entropy of resulting each mode and ask
With arrangement entropy, calculation formula is as follows:
NPEk=PEk/ln(N-d+1)
Wherein, NPEkIt is the normalization arrangement entropy of k-th of mode, PEkIt is the original alignment entropy of k-th of mode, N is
The length of loop output signal, it is summation arrangement entropy that the value of d, which takes 5, SPE,.
In step (5), the picking rule of effective mode are as follows: normalizated correlation coefficient is greater than 0.2 and normalization arrangement
Entropy is less than 0.4.Normalizated correlation coefficient calculation formula is as follows:
Cov represents covariance, uk(t) mode decomposed and obtained is represented, x (t) represents loop output signal, σx(t)It represents back
The standard deviation of road output signal,Represent the standard deviation of k-th of mode, ρkRepresent loop output signal x (t) and k-th of mould
Related coefficient between state, max representative are maximized, λkRepresent the normalizated correlation coefficient of k-th of mode.
In step (6), the concrete mode of Non-Linear Ocsillation is judged whether there is are as follows:
If the centre frequency between two or more effective mode meets ωj/ωi=k, i ≠ j, and | round (k)-
K |≤0.2, then it is equivalent to that there are multiple proportions, then these effective mode just belong to the same Non-Linear Ocsillation；Wherein,
Round is indicated and k closest integer, ωiAnd ωjFor two effective mode to be judged；
If there is single effectively mode is got along well, there are multiple proportions for the centre frequencies of other any mode, then this mode
Just it is considered as an individual linear osccilation.
Compared with prior art, the invention has the following advantages:
1, it is motivated when present invention acquisition signal without external add-in signal, additional disturbance will not be introduced to control system,
It can be realized the detection and diagnosis of non-intrusion type.
2, phase correction signal mean value (PRSA) processing of the present invention can effectively promote the signal-to-noise ratio of frequency spectrum,
Clearer peak value can be obtained under strong noise background.
3, proposed by the invention based on the industrial process nonlinear detection method of oscillations for improving variation mode decomposition, it can
Directly obtain more accurate frequency of oscillation, and a more than frequency range, this to utilize harmonic detecting Non-Linear Ocsillation
This thinking executes simpler and accurate.
4, detection method of the invention, when decomposing oscillator signal, the redundant components and error component and EMD of generation,
The methods of MEMD compared to will much less, reduce exclude redundant components and error component False Rate.
5, the method that the present invention uses data driven type completely, is not necessarily to process priori knowledge, does not also need manually to be done
In advance.
Detailed description of the invention
Fig. 1 is a kind of process based on the industrial process nonlinear detection method of oscillations for improving variation mode decomposition of the present invention
Schematic diagram；
Fig. 2 is the control loop the output of process signal graph to be detected of acquisition of the embodiment of the present invention；
Fig. 3 is the spectrogram of the output of process signal in the embodiment of the present invention；
Fig. 4 is spectrogram of the output of process signal after phase correction signal average value processing in the embodiment of the present invention；
Fig. 5 is that different penalty coefficients correspond to the resulting summation arrangement entropy of VMD decomposition in the embodiment of the present invention；
Fig. 6 is the decomposition result of final VMD in the embodiment of the present invention.
Specific embodiment
Below by taking certain chemical industry flow control circuit as an example, to the chemical process Non-Linear Ocsillation detection side viscid there are valve
Method is described in detail.For the circuit, a priori known system exists by the viscid caused Non-Linear Ocsillation of valve, data source
In " Jelali M, Huang B.Detection and Diagnosis of Stiction in Control Loops:
State of the Art and Advanced Methods [M] .Springer London, first in 2009. " one books
Chemical industry circuit, i.e. chemical.loop1.PV.
As shown in Figure 1, a kind of based on the industrial process nonlinear detection method of oscillations for improving variation mode decomposition, comprising:
Step 1, the control loop the output of process signal to be detected of acquisition.
The method of collection process output signal are as follows: record control loop to be detected within preset each sampling interval
In process data, and in each sampling interval the addition of collected process data at previously process data end collected
End.
Sampling interval refers to the sampling interval of performance evaluation system.Process data is constantly updated as time goes by, every warp
The time span in a sampling interval is crossed, has new process data to be added to the end of the process data previously acquired.Performance
The sampling interval of assessment system is generally identical as the control period in industrial control system, also can choose to control the whole of period
Several times are determined with specific reference to performance monitoring and the limitation of the requirement of real-time and data storage capacity of industry spot.
The initial data of the present embodiment the output of process signal collected is as shown in Fig. 2, abscissa is time, list in Fig. 2
Position is the second, and ordinate is flow.
Step 2, it calculates the frequency spectrum in the circuit and by the frequency spectrum after phase correction signal average value processing, determines mode number
Amount and centre frequency initialization value.
It calculates the frequency spectrum in the circuit and by the frequency spectrum after phase correction signal average value processing, finds the frequency spectrum in the circuit
In there are two peak value, as shown in figure 3, and the frequency spectrum after phase correction signal average value processing only one peak value, such as Fig. 4 institute
Show.
Mode quantity K is determined according to the following formula:
K=max { Kfft,KPRSA}+1
Mode quantity K=3 is obtained, corresponding centre frequency initialization value takes 0.01,0.03,0.05.
In the present embodiment, phase correction signal mean algorithm (PRSA:phase-rectified signal
It averaging is) according to " Bauer A, Kantelhardt J W, Bunde A, et al.Phase-rectified signal
averaging detects quasi-periodicities in non-stationary data[J].Physica A
Statistical Mechanics&Its Applications, what 2006,364:423-434. " was implemented.
Step 3, the search range and step-length of penalty coefficient are determined.
The search range of penalty coefficient is determined substantially 100 to 10000, step-length value is 500 or 1000.
Step 4, it calculates the corresponding VMD of different penalty coefficients and decomposes gained summation arrangement entropy.
Different penalty coefficients correspond to VMD and decompose gained summation arrangement entropy as shown in Fig. 5 and table 1, it can be seen that minimum summation
Arranging the corresponding penalty coefficient of entropy is 8100.
Table 1
| Penalty coefficient | 100 | 1100 | 2100 | 3100 | 4100 |
| Summation arrangement entropy | 0.8084 | 0.5907 | 0.5553 | 0.5466 | 0.5361 |
| Penalty coefficient | 5100 | 6100 | 7100 | 8100 | 9100 |
| Summation arrangement entropy | 0.5331 | 0.5272 | 0.5255 | 0.5254 | 0.5257 |
Step 5, VMD decomposition is carried out, the corresponding centre frequency of effective mode is obtained.
It is 3 in the mode quantity that step 2 and step 4 determine, initialization centre frequency is 0.01,0.03,0.05, punishment system
Under conditions of number is 8100, arrangement entropy, related coefficient and the centre frequency for decomposing gained effectively mode are as shown in table 2.
Table 2
The step carries out obtained decomposition result after VMD decomposition as shown in fig. 6, being followed successively by original signal, again from top to bottom
Structure signal (sum for decomposing gained effectively mode), effective mode u1 and effective mode u2.It can be seen that effective mode u1 and effectively
The curve of mode u2 presents the form of FM amplitude modulation signal, and reconstruction signal is approximately uniform with original signal, and discomposing effect is to enable
People's satisfaction.
Step 6, the centre frequency of these effective mode is calculated with the presence or absence of multiple proportion, and then is judged whether there is non-thread
Property oscillation.
Because the ratio of the centre frequency of effective mode u2 and effective mode u1 is 3.1826, it is evident that | round
(3.1816) -3.1816 |=0.1816≤0.2, so the output signal of this control loop includes a fundametal compoment and one
, that is, there is Non-Linear Ocsillation in a third-harmonic component, conclusion is consistent with priori knowledge.
Technical solution of the present invention and beneficial effect is described in detail in embodiment described above, it should be understood that
Above is only a specific embodiment of the present invention, it is not intended to restrict the invention, it is all to be done in spirit of the invention
Any modification, supplementary, and equivalent replacement, should all be included in the protection scope of the present invention.
Claims (6)
1. a kind of based on the industrial process nonlinear detection method of oscillations for improving variation mode decomposition characterized by comprising
(1) loop output signal of one group of industrial process to be detected is acquired；
(2) frequency spectrum and phase correction signal mean spectrum for calculating the loop output signal, determine mode quantity and centre frequency
Initial value；
(3) search range and step-length for setting penalty coefficient, calculate different penalty coefficients and correspond to VMD and decompose to obtain each mode
The sum of normalization arrangement entropy obtains summation arrangement entropy；
(4) penalty coefficient corresponding to minimum summation arrangement entropy is chosen as optimal penalty coefficient；
(5) penalty coefficient of mode quantity, centre frequency initial value and selection is used to carry out VMD decomposition as parameter, according to normalizing
Change arrangement entropy and related coefficient obtains effective mode；
(6) centre frequency of these effective mode is calculated with the presence or absence of multiple proportion, and then judges whether there is Non-Linear Ocsillation.
2. the industrial process nonlinear detection method of oscillations according to claim 1 based on improvement variation mode decomposition,
It is characterized in that, detailed process is as follows for step (2):
The Fourier spectrum and the frequency spectrum after phase correction signal average value processing of (2-1) calculating process output signal x (t)；
(2-2) determines mode quantity K according to the following formula
K=max { Kfft,KPRSA}+1
Wherein, KfftIndicate the peak value number in Fourier spectrum, KPRSAIndicate the frequency after phase correction signal average value processing
The peak value number of spectrum；
(2-3) is by frequency initialization value ω centered on the frequency values of all peak valuesinit。
3. the industrial process nonlinear detection method of oscillations according to claim 1 based on improvement variation mode decomposition,
It is characterized in that, in step (3), the search range of penalty coefficient is 100 to 10000, and step-length value is 500 to 1000.
4. the industrial process nonlinear detection method of oscillations according to claim 1 based on improvement variation mode decomposition,
It is characterized in that, the detailed process of step (3) are as follows:
(3-1) is limited to the upper limit from the value of penalty coefficient under search range, is spaced a step-length and takes a value；
(3-2) calculates normalization arrangement entropy and the summation that VMD corresponding to each penalty coefficient decomposes resulting each mode
Entropy is arranged, calculation formula is as follows:
NPEk=PEk/ln(N-d+1)
Wherein, NPEkIt is the normalization arrangement entropy of k-th of mode, PEkIt is the original alignment entropy of k-th of mode, N is circuit
The length of output signal, it is summation arrangement entropy that the value of d, which takes 5, SPE,.
5. the industrial process nonlinear detection method of oscillations according to claim 1 based on improvement variation mode decomposition,
It is characterized in that, in step (5), the picking rule of effective mode are as follows: normalizated correlation coefficient is greater than 0.2 and normalization arrangement
Entropy is less than 0.4；Wherein, normalizated correlation coefficient calculation formula is as follows:
Cov represents covariance, uk(t) mode decomposed and obtained is represented, x (t) represents loop output signal, σx(t)It is defeated to represent circuit
The standard deviation of signal out,Represent the standard deviation of k-th of mode, ρkRepresent loop output signal x (t) and k-th mode it
Between related coefficient, max representative be maximized, λkRepresent the normalizated correlation coefficient of k-th of mode.
6. the industrial process nonlinear detection method of oscillations according to claim 1 based on improvement variation mode decomposition,
It is characterized in that, in step (6), judges whether there is the concrete mode of Non-Linear Ocsillation are as follows:
If the centre frequency between two or more effective mode meets ωj/ωi=k, i ≠ j, and | round (k)-k |≤
0.2, then it is equivalent to that there are multiple proportions, then these effective mode just belong to the same Non-Linear Ocsillation, wherein round
It indicates and k closest integer；
If there is single effectively mode is got along well, there are multiple proportions for the centre frequencies of other any mode, then this mode just by
It is considered as an individual linear osccilation.
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