CN108519547A - SiC-GTO device state monitoring methods based on DTW and SVM - Google Patents
SiC-GTO device state monitoring methods based on DTW and SVM Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 40
- 238000000034 method Methods 0.000 title claims abstract description 28
- 238000013461 design Methods 0.000 claims abstract description 4
- 238000005259 measurement Methods 0.000 claims abstract description 4
- 238000012706 support-vector machine Methods 0.000 claims description 25
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 9
- 238000012549 training Methods 0.000 claims description 9
- 230000036541 health Effects 0.000 claims description 5
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- 230000001360 synchronised effect Effects 0.000 claims description 3
- 230000007850 degeneration Effects 0.000 claims description 2
- 230000007246 mechanism Effects 0.000 claims description 2
- 230000003862 health status Effects 0.000 abstract description 9
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
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Abstract
The present invention proposes a kind of SiC GTO device state monitoring methods based on DTW and SVM, and step is：In SiC GTO device detection structures, it is drawn the 3rd area P as function pin, it is defined as the poles Base, and the VA characteristic curve of method measurement device any two ends under low voltage situations using flush type circuit design, the device VA characteristic curve that it is obtained under various circumstances is as monitoring object.And propose new dynamic time warping improved method, its searching route is optimized, can effectively avoid the problem that the regular inaccurate and search width in path need to be artificially arranged in algorithm, while reducing computation complexity and reducing calculation amount.It is finally based on SVM using minimum distortion degree summation as sample characteristics to classify, realizes high voltage SiC GTO device health status monitorings.
Description
Technical field
The present invention relates to SiC-GTO power device health status monitoring technologies, especially a kind of to be based on DTW (Dynamic
Time Warping, dynamic time warping) and SVM (support vector machin, support vector machines) SiC-GTO devices
Part state monitoring method.
Background technology
SiC-GTO power devices (Gate Turn-Off Thyristor) are to be based on the novel wide bandgap semiconductor of the third generation
The power electronic device that SiC is developed, SiC material energy gap is big, and critical breakdown electric field is high, thermal conductivity is high, drift velocity is fast,
Have wide practical use in the power electronic system of the environment such as high-power, high temperature, high pressure, intense radiation.Foreign countries have at present
Ripe commercialization SiC power devices, the country will also succeed in developing and put into application.Power device is that influence power electronic system can
By one of the main component of property, the quality of performance directly affects the global reliability of power electronic system, therefore to SiC-
The research of GTO device reliabilities is extremely necessary.The blocking voltage of SiC-GTO devices up to several kilovolts or more, blocking characteristics and
Switching characteristic is to weigh the important parameter index of device health status.Study the blocking characteristics and dynamic switch of SiC-GTO devices
The state monitoring method of characteristic, and realized by Embedded method and complete to supervise the health status of device in the case of low pressure
Survey is of great significance in practical applications.
The monitoring of SiC-GTO device states is mainly the current and voltage signals at sampler both ends, therefrom obtains component failure
Or the characteristic parameter of defect.Common power device monitoring method mainly has wavelet analysis, the diagnosis of Frechet distances, approximate entropy
The methods of theoretical and dynamic time warping, each method has its feature and the scope of application, wherein dynamic time warping algorithm
It is obvious to the difference of time sequence difference with higher identification precision, it can clearly distinguish whether device occurs defect
And its type, it is the ideal chose for the monitoring of SiC-GTO device states.
Dynamic time warping (DTW) algorithm is to combine one kind of dynamic time warping technology and distance measure computing technique non-
Linear regular algorithm, is one of the effective ways of power device status monitoring.Dynamic time warping algorithm can be to data length
Different time serieses are matched, and are found out the optimal path between two time-serial positions by specific constraints, are made
The distance obtained between two time serieses is most short.The algorithm can solve the problems, such as that sequence data length is inconsistent, have good robust
Property, and it is insensitive to measurement noise, there is significant advantage in the characteristic research to SiC-GTO devices.
Although dynamic time warping algorithm has higher precision in the identification of different time sequence, the plain path phase is being searched
Between point in sequential when mutually being mapped with the longer section of interval time in another sequential, it is regular and calculate to easily cause morbid state
Complexity is higher.And at present in improved dynamic time warping algorithm, Itakura parallelogram window is to path starting point and end
The searching route of point is narrow, though be easy to causeing the regular inaccuracy in beginning and end path, Sakoe-Chiba windows can be global real
Existing equal in width searches element, but it is searched plain width and need to think to be arranged according to actual matrix size.Therefore, current combination dynamic time rule
The effect of the health status monitoring of whole algorithm cannot all meet present situation requirement.
Invention content
The present invention is to overcome above-mentioned technological deficiency, provides a kind of SiC-GTO device states monitoring based on DTW and SVM
Method, this method optimize the constraints, can effectively avoid the regular inaccurate and search width in path that from need to artificially setting
The problem of setting, while reducing computation complexity and reducing calculation amount.
Technical scheme is as follows：
SiC-GTO device state monitoring methods based on DTW and SVM, steps are as follows for specific method：
One, it draws, is defined as using the 3rd area P as function pin in the device architecture of SiC-GTO device health monitorings
The poles Base (B)；
Two, use flush type circuit design measurement device normal when high temperature, high humidity, high power or degeneration successor
The VA characteristic curve at meaning both ends, such as the ends AK, the ends GB；
Three, the matching distance matrix D of two time serieses is established based on dynamic time warping algorithmn×mAnd dynamic time warping
The global constraints in path；
Four, accumulation is apart from minimum path between finding element, and acquires minimum distortion degree summation γ (i, j)；
Five, SVM classifier is trained using minimum distortion degree summation as SiC-GTO devices sample characteristics seek it is optimal
Optimal Separating Hyperplane；
Six, classify to SiC-GTO device samples, realize the monitoring of SiC-GTO device states.
As shown in Figure 1, steps are as follows for the specific method of the present invention：
Step 1: drawn the 3rd area P as function pin in the device architecture of SiC-GTO device health monitorings, it is fixed
Justice is the poles Base (B)；
Step 2: using flush type circuit design measuring appliance under low voltage situations when high temperature, high humidity, high power
Part is normal or VA characteristic curves of any two ends after degenerating, such as the ends AK, the ends GB；
Step 3: establishing the matching distance matrix D of two time serieses based on dynamic time warping algorithmn×mAnd dynamic time
The global constraints in regular path；
Step 4: finding the path that accumulation distance is minimum between element, and acquire minimum distortion degree summation γ (i, j)；
Step 5: using minimum distortion degree summation as SiC-GTO devices sample characteristics to support vector machines (SVM) grader
It is trained and seeks optimal separating hyper plane；
Step 6: classifying to SiC-GTO device samples, the monitoring of SiC-GTO device states is realized.
The present invention is extended on the basis of dynamic time warping algorithm, for SiC-GTO power devices, optimizes its device
Monitoring of structures and parameter acquiring method, and based on dynamic time warpping algorithm in novel SiC-GTO power devices health status monitoring side
Mask has a clear superiority.
Further, show device blocking characteristics during studying the forward blocking characteristic of SiC-GTO devices in step 1
Depend primarily on second N+/P node.Therefore during to SiC-GTO device health monitorings can by its device architecture by the 3rd
A areas P are drawn as function pin, are defined as the poles Base (B), as shown in Figure 2.
Further, following steps are specifically included in step 2：Build flush type circuit low pressure (<In the case of 10V),
Gradually increase the voltage value for being applied to device any two ends (such as ends AK, the ends GB) with the interval less than 0.1V since 0V, and
Voltage, current value synchronous acquisition to device both ends, obtain its VA characteristic curve；In normal, high temperature, high pressure, high power etc.
Device is tested respectively under test environment, obtains the VA characteristic curve under its different conditions, as shown in Figure 3.
Further, following steps are specifically included in step 3：It is R, T to define two time serieses respectively, and calculates two sequences
The matching distance matrix D of rown×m；Sequence R and T are projected into Right-angle plane space, wherein R is horizontal axis, and T is the longitudinal axis, lattice point
(i, j) indicates element riAnd tjIntersection point；Seek the Time Warp path P that a series of lattice points in plane are formed；When establishing dynamic
Between regular path P search constraints range, as shown in Figure 4.
Further, following steps are specifically included in step 4：Define two time serieses distortion factor summation be γ (i,
J), γ (1,1)=0 is enabled, is set out from point (1,1), according to searching route P, recursion is until γ (n, m), as twice sequences repeatedly
The minimum distortion degree summation of row.
Further, following steps are specifically included in step 5：Normal, high temperature, high humidity, high power are sought by above-mentioned steps
When SiC-GTO devices minimum distortion degree summation, as sample characteristics and be divided into training sample and test sample；
Input vector is mapped in a high dimensional feature vector space based on support vector machines for training sample, and in this feature sky
Between middle construction optimal separating hyper plane f (x) dividing the different sample of two classes so that two class intervals are maximum.
Further, following steps are specifically included in step 6：Test sample is divided based on optimal separating hyper plane
Class realizes the monitoring of SiC-GTO device states.
The beneficial effects of the present invention are：
The present invention draws and is defined as the poles B by regarding the 3rd area P in SiC-GTO device architectures as function pin, carries
Go out using flush type circuit to the normal of device any two ends under the environment such as high temperature, high pressure, high humidity, high power or is lied prostrate after degenerating
Peace characteristic curve is obtained, and is improved to the global constraints in wherein regular path based on dynamic time warping algorithm,
Using the obtained minimum distortion degree summation of algorithm as sample characteristics, using which part sample as training sample to svm classifier
Device is trained to obtain optimal separating hyper plane, and is classified to test sample based on the support vector machines after training, realizes
SiC-GTO device states monitor, and this method has a clear superiority in novel SiC-GTO devices health status monitoring.
The present invention is extended on the basis of dynamic time warping algorithm, for SiC-GTO power devices, optimizes its device
Monitoring of structures and parameter acquiring method, and based on dynamic time warpping algorithm in novel SiC-GTO power devices health status monitoring side
Mask has a clear superiority.
Description of the drawings
Fig. 1 is the flow diagram of the present invention；
Fig. 2 is the device architecture schematic diagram of SiC-GTO devices health status monitoring of the present invention；
Fig. 3 is the ends the SiC-GTO device GB VA characteristic curve schematic diagram being monitored under different condition of the present invention；
Fig. 4 is dynamic time warping route searching restriction range schematic diagram of the present invention.
Specific implementation mode
Below in conjunction with attached drawing, the preferred embodiment of the present invention is described in detail.
Fig. 1 is the flow chart of the method for the invention, and this method includes the following steps：
Show that device blocking characteristics mainly take during studying the forward blocking characteristic of SiC-GTO devices in step 1
Certainly in second N+/P node.Therefore during to SiC-GTO device health monitorings can by its device architecture by the 3rd area P
It is drawn as function pin, is defined as the poles Base (B), as shown in Figure 2.
Following steps are specifically included in step 2：Build flush type circuit low pressure (<In the case of 10V), opened from 0V
Begin gradually to increase the voltage value for being applied to device any two ends (such as ends AK, the ends GB) with the interval less than 0.1V, and to device
Voltage, the current value synchronous acquisition at both ends, obtain its VA characteristic curve；In test wrappers such as normal, high temperature, high pressure, high powers
Device is tested respectively under border, obtains the VA characteristic curve under its different conditions, as shown in Figure 3.
In step 3, by taking the ends GB as an example, select under normal circumstances SiC-GTO devices the ends GB VA characteristic curve by its
It is defined as R, VA characteristic curve is defined as T in the case of choosing other：
R=[r1,r2,Λri,rn]
T=[t1,t2,Λti,tn]
In formula, n and m are respectively the dimension of sequence R and T, and distance δ (i, j) is between defining two sequential elements：
δ (i, j)=(ri-tj)2
The matching distance matrix D of two sequences can then be establishedn×m：
A path P is found from matching distance matrix so that cumulative distance is minimum between element, i.e.,
To avoid the regular problem of morbid state of dynamic time warping algorithm, and computation complexity is effectively reduced, when establishing dynamic
Between regular path P search constraints range, as shown in Figure 4.2 straight lines and starting point and end that slope is 1/2 and 2 are used respectively
Point finds two straight-line intersection A, B.And the straight line y of diagonal of a matrix is parallel to based on point A, BOnAnd yUnder, this two straight lines and square
The surrounded range of battle array is dynamic time warpping algorithm Search Area, wherein
yOn=(3mx+5mn-2n2-2m2)/(3n)
yUnder=(3mx+5mn+2n2+2m2)/(3n)
The entire region of search is limited in following region：
In step 4, the distortion factor summation for defining two time serieses is γ (i, j), γ (1,1)=0 is enabled, from point (1,1)
It sets out, according to searching route P, recursion is until γ (n, m), the minimum distortion degree summation of as two time serieses repeatedly.
γ (i, j)=δ (i, j)+min [γ (i-1, j), γ (i, j-1), γ (i-1, j-1)]
In step 5, the mechanism of SVM is to find an optimal separating hyper plane for meeting classificating requirement so that this is super flat
Face can be such that the white space of hyperplane both sides maximizes while ensureing nicety of grading, give training sample set (xi,yi),
I=1,2 ..., l, y ∈ { ± 1 } Optimal Separating Hyperplane is denoted as (wx+b)=0, need to meet following constraint：
It introduces Lagrange functions to solve, obtaining support vector machines decision function is：
In formula, a is Lagrange multiplier, and b is classification thresholds, K (x, xi) it is classification kernel function.
Following steps are specifically included in step 6：Classified to test sample based on optimal separating hyper plane, is realized
The monitoring of SiC-GTO device states.
By above step, the monitoring to SiC-GTO device states can be realized.
Finally illustrate, preferred embodiment above is merely illustrative of the technical solution of the present invention and unrestricted, although logical
It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be
Various changes are made to it in form and in details, without departing from claims of the present invention limited range.
Claims (7)
1. the SiC-GTO device state monitoring methods based on DTW and SVM, it is characterised in that include the following steps：
Step 1：It draws, is defined as using the 3rd area P as function pin in the device architecture of SiC-GTO device health monitorings
The poles Base (B)；
Step 2: under various circumstances, using flush type circuit design, measurement device is normal or degeneration successor under low voltage situations
The VA characteristic curve at meaning both ends, any two ends include the ends AK, the ends GB；
Step 3: establishing the matching distance matrix D of two time serieses based on dynamic time warping algorithmn×mAnd dynamic time warping
The global constraints in path；
Step 4: find the path that accumulation distance is minimum between element, and acquire minimum distortion degree summation γ (i, j), i ∈ (0, n],
j∈(0,m]；
Step 5: being carried out to support vector machines (SVM) grader using minimum distortion degree summation as SiC-GTO devices sample characteristics
Optimal separating hyper plane is sought in training；
Step 6: classifying to SiC-GTO device samples, the monitoring of SiC-GTO device states is realized.
2. the SiC-GTO device state monitoring methods according to claim 1 based on DTW and SVM, it is characterised in that：
In step 2, the low pressure refers to<In the case of 10V, is gradually increased with the interval less than 0.1V since 0V and be applied to device AK
The voltage value at end, the ends GB, and to the voltage at device both ends, current value synchronous acquisition, obtain its VA characteristic curve；It is normal,
Device is tested respectively under the different test environment of high temperature, high pressure, high power, obtains the C-V characteristic under its different conditions
Curve.
3. the SiC-GTO device state monitoring methods according to claim 1 based on DTW and SVM, it is characterised in that：
In step 3, it is R, T to define two time serieses respectively, and calculates the matching distance matrix D of two time seriesesn×m；By time series
R and T are projected into Right-angle plane space, and wherein R is horizontal axis, and T is the longitudinal axis, and lattice point (i, j) indicates element riAnd tjIntersection point；It asks
Take a series of Time Warp path P that lattice points are formed in Right-angle plane space；Establish the search of dynamic time warping path P
Restriction range.
4. the SiC-GTO device state monitoring methods according to claim 3 based on DTW and SVM, it is characterised in that：
In step 4, the distortion factor summation for defining two time serieses is γ (i, j), enables γ (1,1)=0, sets out from point (1,1), according to
Searching route P, recursion is until γ (n, m), the minimum distortion degree summation of as two time serieses repeatedly:γ (i, j)=δ (i, j)+
min[γ(i-1,j),γ(i,j-1),γ(i-1,j-1)],i∈(0,n],j∈(0,m]。
5. the SiC-GTO device state monitoring methods according to claim 1 or 4 based on DTW and SVM, it is characterised in that：
In step 5, minimum distortion degree summation as sample characteristics and is divided into training sample and test sample；For training sample
Input vector is mapped in a high dimensional feature vector space based on support vector machines, and is constructed in this feature space optimal
Optimal Separating Hyperplane f (x) is dividing the different sample of two classes so that two class intervals are maximum.
6. the SiC-GTO device state monitoring methods according to claim 5 based on DTW and SVM, it is characterised in that：
In step 6, classified to test sample based on optimal separating hyper plane, realizes the monitoring of SiC-GTO device states.
7. the SiC-GTO device state monitoring methods according to claim 5 based on DTW and SVM, it is characterised in that：
In step 5, the mechanism of the SVM is to find an optimal separating hyper plane for meeting classificating requirement so that the hyperplane is being protected
While demonstrate,proving nicety of grading, the white space of hyperplane both sides can be made to maximize, give training sample set (xi,yi), i=1,
2 ..., l, y ∈ { ± 1 } Optimal Separating Hyperplane is denoted as (wx+b)=0, need to meet following constraint：
It introduces Lagrange functions to solve, obtaining support vector machines decision function is：
In formula, α is Lagrange multiplier, and b is classification thresholds, K (x, xi) it is classification kernel function.
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