CN109781614A - A comprehensive detection method for the aging degree of composite insulators - Google Patents
A comprehensive detection method for the aging degree of composite insulators Download PDFInfo
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Abstract
本申请提供了一种复合绝缘子老化程度的综合检测方法。通过获得红外光谱分析法、热刺激电流TSC分析法、高光谱谱图分析法和表面电荷密度法的测量结果，利用BP神经网络算法优化不同测试方法获得测试结果的权值；获得复合绝缘子的综合老化程度；通过归一化方法获得复合绝缘子老化的剩余寿命。本申请通过综合多种方法获得复合绝缘子的老化程度，实现了对复合绝缘子老化程度的综合检测，能够更加精准测量复合绝缘子的老化程度，并且预测复合绝缘子的剩余寿命，为输电线路的运维人员及时更换老化程度严重的复合绝缘子提供更加精准的技术支撑，保障输电线路的安全可靠运行。
The present application provides a comprehensive detection method for the aging degree of composite insulators. By obtaining the measurement results of infrared spectrum analysis method, thermal stimulation current TSC analysis method, hyperspectral spectrum analysis method and surface charge density method, using BP neural network algorithm to optimize the weights of different test methods to obtain the test results; The degree of aging; the remaining life of the composite insulator is obtained by the normalization method. The present application obtains the aging degree of the composite insulator by integrating various methods, realizes the comprehensive detection of the aging degree of the composite insulator, can measure the aging degree of the composite insulator more accurately, and predict the remaining life of the composite insulator, which is helpful for the operation and maintenance personnel of the transmission line. Timely replacement of seriously aged composite insulators provides more accurate technical support and ensures the safe and reliable operation of transmission lines.
Description
Technical field
The application belongs to the comprehensive of high-voltage composite insulator technical field more particularly to a kind of composite insulator degree of aging
Close detection method.
Background technique
Currently, composite insulator is because having many advantages, such as high mechanical strength, pollution flashover voltage is high, light-weight, operation and maintenance are simple,
It is widely used in power system transmission line insulation.However, due to being influenced by transmission line of electricity ambient enviroment, including it is ultraviolet
Line, temperature and humidity, pollution degree and corona etc., composite insulator will appear different degrees of aging.The aging master of composite insulator
It shows that full skirt is sliced brittle, dusting and breakage, or even mandrel fracture occurs, the appearance of these phenomenons can seriously affect compound
The normal operation of insulator, and then affect the safe and reliable operation of power grid.Therefore, it for operation and maintenance department, needs
The ageing state of composite insulator is detected, determines when to replace composite insulator.
It in the prior art, include: visual inspection, hydrophobicity test, Fourier to the degradation detecting method of composite insulator
Transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), nuclear magnetic resonance etc..The composite insulator aging of above-mentioned a variety of technique studies
The changing rule of appearance, hydrophobicity and material physical and chemical performance afterwards realizes the assessment to composite insulator material aging degree.
In fact, the ageing state of composite insulator not just represents the existing degree of aging of silastic material, more greatly
Its ageing resistance is reflected in degree, i.e., the ability of degree of aging later period sustainable hanging net operation is prejudged.But it is existing
The composite insulator degradation detecting method for thering is technology to use, it is difficult to which the remaining life judgement for realizing composite insulator can not judge
It is if appropriate for continuation long-time hanging net operation.The composite insulator being seriously damaged when a large amount of ageing resistances for a long time after
When continuous hanging net operation, composite insulator can add under the collective effect of the factors such as electric field, filth, moisture, ultraviolet light, shelf depreciation
The phenomenon that fast aging, these can not be prejudged, may cause huge threat to the safe and reliable operation of transmission line of electricity.
Summary of the invention
This application provides a kind of method for comprehensive detection of composite insulator degree of aging, to solve prior art use
Composite insulator degradation detecting method, it is difficult to realize composite insulator remaining life judgement, can not judge its if appropriate for after
The technical issues of continuous long-time hanging net operation.
A kind of method for comprehensive detection of composite insulator degree of aging, the described method comprises the following steps:
Step S100: composite insulator umbrella skirt slice is obtained, thin rounded flakes sample is made；
Step S200: being wiped using dehydrated alcohol, obtains clean composite insulator umbrella skirt sliced piece specimen；
Step S300: to full skirt sliced piece specimen be utilized respectively infrared spectrum analysis method, thermally stimulated current TSC analytic approach,
EO-1 hyperion spectrum analysis method and surface charge density analytic approach are detected, and test result is obtained, what above-mentioned four kinds of methods obtained
Measurement result is 0 to 1 scalar for reflecting degree of aging, uses a respectively1、a2、a3、a4It indicates；
Step S400: the test result obtained using four kinds of test methods in BP neural network algorithm optimization step S300
a1、a2、a3、a4Corresponding weight, the weight optimized use b respectively1、b2、b3、b4It indicates, and according to formula L=a1b1+
a2b2+a3b3+a4b4The degree of aging of composite insulator is calculated, L indicates the comprehensive degree of aging end value of composite insulator；
Step S500: the remaining life of composite insulator aging is obtained by method for normalizing, is utilized formula D=W (1-L)
The remaining life of composite insulator is found out, wherein W indicates the service life in complete period of insulator, and L indicates the comprehensive aging of composite insulator
Degree value, D indicate the remaining life of composite insulator.
Further, the step S400 is obtained using four kinds of test methods in BP neural network algorithm optimization step S300
Test result a1、a2、a3、a4Corresponding weight, the weight optimized use b respectively1、b2、b3、b4It indicates, optimizes corresponding power
Value formula used are as follows:
F (B)=eT(k)e(k)；
cm(k+1)=cm(k)-αsm；
Bm(k+1)=Bm(k)-αsm(ym-1)T；
SM=-2FM(nM)(t-y)；
Sm=Fm(nm)(Bm+1)TSm+1, m=M-1 ..., 2,1；
Wherein, B is the matrix of weight composition in BP neural network, and F (B) is mean square deviation, and e (k) is that neuron kth time calculates
Result and its expected results difference composition error vector, k be BP neural network the number of iterations, SmIt is defeated for m layers of characterization
Out to the influence degree sensitivity coefficient of F (B) mean square error, M is total number of plies of neural network, nmFor the output of m layers of neuron
Vector, Fm() indicates that m layers of mean square error function, t are that the target of BP neural network exports, and y is the reality of BP neural network
Output, Bm(k+1) be m layers of BP neural network+1 iteration of kth weight matrix, cmIt (k+1) is m layers of BP neural network
+ 1 iteration of kth when the threshold value that uses, α is learning rate.
Further, described to utilize infrared spectrum analysis method to full skirt sliced piece specimen, it includes following for obtaining test result
Step:
Step S301: the infrared spectrum of composite insulator umbrella skirt sliced piece specimen is obtained；
Step S302: the height of composite insulator major absorbance peak is extracted；
Step S303: according to the height of composite insulator major absorbance peak, the scalar that obtained measurement result is 0 to 1 is used
a1It indicates；
Step S304: according to the high measure result a of composite insulator major absorbance peak1To composite insulator degree of aging
It is evaluated, a1Value is that 0-0.25 indicates that degree of aging is lighter, a1Value is that 0.25-0.5 indicates that degree of aging is general, a1Value is
0.5-0.75 indicates that degree of aging is heavier, a1Value is that 0.75-1 indicates that degree of aging is serious.
Further, it is described to full skirt sliced piece specimen utilize thermally stimulated current TSC analytic approach, obtain test result include with
Lower step:
Step S311: the different location of composite insulator umbrella skirt section sample is sampled and is sliced；
Step S312: thermally stimulated current TSC experiment is carried out to the slice, obtains TSC curve；
Step S313: calculating the trapped charge amount and trap level of slice according to TSC curve, obtains reflecting the trap electricity
The scalar that lotus amount and the measurement result of trap level are 0 to 1, uses a2It indicates；
Step S314: according to the measurement result a for reflecting the trapped charge amount and trap level2To composite insulator aging
Degree is evaluated, a2Value is that 0-0.25 indicates that degree of aging is lighter, a2Value is that 0.25-0.5 indicates that degree of aging is general, a2Value
Indicate that degree of aging is heavier for 0.5-0.75, a2Value is that 0.75-1 indicates that degree of aging is serious.
Further, described to utilize EO-1 hyperion spectrum analysis method to full skirt sliced piece specimen, it includes following for obtaining test result
Step:
Step S321: the high spectrum image that composite insulator umbrella skirt is sliced sample is obtained by EO-1 hyperion tester；
Step S322: pre-processing the high spectrum image of acquisition, chooses training sample；
Step S323: establishing composite insulator Ageing Model, Ageing Model quantified, and obtained measurement result is 0 to 1
Scalar uses a3It indicates；
Step S324: the test result a quantitatively obtained according to composite insulator Ageing Model3To composite insulator aging journey
Degree is evaluated, a3Value is that 0-0.25 indicates that degree of aging is lighter, a3Value is that 0.25-0.5 indicates that degree of aging is general, a3Value is
0.5-0.75 indicates that degree of aging is heavier, a3Value is that 0.75-1 indicates that degree of aging is serious.
Further, it is described to full skirt sliced piece specimen utilize surface charge density analytic approach, obtain test result include with
Lower step:
Step S331: DC voltage is applied to full skirt sliced piece specimen using high pressure loading device；
Step S332: the surface charge of surface charge test device measurement full skirt sliced piece specimen is utilized；
Step S333: the average surface charge density of full skirt sliced piece specimen, the mark that obtained measurement result is 0 to 1 are obtained
Amount, uses a4It indicates；
Step S334: according to the test result a of the average surface charge density of full skirt sliced piece specimen4It is old to composite insulator
Change degree is evaluated, a4Value is that 0-0.25 indicates that degree of aging is lighter, a4Value is that 0.25-0.5 indicates that degree of aging is general, a4
Value is that 0.5-0.75 indicates that degree of aging is heavier, a4Value is that 0.75-1 indicates that degree of aging is serious.
Further, the comprehensive degree of aging end value L of composite insulator is calculated in the step S400, to compound inslation
Sub- degree of aging grade classification is four grades: L value is that 0-0.25 indicates that degree of aging is lighter, and L value is that 0.25-0.5 indicates old
Change degree is general, and L value is that 0.5-0.75 indicates that degree of aging is heavier, and L value is that 0.75-1 indicates that degree of aging is serious.
Further, the step S100 thin rounded flakes sample is that diameter is 25mm, tries with a thickness of the thin rounded flakes of 1.2mm
Sample.
The beneficial effect of the application is:
From the above technical scheme, this application provides a kind of method for comprehensive detection of composite insulator degree of aging.
By obtaining infrared spectroscopy, thermally stimulated current TSC analytic approach, EO-1 hyperion spectrum analysis method and surface charge density method
Measurement result obtains the weight of test result using BP neural network algorithm optimization difference test method；Obtain composite insulator
Synthesis degree of aging；The remaining life of composite insulator aging is obtained by method for normalizing.The application is a variety of by synthesis
Method obtains the degree of aging of composite insulator, realizes the comprehensive detection to composite insulator degree of aging, can be more smart
The degree of aging of locating tab assembly composite insulator, and predict the remaining life of composite insulator, it is the operation maintenance personnel of transmission line of electricity
The replacement serious composite insulator of degree of aging provides more accurate technical support in time, ensures the safe and reliable of transmission line of electricity
Operation.
Detailed description of the invention
In order to illustrate more clearly of the technical solution of the application, letter will be made to attached drawing needed in the embodiment below
Singly introduce, it should be apparent that, for those of ordinary skills, without any creative labor,
It is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow chart of the method for comprehensive detection of composite insulator degree of aging of the application；
Fig. 2 is the flow chart that the application utilizes infrared spectroscopy to detect composite insulator degree of aging；
Fig. 3 is the flow chart that the application utilizes thermally stimulated current TSC analytic approach to detect composite insulator degree of aging；
Fig. 4 is the flow chart that the application utilizes EO-1 hyperion spectrum analysis method to detect composite insulator degree of aging；
Fig. 5 is the flow chart that the application utilizes surface charge density analytic approach to detect composite insulator degree of aging.
Specific embodiment
Here embodiment will be illustrated in detail, the example is illustrated in the accompanying drawings.In the following description when referring to the accompanying drawings,
Unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Implement described in following embodiment
Mode does not represent all embodiments consistent with the application.
It is a kind of flow chart of the method for comprehensive detection of composite insulator degree of aging of the application referring to Fig. 1.
A kind of method for comprehensive detection of composite insulator degree of aging, the described method comprises the following steps:
Step S100: composite insulator umbrella skirt slice is obtained, thin rounded flakes sample is made；
Step S200: being wiped using dehydrated alcohol, obtains clean composite insulator umbrella skirt sliced piece specimen；
Step S300: to full skirt sliced piece specimen be utilized respectively infrared spectrum analysis method, thermally stimulated current TSC analytic approach,
EO-1 hyperion spectrum analysis method and surface charge density analytic approach are detected, and test result is obtained, what above-mentioned four kinds of methods obtained
Measurement result is 0 to 1 scalar for reflecting degree of aging, uses a respectively1、a2、a3、a4It indicates；
Step S400: the test result obtained using four kinds of test methods in BP neural network algorithm optimization step S300
a1、a2、a3、a4Corresponding weight, the weight optimized use b respectively1、b2、b3、b4It indicates, and according to formula L=a1b1+
a2b2+a3b3+a4b4The synthesis degree of aging of composite insulator is calculated, L indicates the comprehensive degree of aging end value of composite insulator；
Step S500: the remaining life of composite insulator aging is obtained by method for normalizing, is utilized formula D=W (1-L)
The remaining life of composite insulator is found out, wherein W indicates the service life in complete period of insulator, and L is the comprehensive aging journey of composite insulator
Angle value, D indicate the remaining life of composite insulator.
It in the prior art, include: visual inspection, hydrophobicity test, Fourier to the degradation detecting method of composite insulator
Transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), nuclear magnetic resonance etc..The composite insulator aging of above-mentioned a variety of technique studies
The changing rule of appearance, hydrophobicity and material physical and chemical performance afterwards realizes the assessment to composite insulator material aging degree.
In fact, the ageing state of composite insulator not just represents the existing degree of aging of silastic material, more greatly
Its ageing resistance is reflected in degree, i.e., the ability of degree of aging later period sustainable hanging net operation is prejudged.But it is existing
The composite insulator degradation detecting method for thering is technology to use, it is difficult to which the remaining life judgement for realizing composite insulator can not judge
It is if appropriate for continuation long-time hanging net operation.The composite insulator being seriously damaged when a large amount of ageing resistances for a long time after
When continuous hanging net operation, composite insulator can add under the collective effect of the factors such as electric field, filth, moisture, ultraviolet light, shelf depreciation
The phenomenon that fast aging, these can not be prejudged, may cause huge threat to the safe and reliable operation of transmission line of electricity.
Optionally, step S100: composite insulator umbrella skirt slice is obtained, thin rounded flakes sample is made；
Composite insulator is that the insulation mandrel for undertaking mechanical load by one and overcoating polymer umbrella cover are constituted, and machinery is negative
Lotus passes to plug by metal-ware.The full skirt of composite insulator is the building block of composite insulator product external insulation.It
Being insulation compound by being kneaded is formed by particular manufacturing craft through the vulcanization of rubber elevated temperature cure that pressurizes.Composite insulator is transmission of electricity
The insulating element of conducting wire is hung on route, in the process of running, full skirt insulation performance is easily influenced by ambient environmental factors, especially
It is that the influence of fouling products will lead to the transmission line of electricity generation pollution flashover tripping loss of power accident, it is ensured that the safe operation of transmission line of electricity,
Other than guaranteeing surface insulation performance in such a way that full skirt quantity increases creepage distance, it is necessary to exhausted using full skirt to greatest extent
The distinctive hydrophobicity of silastic material and hydrophobicity migration performance in edge improve the anti-pollution lightning voltage levels of insulator surface.Due to
The hydrophobicity and hydrophobicity migration performance that silicon rubber has can limit leakage current, improve flashover voltage, therefore, composite insulator
External insulation has brilliant anti-pollution, can be effectively prevented transmission line of electricity due to the generation of pollution flashover separating brake accident, guarantee line
The safe operation on road.Therefore, the degree of aging of composite insulator and ageing resistance are evaluated, compound inslation need to be obtained
The full skirt slice of son is tested.Composite insulator 10 for choosing same model difference degree of aging, in 10 compound inslations
Full skirt slice is intercepted on son respectively.Full skirt slice should be complete, no breakage.
Step S200: being wiped using dehydrated alcohol, obtains clean composite insulator umbrella skirt sliced piece specimen；
Optionally, after being cleaned using dehydrated alcohol to composite insulator umbrella skirt slice, then with deionized water to full skirt
Slice surface is cleaned, and is then placed in drying box, 3 hours dry in the case where temperature is 303K.
Step S300: to full skirt sliced piece specimen be utilized respectively infrared spectrum analysis method, thermally stimulated current TSC analytic approach,
EO-1 hyperion spectrum analysis method and surface charge density analytic approach are detected, and test result is obtained, what above-mentioned four kinds of methods obtained
Measurement result is 0 to 1 scalar for reflecting degree of aging, uses a respectively1、a2、a3、a4It indicates；
Optionally, 10 groups of composite insulator umbrella skirts are measured using infrared spectrum analysis method to be sliced, obtains 10 groups of data, and
It is normalized, obtains average value, the scalar a that measurement result is 0 to 11It indicates；It is analyzed using thermally stimulated current TSC
Method measures 10 groups of composite insulator umbrella skirt slices, obtains 10 groups of data, and be normalized, and obtains average value, measurement knot
The scalar a that fruit is 0 to 12It indicates；10 groups of composite insulator umbrella skirts are measured using EO-1 hyperion spectrum analysis method to be sliced, and obtain 10
Group data, and be normalized, obtain average value, the scalar a that measurement result is 0 to 13It indicates；Utilize surface charge
Density analysis method measures 10 groups of composite insulator umbrella skirt slices, obtains 10 groups of data, and be normalized, is averaged
Value, the scalar a that measurement result is 0 to 14It indicates；
Step S400: the test result obtained using four kinds of test methods in BP neural network algorithm optimization step S300
a1、a2、a3、a4Corresponding weight, the weight optimized use b respectively1、b2、b3、b4It indicates, and according to formula L=a1b1+
a2b2+a3b3+a4b4The synthesis degree of aging of composite insulator is calculated, L indicates the comprehensive degree of aging end value of composite insulator；
Step S500: the remaining life of composite insulator aging is obtained by method for normalizing, is utilized formula D=W (1-L)
The remaining life of composite insulator is found out, wherein W indicates the service life in complete period of insulator, and L indicates composite insulator degree of aging
Value, D indicate the remaining life of composite insulator.
Normalization is a kind of dimensionless processing means, and the absolute value of physical system numerical value is made to become certain relative value relationship.
To by being normalized into the effective way for reducing magnitude to simplify the calculation.Composite insulator residue is quantified, is helped
The serious composite insulator of degree of aging is replaced in time in the operation maintenance personnel for transmission line of electricity, and more accurate technical support is provided,
Ensure the safe and reliable operation of transmission line of electricity.
From the above technical scheme, this application provides a kind of method for comprehensive detection of composite insulator degree of aging.
By obtaining infrared spectroscopy, thermally stimulated current TSC analytic approach, EO-1 hyperion spectrum analysis method and surface charge density method
Measurement result obtains the weight of test result using BP neural network algorithm optimization difference test method；Obtain composite insulator
Synthesis degree of aging；The remaining life of composite insulator aging is obtained by method for normalizing.The application is a variety of by synthesis
Method obtains the degree of aging of composite insulator, realizes the comprehensive detection to composite insulator degree of aging, can be more smart
The degree of aging of locating tab assembly composite insulator, and predict the remaining life of composite insulator, it is the operation maintenance personnel of transmission line of electricity
The replacement serious composite insulator of degree of aging provides more accurate technical support in time, ensures the safe and reliable of transmission line of electricity
Operation.
Further, the step S400 is obtained using four kinds of test methods in BP neural network algorithm optimization step S300
Test result a1、a2、a3、a4Corresponding weight, the weight optimized use b respectively1、b2、b3、b4It indicates, optimizes corresponding power
Value formula used are as follows:
F (B)=eT(k)e(k)；
cm(k+1)=cm(k)-αsm；
Bm(k+1)=Bm(k)-αsm(ym-1)T；
SM=-2FM(nM)(t-y)；
Sm=Fm(nm)(Bm+1)TSm+1, m=M-1 ..., 2,1；
Wherein, B is the matrix of weight composition in BP neural network, and F (B) is mean square deviation, and e (k) is that neuron kth time calculates
Result and its expected results difference composition error vector, k be BP neural network the number of iterations, SmIt is defeated for m layers of characterization
Out to the influence degree sensitivity coefficient of F (B) mean square error, M is total number of plies of neural network, nmFor the output of m layers of neuron
Vector, Fm() indicates that m layers of mean square error function, t are that the target of BP neural network exports, and y is the reality of BP neural network
Output, Bm(k+1) be m layers of BP neural network+1 iteration of kth weight matrix, cmIt (k+1) is m layers of BP neural network
+ 1 iteration of kth when the threshold value that uses, α is learning rate.
BP neural network needs certain data accumulation, specifically, first optimize the composite insulators of different degree of agings into
Row measurement, and neural network is trained using the measurement data of acquisition；Meanwhile it being built for the composite insulator of different model
Different BP neural network models is found, and training sample is more, model accuracy rate is also higher.
Referring to fig. 2, the flow chart for utilizing infrared spectroscopy to detect composite insulator degree of aging for the application.
Further, described to utilize infrared spectrum analysis method to full skirt sliced piece specimen, it includes following for obtaining test result
Step:
Step S301: the infrared spectrum of composite insulator umbrella skirt sliced piece specimen is obtained；
Step S302: the height of composite insulator major absorbance peak is extracted；
Step S303: according to the height of composite insulator major absorbance peak, the scalar that obtained measurement result is 0 to 1 is used
a1It indicates；
Step S304: according to the high measure result a of composite insulator major absorbance peak1To composite insulator degree of aging
It is evaluated, a1Value is that 0-0.25 indicates that degree of aging is lighter, a1Value is that 0.25-0.5 indicates that degree of aging is general, a1Value is
0.5-0.75 indicates that degree of aging is heavier, a1Value is that 0.75-1 indicates that degree of aging is serious.
Optionally, obtain composite insulator umbrella skirt sliced piece specimen infrared spectrum, extract Si-0-Si main chain group and
Si-CH3 side chain group is corresponding to absorb peak heights, and the absorption peak heights of acquisition are normalized, and reaches the mark that measurement result is 0 to 1
Amount, obtains a1, and evaluation is distinguished to degree of aging.
Work as a1When value is 0.75-1, it is serious to indicate that degree of aging occurs in the class composite insulator, then the class is compound absolutely
Edge cannot continue the hanging net operation long period；Work as a1Value is that 0-0.25 indicates that degree of aging is lighter, then the class compound inslation
Son may continue to the hanging net operation long period, without aging phenomenon；Work as a1Value is that 0.25-0.5 indicates degree of aging one
As, a1Value is that 0.5-0.75 indicates that degree of aging is heavier, demonstrates the need for carrying out the ageing resistance of the class composite insulator
It further determines, by assessing the remaining life of the class composite insulator aging, is tieed up to be run to transmission line of electricity
Shield personnel replace composite insulator in time and provide technical data support.
Referring to Fig. 3, the process for utilizing thermally stimulated current TSC analytic approach to detect composite insulator degree of aging for the application
Figure.
Further, it is described to full skirt sliced piece specimen utilize thermally stimulated current TSC analytic approach, obtain test result include with
Lower step:
Step S311: the different location of composite insulator umbrella skirt section sample is sampled and is sliced；
Step S312: thermally stimulated current TSC experiment is carried out to the slice, obtains TSC curve；
Step S313: calculating the trapped charge amount and trap level of slice according to TSC curve, obtains reflecting the trap electricity
The scalar that lotus amount and the measurement result of trap level are 0 to 1, uses a2It indicates；
Step S314: according to the measurement result a for reflecting the trapped charge amount and trap level2To composite insulator aging
Degree is evaluated, a2Value is that 0-0.25 indicates that degree of aging is lighter, a2Value is that 0.25-0.5 indicates that degree of aging is general, a2Value
Indicate that degree of aging is heavier for 0.5-0.75, a2Value is that 0.75-1 indicates that degree of aging is serious.
Optionally, thermally stimulated current (Thermally stimulated currents TSC) method, can measure object
Matter, for example, dielectric, insulating materials, semiconductor, garrison the micro-parameter of polar body etc..Thermally stimulated current method is in temperature change
While measure the parameter of material, it is easy to activation energy different in material or the charged particle of slack time are separated, to ask
Obtain respective parameter.Will be cut from composite insulator from different location full skirt slice, be placed in dehydrated alcohol later into
Row rinsing, is put into baking oven after rinsing, is dried, vacuum evaporation golden film, as slice test electrode.Sliced piece specimen is put
Enter in vacuum tank, by two terminal shortcircuit of sample, heats up, and add high pressure, be then injected into liquid nitrogen, sliced piece specimen is cooling, then
By two terminal shortcircuit of sliced piece specimen, temperature is then increased, while electrometer is accessed into circuit record current variation with temperature situation,
Obtain TSC curve.The trapped charge amount and trap level that slice is calculated according to TSC curve, obtain reflecting the trapped charge amount
The scalar that measurement result with trap level is 0 to 1, uses a2It indicates.
Referring to fig. 4, the flow chart for utilizing EO-1 hyperion spectrum analysis method to detect composite insulator degree of aging for the application.
Further, described to utilize EO-1 hyperion spectrum analysis method to full skirt sliced piece specimen, it includes following for obtaining test result
Step:
Step S321: the high spectrum image that composite insulator umbrella skirt is sliced sample is obtained by EO-1 hyperion tester；
Step S322: pre-processing the high spectrum image of acquisition, chooses training sample；
Step S323: establishing composite insulator Ageing Model, Ageing Model quantified, and obtained measurement result is 0 to 1
Scalar uses a3It indicates；
Step S324: the test result a quantitatively obtained according to composite insulator Ageing Model3To composite insulator aging journey
Degree is evaluated, a3Value is that 0-0.25 indicates that degree of aging is lighter, a3Value is that 0.25-0.5 indicates that degree of aging is general, a3Value is
0.5-0.75 indicates that degree of aging is heavier, a3Value is that 0.75-1 indicates that degree of aging is serious.
Optionally, composite insulator umbrella skirt slice is obtained to composite insulator umbrella skirt slice imaging with hyperspectral imager
High spectrum image.The high spectrum image of acquisition is pre-processed, including geometric correction, filtering and noise reduction, radiant correction, thus
Accurately spectral information is compared in acquisition.Training sample is chosen, including determining status number, the sample area for choosing every kind of state, taking mean value,
Obtain the maenvalue of every kind of state.Establish composite insulator Ageing Model: quantization degree of aging first extracts spectral signature,
Establish composite insulator Ageing Model.Ageing Model parameter is resolved with minimum two methods.The knot that Ageing Model is quantified
Fruit evaluates composite insulator degree of aging.The degree of aging that composite insulator is judged with Ageing Model, from EO-1 hyperion shadow
As upper, then the pixel region of extraction composite insulator umbrella skirt sliced piece specimen judges pixel in region one by one with Ageing Model
Aging coefficient takes mean value to the degree of aging of all pixels in region, the degree of aging of composite insulator can be obtained.
Referring to Fig. 5, the process for utilizing surface charge density analytic approach to detect composite insulator degree of aging for the application
Figure.
Further, it is described to full skirt sliced piece specimen utilize surface charge density analytic approach, obtain test result include with
Lower step:
Step S331: DC voltage is applied to full skirt sliced piece specimen using high pressure loading device；
Step S332: the surface charge of surface charge test device measurement full skirt sliced piece specimen is utilized；
Step S333: the average surface charge density of full skirt sliced piece specimen, the mark that obtained measurement result is 0 to 1 are obtained
Amount, uses a4It indicates；
Step S334: according to the test result a of the average surface charge density of full skirt sliced piece specimen4It is old to composite insulator
Change degree is evaluated, a4Value is that 0-0.25 indicates that degree of aging is lighter, a4Value is that 0.25-0.5 indicates that degree of aging is general, a4
Value is that 0.5-0.75 indicates that degree of aging is heavier, a4Value is that 0.75-1 indicates that degree of aging is serious.
Optionally, it is pressurizeed using high pressure loading equipemtn to composite insulator umbrella skirt sample, high pressure is removed after 3min.Benefit
With the surface charge of surface charge test device measurement composite insulator umbrella skirt sample, the table that will be surveyed in specimen surface a certain range
Surface charge draws x-y- σ three-dimensional figure.The a certain range of average surface charge of setting for calculating composite insulator umbrella skirt sample is close
Degree,WhereinFor average surface charge density, n is test point sum, σiFor the surface charge of i-th of test point.
Average surface charge density is higher in x-y- σ three-dimensional figure, illustrates that the charge of the trap capture of composite insulator umbrella skirt sample is more,
Trap level is deeper, and trap density is higher.Somewhere surface charge is more in x-y- σ three-dimensional figure, illustrates that the charge captured herein is got over
More, trap level is deeper.With the increase of the degree of aging of composite insulator umbrella skirt sample, trap level is deepened, and trap is close
Degree increases, and the charge that composite insulator umbrella skirt sample can capture under identical voltage increases, and average charge density increases, when flat
Equal charge density is more than 0.52 μ C/m2, it is believed that composite insulator degree of aging is serious, is replaced, at this time a4Value is
0.75-1 indicates that degree of aging is serious.
Further, the comprehensive degree of aging end value L of composite insulator is calculated in the step S400, to compound inslation
Sub- degree of aging grade classification is four grades: L value is that 0-0.25 indicates that degree of aging is lighter, and L value is that 0.25-0.5 indicates old
Change degree is general, and L value is that 0.5-0.75 indicates that degree of aging is heavier, and L value is that 0.75-1 indicates that degree of aging is serious.
Optionally, in order to facilitate operation maintenance personnel de-quantization composite insulator degree of aging, by composite insulator aging journey
Correspondence is classified after metrization.
Further, the step S100 thin rounded flakes sample is that diameter is 25mm, tries with a thickness of the thin rounded flakes of 1.2mm
Sample.
Field strength is closely connected together around the aging of composite insulator and composite insulator.For composite insulator
The high region of surrounding field strength, it is easier to aging occur.Optionally, the composite insulator umbrella skirt table crossed using food slicer from hanging net operation
It is 25mm, the thin rounded flakes sample with a thickness of 1.2mm that diameter is cut in face.To avoid choosing composite insulator umbrella skirt sample thickness
It spends thin, and in the case that surrounding field strength is high herein, the practical degree of aging of composite insulator can not be assessed；And it avoids
After choosing composite insulator umbrella skirt sample thickness, and in the case that surrounding field strength is low herein, unnecessary full skirt part is cut
It causes to waste.
From the above technical scheme, this application provides a kind of method for comprehensive detection of composite insulator degree of aging.
By obtaining infrared spectroscopy, thermally stimulated current TSC analytic approach, EO-1 hyperion spectrum analysis method and surface charge density method
Measurement result obtains the weight of test result using BP neural network algorithm optimization difference test method；Obtain composite insulator
Synthesis degree of aging；The remaining life of composite insulator aging is obtained by method for normalizing.The application is a variety of by synthesis
Method obtains the degree of aging of composite insulator, realizes the comprehensive detection to composite insulator degree of aging, can be more smart
The degree of aging of locating tab assembly composite insulator, and predict the remaining life of composite insulator, it is the operation maintenance personnel of transmission line of electricity
The replacement serious composite insulator of degree of aging provides more accurate technical support in time, ensures the safe and reliable of transmission line of electricity
Operation.
Similar portion cross-reference between embodiment provided by the present application, specific embodiment provided above is only
It is several examples under the total design of the application, does not constitute the restriction of the application protection scope.For those skilled in the art
For member, any other embodiment expanded without creative efforts according to application scheme all belongs to
In the protection scope of the application.
Claims (8)
1. a kind of method for comprehensive detection of composite insulator degree of aging, which is characterized in that the described method comprises the following steps:
Step S100: composite insulator umbrella skirt slice is obtained, thin rounded flakes sample is made；
Step S200: being wiped using dehydrated alcohol, obtains clean composite insulator umbrella skirt sliced piece specimen；
Step S300: infrared spectrum analysis method, thermally stimulated current TSC analytic approach, bloom are utilized respectively to full skirt sliced piece specimen
Spectrum spectrum analysis method and surface charge density analytic approach are detected, and test result, the measurement that above-mentioned four kinds of methods obtain are obtained
As a result it is 0 to 1 scalar of reflection degree of aging, uses a respectively1、a2、a3、a4It indicates；
Step S400: the test result a obtained using four kinds of test methods in BP neural network algorithm optimization step S3001、a2、
a3、a4Corresponding weight, the weight optimized use b respectively1、b2、b3、b4It indicates, and according to formula L=a1b1+a2b2+a3b3
+a4b4The synthesis degree of aging of composite insulator is calculated, L indicates the comprehensive degree of aging end value of composite insulator；
Step S500: the remaining life of composite insulator aging is obtained by method for normalizing, is found out using formula D=W (1-L)
The remaining life of composite insulator, wherein W indicates the service life in complete period of insulator, and L indicates the comprehensive degree of aging of composite insulator
Value, D indicate the remaining life of composite insulator.
2. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that the step
The test result a that S400 is obtained using four kinds of test methods in BP neural network algorithm optimization step S3001、a2、a3、a4Institute is right
The weight answered, the weight optimized use b respectively1、b2、b3、b4It indicates, optimizes formula used in corresponding weight are as follows:
F (B)=eT(k)e(k)；
cm(k+1)=cm(k)-αsm；
Bm(k+1)=Bm(k)-αsm(ym-1)T；
SM=-2FM(nM)(t-y)；
Sm=Fm(nm)(Bm+1)TSm+1, m=M-1 ..., 2,1；
Wherein, B is the matrix of weight composition in BP neural network, and F (B) is mean square deviation, and e (k) is the knot that neuron kth time calculates
The error vector of the difference of fruit and its expected results composition, k are the number of iterations of BP neural network, SmIt is m layers of output of characterization to F
(B) the influence degree sensitivity coefficient of mean square error, M are total number of plies of neural network, nmFor the output vector of m layers of neuron, Fm
() indicates that m layers of mean square error function, t are that the target of BP neural network exports, and y is the reality output of BP neural network, Bm
(k+1) be m layers of BP neural network+1 iteration of kth weight matrix, cm(k+1) be m layers of BP neural network kth+1
The threshold value used when secondary iteration, α are learning rate.
3. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that described to umbrella
Skirt sliced piece specimen utilize infrared spectrum analysis method, obtain test result the following steps are included:
Step S301: the infrared spectrum of composite insulator umbrella skirt sliced piece specimen is obtained；
Step S302: the height of composite insulator major absorbance peak is extracted；
Step S303: according to the height of composite insulator major absorbance peak, the scalar that obtained measurement result is 0 to 1 uses a1Table
Show；
Step S304: according to the high measure result a of composite insulator major absorbance peak1Composite insulator degree of aging is carried out
Evaluation, a1Value is that 0-0.25 indicates that degree of aging is lighter, a1Value is that 0.25-0.5 indicates that degree of aging is general, a1Value is 0.5-
0.75 indicates that degree of aging is heavier, a1Value is that 0.75-1 indicates that degree of aging is serious.
4. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that described to umbrella
Skirt sliced piece specimen utilize thermally stimulated current TSC analytic approach, obtain test result the following steps are included:
Step S311: the different location of composite insulator umbrella skirt section sample is sampled and is sliced；
Step S312: thermally stimulated current TSC experiment is carried out to the slice, obtains TSC curve；
Step S313: the trapped charge amount and trap level of slice are calculated according to TSC curve, obtains reflecting the trapped charge amount
The scalar that measurement result with trap level is 0 to 1, uses a2It indicates；
Step S314: according to the measurement result a for reflecting the trapped charge amount and trap level2To composite insulator degree of aging
It is evaluated, a2Value is that 0-0.25 indicates that degree of aging is lighter, a2Value is that 0.25-0.5 indicates that degree of aging is general, a2Value is
0.5-0.75 indicates that degree of aging is heavier, a2Value is that 0.75-1 indicates that degree of aging is serious.
5. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that described to umbrella
Skirt sliced piece specimen utilize EO-1 hyperion spectrum analysis method, obtain test result the following steps are included:
Step S321: the high spectrum image that composite insulator umbrella skirt is sliced sample is obtained by EO-1 hyperion tester；
Step S322: pre-processing the high spectrum image of acquisition, chooses training sample；
Step S323: establishing composite insulator Ageing Model, Ageing Model quantified, the mark that obtained measurement result is 0 to 1
Amount, uses a3It indicates；
Step S324: the test result a quantitatively obtained according to composite insulator Ageing Model3To composite insulator degree of aging into
Row evaluation, a3Value is that 0-0.25 indicates that degree of aging is lighter, a3Value is that 0.25-0.5 indicates that degree of aging is general, a3Value is 0.5-
0.75 indicates that degree of aging is heavier, a3Value is that 0.75-1 indicates that degree of aging is serious.
6. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that described to umbrella
Skirt sliced piece specimen utilize surface charge density analytic approach, obtain test result the following steps are included:
Step S331: DC voltage is applied to full skirt sliced piece specimen using high pressure loading device；
Step S332: the surface charge of surface charge test device measurement full skirt sliced piece specimen is utilized；
Step S333: obtaining the average surface charge density of full skirt sliced piece specimen, and the scalar that obtained measurement result is 0 to 1 is used
a4It indicates；
Step S334: according to the test result a of the average surface charge density of full skirt sliced piece specimen4To composite insulator aging journey
Degree is evaluated, a4Value is that 0-0.25 indicates that degree of aging is lighter, a4Value is that 0.25-0.5 indicates that degree of aging is general, a4Value is
0.5-0.75 indicates that degree of aging is heavier, a4Value is that 0.75-1 indicates that degree of aging is serious.
7. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that the step
The comprehensive degree of aging end value L of composite insulator is calculated in S400, is four to composite insulator degree of aging grade classification
Grade: L value is that 0-0.25 indicates that degree of aging is lighter, and L value is that 0.25-0.5 indicates that degree of aging is general, and L value is 0.5-0.75
Indicate that degree of aging is heavier, L value is that 0.75-1 indicates that degree of aging is serious.
8. the method for comprehensive detection of composite insulator degree of aging according to claim 1, which is characterized in that the step
S100 thin rounded flakes sample be diameter be 25mm, the thin rounded flakes sample with a thickness of 1.2mm.
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-
2019
- 2019-03-29 CN CN201910247018.4A patent/CN109781614A/en active Pending
Non-Patent Citations (1)
| Title |
|---|
| 赵智大: "《高电压技术》", 31 May 1999, 北京：中国电力出版社 * |
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Application publication date: 20190521 |