CN106771895A - A kind of cable degradation detecting method based on magnetic field harmonics detection - Google Patents
A kind of cable degradation detecting method based on magnetic field harmonics detection Download PDFInfo
- Publication number
- CN106771895A CN106771895A CN201611050368.4A CN201611050368A CN106771895A CN 106771895 A CN106771895 A CN 106771895A CN 201611050368 A CN201611050368 A CN 201611050368A CN 106771895 A CN106771895 A CN 106771895A
- Authority
- CN
- China
- Prior art keywords
- cable
- frequency spectrum
- magnetic field
- magnetic
- signal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1272—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of cable, line or wire insulation, e.g. using partial discharge measurements
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/16—Spectrum analysis; Fourier analysis
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Locating Faults (AREA)
Abstract
The present invention relates to a kind of cable degradation detecting method based on magnetic field harmonics detection, it is characterised in that comprise the following steps：1) the magnetic signature frequency spectrum data storehouse of all kinds of cables is set up；2) gathered using noncontacting proximity sensor and quantify to be tested the magnetic field signal that cable sends in energization；3) through fft analysis process, by step 1) collection the isolated fundamental signal of magnetic field signal and each harmonic signal；4) according to step 3) fundamental signal and each harmonic signal that obtain, the ratio of each harmonic signal intensity and fundamental signal intensity is obtained, the ratio is the magnetic signature frequency spectrum of tested cable；5) by step 4) the magnetic signature frequency spectrum of tested cable and the magnetic signature frequency spectrum data in the magnetic signature frequency spectrum data storehouse of all kinds of cables that obtain contrasted, and obtains the operation conditions of tested cable.Compared with prior art, the present invention has non-contact type diagnosis, is not required to have a power failure detection, simple operation and other advantages.
Description
Technical field
The present invention relates to electromagnetism field, more particularly, to a kind of cable ageing management side based on magnetic field harmonics detection
Method.
Background technology
Recently as city net and the implementation of the upgrading of rural power grids, and because power cable is reliable, it is positioned at inferior
Shelter, is destroyed small by external force, and the chance for breaking down is less, power supply safety, will not be caused harm to the person, maintenance workload
It is small, the features such as frequently patrolling and examining is not required to, the amount of laying of power cable is more and more in power system.And in power cable operation
Harmonic frequency produced by magnetic field is high, and harmonic wave resistance ratio fundamental wave is made under the influence of the kelvin effect, kindred effect in cable conductor
Resistance is big, and the extension wire resistance loss that harmonic wave causes is non-negligible.For the transmission system using power cable, due to insulation
There is distribution capacity in medium, can also produce additional insulation dielectric loss.Cable with screen layer is as high-frequency harmonic
Presence, larger resistance loss, including eddy-current loss, circulation loss and the footpath by flowing through dielectric are caused in screen layer
The shielding resistance loss caused to capacity current.Harmonic wave is in addition to causing added losses, it is also possible to voltage waveform spike is occurred,
So as to accelerate the aging of cable insulation, cause the shelf depreciation of varnished insulation, also increase dielectric loss and increase with temperature rise, shorten
The service life of cable causes system sinusoidal waveforms to distort, produces the equipment and load of higher hamonic wave, as higher hamonic wave source or
Harmonic source.
(1) kelvin effect based on cable under harmonic condition, the loss P that can obtain cable is：
In formula, RDCIt is equivalent d.c. resistance in cable, I1It is fundamental current, InIt is nth harmonic effective current value, n>1, Im
It is m subharmonic effective current values, RACmIt is correspondence I in cablemEquivalent AC resistance.
It is ignored because very little is influenceed under mains frequency for kelvin effect, but about in more than 300Hz (that is, seven times
When harmonic wave and its above), kelvin effect will become more significantly to cause additional loss and cause overheat.
(2) mutually there is direct-to-ground capacitance mainly due to power cable is each in terms of cable, so electricity during operation on circuit
Capacitance current is unequal, and there is higher harmonic current again in circuit, if cable laying distance is more long, capacitance current is discrete
Property will be bigger.In high frequency, the electric capacity of cable determines the efficiency of transmission of cable, and capacitance current accounts for the phase of cable current-carrying capacity
Work as a part, and can reach with conductor current identical numerical value, make that the transmission range of cable reduces and reactive loss increases.
The electric capacity C of cable is：
In formula, G is geometrical geometric element, and n is cable number, and ε is the relative dielectric constant of insulating materials.
Capacitance charging current is IC：
IC=2 π fUC
In formula, f is frequency, and U is voltage.
The dielectric loss of cable is Wd：
Wd=2 π fU2Ctanδ
In formula, δ is dielectric loss angle.
When the voltage of higher hamonic wave adds to cable two ends, because cable insulation electric capacity ability to bear is limited, cable is easy to
Generation overload causes insulation damages；Higher hamonic wave causes cable in-fighting to increase, and electric cable heating shortens the service life of cable.
Mainly obtain each using Fast Fourier Transform (FFT) at this stage in power cable harmonic detecting on frequency spectrum detection
The coherent signal of subharmonic.But carry out harmonic detecting using the method and still there is problems with：Spectral aliasing, spectrum leakage
And fence effect etc..These factors cause signal parameter (frequency, the amplitude and phase) degree of accuracy for detecting not high, it is impossible to meet
The required precision of harmonic detecting.For above-mentioned reason, various countries experts and scholars propose many improved methods, its main improvement side
Method is as follows：
(1) modified ideal sampling frequency method.When the ratio of sampling interval length and sampling time interval is integer, frequency spectrum
Leakage phenomenon would not be present.What the method was exactly proposed using this principle.It is modified to each sampled point, obtains
Sampled value under ideal frequency.The method is not high to hardware requirement, and real-time is good, is adapted to on-line checking, but can only reduce
The leakage of half.
(2) method being modified to fft algorithm using windowed interpolation method.The method adds different window letters by selecting
Number reduces the error that fence effect is brought to reduce spectrum leakage by interpolation algorithm.It can effectively reduce leakage, suppression
Interfering between harmonic wave processed and the interference of other factorses, such that it is able to accurately detect the parameter value of each harmonic.
(3) synchronized sampling method.Realized including hardware and software two ways.Synchronous sampling by software method is by measurement signal week
Phase adjusts the sampling interval in good time, so that signal frequency is synchronous with sample frequency holding；Hardware based synchronized sampling method
Synchronized sampling is realized using the hardware unit such as zero-crossing comparator or digital phase locking unit.Software approach application flexibly, is examined
High precision is surveyed, but real-time aspect cannot well ensure that hardware approach is by optimizing sampling period or weekly sampling number
Carry out approximation signal frequency, real-time is preferable, but accuracy of detection can be affected.
(4) quasi-synchronuous sampling method.The method is set up on the basis of synchronized sampling, and sampled point and use are increased by appropriate
Corresponding algorithm carries out the treatment of data.Harmonic detecting is carried out using the method, can effectively suppress harmonic wave to measurement parameter
Influence, while the error for reducing non-Complete Synchronization and producing, accuracy of detection is higher, but the method needs data volume to be processed
Very big, real-time aspect is not good enough, and there is larger phase error.
The content of the invention
The purpose of the present invention is exactly to provide a kind of based on magnetic field harmonics for the defect for overcoming above-mentioned prior art to exist
The cable degradation detecting method of detection, with non-contact type diagnosis, is not required to have a power failure detection, simple operation and other advantages.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of cable degradation detecting method based on magnetic field harmonics detection is comprised the following steps：
1) the magnetic signature frequency spectrum data storehouse of all kinds of cables is set up；
2) gathered using noncontacting proximity sensor and quantify to be tested the magnetic field signal that cable sends in energization；
3) through fft analysis process, by step 1) collection the isolated fundamental signal of magnetic field signal and each harmonic signal；
4) according to step 3) fundamental signal and each harmonic signal that obtain, obtain each harmonic signal intensity and believe with fundamental wave
The ratio of number intensity, the ratio is the magnetic signature frequency spectrum of tested cable；
5) by step 4) the magnetic signature frequency spectrum data storehouse of the magnetic signature frequency spectrum of tested cable that obtains and all kinds of cables
In magnetic signature frequency spectrum data contrasted, obtain the operation conditions of tested cable, the degree aging for evaluating cable.
The noncontacting proximity sensor is aligned and is close to the first and last end of tested cable and measures successively.
The step 5) also include step 6 afterwards)：If the operation conditions of the tested cable is abnormal, according to first and last end according to
The secondary magnetic field signal for measuring judges to obtain the position of abnormity point.
The step 6) in the magnetic field signal that is measured successively according to first and last end judge the side of the position for obtaining abnormity point
Method is specially：
601：The magnetic field signal measured successively according to first and last end obtains the magnetic signature frequency spectrum at first and last end；
602：The numerical values recited of the magnetic signature frequency spectrum at contrast first and last end, two-section cut cable is divided into by tested cable,
The corresponding cut cable in one end for selecting the numerical value of magnetic signature frequency spectrum bigger；
603：Whether the length of cut cable is judged less than setting value, if so, then the cut cable is the position of abnormity point, if
It is no, using cut cable as new by side object, jump procedure 601.
Magnetic signature frequency spectrum data in the magnetic signature frequency spectrum data storehouse is categorized as：Normal magnetic field characteristic frequency spectrum data
Class and anomalous field characteristic frequency spectrum data class, the anomalous field characteristic frequency spectrum data class are categorized as：Protective layer sublayer boundary lacks
Subclass, screen layer sublayer boundary defect subclass, protective layer is fallen into damage subclass, insulating barrier and contain containing foreign matter or damage subclass, screen layer
Air gap subclass, conductor damage subclass.
The operation conditions of the tested cable is categorized as normal condition and exception according to magnetic signature frequency spectrum data storehouse correspondence
Situation, the unusual condition is protective layer sublayer boundary defect unusual condition, screen layer sublayer boundary defect unusual condition, protection
Layer is containing foreign matter or damages unusual condition, screen layer damage unusual condition, insulating barrier unusual condition containing air gap, the abnormal shape of conductor damage
One or more in condition.
Compared with prior art, the present invention has advantages below：
1st, using noncontacting proximity sensor realize non-contact type diagnose, including power cable aging analysis and damage inspection
Survey, long-distance cable, the cable that is blocked, submerged cable etc. can be detected, it is practical.
2nd, using magnetic field signal as detection signal, the detection that has a power failure is not required to, on-line checking can be carried out to 24 hours operational outfits,
And test is not influenceed by cable itself load variations.
3rd, cable aging analysis step operation is simple, quickly generates detailed report.
4th, suitable for simultaneously early warning, guide maintenance of pinpointing the problems in advance, it is to avoid burst accident.
5th, the data measured successively using the first and last end of tested cable, realize the acquisition of the position of abnormity point, measurement
Number of times is few, and Data duplication utilization rate is high, reduces duplicate measurements, and data result obtains fast and accurate.
6th, it is various by magnetic signature frequency spectrum data disaggregated classification, realizes the inspection of different types of cable integrated operation state
Survey, overcome the defect of single-measurement result or rough error measurement result.
Brief description of the drawings
Fig. 1 is the flow chart of cable degradation detecting method of the present invention；
Fig. 2 is the applied environment schematic diagram of cable degradation detecting method of the present invention；
Fig. 3 is waveform processing schematic diagram；
Fig. 4 is cable internal flaw and magnetic field dependence schematic diagram.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention
Premised on implemented, give detailed implementation method and specific operating process, but protection scope of the present invention is not limited to
Following embodiments.
Electric energy in the ideal situation, can be transported to another place, its energy by power cable with 100% from one place
Conveying capacity be 100%, and in the middle of actual motion, due to by cable running environment, construction quality and external disturbance etc. because
The influence of element, can not reach 100% conveying capacity.After cable occurs aging, its electric energy will occur in course of conveying
Energy loss, for power cable generally speaking, the energy reduction after the conversion of its useful energy, Parameters variation or transmission；And
It is consumed in and overcomes the amount of work of all parts energy loss to increase.The generation of higher hamonic wave and the aging of power cable and available energy
There is one-to-one relation in the loss of amount.And harmonic energy has relation with the equipment components natural frequency of vibration and degree of aging.When
When equipment occurs balanced aging, the symptoms of aging such as equipment heating are presented as, when a certain part occurs big energy loss, pointed out
Component malfunction or failure symptom representated by the frequency.
As shown in Fig. 2 this method gathers and quantifies the electromagnetism of the higher hamonic wave that cable sends using noncontacting proximity sensor
Ripple, by after fft analysis, using expert system, being analyzed by contrasting the same section of harmonic spectrum changing features at cable two ends
This section of status information of cable, A is band testing equipment in Fig. 2, and B is the data acquisition device with noncontacting proximity sensor, and C is band
There is the host computer of expert system, D is the electromagnetic wave of collection.Can intuitively react that cable is aging and incipient fault, and can
Accomplish Incipient Fault Diagnosis and the analysis of this kind equipment.Because the characteristic quantity that the method is obtained is the ratio of each harmonic and fundamental wave
Relation, therefore need not simultaneously be measured under identical load rate, greatly facilitate onsite application.The harmonic spectrum that scene measures is special
Levy by with database in all kinds of cable spectrum characteristics (including detection data under the ecotopia of laboratory or scene in the past
The historical data of detection) contrasted, finally it is inferred to the actual state of surveyed cable.
Original detectable substance reason amount is energy (joule) in detection process, and power (watt) is obtained after being calculated with sample time,
And power contrast degree is obtained by software processing, its unit is the ratio of percentage (%), i.e. higher harmonic components and fundametal compoment
Value.The data acquisition range of the method generally includes 2-40 subharmonic.Recycle harmonic spectrum that time-domain signal is converted into frequency domain
Divided.The purpose of spectrum analysis is, complicated time history waveform, to be decomposed into by Fourier transformation some single humorous
Wave component is studied, obtaining the frequency structure and each harmonic wave and phase information of signal.Such as try to achieve each in Dynamic Signal
Frequency content and frequency distribution scope, obtain the amplitude distribution and Energy distribution of each frequency content, so as to obtain main amplitude
With the frequency values of Energy distribution.
To function f (t), if its absolute integrable, i.e. only jump, only limited extreme value, and it is full
Sufficient dirichlet series condition, then can carry out Fourier transformation to it.If a waveform can resolve into multiple different frequencies
Sine wave sum, and the sine wave linear combination of these different frequencies can recover original signal, then Fu of this waveform
In leaf transformation be assured that.Here it is in this method, the basis of harmonic detecting is carried out using FFT.Mathematically, Fourier
Conversion (FFT) is represented by：
The f (t) of above formula is given, it is believed that it can be the waveform for being broken down into multiple SIN function sums.Claim
It is the Fourier transformation of f (t), is usually denoted asF in formula is referred to as Fourier's operator.If λ is seen
Into frequency variable, t regards time variable as,Thus referred to as spectral function, its mould is referred to as frequency spectrum, and frequency spectrum function is illustrated respectively
Deal shared by frequency waveform.Therefore, the frequency spectrum of each waveform can be obtained by FFT computings, according to the frequency spectrum of waveform, it is possible to
Determine the frequency content contained in signal.
Processing mode is as shown in Figure 3.
Then a kind of cable degradation detecting method based on magnetic field harmonics detection is comprised the following steps：
1) the magnetic signature frequency spectrum data storehouse of all kinds of cables is set up；
2) gathered using noncontacting proximity sensor and quantify to be tested the magnetic field signal that cable sends in energization, it is specifically non-to connect
Touch sensor alignment is simultaneously measured successively near the first and last end of tested cable；
3) through fft analysis process, by step 1) collection the isolated fundamental signal of magnetic field signal and each harmonic signal；
4) according to step 3) fundamental signal and each harmonic signal that obtain, obtain each harmonic signal intensity and believe with fundamental wave
The ratio of number intensity, the ratio is the magnetic signature frequency spectrum of tested cable；
5) by step 4) the magnetic signature frequency spectrum data storehouse of the magnetic signature frequency spectrum of tested cable that obtains and all kinds of cables
In magnetic signature frequency spectrum data contrasted, obtain the operation conditions of tested cable.
If 6) operation conditions of the tested cable is abnormal, the magnetic field signal measured successively according to first and last end judges to obtain
Take the position of abnormity point.
Step 6) in the magnetic field signal that is measured successively according to first and last end judge the method tool of the position for obtaining abnormity point
Body is：
601：The magnetic field signal measured successively according to first and last end obtains the magnetic signature frequency spectrum at first and last end；
602：The numerical values recited of the magnetic signature frequency spectrum at contrast first and last end, two-section cut cable is divided into by tested cable,
The corresponding cut cable in one end for selecting the numerical value of magnetic signature frequency spectrum bigger；
603：Whether the length of cut cable is judged less than setting value, if so, then the cut cable is the position of abnormity point, if
It is no, using cut cable as new by side object, jump procedure 601.
Magnetic signature frequency spectrum data in magnetic signature frequency spectrum data storehouse is categorized as：Normal magnetic field characteristic frequency spectrum data class and
Anomalous field characteristic frequency spectrum data class, anomalous field characteristic frequency spectrum data class is categorized as：Protective layer sublayer boundary defect subclass, screen
Cover a layer sublayer boundary defect subclass, protective layer containing foreign matter or damage subclass, screen layer damage subclass, insulating barrier subclass containing air gap,
Conductor damages subclass.
The operation conditions of tested cable is categorized as normal condition and unusual condition according to magnetic signature frequency spectrum data storehouse correspondence,
Unusual condition is protective layer sublayer boundary defect unusual condition, screen layer sublayer boundary defect unusual condition, protective layer containing foreign matter
Or damage unusual condition, screen layer are damaged in unusual condition, insulating barrier unusual condition containing air gap, conductor damage unusual condition one
Plant or various.
As shown in figure 4, power cable includes conductor, insulating barrier, screen layer and protective layer successively from the inside to the outside, in electric power electricity
When cable passes through electric current I, because of different abnormalities, different magnetic fluxs and corresponding electric current can be produced, the inventive method is then utilized
This principle obtains magnetic signature frequency spectrum data storehouse, is used to judge the running status of cable, and specifically, protective layer sublayer boundary lacks
Fall into the corresponding equivalent magnetic flux Φ of unusual conditionf, equivalent magnetic flux ΦfOn the profile of protective layer internal layer, and with being overheated because of defect
And the equivalent magnetic flux Φ for producingtWith equivalent current It1, the corresponding equivalent magnetic flux Φ of screen layer sublayer boundary defect unusual conditione,
Equivalent magnetic flux ΦeOn the profile of screen layer internal layer, protective layer is containing foreign matter or damages the corresponding equivalent magnetic flux Φ of unusual conditiond,
Equivalent magnetic flux ΦdOn profile between protective layer ectonexine, screen layer damages the corresponding equivalent magnetic flux Φ of unusual conditionc, etc.
Effect magnetic flux ΦcOn profile between screen layer ectonexine, and equivalent current Ic1, Ic2, insulating barrier gassiness are produced because damaging
The corresponding equivalent magnetic flux Φ of gap unusual conditionb, equivalent magnetic flux ΦbOn profile between insulating barrier ectonexine, conductor damages different
The corresponding equivalent magnetic flux Φ of normal situationa, equivalent magnetic flux ΦaOn profile between screen layer ectonexine, and because damaging generation etc.
Effect electric current Ia1, Ia2.
Claims (6)
1. it is a kind of based on magnetic field harmonics detection cable degradation detecting method, it is characterised in that comprise the following steps：
1) the magnetic signature frequency spectrum data storehouse of all kinds of cables is set up；
2) gathered using noncontacting proximity sensor and quantify to be tested the magnetic field signal that cable sends in energization；
3) through fft analysis process, by step 1) collection the isolated fundamental signal of magnetic field signal and each harmonic signal；
4) according to step 3) fundamental signal and each harmonic signal that obtain, obtain each harmonic signal intensity strong with fundamental signal
The ratio of degree, the ratio is the magnetic signature frequency spectrum of tested cable；
5) by step 4) in the magnetic signature frequency spectrum of tested cable that obtains and the magnetic signature frequency spectrum data storehouse of all kinds of cables
Magnetic signature frequency spectrum data is contrasted, and obtains the operation conditions of tested cable.
2. it is according to claim 1 it is a kind of based on magnetic field harmonics detection cable degradation detecting method, it is characterised in that institute
State noncontacting proximity sensor and be aligned and be close to the first and last end of tested cable and measure successively.
3. it is according to claim 2 it is a kind of based on magnetic field harmonics detection cable degradation detecting method, it is characterised in that institute
State step 5) also include step 6 afterwards)：If the operation conditions of the tested cable is abnormal, measured successively according to first and last end
Magnetic field signal judge obtain abnormity point position.
4. it is according to claim 3 it is a kind of based on magnetic field harmonics detection cable degradation detecting method, it is characterised in that institute
State step 6) in the magnetic field signal that is measured successively according to first and last end judge that the method for the position for obtaining abnormity point is specially：
601：The magnetic field signal measured successively according to first and last end obtains the magnetic signature frequency spectrum at first and last end；
602：The numerical values recited of the magnetic signature frequency spectrum at contrast first and last end, two-section cut cable, selection are divided into by tested cable
The bigger corresponding cut cable in one end of the numerical value of magnetic signature frequency spectrum；
603：Whether the length of cut cable is judged less than setting value, if so, then the cut cable is the position of abnormity point, if it is not, will
Cut cable is as new by side object, jump procedure 601.
5. it is according to claim 1 it is a kind of based on magnetic field harmonics detection cable degradation detecting method, it is characterised in that institute
The magnetic signature frequency spectrum data stated in magnetic signature frequency spectrum data storehouse is categorized as：Normal magnetic field characteristic frequency spectrum data class and abnormal magnetic
Field characteristic frequency spectrum data class, the anomalous field characteristic frequency spectrum data class is categorized as：Protective layer sublayer boundary defect subclass, shielding
Layer sublayer boundary defect subclass, protective layer damage subclass, insulating barrier subclass containing air gap, lead containing foreign matter or damage subclass, screen layer
Bulk damage subclass.
6. it is according to claim 5 it is a kind of based on magnetic field harmonics detection cable degradation detecting method, it is characterised in that institute
The operation conditions for stating tested cable is categorized as normal condition and unusual condition according to magnetic signature frequency spectrum data storehouse correspondence, described different
Normal situation be protective layer sublayer boundary defect unusual condition, screen layer sublayer boundary defect unusual condition, protective layer containing foreign matter or
Damage unusual condition, screen layer and damage one kind that unusual condition, insulating barrier unusual condition containing air gap, conductor are damaged in unusual condition
Or it is various.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611050368.4A CN106771895A (en) | 2016-11-25 | 2016-11-25 | A kind of cable degradation detecting method based on magnetic field harmonics detection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611050368.4A CN106771895A (en) | 2016-11-25 | 2016-11-25 | A kind of cable degradation detecting method based on magnetic field harmonics detection |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106771895A true CN106771895A (en) | 2017-05-31 |
Family
ID=58910581
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611050368.4A Pending CN106771895A (en) | 2016-11-25 | 2016-11-25 | A kind of cable degradation detecting method based on magnetic field harmonics detection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106771895A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109061401A (en) * | 2018-11-02 | 2018-12-21 | 国网山西省电力公司电力科学研究院 | A kind of method for building up of electric cable stoppage assessment system |
| CN109116191A (en) * | 2018-11-02 | 2019-01-01 | 国网山西省电力公司电力科学研究院 | A kind of test of electric cable stoppage higher hamonic wave and detection system |
| CN109239550A (en) * | 2018-09-04 | 2019-01-18 | 国网山东省电力公司青岛供电公司 | A kind of line insulation situation judgment method |
| CN109272257A (en) * | 2018-11-02 | 2019-01-25 | 国网山西省电力公司电力科学研究院 | A kind of electric cable stoppage appraisal procedure and system based on higher hamonic wave database |
| CN110543965A (en) * | 2019-07-19 | 2019-12-06 | 中国工商银行股份有限公司 | Baseline prediction method, baseline prediction device, electronic apparatus, and medium |
| CN111044860A (en) * | 2019-12-19 | 2020-04-21 | 国网北京市电力公司 | Method and device for analyzing insulation defect of cable body, storage medium and processor |
| CN111722022A (en) * | 2020-05-09 | 2020-09-29 | 上海达铭科技有限公司 | Cable path detection method based on weak magnetic signal measurement |
| EP3839524A1 (en) * | 2019-12-16 | 2021-06-23 | E.On Se | Method, device and arrangement for monitoring alternating current electric apparatuses |
| CN113050628A (en) * | 2021-03-05 | 2021-06-29 | 国网四川省电力公司技能培训中心 | Automatic tracking system and method for cable inspection |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1032239A (en) * | 1987-08-07 | 1989-04-05 | 三井石油化学工业株式会社 | The detection method of state of insulation and device |
| CN1748152A (en) * | 2003-02-07 | 2006-03-15 | 阿泰克株式会社 | Harmonic diagnosing method for electric facility |
| CN101706527A (en) * | 2009-10-30 | 2010-05-12 | 西安交通大学 | Method for detecting arc faults based on time-frequency characteristics of high-frequency current component |
| CN102565631A (en) * | 2012-02-23 | 2012-07-11 | 广东电网公司电力科学研究院 | Method for positioning fault region of inter-regional transmission line based on distribution type monitoring |
| CN103499775A (en) * | 2013-08-29 | 2014-01-08 | 国家电网公司 | Method for detecting XLPE insulation degree based on partial discharge frequency properties |
| CN103760467A (en) * | 2014-01-27 | 2014-04-30 | 西安兴汇电力科技有限公司 | Method for inspecting single-phase earth fault point of power distribution network |
| CN103969556A (en) * | 2014-03-14 | 2014-08-06 | 上海交通大学 | Insulation electrified detection device for cable accessories |
| CN104090214A (en) * | 2014-07-31 | 2014-10-08 | 成都高斯电子技术有限公司 | Cable fault detection and aging analysis method |
| CN104849628A (en) * | 2015-04-24 | 2015-08-19 | 国网四川省电力公司电力科学研究院 | Fault analysis detection method for cable accessory |
| CN105203936A (en) * | 2015-10-26 | 2015-12-30 | 云南电网有限责任公司电力科学研究院 | Method for determining power cable partial discharge defect type based on spectral analysis |
-
2016
- 2016-11-25 CN CN201611050368.4A patent/CN106771895A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1032239A (en) * | 1987-08-07 | 1989-04-05 | 三井石油化学工业株式会社 | The detection method of state of insulation and device |
| CN1748152A (en) * | 2003-02-07 | 2006-03-15 | 阿泰克株式会社 | Harmonic diagnosing method for electric facility |
| CN101706527A (en) * | 2009-10-30 | 2010-05-12 | 西安交通大学 | Method for detecting arc faults based on time-frequency characteristics of high-frequency current component |
| CN102565631A (en) * | 2012-02-23 | 2012-07-11 | 广东电网公司电力科学研究院 | Method for positioning fault region of inter-regional transmission line based on distribution type monitoring |
| CN103499775A (en) * | 2013-08-29 | 2014-01-08 | 国家电网公司 | Method for detecting XLPE insulation degree based on partial discharge frequency properties |
| CN103760467A (en) * | 2014-01-27 | 2014-04-30 | 西安兴汇电力科技有限公司 | Method for inspecting single-phase earth fault point of power distribution network |
| CN103969556A (en) * | 2014-03-14 | 2014-08-06 | 上海交通大学 | Insulation electrified detection device for cable accessories |
| CN104090214A (en) * | 2014-07-31 | 2014-10-08 | 成都高斯电子技术有限公司 | Cable fault detection and aging analysis method |
| CN104849628A (en) * | 2015-04-24 | 2015-08-19 | 国网四川省电力公司电力科学研究院 | Fault analysis detection method for cable accessory |
| CN105203936A (en) * | 2015-10-26 | 2015-12-30 | 云南电网有限责任公司电力科学研究院 | Method for determining power cable partial discharge defect type based on spectral analysis |
Non-Patent Citations (3)
| Title |
|---|
| ALBERT_QU: "谐波法设备状态数据诊断系统", 《百度文库》 * |
| XMWJE151: "电力系统", 《百度文库》 * |
| 戴铭: "10kV地下电缆早期故障检测与识别方法探讨", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109239550B (en) * | 2018-09-04 | 2020-11-27 | 国网山东省电力公司青岛供电公司 | Line insulation condition judgment method |
| CN109239550A (en) * | 2018-09-04 | 2019-01-18 | 国网山东省电力公司青岛供电公司 | A kind of line insulation situation judgment method |
| CN109116191A (en) * | 2018-11-02 | 2019-01-01 | 国网山西省电力公司电力科学研究院 | A kind of test of electric cable stoppage higher hamonic wave and detection system |
| CN109272257A (en) * | 2018-11-02 | 2019-01-25 | 国网山西省电力公司电力科学研究院 | A kind of electric cable stoppage appraisal procedure and system based on higher hamonic wave database |
| CN109061401A (en) * | 2018-11-02 | 2018-12-21 | 国网山西省电力公司电力科学研究院 | A kind of method for building up of electric cable stoppage assessment system |
| CN110543965A (en) * | 2019-07-19 | 2019-12-06 | 中国工商银行股份有限公司 | Baseline prediction method, baseline prediction device, electronic apparatus, and medium |
| CN110543965B (en) * | 2019-07-19 | 2023-01-06 | 中国工商银行股份有限公司 | Baseline prediction method, baseline prediction device, electronic apparatus, and medium |
| WO2021121821A1 (en) * | 2019-12-16 | 2021-06-24 | E.On Se | Method, device and arrangement for monitoring alternating current electric apparatuses |
| EP3839524A1 (en) * | 2019-12-16 | 2021-06-23 | E.On Se | Method, device and arrangement for monitoring alternating current electric apparatuses |
| US11821962B2 (en) | 2019-12-16 | 2023-11-21 | E.On Se | Method, device and arrangement for monitoring alternating current electric apparatuses |
| CN111044860A (en) * | 2019-12-19 | 2020-04-21 | 国网北京市电力公司 | Method and device for analyzing insulation defect of cable body, storage medium and processor |
| CN111722022A (en) * | 2020-05-09 | 2020-09-29 | 上海达铭科技有限公司 | Cable path detection method based on weak magnetic signal measurement |
| CN111722022B (en) * | 2020-05-09 | 2023-02-14 | 上海达铭科技有限公司 | Cable path detection method based on weak magnetic signal measurement |
| CN113050628A (en) * | 2021-03-05 | 2021-06-29 | 国网四川省电力公司技能培训中心 | Automatic tracking system and method for cable inspection |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106771895A (en) | A kind of cable degradation detecting method based on magnetic field harmonics detection | |
| CN104090214B (en) | A kind of Cable fault examination and aging analysis method | |
| CN104937427B (en) | Monitor the method and system of cable status | |
| Yao et al. | Transformer winding deformation diagnostic system using online high frequency signal injection by capacitive coupling | |
| CN104714155A (en) | Detection and evaluation device and method for partial discharge of direct current XLPE cables | |
| CN109870613B (en) | Transient voltage disturbance-based transformer bushing dielectric loss live detection method and system | |
| CN107632241A (en) | A kind of apparatus and method for testing paper oil insulation partial discharge characteristic | |
| EP2750258B1 (en) | Methods for locating ground faults and insulation degradation condition in energy conversion systems | |
| CN110726908A (en) | Insulation aging monitoring method for converter transformer | |
| CN105223483A (en) | A kind of DC transmission engineering insulator chain defect online detection method and device | |
| CN109521391B (en) | Device and method for detecting turn-to-turn short circuit fault of generator voltage transformer winding | |
| Huang et al. | Research on partial discharge monitoring system of switchgear based on wireless distributed TEV sensors | |
| CN103135035A (en) | Transformer winding state diagnosis method | |
| Nussbaumer et al. | Online detection of insulation degradation in inverter fed drive systems based on high frequency current sampling | |
| Chen et al. | Comparative study on partial discharge characteristics of seven accessory defects under four on-site testing voltages of a 10-kV cable line | |
| Carvalho et al. | Virtual instrumentation for high voltage power capacitors assessment through capacitance monitoring and acoustic partial discharge detection | |
| Li et al. | Partial discharge monitoring system for PD characteristics of typical defects in GIS using UHF method | |
| Artale et al. | DC series arc faults in PV systems. Detection methods and experimental characterization | |
| CN209606602U (en) | The detection device of generator voltage mutual inductor winding interturn short-circuit failure | |
| CN112214950B (en) | Capacitor capacity abnormity detection method | |
| RU2532762C1 (en) | Method to diagnose and assess residual resource of ac electric drives | |
| Probst et al. | Using capacitive electric field sensors to measure transient overvoltages: A case study | |
| Sun et al. | Research on diagnosis technology of insulation performance of high voltage electrical equipment | |
| Li et al. | Survey of frequency response analysis on winding deformation of transformers | |
| US20240319256A1 (en) | System and method for analysis of the insulation condition of an electrical machine by the phases, and, storage media |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170531 |
|
| RJ01 | Rejection of invention patent application after publication |