CN109884483A - Insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device - Google Patents
Insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device Download PDFInfo
- Publication number
- CN109884483A CN109884483A CN201910159875.9A CN201910159875A CN109884483A CN 109884483 A CN109884483 A CN 109884483A CN 201910159875 A CN201910159875 A CN 201910159875A CN 109884483 A CN109884483 A CN 109884483A
- Authority
- CN
- China
- Prior art keywords
- signal
- tube type
- insulating tube
- imf
- shelf depreciation
- 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
- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000012544 monitoring process Methods 0.000 title claims abstract description 11
- 230000003750 conditioning effect Effects 0.000 claims abstract description 25
- 230000008878 coupling Effects 0.000 claims abstract description 20
- 238000010168 coupling process Methods 0.000 claims abstract description 20
- 238000005859 coupling reaction Methods 0.000 claims abstract description 20
- 238000012545 processing Methods 0.000 claims description 47
- 238000006243 chemical reaction Methods 0.000 claims description 36
- 238000000354 decomposition reaction Methods 0.000 claims description 31
- 238000004891 communication Methods 0.000 claims description 23
- 230000003044 adaptive effect Effects 0.000 claims description 18
- 230000006870 function Effects 0.000 claims description 17
- 230000009467 reduction Effects 0.000 claims description 15
- 238000011946 reduction process Methods 0.000 claims description 15
- 238000010276 construction Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 4
- 230000008859 change Effects 0.000 claims description 3
- 230000007547 defect Effects 0.000 abstract description 8
- 238000012360 testing method Methods 0.000 abstract description 7
- 238000009413 insulation Methods 0.000 abstract description 6
- 238000001514 detection method Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000009795 derivation Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000011478 gradient descent method Methods 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000002045 lasting effect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Landscapes
- Testing Relating To Insulation (AREA)
Abstract
The present invention provides a kind of insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device, is coupled from tested insulating tube type busbar by acoustics coupling sensor and obtains original coupled signal；The conditionings means coupled signal that obtains on tested insulating tube type busbar that treated such as denoised, amplified to original coupled signal；Blind source separating is carried out to treated the coupled signal by software algorithm, excludes the interference of work on the spot noise and other noises to signal, the accurate local discharge signal obtained on insulating tube type busbar.The present invention can effectively and timely come out the shelf depreciation defects detection of insulating tube type busbar, provide more efficiently sensitive method for the test and judge of the quality of insulation of insulating tube type busbar.
Description
Technical field
The present invention relates to the partial discharge monitoring field of insulating tube type busbar, specifically a kind of insulating tube type busbar is locally put
Electroacoustics on-line monitoring method and device.
Background technique
According to existing insulating tube type busbar completion test standard, insulating tube type busbar route, should be able to after commissioning test
Biggish defect caused by detecting due to transport and scene laying, but there are still some after overtesting, is putting into operation soon
Just the case punctured.Main cause is the insulation defect that commissioning test cannot effectively detect insulating tube type busbar route, or
Say it is potential insulation defect, and route is after running for a period of time, these defects are gradually expanded, and recessive defect is gradually dominant
Change, has eventually led to the breakdown of insulating tube type busbar route.And the monitoring of shelf depreciation is timely discovery potential faults and prediction
Service life and the important means for ensureing insulating tube type busbar line security reliability service, are one of most effective means.
It is mainly at present supercritical ultrasonics technology and hyperfrequency method, the detection of hyperfrequency method to the measurement of partial discharge of insulating tube type busbar
Frequency range it is relatively high, signal decaying it is also bigger, therefore to the selection of test point have it is higher requirement and cost it is higher；Supercritical ultrasonics technology
Structure is more complicated and experience to testing staff etc. is more demanding.The insulating layer of insulating tube type busbar appearance is to high frequency waves, sound
The absorbability of wave is stronger, and which results in high frequency waves in original signal substantially to decay, this reason limit ultrasonic method and
The popularization of hyperfrequency method.
Summary of the invention
The problem to be solved in the present invention is the on-line monitoring method and device of a kind of cable local discharge, solves existing insulation
There are many extraneous strong-electromagnetic field interference source in environment locating for tube type bus route, and local discharge signal amount is faint, amplitude very little, pole
The problem of easily being flooded by ambient noise, and the original waveform distortion of collected signal after processing, being easy to cause erroneous judgement.
The technical solution of the present invention is as follows:
A kind of insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device, including acoustics coupling sensor, the first signal
Conditioning circuit, analog-to-digital conversion and signal processing circuit, background terminal；
The acoustics coupling sensor is mounted on each insulating sleeve and insulating tube type busbar on insulating tube type busbar route
The outer surface of terminal；
First signal conditioning circuit and the acoustics coupling sensor communicate to connect, for acoustics coupling sensor
The original signal being coupled to is denoised, amplifies conditioning, obtain noisy shelf depreciation acoustic emission signal be sent into analog-to-digital conversion and
Signal processing circuit；
The analog-to-digital conversion and signal processing circuit are for carrying out set experience to noisy shelf depreciation acoustic emission signal
Mode decomposition and wavelet adaptive threshold noise reduction process, the local discharge signal after obtaining noise reduction；
The background terminal and the analog-to-digital conversion and signal processing circuit communicate to connect, and being used for will be through analog-to-digital conversion and letter
The signal data construction feature vector of the local discharge signal obtained after number processing circuit processes, is transported for the first time with insulating tube type busbar
Collected basic data analyzes when row, to make corresponding state evaluation.
Further, the signal data construction feature vector includes phase, number of pulses and Energy-Entropy.
It further, further include leakage current sensor, second signal conditioning circuit, leakage current sensor passes through second
Signal conditioning circuit is connect with analog-to-digital conversion and signal processing circuit, includes signal acquisition in analog-to-digital conversion and signal processing circuit
Processing module, the sampling trigger signal of signal acquisition process module are power frequency zero cross signal, and leakage current sensor obtains power frequency
The phase of signal obtains power frequency zero cross signal after the processing of second signal conditioning circuit.
Further, the analog-to-digital conversion and signal processing circuit are analog-to-digital conversion and signal processing circuit.
Further, analog-to-digital conversion and signal processing circuit are connect with first communication module, and background terminal is communicated with second
Module connection, first communication module are communicatively coupled with second communication module.
Further, the analog-to-digital conversion and signal processing circuit are used to carry out noisy shelf depreciation acoustic emission signal
Gather empirical mode decomposition and wavelet adaptive threshold noise reduction process, the local discharge signal after obtaining noise reduction is specific to walk
It is rapid as follows:
Step 1: carrying out set empirical mode decomposition to noisy shelf depreciation acoustic emission signal；
Step 2: extracting each intrinsic mode functions IMF, and the energy of original energy and each IMF is calculated, simultaneously
The related coefficient for calculating each IMF and original signal, comprehensively considers energy accounting and related coefficient size carries out the screening of IMF component
Reconstruct, obtains reconstruction signal；
Step 3: wavelet adaptive threshold noise reduction process is carried out to reconstruction signal, the local discharge signal after obtaining noise reduction.
Further, the step 1 specifically:
1) it determines the amplitude n of the white noise of operation times M and addition, defines the decomposition number that m is EMD, M is operation time
Number, n are the amplitude for the white noise being added, and m meets 1≤m≤M, by the white noise signal n of different amplitudesm(t) it is added to wait divide
It solves in signal x (t), obtains new signal x to be decomposedm(t), i.e.,
xm(t)=x (t)+nm(t) (1)
2) to the signal x after addition white noisem(t) EMD decomposition is carried out, obtains several intrinsic mode functions (IMF) components,
It is indicated with Cmi, i.e., i-th of the IMF component obtained after being decomposed after m-th addition white noise signal by EMD；
3) m successively takes 1 to M, and iteration carries out step 1) and 2), the available M group IMF vector sequence decomposited, i.e.,
{Cmi}；
4) it averages to the M group IMF component decomposited, eliminates white noise and obtain measured signal simultaneously by EEMD decomposition
Each rank IMF afterwards, definitionAs i-th of IMF component of the EEMD measured signal decomposed, i.e.,
The ENERGY E of IMF and related coefficient calculation formula are as follows in the step 2, i.e.,
E=∑ x2(n) (3)
A kind of insulating tube type busbar shelf depreciation acoustics on-line monitoring method, includes the following steps:
The original signal that first signal conditioning circuit is coupled to acoustics coupling sensor is denoised, amplifies conditioning, is obtained
Analog-to-digital conversion and signal processing circuit are sent into noisy shelf depreciation acoustic emission signal；
Analog-to-digital conversion and signal processing circuit carry out set empirical mode decomposition to noisy shelf depreciation acoustic emission signal
And wavelet adaptive threshold noise reduction process, the local discharge signal after obtaining noise reduction；
Background terminal is by the signal data construction feature vector of local discharge signal, when running for the first time with insulating tube type busbar
Collected basic data analyzes, to make corresponding state evaluation.
Further, the analog-to-digital conversion and signal processing circuit gather noisy shelf depreciation acoustic emission signal
Empirical mode decomposition and wavelet adaptive threshold noise reduction process, steps are as follows for the local discharge signal body after obtaining noise reduction:
Step 1: carrying out set empirical mode decomposition to noisy shelf depreciation acoustic emission signal；
Step 2: extracting each intrinsic mode functions IMF, and the energy of original energy and each IMF is calculated, simultaneously
The related coefficient for calculating each IMF and original signal, comprehensively considers energy accounting and related coefficient size carries out the screening of IMF component
Reconstruct, obtains reconstruction signal；
Step 3: wavelet adaptive threshold noise reduction process is carried out to reconstruction signal, the local discharge signal after obtaining noise reduction.
Further, the step 1 specifically:
1) it determines the amplitude n of the white noise of operation times M and addition, defines the decomposition number that m is EMD, M is operation time
Number, n are the amplitude for the white noise being added, and m meets 1≤m≤M, by the white noise signal n of different amplitudesm(t) it is added to wait divide
It solves in signal x (t), obtains new signal x to be decomposedm(t), i.e.,
xm(t)=x (t)+nm(t) (1)
2) to the signal x after addition white noisem(t) EMD decomposition is carried out, obtains several intrinsic mode functions IMF component, is used
Cmi indicates, i.e., is added after white noise signal through obtained i-th of IMF component after EMD decomposition for m-th；
3) m successively takes 1 to M, and iteration carries out step 1) and 2), the available M group IMF vector sequence decomposited, i.e.,
{Cmi}；
4) it averages to the M group IMF component decomposited, eliminates white noise and obtain measured signal simultaneously by EEMD decomposition
Each rank IMF afterwards, definitionAs i-th of IMF component of the EEMD measured signal decomposed, i.e.,
The ENERGY E of IMF and related coefficient calculation formula are as follows in the step 2, i.e.,
E=∑ x2(n) (3)
The present invention is coupled from tested insulating tube type busbar by acoustics coupling sensor and obtains original coupled signal；To original
Beginning coupled signal such as is denoised, is amplified at the conditionings means coupled signal that obtains on tested insulating tube type busbar that treated；It is logical
It crosses software algorithm and blind source separating is carried out to treated the coupled signal, exclude work on the spot noise and other noises to signal
Interference, the accurate local discharge signal obtained on insulating tube type busbar.The present invention can be effectively and timely by insulating tube type busbar
Shelf depreciation defects detection comes out, for the quality of insulation of insulating tube type busbar test and judge provide it is more efficiently sensitive
Method.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device of the present invention.
In figure: 1-acoustics coupling sensor, the 2-the first signal conditioning circuit, 3-leakage current sensors, 4-the second
Signal conditioning circuit, 5-analog-to-digital conversions and signal processing circuit, 6-first communication modules, 7-second communication modules, after 8-
Platform terminal.
Specific embodiment
Below in conjunction with the attached drawing in the present invention, the technical solution in the present invention is clearly and completely described.
Referring to Fig. 1, it is the structural schematic diagram of insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device of the present invention,
Described device includes acoustics coupling sensor 1, the first signal conditioning circuit 2, leakage current sensor 3, second signal conditioning electricity
Road 4, analog-to-digital conversion and signal processing circuit 5, first communication module 6, second communication module 7, background terminal 8.The modulus turns
It changes and arm processor can be used with signal processing circuit 5.
Acoustics coupling is installed in the outer surface of each insulating sleeve and insulating tube type busbar terminal on insulating tube type busbar route
Sensor 1 is closed, and acoustics coupling sensor 1 and insulating tube type busbar outer wall are in close contact.First signal conditioning circuit 2 and acoustics
The conditionings means such as coupling sensor 1 connects, and the original signal for being coupled to acoustics coupling sensor 1 is denoised, amplified
It obtains analog-to-digital conversion and signal processing circuit 5 after noisy shelf depreciation acoustic emission signal is sent into be handled, acoustics coupling passes
The signal frequency of 1 coupled signal of sensor is 600-8000HZ.The insulating tube type busbar shelf depreciation acoustic emission signal of actual acquisition
Signal-to-noise ratio is very low, and the present invention uses EEMD (set empirical mode decomposition) in conjunction with wavelet adaptive threshold method, Neng Gouyou
Effect improves its noise reduction effect, improves the accuracy of feature extraction.
It include signal acquisition process module, the sampling of signal acquisition process module in analog-to-digital conversion and signal processing circuit 5
Trigger signal is power frequency zero cross signal, and leakage current sensor 3 obtains the phase of power frequency component, through second signal conditioning circuit 4
Power frequency zero cross signal is obtained after processing, the time that continuous data acquires after sampling triggering every time is 60ms.Analog-to-digital conversion and signal
5 pairs of collected signals of institute of processing circuit carry out signal denoising, blind source separating, obtain the local discharge signal of insulating tube type busbar
The features such as phase, number of pulses.
Analog-to-digital conversion and signal processing circuit 5 are for carrying out set empirical modal to noisy shelf depreciation acoustic emission signal
Decomposition and wavelet adaptive threshold noise reduction process, the local discharge signal after obtaining noise reduction.Specific step is as follows:
Step 1: carrying out set empirical mode decomposition (EEMD) to noisy shelf depreciation acoustic emission signal
1) it determines the amplitude n of the white noise of operation times M and addition, defines the decomposition number that m is EMD, M is operation time
Number, n are the amplitude for the white noise being added, and m meets 1≤m≤M, by the white noise signal n of different amplitudesm(t) it is added to wait divide
It solves in signal x (t), obtains new signal x to be decomposedm(t), i.e.,
xm(t)=x (t)+nm(t) (1)
General operation times are bigger, and the eradicating efficacy of finally average rear white noise is better, but operation times are bigger, operation
Time is longer.When analyzed signal is mainly high-frequency signal, added white noise acoustic amplitude can be slightly smaller, and analyzed signal is mainly
When low frequency signal, added white noise acoustic amplitude can be somewhat larger.The embodiment of the present invention takes operation times M=100, the auxiliary fortune of addition
The white noise amplitude of calculation is n=0.1.
2) to the signal x after addition white noisem(t) EMD decomposition is carried out, obtains several intrinsic mode functions (IMF) components,
It is indicated with Cmi, i.e., i-th of the IMF component obtained after being decomposed after m-th addition white noise signal by EMD；
3) m successively takes 1 to M, and iteration carries out step 1) and 2), the available M group IMF vector sequence decomposited, i.e.,
{Cmi}；
4) it averages to the M group IMF component decomposited, eliminates white noise and obtain measured signal simultaneously by EEMD decomposition
Each rank IMF afterwards, definitionAs i-th of IMF component of the EEMD measured signal decomposed, i.e.,
Step 2: extracting each intrinsic mode functions (IMF), and the energy of original energy and each IMF is calculated, together
When calculate the related coefficient of each IMF and original signal, comprehensively consider energy accounting and related coefficient size carry out the sieve of IMF component
Choosing reconstruct, obtains reconstruction signal.
The ENERGY E of IMF and related coefficient calculation formula are as follows, i.e.,
E=∑ x2(n) (3)
Wherein E is energy, and p is related coefficient；
Comprehensively consider ENERGY E and the two factors of related coefficient carry out the screening reconstruct of IMF component, specific criterion are as follows: 1.
The energy for calculating each IMF component accounts for the specific gravity of original signal energy, 2. the amount that record accounting is less than maximum accounting 1/10 calculates respectively
The related coefficient of a IMF component and original signal, record related coefficient are less than greatest coefficient 1/10.Comprehensively consider 1. 2. index sieve
Choosing, remaining IMF component is reconstructed, reconstruction signal is obtained.
Step 3: wavelet adaptive threshold noise reduction process is carried out to reconstruction signal, the local discharge signal after obtaining noise reduction.
Using in wavelet adaptive threshold noise reduction process, using the unbiased disaster risk estimation method of adaptive Stein, principle is,
Adaptive wavelet threshold uses gradient descent method, next threshold value be equal to present threshold value and mean square error function gradient value it
Difference, i.e.,
In formula,WithPresent threshold value and next threshold value are respectively indicated, μ is iteration step length,It is square
The gradient value of error function ξ, is represented by
In formula,AndAs threshold function table.
The wavelet basis selected is determined first and sets Decomposition order, and the present embodiment selects sym8 small echo and sets Decomposition order
It is 6, and chooses Sigmoid function as threshold function table adaptive iteration and obtain optimal threshold, the expression formula of threshold function table is
In formula, formula (7) are substituted into g by β=2iAnd derivation is carried out, then substitute into formula (5) and (6) and can change based on gradient decline
In generation, seeks threshold value, and first derivative is
And corresponding second dervative is
Threshold function table mentioned in step 3, which is substituted into, to carry out wavelet adaptive threshold noise reduction process to reconstruction signal, obtained
The signal for noise reduction process of learning from else's experience.Eventually pass through EEMD and small echo processing obtain de-noising signal, exclude work on the spot noise and its
It is female to obtain insulation insulating tube type for his interference of the noise to signal, the accurate failure acoustic emission signal obtained on insulating tube type busbar
The time-frequency characteristic of line shelf depreciation acoustic emission signal.
Analog-to-digital conversion and signal processing circuit 5 are communicatively coupled with background terminal 8, specifically, analog-to-digital conversion and signal
Processing circuit 5 is connect with first communication module 6, and background terminal 8 is connect with second communication module 7, first communication module 6 and second
Communication module 7 is communicatively coupled, to realize the communication connection of analog-to-digital conversion and signal processing circuit 5 and background terminal 8.Institute
It states first communication module 6 and 4G communication module can be used in second communication module 7.The first communication module 6 and background terminal 8 it
Between connected by serial communication port, second communication module 7 and analog-to-digital conversion and signal processing circuit 5 pass through serial communication end
Mouth connection.
Background terminal 8 is by signals numbers such as the phases, number of pulses and Energy-Entropy of the local discharge signal obtained after processing
According to construction feature vector, collected basic data analyzes when running for the first time with insulating tube type busbar, to make phase
The state evaluation answered, if the increase that the characteristic quantities such as the phase of the local discharge signal of insulating tube type busbar, number of pulses are lasting
Or significant increase, then it can determine that shelf depreciation defect；When occurring abnormal, system sends a warning.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Belong to those skilled in the art in the technical scope disclosed by the present invention, any changes or substitutions that can be easily thought of, all answers
It is included within the scope of the present invention.
Claims (10)
1. a kind of insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device, it is characterised in that: including acoustics coupling sensor,
First signal conditioning circuit, analog-to-digital conversion and signal processing circuit, background terminal；
The acoustics coupling sensor is mounted on each insulating sleeve and insulating tube type busbar terminal on insulating tube type busbar route
Outer surface；
First signal conditioning circuit and the acoustics coupling sensor communicate to connect, for coupling to acoustics coupling sensor
To original signal denoised, amplify conditioning, obtain noisy shelf depreciation acoustic emission signal and be sent into analog-to-digital conversion and signal
Processing circuit；
The analog-to-digital conversion and signal processing circuit are for carrying out set empirical modal to noisy shelf depreciation acoustic emission signal
Decomposition and wavelet adaptive threshold noise reduction process, the local discharge signal after obtaining noise reduction；
The background terminal and the analog-to-digital conversion and signal processing circuit communicate to connect, at will be through analog-to-digital conversion and signal
The signal data construction feature vector of the local discharge signal obtained after reason processing of circuit, when being run for the first time with insulating tube type busbar
Collected basic data analyzes, to make corresponding state evaluation.
2. insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device as described in claim 1, it is characterised in that: the letter
Number construction feature vector includes phase, number of pulses and Energy-Entropy.
3. insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device as described in claim 1, it is characterised in that: further include
Leakage current sensor, second signal conditioning circuit, leakage current sensor pass through second signal conditioning circuit and analog-to-digital conversion
It is connected with signal processing circuit, includes signal acquisition process module, signal acquisition process in analog-to-digital conversion and signal processing circuit
The sampling trigger signal of module is power frequency zero cross signal, and leakage current sensor obtains the phase of power frequency component, through second signal
Power frequency zero cross signal is obtained after conditioning circuit processing.
4. insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device as described in claim 1, it is characterised in that: the mould
Number is converted and signal processing circuit is analog-to-digital conversion and signal processing circuit.
5. insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device as described in claim 1, it is characterised in that: modulus turns
Change and connect with signal processing circuit with first communication module, background terminal is connect with second communication module, first communication module with
Second communication module is communicatively coupled.
6. insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device as described in claim 1, it is characterised in that: the mould
Number conversion and signal processing circuit are used to carry out noisy shelf depreciation acoustic emission signal set empirical mode decomposition and small
The processing of wave self-adaption threshold deniosing, the local discharge signal after obtaining noise reduction, the specific steps of which are as follows:
Step 1: carrying out set empirical mode decomposition to noisy shelf depreciation acoustic emission signal；
Step 2: extracting each intrinsic mode functions IMF, and the energy of original energy and each IMF is calculated, calculated simultaneously
The related coefficient of each IMF and original signal, comprehensively consider energy accounting and related coefficient size carries out the screening weight of IMF component
Structure obtains reconstruction signal；
Step 3: wavelet adaptive threshold noise reduction process is carried out to reconstruction signal, the local discharge signal after obtaining noise reduction.
7. insulating tube type busbar shelf depreciation acoustics on-Line Monitor Device as claimed in claim 6, it is characterised in that: the step
Rapid one specifically:
1) it determines the amplitude n of the white noise of operation times M and addition, defines the decomposition number that m is EMD, M is operation times, and n is
The amplitude of the white noise of addition, m meets 1≤m≤M, by the white noise signal n of different amplitudesm(t) it is added to signal x to be decomposed
(t) in, new signal x to be decomposed is obtainedm(t), i.e.,
xm(t)=x (t)+nm(t) (1)
2) to the signal x after addition white noisem(t) EMD decomposition is carried out, several intrinsic mode functions (IMF) components is obtained, uses Cmi
It indicates, i.e., i-th of the IMF component obtained after being decomposed after m-th addition white noise signal by EMD；
3) m successively takes 1 to M, and iteration carries out step 1) and 2), the available M group IMF vector sequence decomposited, i.e., { Cmi }；
4) it averages to the M group IMF component decomposited, eliminates white noise and obtain measured signal after EEMD is decomposed simultaneously
Each rank IMF, definitionAs i-th of IMF component of the EEMD measured signal decomposed, i.e.,
The ENERGY E of IMF and related coefficient calculation formula are as follows in the step 2, i.e.,
E=∑ x2(n) (3)
8. a kind of insulating tube type busbar shelf depreciation acoustics on-line monitoring method, it is characterised in that include the following steps:
The original signal that first signal conditioning circuit is coupled to acoustics coupling sensor is denoised, amplifies conditioning, is contained
The shelf depreciation acoustic emission signal made an uproar is sent into analog-to-digital conversion and signal processing circuit；
Analog-to-digital conversion and signal processing circuit to noisy shelf depreciation acoustic emission signal carry out set empirical mode decomposition and
Wavelet adaptive threshold noise reduction process, the local discharge signal after obtaining noise reduction；
Background terminal is by the signal data construction feature vector of local discharge signal, acquisition when running for the first time with insulating tube type busbar
To basic data analyze, to make corresponding state evaluation.
9. insulating tube type busbar shelf depreciation acoustics on-line monitoring method as claimed in claim 8, it is characterised in that: the mould
Number conversion and signal processing circuit carry out set empirical mode decomposition and small echo certainly to noisy shelf depreciation acoustic emission signal
Threshold deniosing processing is adapted to, steps are as follows for the local discharge signal body after obtaining noise reduction:
Step 1: carrying out set empirical mode decomposition to noisy shelf depreciation acoustic emission signal；
Step 2: extracting each intrinsic mode functions IMF, and the energy of original energy and each IMF is calculated, calculated simultaneously
The related coefficient of each IMF and original signal, comprehensively consider energy accounting and related coefficient size carries out the screening weight of IMF component
Structure obtains reconstruction signal；
Step 3: wavelet adaptive threshold noise reduction process is carried out to reconstruction signal, the local discharge signal after obtaining noise reduction.
10. insulating tube type busbar shelf depreciation acoustics on-line monitoring method as claimed in claim 9, it is characterised in that the step
Rapid one specifically:
1) it determines the amplitude n of the white noise of operation times M and addition, defines the decomposition number that m is EMD, M is operation times, and n is
The amplitude of the white noise of addition, m meets 1≤m≤M, by the white noise signal n of different amplitudesm(t) it is added to signal x to be decomposed
(t) in, new signal x to be decomposed is obtainedm(t), i.e.,
xm(t)=x (t)+nm(t) (1)
2) to the signal x after addition white noisem(t) EMD decomposition is carried out, several intrinsic mode functions IMF component is obtained, with Cmi table
Show, i.e., i-th of the IMF component obtained after being decomposed after m-th addition white noise signal by EMD；
3) m successively takes 1 to M, and iteration carries out step 1) and 2), the available M group IMF vector sequence decomposited, i.e., { Cmi }；
4) it averages to the M group IMF component decomposited, eliminates white noise and obtain measured signal after EEMD is decomposed simultaneously
Each rank IMF, definitionAs i-th of IMF component of the EEMD measured signal decomposed, i.e.,
The ENERGY E of IMF and related coefficient calculation formula are as follows in the step 2, i.e. E=∑ x2(n) (3)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910159875.9A CN109884483A (en) | 2019-03-04 | 2019-03-04 | Insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910159875.9A CN109884483A (en) | 2019-03-04 | 2019-03-04 | Insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109884483A true CN109884483A (en) | 2019-06-14 |
Family
ID=66930401
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910159875.9A Pending CN109884483A (en) | 2019-03-04 | 2019-03-04 | Insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109884483A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111044865A (en) * | 2019-12-30 | 2020-04-21 | 杭州国洲电力科技有限公司 | Partial discharge wavelet denoising method for direct-current gas insulation electrical equipment |
| CN113190788A (en) * | 2021-05-14 | 2021-07-30 | 浙江大学 | Method and device for adaptively extracting and reducing bus characteristics of power distribution system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203811750U (en) * | 2013-11-27 | 2014-09-03 | 云南电网公司保山供电局 | Live-line detection system for partial discharge of transformer |
| CN104515938A (en) * | 2013-10-01 | 2015-04-15 | 洛克威尔自动控制技术股份有限公司 | Systems and methods for detecting partial discharge in electrical components |
| CN109342907A (en) * | 2018-12-13 | 2019-02-15 | 武汉理工大学 | The optical fibre sensor structure and demodulation method and monitoring method of partial discharge of transformer |
-
2019
- 2019-03-04 CN CN201910159875.9A patent/CN109884483A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104515938A (en) * | 2013-10-01 | 2015-04-15 | 洛克威尔自动控制技术股份有限公司 | Systems and methods for detecting partial discharge in electrical components |
| CN203811750U (en) * | 2013-11-27 | 2014-09-03 | 云南电网公司保山供电局 | Live-line detection system for partial discharge of transformer |
| CN109342907A (en) * | 2018-12-13 | 2019-02-15 | 武汉理工大学 | The optical fibre sensor structure and demodulation method and monitoring method of partial discharge of transformer |
Non-Patent Citations (3)
| Title |
|---|
| 张建文 等: "基于CEEMDAN与小波自适应阈值的去噪新方法", 《电测与仪表》 * |
| 曹文彬: "高压开关柜绝缘检测的声波方法研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 朱永利 等: "并行EEMD算法及其在局部放电信号特征提取中的应用", 《电工技术学报》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111044865A (en) * | 2019-12-30 | 2020-04-21 | 杭州国洲电力科技有限公司 | Partial discharge wavelet denoising method for direct-current gas insulation electrical equipment |
| CN113190788A (en) * | 2021-05-14 | 2021-07-30 | 浙江大学 | Method and device for adaptively extracting and reducing bus characteristics of power distribution system |
| CN113190788B (en) * | 2021-05-14 | 2023-08-18 | 浙江大学 | Method and device for adaptively extracting and reducing noise of bus characteristics of power distribution system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109557429B (en) | GIS partial discharge fault detection method based on improved wavelet threshold denoising | |
| CN102680860B (en) | Automatic fault-point locating method for traveling-wave based fault location of high-voltage electric power lines | |
| CN108956787B (en) | Steel rail damage detection method based on neural network | |
| CN106546892A (en) | The recognition methodss of shelf depreciation ultrasonic audio and system based on deep learning | |
| CN109649432B (en) | System and method for monitoring integrity of steel rail of cloud platform based on guided wave technology | |
| CN107963239B (en) | Carrier rocket fault detection device and method based on audio | |
| CN207300606U (en) | Transformer information collecting device based on Principles of Acoustics | |
| CN109855874B (en) | Random resonance filter for enhancing detection of weak signals in vibration assisted by sound | |
| CN112101174A (en) | LOF-Kurtogram-based mechanical fault diagnosis method | |
| CN110967409A (en) | Method for extracting and identifying original data features based on multi-channel ultrasonic flaw detection | |
| RU2570592C1 (en) | Method of detecting and analysing acoustic emission signals | |
| CN113567969B (en) | Illegal sand dredger automatic monitoring method and system based on underwater acoustic signals | |
| CN109884483A (en) | Insulating tube type busbar shelf depreciation acoustics on-line monitoring method and device | |
| CN104237713A (en) | Transformer winding deformation diagnostic method based on discrete wavelet transform | |
| CN110703076A (en) | GIS fault diagnosis method based on vibration signal frequency domain energy ratio | |
| CN109116196A (en) | A kind of power cable fault discharging sound intelligent identification Method | |
| CN107192930A (en) | A kind of transformer partial discharge positioning method | |
| CN110703078A (en) | GIS fault diagnosis method based on spectral energy analysis and self-organizing competition algorithm | |
| CN113345399A (en) | Method for monitoring sound of machine equipment in strong noise environment | |
| CN115078912A (en) | Method and system for detecting abnormity of roof high-voltage cable connector in real time and train | |
| CN114839269A (en) | Nondestructive testing method and device for internal defect stress of GIS solid insulating part | |
| CN110780162B (en) | Method for extracting partial discharge signal of primary and secondary fusion power distribution switch and detection device | |
| CN110764027B (en) | Electric connector intermittent fault diagnosis method based on frequency spectrum characteristic change | |
| CN114137364B (en) | Interference wave elimination method based on time domain reflection method | |
| CN112033656A (en) | Mechanical system fault detection method based on broadband spectrum processing |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190827 Address after: 430077, 227 East Main Street, Wuchang District, Hubei, Wuhan Applicant after: Power Science Research Institute of Hubei Electric Power Co., Ltd. Address before: 430077, 227 East Main Street, Hongshan District, Hubei, Wuhan Applicant before: Power Science Research Institute of Hubei Electric Power Co., Ltd. Applicant before: State Grid Corporation of China Applicant before: Wuhan new electrical Limited by Share Ltd |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190614 |
|
| RJ01 | Rejection of invention patent application after publication |