CN110333078A - A kind of rolling bearing degenerate state stage determines method - Google Patents
A kind of rolling bearing degenerate state stage determines method Download PDFInfo
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- CN110333078A CN110333078A CN201910771770.9A CN201910771770A CN110333078A CN 110333078 A CN110333078 A CN 110333078A CN 201910771770 A CN201910771770 A CN 201910771770A CN 110333078 A CN110333078 A CN 110333078A
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- G—PHYSICS
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/04—Bearings
- G01M13/045—Acoustic or vibration analysis
Abstract
The present invention provides a kind of rolling bearing degenerate state stages to determine method, include the following steps: step 1, the vibration signal simultaneously denoising of acquisition characterization rolling bearing steady-working state, obtains the useful signal sequence for capableing of embodiments rolling bearing steady-working state；Step 2, multiple dimensioned Tsallis is calculated to useful signal sequence and arranges entropy, obtain health status exponential time sequence；Step 3, according to health status exponential time sequence, average value and variance yields are calculated；Step 4, alarm threshold value is calculated according to average value and variance yields, and arranges the variation tendency of entropy makeup time sequence according to multiple dimensioned Tsallis, rolling bearing catagen phase sart point in time is identified.The present invention using multiple dimensioned Tsallis arrangement entropy be adjusted entropy index adapt to it is a variety of under the conditions of system state machine monitoring capability and preferable sense mechanism system state change ability, realize the determination in rolling bearing degenerate state stage, recognition effect is preferably and with faster calculating speed.
Description
Technical field
The present invention relates to system state machine monitorings and Life Assessment Technology field, in particular to a kind of axis of rolling
Holding the degenerate state stage determines method.
Background technique
The vibration that many mechanical system degenerate state identifications in China at this stage mainly pass through data-driven with appraisal procedure exists
Line monitoring method has been widely used among the condition monitoring and fault diagnosis of rotating machinery.The existing vibration based on comentropy
The method of dynamic its health index of signal complexity survey calculation has preferable computational efficiency, can be fast from time of vibration sequence
The rapid variation of fast perceptive object system dynamics behavior.Arrangement plan method is a kind of representative calculating time of vibration sequence
The method of column signal complexity, but since mechanical system is typically under a variety of different operating conditions, need according to reality
Condition calculated to be arranged the parameter of health index, and common arrangement entropy can not be configured according to condition.Cause
This this method proposes to calculate the health index of rolling bearing based on multiple dimensioned Tsallis arrangement entropy, can be according to object
Condition carries out the entropy index factor and scale is configured, and calculates alarm threshold value according to 3 σ methods, realizes rolling bearing degeneration shape
The determination in state stage.
Summary of the invention
It is an object of the invention to avoid in the prior art insufficient and to provide a kind of rolling bearing degenerate state stage true
Determine method.
The purpose of the present invention is achieved through the following technical solutions:
A kind of rolling bearing degenerate state stage determines method, includes the following steps:
Step 1, the vibration signal of acquisition characterization rolling bearing steady-working state and denoising, obtaining being capable of specific table
Levy the useful signal sequence of rolling bearing steady-working state；
Step 2, multiple dimensioned Tsallis is calculated to the useful signal sequence that step 1 obtains and arranges entropy, obtain health status
Exponential time sequence；
Step 3, the health status exponential time sequence obtained according to step 2 calculates average value and variance yields；
Step 4, the average value and variance yields obtained according to step 3 calculates alarm threshold value, and is arranged according to multiple dimensioned Tsallis
The variation tendency of column entropy makeup time sequence, identifies rolling bearing catagen phase sart point in time.
Optionally, in step 1, the vibration signal for characterizing rolling bearing steady-working state is in same period point
It acquires and obtains, and there is certain time length.
Optionally, in step 3, the calculation method of multiple dimensioned Tsallis arrangement entropy are as follows:
Selected entropy index q and time scale s, the time of vibration sequence { x tested for k-th of time pointk(i),i
=1,2 ..., r }, according to formulaConstruct Time Sub-seriesWherein N=[r/
S] it indicates to r/s round numbers, s indicates that time scale, the length of Time Sub-series are N=[r/s]；
Embedded dimensions m and time delay τ are determined, to time sequences ys(j), j=1,2 ..., N carries out phase space reconfiguration such as
Under:
Then any Ys(i) m real number in can arrange as follows according to increasing:
ys(j+(k1-1)τ)≤ys(j+(k2-1)τ)≤…≤ys(j+(km-1)τ)
If Ys(j) y ins(j) there is identical value and their initial positions are km-1≤km, then y is enableds(j+(km-1-1)τ)
≤ys(j+(km-1)τ)；
Vector Ys(i) with S (l)=(k1,k2,…,km) symbolic vector correspond, wherein l=1,2 ..., K, K≤m！
Indicate the maximum number of arrangement, S (l), l=1,2 ..., K indicates m！One in a symbol arrangement；
MakeIndicate the corresponding probability distribution of K symbol arrangement, then multiple dimensioned Tsallis arranges entropy is defined as:
Optionally, in step 3, according to health status exponential time sequence, the method for calculating average value and variance yields are as follows:
Optionally, in step 4, alarm threshold value is calculated according to 3 σ criterion, calculation method are as follows:
It is obtained by the present invention the utility model has the advantages that the present invention is based under equal time distances at the time of point in mechanical system work
Make the vibration acceleration time series signal acquired in state degenerative process, it can be preferable using multiple dimensioned Tsallis arrangement entropy
The ability of sense mechanism system mode mutation adapts to system state machine prison under different condition with that can pass through the adjusting entropy index factor
The ability of survey realizes the determination in rolling bearing degenerate state stage, and calculating speed is fast and effect is preferable.
Detailed description of the invention
From following description with reference to the accompanying drawings it will be further appreciated that the present invention, focuses on the principle for showing embodiment
On.
Fig. 1 is calculation flow chart of the invention；
Fig. 2 be in the present invention the multiple dimensioned Tsallis of certain emulation signal arrange entropy and multiple dimensioned arrangement entropy different scale because
Comparison figure under son；
Fig. 3 is that the multiple dimensioned Tsallis of rolling bearing degenerative process of example in the present invention arranges the ratio of entropy and conventional indexes
Compared with figure.
Fig. 4 is the identification figure in the rolling bearing degenerative process degenerate state stage of example in the present invention.
Specific embodiment
In order to enable the objectives, technical solutions, and advantages of the present invention are more clearly understood, below in conjunction with embodiment, to this
Invention is further elaborated；It should be appreciated that described herein, the specific embodiments are only for explaining the present invention, and does not have to
It is of the invention in limiting.To those skilled in the art, after access is described in detail below, other systems of the present embodiment
System, method and/or feature will become obvious.All such additional systems, method, feature and advantage are intended to be included in
It in this specification, is included within the scope of the invention, and by the protection of the appended claims.In description described in detail below
The other feature of the disclosed embodiments, and these characteristic roots will be apparent according to described in detail below.
The same or similar label correspond to the same or similar components in the attached drawing of the embodiment of the present invention；It is retouched in of the invention
In stating, it is to be understood that if the orientation or positional relationship for having the instructions such as term " on ", "lower", "left", "right" is based on attached drawing
Shown in orientation or positional relationship, be merely for convenience of description of the present invention and simplification of the description, rather than indication or suggestion is signified
Device or component must have a particular orientation, be constructed and operated in a specific orientation, therefore positional relationship is described in attached drawing
Term only for illustration, should not be understood as the limitation to this patent, for the ordinary skill in the art, can
To understand the concrete meaning of above-mentioned term as the case may be.
The present invention is to determine method in a kind of rolling bearing degenerate state stage, and following embodiment is told about according to Fig. 1-4:
Embodiment one:
Please refer to Fig. 1, a kind of rolling bearing degenerate state stage determines method, includes the following steps:
Step 1, the vibration signal of acquisition characterization rolling bearing steady-working state and denoising, obtaining being capable of specific table
Levy the useful signal sequence of rolling bearing steady-working state；
Step 2, multiple dimensioned Tsallis is calculated to the useful signal sequence that step 1 obtains and arranges entropy, obtain health status
Exponential time sequence；
Step 3, the health status exponential time sequence obtained according to step 2 calculates average value and variance yields；
Step 4, the average value and variance yields obtained according to step 3 calculates alarm threshold value, and is arranged according to multiple dimensioned Tsallis
The variation tendency of column entropy makeup time sequence, identifies rolling bearing catagen phase sart point in time.
In step 4, alarm threshold value is calculated according to 3 σ criterion, calculation method are as follows:
3 σ criterion are also known as Pauta criterion, it is first to assume that one group of detection data contains only random error, carry out to it
Calculation processing obtains standard deviation, by one section of certain determine the probability, it is believed that all errors more than this section are just not belonging to
Random error but gross error, the data containing the error should give rejecting.3 σ principles be suitable for have compared with multi-group data when
It waits.
3 σ criterion are built upon on the basis of the equally accurate duplicate measurements of normal distribution and cause the interference of singular data or make an uproar
Sound is difficult to meet normal distribution.It, should if 3 σ of absolute value ν i > of the residual error of some measured value in one group of measurement data
Measured value is bad value, should be rejected.
Usually the error equal to ± 3 σ falls in other than ± 3 σ the random error of normal distribution as limit error
Probability there was only 0.27%, a possibility that it occurs in finite measurement very little, therefore there are 3 σ criterion.3 σ criterion are the most frequently used
It is also simplest gross error criterion, it is generally used for pendulous frequency sufficiently more (n >=30) or when n > 10 is done roughly
The case where when differentiation.
For normal distribution tool there are two the distribution of parameter μ and the random variable of continuous type of σ ^2, the first parameter μ is to obey normal state
The mean value of the stochastic variable of distribution, second parameter σ ^2 are this variance of a random variables, so normal distribution is denoted as N (μ, σ 2).
μ is the location parameter of normal distribution, describes the central tendency position of normal distribution.Probabilistic law is neighbouring with μ to take
Value probability it is big, and take the probability of the value remoter from μ smaller.Using X=μ as symmetry axis, left and right is full symmetric for normal distribution.Just
The expectation of state distribution, mean, median, mode are identical, are equal to μ.
σ describes the dispersion degree of normal distribution data distribution, and σ is bigger, and data distribution is more dispersed, and σ is smaller, data point
Cloth is more concentrated.It is also referred to as the form parameter of normal distribution, σ is bigger, and curve is more flat, conversely, σ is smaller, curve is taller and thinner.
3 σ principles are as follows:
Probability of the numeric distribution in (μ-σ, μ+σ) is 0.6827,
Probability of the numeric distribution in (+2 σ of μ -2 σ, μ) is 0.954,
Probability of the numeric distribution in (+3 σ of μ -3 σ, μ) is 0.9973,
It is believed that the value almost all of Y concentrates in the section (+3 σ of μ -3 σ, μ), super a possibility that going beyond the scope
It only accounts for less than 0.3%.
And in step 1, the vibration signal of characterization rolling bearing steady-working state is acquired in same period point
And obtain, and with certain time length.
Embodiment two:
Method is determined in a kind of rolling bearing degenerate state stage to further describe the present invention, it is in step 2, multiple dimensioned
The calculation method of Tsallis arrangement entropy are as follows:
Selected entropy index q and time scale s, the time of vibration sequence { x tested for k-th of time pointk(i),i
=1,2 ..., r }, according to formulaConstruct Time Sub-seriesWherein N=[r/
S] it indicates to r/s round numbers, s indicates that time scale, the length of Time Sub-series are N=[r/s]；
Embedded dimensions m and time delay τ are determined, to time sequences ys(j), j=1,2 ..., N carries out phase space reconfiguration such as
Under:
Then any Ys(i) m real number in can arrange as follows according to increasing:
ys(j+(k1-1)τ)≤ys(j+(k2-1)τ)≤…≤ys(j+(km-1)τ)
If Ys(j) y ins(j) there are identical value, such as ys(j+(km-1- 1) τ)=xij(j+(km- 1) τ), and at the beginning of them
The position of beginning is km-1≤km, then y is enableds(j+(km-1-1)τ)≤ys(j+(km-1)τ)；
Vector Ys(i) with S (l)=(k1,k2,…,km) symbolic vector correspond, wherein l=1,2 ..., K, K≤m！
Indicate the maximum number of arrangement, S (l), l=1,2 ..., K indicates m！One in a symbol arrangement；
MakeIndicate the corresponding probability distribution of K symbol arrangement, then multiple dimensioned Tsallis arranges entropy is defined as:
In step 3, according to health status exponential time sequence, the method for calculating average value and variance yields are as follows:
Embodiment three:
It, below will be to a kind of rolling bearing degenerate state stage determination side on the basis of embodiment one and embodiment two
Method is tested, referring again to Fig. 1 to Fig. 4 and following five step.
1. the acquisition of mechanical system vibration acceleration time series signal and processing.
To can be realized this method to the trend prediction of mechanical system degenerate state and illustrate the feasibility of this method, to roll
Based on the experiment of bearing life cycle management, every the one group of vibration acceleration time series signal of acquisition in 5 minutes, every group of time series
The length of signal is 4096, acquires 530 groups of time series signals altogether, mat file will be formed after above-mentioned signal acquisition,
Denoising is carried out using 2 layers of wavelet method of adaptability inside Matlab.
2. multiple dimensioned Tsallis arranges entropy.
The vibration acceleration time series signal x obtained for k-th of moment measurementk(1),xk(2),…,xk(4096) it adopts
Denoising, selective entropy scale factor q=-0.5, s=8, according to formula are carried out with wavelet methodConstructing a new length is time series signalWhen to this
Between sequence carry out phase space reconfiguration, wherein Embedded dimensions be 6, time delay coefficient be 3, then again to the multiple dimensioned of signal
Tsallis arrangement entropy is calculated, and the result obtained is as shown in Figure 2.
3. calculating health status exponential time serial mean and standard deviation square value.
According to obtained health status exponential time sequence according to equationWith
AndCalculate the average value and standard deviation square value of the time series.
4. alarming threshold value calculates.
Average value and standard deviation square value based on obtained time series are according to equationIt calculates
High alarm setting threshold values, as a result as shown in Figure 3 and 4.
5. rolling bearing catagen phase starting point identifies.
It whether is more than alarming threshold value according to health status exponential time sequence variation trend and some time point health index
Confirm rolling bearing catagen phase starting point.
As shown in figure 4, can then confirm that rolling bearing is in the healthy stage when health index is less than alarm threshold value.
When health index is more than alarm threshold value, then it can be confirmed that rolling bearing has been in catagen phase, in turn
Confirm the starting point of rolling bearing catagen phase.
Core of the invention is to provide a kind of rolling bearing based on multiple dimensioned Tsallis arrangement entropy and 3 σ alarm threshold values
The degenerate state stage determines method, is adopted based on moment point under the conditions of same intervals in rotatory mechanical system working condition degenerative process
The vibration acceleration time series signal of collection can preferably sense mechanism system mode be dashed forward using multiple dimensioned Tsallis arrangement entropy
The ability of change and the ability that can adapt to system state machine monitoring under different condition by adjusting the entropy index factor, realize the axis of rolling
The determination in degenerate state stage is held, calculating speed is fast and effect is preferable.
Although describing the present invention by reference to various embodiments above, but it is to be understood that of the invention not departing from
In the case where range, many changes and modifications can be carried out.That is methods discussed above, system and equipment are examples,
Various processes or component can suitably be omitted, replace or be added to various configurations.For example, in alternative configuration, can with institute
The order in a different order of description executes method and/or can add, omits and/or combine various parts.Moreover, about certain
The feature of configuration description can be combined with various other configurations, can such as combine the different aspect and member of configuration in a similar way
Element.In addition, can update as technology develops element therein, i.e., many elements are examples, be not intended to limit the present invention disclose or
The scope of the claims.
Give detail in the description to provide to the thorough understanding for including the exemplary configuration realized.However,
Configuration can be practiced without these specific details, such as has been illustrated with well-known circuit, process, calculation
Method, structure and technology are without unnecessary details, to avoid fuzzy configuration.The description only provides example arrangement, and unlimited
The scope of the claims processed, applicability or configuration.It is used on the contrary, front will provide the description of configuration for those skilled in the art
Realize the enabled description of described technology.It, can be to element in the case where not departing from spirit or scope disclosed by the invention
Function and arrangement carry out various changes.
To sum up, be intended to foregoing detailed description be considered as it is illustrative and not restrictive, and it is to be understood that below
Claim (including all equivalents) is intended to limit the spirit and scope of the present invention.The above embodiment is interpreted as only using
In illustrating the present invention rather than limit the scope of the invention.After the content for having read record of the invention, technology
Personnel can make various changes or modifications the present invention, these equivalence changes and modification equally fall into the claims in the present invention and limited
Fixed range.
Claims (5)
1. a kind of rolling bearing degenerate state stage determines method, include the following steps:
Step 1, it is steady to obtain characterization rolling bearing for the vibration signal of acquisition characterization rolling bearing steady-working state and denoising
Determine the useful signal sequence of working condition；
Step 2, multiple dimensioned Tsallis is calculated using the useful signal sequence that step 1 obtains and arrange entropy, obtain health status and refer to
Number time series；
Step 3, the average value and variance yields of the health status exponential time sequence that step 2 obtains are calculated；
Step 4, the average value and variance yields obtained using step 3 calculates alarm threshold value, and arranges entropy according to multiple dimensioned Tsallis
It is worth the variation tendency of makeup time sequence, rolling bearing catagen phase sart point in time is identified.
2. a kind of rolling bearing degenerate state stage as described in claim 1 determines method, which is characterized in that in step 1,
The vibration signal of characterization rolling bearing steady-working state is to acquire and obtain in same period point, and have certain time long
Degree.
3. a kind of rolling bearing degenerate state stage as described in claim 1 determines method, which is characterized in that in step 2,
The calculation method of multiple dimensioned Tsallis arrangement entropy are as follows:
Selected entropy index q and time scale s, the time of vibration sequence { x tested for k-th of time pointk(i), i=1,
2 ..., r }, according to formulaConstruct Time Sub-seriesWherein N=[r/s] table
Show to r/s round numbers, s indicates that time scale, the length of Time Sub-series are N=[r/s]；
Embedded dimensions m and time delay τ are determined, to time sequences ys(j), j=1,2 ..., it is as follows that N carries out phase space reconfiguration:
Then any Ys(i) m real number in can arrange as follows according to increasing:
ys(j+(k1-1)τ)≤ys(j+(k2-1)τ)≤…≤ys(j+(km-1)τ)
If Ys(j) y ins(j) there is identical value and their initial positions are km-1≤km, then y is enableds(j+(km-1-1)τ)≤ys
(j+(km-1)τ)；
Vector Ys(i) with S (l)=(k1,k2,…,km) symbolic vector correspond, wherein l=1,2 ..., K, K≤m！It indicates
The maximum number of arrangement, S (l), l=1,2 ..., K indicate m！One in a symbol arrangement；
MakeIndicate the corresponding probability distribution of K symbol arrangement, then multiple dimensioned Tsallis arranges entropy is defined as:
4. a kind of rolling bearing degenerate state stage as described in claim 1 determines method, which is characterized in that in step 3,
According to health status exponential time sequence, calculates average value and variance yields and calculates according to the following formula respectively:
5. a kind of rolling bearing degenerate state stage as described in claim 1 determines method, which is characterized in that in step 4,
Alarm threshold value is calculate by the following formula according to 3 σ criterion:
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110928237A (en) * | 2019-12-20 | 2020-03-27 | 华中科技大学 | Vibration signal-based numerical control machining center flutter online identification method |
| CN112001295A (en) * | 2020-08-19 | 2020-11-27 | 北京航天飞行控制中心 | Performance evaluation method and device for high-speed rotor shafting, storage medium and processor |
| CN113654771A (en) * | 2021-06-30 | 2021-11-16 | 中国电力科学研究院有限公司 | Formatting method and system for vibration waveform of spring type operating mechanism |
| CN114427972A (en) * | 2022-02-09 | 2022-05-03 | 中国人民解放军战略支援部队航天工程大学士官学校 | Rolling bearing performance degradation feature extraction method and system |
| CN113654771B (en) * | 2021-06-30 | 2024-05-17 | 中国电力科学研究院有限公司 | Formatting method and system for vibration waveform of spring type operating mechanism |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060189875A1 (en) * | 2005-02-18 | 2006-08-24 | Beth Israel Deaconess Medical Center | Complexity-based dynamical assay for assessing the toxicity and efficacy of pharmaceutical and other therapeutic interventions |
| CN101672873A (en) * | 2009-10-20 | 2010-03-17 | 哈尔滨工业大学 | Detection method of transient harmonic signals of power system based on combination of Tsallis wavelet singular entropy and FFT computation |
| CN105956526A (en) * | 2016-04-22 | 2016-09-21 | 山东科技大学 | Method for identifying a microearthquake event with low signal-to-noise ratio based on multi-scale permutation entropy |
| CN106600584A (en) * | 2016-12-07 | 2017-04-26 | 电子科技大学 | Tsallis entropy selection-based suspected pulmonary nodule detection method |
| CN108982107A (en) * | 2018-07-26 | 2018-12-11 | 北京工业大学 | It is a kind of based on morphology and it is multiple dimensioned arrangement entropy mean value bearing fault quantify trend diagnosis method |
-
2019
- 2019-08-21 CN CN201910771770.9A patent/CN110333078B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060189875A1 (en) * | 2005-02-18 | 2006-08-24 | Beth Israel Deaconess Medical Center | Complexity-based dynamical assay for assessing the toxicity and efficacy of pharmaceutical and other therapeutic interventions |
| CN101672873A (en) * | 2009-10-20 | 2010-03-17 | 哈尔滨工业大学 | Detection method of transient harmonic signals of power system based on combination of Tsallis wavelet singular entropy and FFT computation |
| CN105956526A (en) * | 2016-04-22 | 2016-09-21 | 山东科技大学 | Method for identifying a microearthquake event with low signal-to-noise ratio based on multi-scale permutation entropy |
| CN106600584A (en) * | 2016-12-07 | 2017-04-26 | 电子科技大学 | Tsallis entropy selection-based suspected pulmonary nodule detection method |
| CN108982107A (en) * | 2018-07-26 | 2018-12-11 | 北京工业大学 | It is a kind of based on morphology and it is multiple dimensioned arrangement entropy mean value bearing fault quantify trend diagnosis method |
Non-Patent Citations (1)
| Title |
|---|
| LI CHAO 等: "multiscale tsallis permutation entropy analysis for complex physiological time series", 《PHYSICA A STATISTICAL MECHANICS & ITS APPLICATION》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110928237A (en) * | 2019-12-20 | 2020-03-27 | 华中科技大学 | Vibration signal-based numerical control machining center flutter online identification method |
| CN110928237B (en) * | 2019-12-20 | 2020-12-29 | 华中科技大学 | Vibration signal-based numerical control machining center flutter online identification method |
| CN112001295A (en) * | 2020-08-19 | 2020-11-27 | 北京航天飞行控制中心 | Performance evaluation method and device for high-speed rotor shafting, storage medium and processor |
| CN112001295B (en) * | 2020-08-19 | 2023-12-08 | 北京航天飞行控制中心 | Performance evaluation method and device of high-speed rotor shaft system, storage medium and processor |
| CN113654771A (en) * | 2021-06-30 | 2021-11-16 | 中国电力科学研究院有限公司 | Formatting method and system for vibration waveform of spring type operating mechanism |
| CN113654771B (en) * | 2021-06-30 | 2024-05-17 | 中国电力科学研究院有限公司 | Formatting method and system for vibration waveform of spring type operating mechanism |
| CN114427972A (en) * | 2022-02-09 | 2022-05-03 | 中国人民解放军战略支援部队航天工程大学士官学校 | Rolling bearing performance degradation feature extraction method and system |
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