CN109598255A - A kind of reciprocating mechanical vibration signal impact initial point self-adaptation extraction method based on energy operator k- gradient - Google Patents
A kind of reciprocating mechanical vibration signal impact initial point self-adaptation extraction method based on energy operator k- gradient Download PDFInfo
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Abstract
The present invention provides a kind of reciprocating mechanical vibration signal impact initial point self-adaptation extraction method based on energy operator k- gradient, the problem of threshold value sets unreasonable and bad adaptability in conventional impact initial point extractive technique is avoided, achievees the effect that vibration signal impact initial point is extracted in adaptive and optimization.This method carries out the processing of EMD adaptive-filtering to vibration signal first, removes the low-frequency component in signal, reserved high-frequency ingredient；Then Teager energy operator, prominent transient oscillation impact energy are calculated；The k- gradient and k- gradient neighborhood of Teager energy operator are calculated again, and using first point of the k- gradient neighborhood in time series as impact starting point；Characteristic paracycle finally impacted according to reciprocating mechanical vibration signal, outlier inspection is carried out using 3- σ criterion to calculated result, and the calculated result of outlier is optimized by adjust automatically k value and the criterion of setting, to achieve the purpose that adaptive accurate extraction vibration signal impact initial point.
Description
Technical field
The vibration performance processing method extracted the present invention relates to a kind of vibratory impulse initial point more particularly to a kind of reciprocating machine
Vibration signal impacts initial point self-adaptation extraction method, suitable for status monitoring and fault diagnosis field based on vibration signal.
Background technique
Impact is usually to generate because components stress is caused to mutate for contact-impact, and then make corresponding mechanical part
Force unbalance is vibrated, and is presented as that moment increases the local assault of simultaneously rapid decay on the vibration signal of equipment.Back and forth
Mechanical actual vibration signal is generally mainly made of the local assault with clear physical significance, such as the cylinder cap vibration of internal combustion engine
Dynamic signal is generally made of igniter shock, valve opening and closing impact etc.；Reciprocating compressor cylinder vibration signal is generally impacted by valve block
Vibration composition.Impact initial point is an important feature of local assault signal, may generally serve as Fault-Sensitive feature for equipment
Fault diagnosis, such as the impact initial point feature of engine valve opening and closing can be used for diagnosing valve clearance abnormal failure.
Currently, extracting for vibration and shock signal initial point, threshold decision is one of most common technology.For single part
For impact signal, the position that vibration amplitude passes through threshold line for the first time is generally taken as impact initial point.But due to the setting of threshold value
It is usually empirically determined, in the actual complex vibration signal being made of the impact of multiple and different amplitudes, generally existing threshold value
Set unreasonable or poor adaptivity problem.In addition, the impact initial point recognition methods based on energy maximum rising gradient can
Achieve the purpose that adaptive polo placement, but actual vibration signal is influenced by many disturbing factors, impacts the vibrational energy of initial position
Amount rising gradient may be the greater in the shock zone, rather than the maximum, by identifying energy gradient maximum value position
Extracting method often there is large error.
The characteristics of present invention is according to shock zone energy variation, in conjunction with Teager energy operator in identification transient oscillation variation
The advantage of aspect is extracted the larger value point that energy rising gradient meets setting condition by designing reasonable rules self-adaptive, is mentioned
The adaptive accurate new method for extracting of a kind of vibratory impulse initial point based on Teager energy operator rising gradient out, to overcome biography
Threshold value setting adaptivity is poor in system method, problem of computational accuracy difference, is impacted with reaching adaptive accurate extraction vibration signal
The purpose of initial point.
Summary of the invention
It is an object of the invention to not high for existing impact initial point extracting method bad adaptability, the precision generallyd use
Problem provides a kind of impact initial point based on Teager energy operator rising gradient adaptively accurate extracting method.
The invention is realized by the following technical scheme: carrying out the processing of EMD adaptive-filtering to vibration signal first；Then it counts
Calculate Teager energy operator, prominent transient oscillation impact energy；Gradient is asked to local energy operator again, obtains the calculation of Teager energy
Sub- gradient；It is proposed k- gradient and k- gradient neighborhood concept, and using first point of the k- gradient neighborhood in time series as
Impact starting point；Characteristic paracycle finally impacted according to reciprocating mechanical vibration signal carries out calculated result using 3- σ criterion
Outlier is examined, and optimizes the calculated result of outlier by adjust automatically k value and the criterion of setting, to reach adaptive essence
Really extract the purpose of vibration signal impact initial point.
1, a kind of reciprocating mechanical vibration signal based on energy operator k- gradient impacts initial point self-adaptation extraction method, special
Sign be the following steps are included:
(1) actually measured reciprocating machine vibration signal complete cycle is carried out based on empirical mode decomposition (Empirical
Mode Decomposition, EMD) adaptive-filtering pretreatment；
(2) angular domain resampling is carried out to above-mentioned filtered discrete signal；
(3) the local T eager energy operator at each data point is calculated；
(4) positive integer k is initially set, the k- gradient of energy operator is calculated, is extracted in energy gradient time series
Position where belonging to the energy gradient of k- gradient neighborhood for the first time is used as impact initial point；
(5) according to the stable periodicity of reciprocating machine vibration and shock signal, the flat of n signal complete cycle impact initial point is calculated
Mean μ and standard deviation sigma, the outlier of 3 σ or more of deviation average, then change k value and recalculate, by adjusting k repeatedly if it exists
Value, until meeting termination condition, determines final impact initial point.
2, in above-mentioned steps (1), after EMD adaptive decomposition, each intrinsic modal components (Intrinsic Mode is obtained
Function, IMF), the Pearson correlation coefficient r of each IMF component and original signal is calculated, is calculated by following formula:
Wherein, x indicates original signal, and j indicates the serial number of IMF component, and IMF (j) indicates j-th of IMF component, Cov (IMF
(j), x) indicate the covariance of IMF (j) and x, Var [IMF (j)] and Var [x] respectively indicate the variance of IMF (j) He x, r (j) table
Show the related coefficient of IMF (j) Yu x.
Then selection related coefficient carries out weight not less than each intrinsic modal components of threshold value c (taking the number between 0.1~0.5)
Structure.
2, in above-mentioned steps (2), angular domain resampling using angularly method for resampling, angle interval d take 0.1~0.5 it
Between numerical value.
3, in above-mentioned steps (3), the local T eager energy operator in discrete-time series vibration signal x is counted according to the following formula
It calculates:
ψd(i)=| x2(i)-x(i-1)x(i+1)|
Wherein x indicates that the vibration signal obtained after angular domain resampling, i indicate point serial number, x (i-1), x (i), x (i+1)
Respectively indicate numerical value of the x at Serial No. i-1, i, i+1, ψd(i) the Teager energy operator at serial number i is indicated.
4, k- gradient involved in above-mentioned steps (4), is defined as follows: to random natural number k, definition energy gradient is energy
Operator ψdGradient at i, with D ψd(i) it indicates, k- gradient D ψk-gradIt indicates in energy gradient sequence, meets following two item
The energy gradient of part:
(1) in energy gradient sequence, at least there are k point p and meet D ψd(p)≥Dψk-grad；
(2) in energy gradient sequence, at most there are k-1 point p and meet D ψd(p) > D ψk-grad；
K- gradient D ψk-gradCalculating step: first calculating time series in all positions energy gradient, D ψd(i)
=ψd(i+1)-ψd(i)；Then the energy gradient of each position is subjected to descending arrangement, select obtained by sequence k-th of value as k-
Gradient.
5, k- gradient neighborhood N involved in above-mentioned steps (4)k, it is defined as follows: the k- gradient D of given energy operator
ψk-grad, k- gradient neighborhood NkTo be not less than D ψ comprising gradient valuek-gradAll energy gradient values.
6, the selection of initial k value involved in above-mentioned steps (4), the present invention provide two schemes, scheme one: directly select
Natural number between 5~20；Scheme two: it is determined based on " variance is minimum " principle, i.e. calculating multi-group data is under different value of K
The variance of result is extracted, the corresponding k value of variance minimum result is selected, as k initial value.
7, average value mu and standard deviation sigma involved in above-mentioned steps (5) are calculated by following formula:
Wherein, n for taken complete cycle vibration signal group number；Y is that the impact initial point of n group vibration signal extracts result group
At array；Q indicates that the sequence number of y array, y (q) are that the impact initial point of q group vibration signal complete cycle extracts result.
8, change the strategy of k value involved in above-mentioned steps (5) for outlier are as follows: setting adjusting step step (take 1~
3), when calculated result is greater than 3 times of standard deviations of average value or more, then k value is adjusted to the direction of increase；When calculated result is less than
Below average value when 3 times of standard deviations, then k value is adjusted to reduced direction.Adjustment k value during meet following two condition it
First terminate, condition one: new calculated result is judged as non-outlier, i.e. calculated result is within 3 times of variances of average value；
Condition two: reach m adjustment (m value 5~20) of setting.If calculating process finally with the termination of condition two, takes m calculating knot
Near the result of average value as impact initial point in fruit.
Each step of the invention is described in further detail below, as follows:
The first step carries out the pretreatment of EMD adaptive-filtering to reciprocating machine vibration signal complete cycle, and selects and original letter
Number Pearson correlation coefficient not less than threshold value c (value 0.1~0.5) modal components carry out signal reconstruction, obtain signal s
(i)；
Second step carries out angularly angular domain resampling to s (i), and sampling angle interval d value 0.1~0.5 obtains signal x
(i)；
Third step calculates the discrete signal x (i) after EMD adaptive-filtering and angular domain resampling at each data point i
Local T eager energy operator ψd(i)=| x2(i)-x(i-1)x(i+1)|；
4th step calculates local energy operator ψd(i) energy gradient D ψd(i)=ψd(i+1)-ψd(i)；Then by everybody
The energy gradient set carries out descending arrangement, and initial k value is selected (to directly select the natural number between 5~20, or calculate multi-group data
The variance that result is extracted under different value of K, selects the corresponding k value of variance minimum result as k initial value), take energy gradient to drop
K-th of value is as k- gradient in sequence arrangement gained sequence；And then whole numbers of k- gradient will be not less than in energy gradient sequence
Value extracts, and obtains k- gradient field Nk；First is finally extracted in the time series of energy operator belongs to k- gradient neck
Domain NkPoint, as impact initial point.
5th step calculates n (taking the number between 20~40) a complete cycle using the quasi periodic of reciprocating mechanical vibration signal
Signal impacts the average value of initial point position y (q)And standard deviationUsing 3 σ criterion
The judgement of discrete point is carried out, and the method for recycling adjustment k value is calculated.The method of adjustment of k value are as follows: setting adjusting step first
Step (taking 1~3) and cycle-index m (m value 5~20) adjusts k value and recalculates extraction as a result, to new calculated result
Outlier judgement is carried out, if it is determined that being non-outlier, then terminates calculating；If being still judged as outlier, continue to adjust the repetition of k value
Above-mentioned calculating process, until cycle calculations number reaches setting value m.The adjustable strategies of k value are as follows: if calculated result is greater than average value
Above 3 times of standard deviations then adjust k value to the direction of increase；If calculated result is less than 3 times of standard deviations of average value or less, by k
It is worth to reduced direction adjustment.
Detailed description of the invention
Fig. 1 engine cylinder head system signal complete cycle original waveform
Engine cylinder head system complete cycle signal of the Fig. 2 after EMD adaptive-filtering and angularly angular domain resampling
The Teager energy operator of Fig. 3 cylinder-head vibration signals complete cycle
Initial point is impacted in the case of the initial k=15 of Fig. 4 extracts result
Fig. 5 outlier treated impact initial point extract result
Specific embodiment
In order to be best understood from technical solution of the present invention, the present invention is rushed in internal combustion engine valve-closing below in conjunction with attached drawing
The application in terms of start-phase feature extraction is hit to be described in further detail.
The first step, engine cylinder head system signal complete cycle is as shown in Figure 1, carry out EMD adaptive decomposition to cylinder-head vibration signals
Intrinsic modal components are obtained, the sheet for being not less than given threshold c=0.4 with the Pearson correlation coefficient of original vibration signal is chosen
Sign modal components are reconstructed, and obtain adaptive-filtering treated signal s (i)；
Second step carries out angularly angular domain resampling to s (i), and sampling angle interval d value 0.1~0.5 obtains signal x
(i), as shown in Figure 2；
Third step calculates the local T eager energy operator at the above-mentioned filtered each data point i of discrete signal x (i)
ψd(i)=| x2(i)-x (i-1) x (i+1) |, calculated result is as shown in Figure 3；
4th step, this example are illustrated for the exhaust valve closing impact in 0~90 ° of crank angle in map.It calculates
Local energy operator ψd(i) energy gradient D ψd(i)=ψd(i+1)-ψd(i)；K=1, k=5, k=10, k=15, k=are set
20, and calculate k- gradient and be respectively as follows: D ψ1-grad=1.43x105,Dψ5-grad=7.58x104,Dψ10-grad=5.69x104,D
ψ15-grad=4.31x104,Dψ20-grad=2.64x104；And then determine corresponding k- gradient field Nk, first in time series
It is a to belong to NkThe serial number of point be respectively as follows: PK=1=137, PK=5=120, PK=10=120PK=15=120, PK=20=109, then on
It states a serial number and corresponds to impact initial point under different value of K, be converted in angular domain phase and be respectively as follows: Select the corresponding side of each group k value
Difference is respectively as follows: σK=1=29.65, σK=5=11.65, σK=10=4.99, σK=15=3.61, σK=20=3.94, therefore select k=
15 are used as initial value.Select 480 groups complete cycle vibrational waveform, in initial k=15, extract calculated result it is as shown in Figure 4.
4th step, in initial k=15, above-mentioned 480 groups of complete cycles of signal vibrational waveform, target impact initial point position
Average value mu=14.48 and standard deviation sigma=3.61 of y (i), there are 4 calculated results to be greater than 3 times of standard deviations of average value or more
Outlier and 3 are less than the outlier of 3 times of standard deviations of average value or less, and for each outlier, adjusting k value repeatedly, (step-length is
2), before reaching the cycle-index m=10 of setting, each outlier is all satisfied 3 σ criterion, as a result as shown in Figure 5.
Claims (8)
1. a kind of reciprocating mechanical vibration signal based on energy operator k- gradient impacts initial point self-adaptation extraction method, feature exists
In the following steps are included:
(1) adaptive-filtering based on empirical mode decomposition is carried out to actually measured reciprocating machine vibration signal complete cycle to locate in advance
Reason；
(2) angular domain resampling is carried out to above-mentioned filtered discrete signal；
(3) the local T eager energy operator at each data point is calculated；
(4) positive integer k is initially set, the k- gradient of energy operator is calculated, is extracted in energy gradient time series for the first time
Position where belonging to the energy gradient of k- gradient neighborhood is used as impact initial point；
(5) according to the quasi periodic of reciprocating machine vibration and shock signal, the average value mu of n signal complete cycle impact initial point is calculated
And standard deviation sigma, the outlier of 3 σ or more of deviation average, then change k value and recalculate, by adjusting k value repeatedly, directly if it exists
To termination condition is met, final impact initial point is determined.
2. according to the method described in claim 1, it is characterized by: after EMD adaptive decomposition, being obtained each in above-mentioned steps (1)
Intrinsic modal components calculate the Pearson correlation coefficient r of each IMF component and original signal, are calculated by following formula:
Wherein, x expression original signal, the serial number of j expression IMF component, IMF (j) j-th of IMF component of expression, Cov (IMF (j),
X) covariance of IMF (j) and x are indicated, Var [IMF (j)] and Var [x] respectively indicate the variance of IMF (j) He x, and r (j) is indicated
The related coefficient of IMF (j) and x.
Then each intrinsic modal components of the selection related coefficient not less than threshold value c are reconstructed, and wherein c takes between 0.1~0.5
Number.
3. according to the method described in claim 1, it is characterized by: angular domain resampling use angularly weighs in above-mentioned steps (2)
The method of sampling, angle interval d take the numerical value between 0.1~0.5.
4. according to the method described in claim 1, it is characterized by: in above-mentioned steps (3), discrete-time series vibration signal x
In local T eager energy operator calculate according to the following formula:
ψd(i)=| x2(i)-x(i-1)x(i+1)|
Wherein x indicates that the vibration signal obtained after angular domain resampling, i indicate point serial number, and x (i-1), x (i), x (i+1) are respectively
Indicate numerical value of the x at Serial No. i-1, i, i+1, ψd(i) the Teager energy operator at serial number i is indicated.
5. according to the method described in claim 1, it is characterized by: k- gradient involved in above-mentioned steps (4), is defined as follows:
To random natural number k, definition energy gradient is energy operator ψdGradient at i, with D ψd(i) it indicates, k- gradient D ψk-gradTable
Show in energy gradient sequence, meet the energy gradient of following two condition:
1) in energy gradient sequence, at least there are k point p and meet D ψd(p)≥Dψk-grad；
2) in energy gradient sequence, at most there are k-1 point p and meet D ψd(p) > D ψk-grad；
K- gradient D ψk-gradCalculating step: first calculating time series in all positions energy gradient, D ψd(i)=ψd(i
+1)-ψd(i)；Then the energy gradient of each position is subjected to descending arrangement, select obtained by sequence k-th of value as k- gradient；
The k- gradient neighborhood N being related tok, it is defined as follows: the k- gradient D ψ of given energy operatork-grad, k- gradient neighborhood NkFor comprising
Gradient value is not less than D ψk-gradAll energy gradient values.
6. according to the method described in claim 1, it is characterized by: the selection of initial k value involved in above-mentioned steps (4), is adopted
With one of following two schemes, scheme one: the natural number between 5~20 is directly selected；Scheme two: based on " variance is minimum " principle
It is determined, that is, calculates the variance that multi-group data extracts result under different value of K, select the corresponding k value of variance minimum result, make
For k initial value.
7. according to the method described in claim 1, it is characterized by: average value mu and standard deviation sigma involved in above-mentioned steps (5)
It is calculated by following formula:
Wherein, n for taken complete cycle vibration signal group number；Y is that the impact initial point of n group vibration signal extracts result composition
Array；Q indicates that the sequence number of y array, y (q) are that the impact initial point of q group vibration signal complete cycle extracts result.
8. according to the method described in claim 1, it is characterized by: changing k value for outlier involved in above-mentioned steps (5)
Strategy are as follows: set adjusting step step as 1~3, when calculated result is greater than 3 times of standard deviations of average value or more, then by k value to
The direction of increase adjusts；When calculated result is less than 3 times of standard deviations of average value or less, then k value is adjusted to reduced direction；It adjusts
Meet first terminating for following two condition during whole k value, condition one: new calculated result is judged as non-outlier, that is, counts
Result is calculated to be within 3 times of variances of average value；Condition two: reach m adjustment of setting, m takes 5~20, if calculating process is most
Eventually with the termination of condition two, then take in m calculated result near the result of average value as impact initial point.
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| CN110954312B (en) * | 2020-02-19 | 2020-11-20 | 北京化工大学 | Reciprocating mechanical fault diagnosis method based on keyless phase whole-cycle signal |
| CN112183344A (en) * | 2020-09-28 | 2021-01-05 | 广东石油化工学院 | Large unit friction fault analysis method and system based on waveform and dimensionless learning |
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