CN105631238A - Method and system for detecting vibration performance variation of antifriction bearing - Google Patents

Abstract

The invention relates to a method and system for detecting vibration performance variation of an antifriction bearing. The method comprises the steps that firstly, vibration data sequences of the antifriction bearing at different time stages are obtained; secondly, absolute values of the vibration data of the antifriction bearing are obtained, an absolute value collating sequence is obtained, and the median of the absolute value collating sequence is found out; thirdly, an improved data sequence of the absolute value collating sequence and the average value of the improved data sequence are obtained according to the Huber M estimation principle, and the absolute difference between the average value of the improved data sequence and the median of the absolute value collating sequence is calculated; fourthly, a local eigen section and a total eigen section are obtained according to the absolute difference; finally, the vibration performance variation rate of the antifriction bearing is calculated according to the total eigen section, and the degradation situation of the vibration performance of the antifriction bearing can be detected according to the variation rate. According to the method and system, it is not required to assume a performance degradation model, the distribution law, the probability density function and threshold values in advance, the total eigen section can be directly acquired after sound processing of the bearing vibration data measured actually, and performance degradation detection is achieved.

Description

The detection method of a kind of bearing vibration performance variation and system

Technical field

The present invention relates to the detection method of a kind of bearing vibration performance variation and system, belong to degeneration detection technique field.

Background technology

Rolling bearing performance mainly comprises vibration, noise, moment of friction, temperature rise, running accuracy etc., and the operating performance of mechanical system is had material impact by these performances. Vibration is an important performance indexes of rolling bearing, comprehensively reflects the factors such as the manufacture of bearing, installation, lubrication, has influence on the kinetic characteristic of bearing, life-span and reliability. The method of disclosed research bearing vibration performance mainly contains temporal signatures and the neural network method of bearing vibration signal data at present, the spectroscopic analysis of bearing vibration signal, the grey self-service method of bear vibration data, based on the bear vibration specificity analysis method of Hilbert-Huang, based on the analytical method etc. of the bearing vibration characteristic parameter of phase space. These methods need to assume specific Performance Degradation Model, distribution rule, probability density function and threshold value in advance, and do not relate to the robustness problem of bearing vibration data. Such as application number be 201410058010.0 patent application document disclose a kind of bearing vibration performance reliability mutation process detection method and device, it is by carrying out variation intensity raw information self-service sampling again, simulate a large amount of generation information of variation intensity, information is generated by grey prediction models treated, obtaining variation intensity estimated value, whole testing process needs self-service for ash principle is incorporated Poisson process. This patent application document visible both needs to realize the grey prediction model supposed, lacks again the robustness Study on Problems to bearing vibration data.

Summary of the invention

It is an object of the invention to provide the detection method of a kind of bearing vibration performance variation and system, lack, to solve during current rolling bearing performance variation detects, the problem its robustness detected.

The present invention provides the detection method of a kind of bearing vibration performance variation for solving the problems of the technologies described above, and the step of this detection method is as follows:

1) vibration of rolling bearing during one's term of military service in the different time stage is measured, obtain the bearing vibration data in different time stage, and formed the data sequence of m time phase;

2) by bearing vibration data fetch absolute value, according to order from small to large, absolute value collating sequence Y is obtained_i, and determine the median of this sequence;

3) to absolute value collating sequence Y_iCarry out HuberM estimation, the data that are improved sequence, and the mean value of computed improved sequence;

4) absolute difference of computed improved data sequence average value and absolute value collating sequence median;

5) by improving between the intrinsic region, absolute difference computation office territory of data sequence average value and absolute value collating sequence median and between overall intrinsic region;

6) by overall intrinsic interval computation bearing vibration performance variation rate, the variation situation of bearing vibration performance can be detected out according to aberration rate.

Described step 3) the improvement data sequence that obtains is Z_i(n₁,n₂) it is:

Z_i(n₁,n₂)={ z_i(n; n₁,n₂); I=1,2 ..., m; N=1,2 ..., N

Wherein Z_i(n₁,n₂) for improving data sequence, z_i(n; n₁,n₂) for improving the n-th data of data sequence, i is time phase sequence number, and n is data sequence number, N is the data amount check that i-th time phase obtains, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

Described step 5) in deterministic process between intrinsic region, office territory as follows:

A. the absolute difference D improving data sequence average value and absolute value collating sequence median is found_i(n₁,n₂) minimum value D_imin;

B. D is calculated_iminThe first data y of corresponding left sequence_iB () and right sequence mantissa are according to y_iE () is respectively K_i1And K_i2, [K_i1,K_i2] be between the intrinsic region, office territory of i-th time phase.

Described step 5) in [K between overall intrinsic region_min1,K_min2] it is [K between the intrinsic region, office territory by i-th time phase_i1,K_i2] obtain, K_min1It is K_i1Minimum value, K_min2It is K_i2Minimum value; I is time phase sequence number; I=1,2 ..., m; M is time phase number.

Described step 6) in aberration rate v_iFor:

$v_i=\frac{n_{vi}}{N}\×100\%;i=1,2,...,m$

Wherein v_iFor bearing vibration performance variation rate, n_viIt is i-th time phase bear vibration data absolute value not [K between overall intrinsic region_min1,K_min2] in data amount check, K_min1For floor value between overall intrinsic region, K_min2For upper bound value between overall intrinsic region, i is time phase sequence number, and m is time phase number, and N is the data amount check that i-th time phase obtains.

Present invention also offers the detection system of a kind of bearing vibration performance variation, this detection system comprises measures module, series processing module, HuberM estimation module, absolute difference computation module, intrinsic interval computation module and aberration rate calculating module,

Described measurement module is used for the vibration of rolling bearing during one's term of military service in the different time stage being measured, and obtains the bearing vibration data in different time stage, and is formed the data sequence of m time phase;

Described series processing module is used for bearing vibration data fetch absolute value, according to order from small to large, obtains absolute value collating sequence Y_i, and determine the median of this sequence;

Described HuberM estimation module is used for absolute value collating sequence Y_iCarry out HuberM estimation, the data that are improved sequence, and the mean value of computed improved sequence;

Described absolute difference computation module is used for the absolute difference of computed improved data sequence average value and absolute value collating sequence median;

Described intrinsic interval computation module is between the intrinsic region, absolute difference computation office territory according to improvement data sequence average value and absolute value collating sequence median and between overall intrinsic region;

Described aberration rate calculates module and is used for according to overall intrinsic interval computation bearing vibration performance variation rate, can detect out the variation situation of bearing vibration performance according to aberration rate.

The improvement data sequence that described HuberM estimation module obtains is Z_i(n₁,n₂) it is:

Z_i(n₁,n₂)={ z_i(n; n₁,n₂); I=1,2 ..., m; N=1,2 ..., N

Wherein Z_i(n₁,n₂) for improving data sequence, z_i(n; n₁,n₂) for improving the n-th data of data sequence, i is time phase sequence number, and n is data sequence number, N is the data amount check that i-th time phase obtains, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

Process between intrinsic region, described intrinsic interval computation module calculating office territory is as follows:

A. the absolute difference D improving data sequence average value and absolute value collating sequence median is found_i(n₁,n₂) minimum value D_imin;

B. D is calculated_iminThe first data y of corresponding left sequence_iB () and right sequence mantissa are according to y_iE () is respectively K_i1And K_i2, [K_i1,K_i2] be between the intrinsic region, office territory of i-th time phase.

[K between described overall intrinsic region_min1,K_min2] it is [K between the intrinsic region, office territory by i-th time phase_i1,K_i2] obtain, K_min1It is K_i1Minimum value, K_min2It is K_i2Minimum value; I is time phase sequence number; I=1,2 ..., m; M is time phase number.

Described bearing vibration performance variation rate v_iFor:

$v_i=\frac{n_{vi}}{N}\×100\%;i=1,2,...,m$

Wherein v_iFor bearing vibration performance variation rate, n_viIt is i-th time phase bear vibration data absolute value not [K between overall intrinsic region_min1,K_min2] in data amount check, K_min1For floor value between overall intrinsic region, K_min2For upper bound value between overall intrinsic region, i is time phase sequence number, and m is time phase number, and N is the data amount check that i-th time phase obtains.

The detection method of a kind of bearing vibration performance variation of the present invention and system be project approval number be 51475144 state natural sciences fund subsidy under complete.

The invention has the beneficial effects as follows: first the vibration of rolling bearing during one's term of military service in the different time stage measured by the present invention, to obtain the bearing vibration data sequence in different time stage; Then by bearing vibration data fetch absolute value, according to order from small to large, obtain absolute value collating sequence and find out absolute value collating sequence median; According to HuberM estimation principle, obtain it and improve data sequence and improve data sequence average value; The absolute difference of computed improved data sequence average value and absolute value collating sequence median; By the absolute difference improving data sequence average value and absolute value collating sequence median, obtain between innings intrinsic region, territory and between overall intrinsic region; By overall intrinsic interval computation bearing vibration performance variation rate, the degraded condition of bearing vibration performance can be detected out according to aberration rate. The present invention does not need to assume Performance Degradation Model, distribution rule, probability density function and threshold value in advance, bear vibration data reality measured directly obtain between overall intrinsic region after carrying out saneization process, and then implement performance degradation detection, for detection and the engineer applied thereof of bearing vibration performance provides novel method.

Accompanying drawing explanation

Fig. 1 raceway lesion diameter d₁The bearing vibration data sequence X of=0mm₁Schematic diagram;

Fig. 2 raceway lesion diameter d₂The bearing vibration data sequence X of=0.1778mm₂Schematic diagram;

Fig. 3 raceway lesion diameter d₃The bearing vibration data sequence X of=0.5334mm₃Schematic diagram;

Fig. 4 raceway lesion diameter d₄The bearing vibration data sequence X of=0.7112mm₄Schematic diagram;

The graph of a relation of Fig. 5 bearing vibration performance variation rate and time phase;

The graph of a relation of Fig. 6 raceway lesion diameter and bearing vibration performance variation rate.

Embodiment

Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described further.

Data according to modern statistics steadily and surely change principle, and the robustness of data is one of most primary condition of data analysis, and data are more sane, and the detected result of acquisition is more reliable. Therefore, the saneization treatment process of data just seems extremely important. HuberM estimate and medion estimator be in modern statistics data steadily and surely change process minimization maximum principle under two kinds of optimal estimations, HuberM estimates to reflect conceptual data situation, there is threshold value, and centered by data zero, be the odd function about zero centrosymmetry, actual engineering technology problem is difficult to meet this condition, lack practicality, medion estimator is a robust data, it is possible to reflection Data Position feature, but can not reflect conceptual data situation. Therefore two kinds of optimal estimations are organically blended by the present invention, have complementary advantages, propose a kind of to reflect that Data Position feature can reflect that again the data of conceptual data situation steadily and surely change treatment process, for assessment of the variability of bearing vibration data, to detect rolling bearing performance degradation situation during one's term of military service.

The embodiment of the detection method of a kind of bearing vibration performance variation of the present invention

The situation causing bearing vibration acceleration to morph for channel surface abrasion below is described, and variation root specifically arrives the damage of rolling bearing inner ring raceway groove. Experimental data in the present embodiment is from the bearing Data centre website of U.S. CaseWesternReserveUniversity, and this center has a special rolling bearing fault simulated experiment platform. Experiment table is made up of electric motor, torque transducer/decoder and power test meter etc. SKF6205 roller bearings to be detected the rotating shaft of electric motor, measures bearing vibration acceleration with acceleration transducer, and unit is V. Bearing rotating speed is 1797r/min, and sample frequency is 12kHz, rolling bearing inner ring raceway groove lesion diameter d_iIt is respectively d₁=0mm, d₂=0.1778mm, d₃=0.5334mm and d₄=0.7112mm; I is sequence number; I=1,2,3,4.

1. pair during one's term of military service the vibration of rolling bearing in the different time stage is measured, and obtains the bearing vibration data in different time stage, forms the data sequence of m time phase, and wherein the data sequence of i-th time phase is X_i:

X_i={ x_i(n) }; N=1,2 ..., N; I=1,2 ..., m (1)

In formula, X_iBeing the bearing vibration data sequence of i-th time phase, i is time phase sequence number, and n is data sequence number, x_iN () is the n-th data of i-th time phase, N is the data amount check that i-th time phase obtains, and m is time phase number.

The implementation case is respectively by 4 kinds of lesion diameter d₁=0mm, d₂=0.1778mm, d₃=0.5334mm and d₄The bearing vibration data series model obtained under=0.7112mm is the bearing vibration data sequence X obtained in 4 time phases₁, X₂, X₃And X₄; I=1,2,3,4; I is time phase sequence number; Time phase number m=4; Each vibration data sequence has N=1600 data, and the bearing vibration data sequence obtained is as shown in Figure 1 to 4.

2. obtain absolute value collating sequence

By bearing vibration data fetch absolute value, according to order from small to large, obtain absolute value collating sequence Y_i:

Y_i={ y_i(n) }; I=1,2 ..., m; N=1,2 ..., N (2)

In formula, Y_iFor absolute value collating sequence, i is time phase sequence number, and n is data sequence number, and N is the data amount check that i-th time phase obtains, and m is time phase number, y_iN () is the n-th data in absolute value collating sequence.

3., according to statistics, find out absolute value collating sequence median ��_i:

In formula, ��_iFor absolute value collating sequence median; I is time phase sequence number; N is the data amount check that i-th time phase obtains; M is time phase number; y_iN () is the n-th data in absolute value collating sequence; N is data sequence number; N=1,2 ..., N; N is the data amount check that i-th time phase obtains.

4., according to HuberM estimation principle, obtain and improve data sequence

Assume y_i(b) and y_iE () is b data in absolute value collating sequence and the e data respectively, b and e is 1,2 ..., two data in N, and y_i(b)�ܦ�_i, ��_i��y_i(e); Definition order y from small to large_i(b),��,��_iCollating sequence be left sequence; The data amount check of left sequence is n₁; y_iB () is the first data of left sequence; Definition order �� from small to large_i,��,y_iE the collating sequence of () is right sequence; The data amount check of right sequence is n₂; y_iE () is right sequence mantissa certificate.

According to HuberM estimation principle, work as y_i(n)��y_iTime (b), use y_iB () replaces y_i(n); Work as y_i(n)��y_iTime (e), use y_iE () replaces y_i(n). The data sequence Z so being improved_i(n₁,n₂):

Z_i(n₁,n₂)={ z_i(n; n₁,n₂); I=1,2 ..., m; N=1,2 ..., N (4)

In formula, Z_i(n₁,n₂) for improving data sequence, z_i(n; n₁,n₂) for improving the n-th data of data sequence, i is time phase sequence number, and n is data sequence number, N is the data amount check that i-th time phase obtains, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

5., according to statistics, obtain and improve data sequence average value ��_i(n₁,n₂):

${\mathrm{\η}}_i(n_1,n_2)=\frac{1}{N}\underset{n=1}{\overset{N}{\Σ}}{z}_i(n;n_1,n_2);i=1,2,...,m---\left(5\right)$

In formula, ��_i(n₁,n₂) for improving data sequence average value, z_i(n; n₁,n₂) for improving the n-th data of data sequence, i is time phase sequence number, and n is data sequence number, N is the data amount check that i-th time phase obtains, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

6. the absolute difference D of computed improved data sequence average value and absolute value collating sequence median_i(n₁,n₂):

D_i(n₁,n₂)=| ��_i-��_i(n₁,n₂) |; I=1,2 ..., m (6)

In formula, D_i(n₁,n₂) for improving the absolute difference of data sequence average value and absolute value collating sequence median, ��_iFor absolute value collating sequence median, ��_i(n₁,n₂) for improving data sequence average value, i is time phase sequence number, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

7. [K between intrinsic region, acquisition office territory_i1,K_i2] and overall intrinsic region between [K_min1,K_min2]

Sane feature according to modern statistics median, gets n when N is even number₁=n₂=1,2 ..., N/2; N gets n when being odd number₁=n₂=1,2 ..., (N+1)/2; N is the data amount check that i-th time phase obtains; I is time phase sequence number; n₁For the data amount check of left sequence; n₂For the data amount check of right sequence. Get different n₁And n₂Value, obtains different improvement data sequence average values and the absolute difference D of absolute value collating sequence median_i(n₁,n₂). Data robustness according to modern statistics is theoretical, and for robust data, significance level is ��=(n₁+n₂)/N=0��0.1, ultimate value is 0.1.

Find D_i(n₁,n₂) minimum value D_imin, D_iminThe first data y of corresponding left sequence_iB () and right sequence mantissa are according to y_iE () is respectively K_i1And K_i2; It is [K between the intrinsic region, office territory of i-th time phase_i1,K_i2]; K_i1For floor value between intrinsic region, office territory; K_i2For upper bound value between intrinsic region, office territory. By [K between the intrinsic region, office territory of i-th time phase_i1,K_i2], obtain [K between overall intrinsic region_min1,K_min2]; K_min1It is K_i1Minimum value, K_min2It is K_i2Minimum value; I is time phase sequence number; I=1,2 ..., m; M is time phase number.

By calculating, obtaining between the intrinsic region, office territory of 4 time phases and as shown in table 1 between overall intrinsic region in the present embodiment, corresponding significance level is 0.1.

Table 1

8. obtain aberration rate, detect the degraded condition of bearing vibration performance according to aberration rate.

Aberration rate is the judging quota of bearing vibration performance variation, and aberration rate is more big, and bearing vibration performance variation is more big, and performance becomes more poor, and performance degradation is more serious, lost efficacy possibility is more big.

At i-th time phase, if the absolute value of certain vibration data not [K between overall intrinsic region_min1,K_min2] in, then claim this vibration data for variation data; Variation data representation rolling bearing performance there occurs variation, degree of variation aberration rate v_iCharacterize:

$v_i=\frac{n_{vi}}{N}\×100\%;i=1,2,...,m---\left(7\right)$

In formula, v_iFor bearing vibration performance variation rate, n_viIt is i-th time phase bear vibration data absolute value not [K between overall intrinsic region_min1,K_min2] in data amount check, K_min1For floor value between overall intrinsic region, K_min2For upper bound value between overall intrinsic region, i is time phase sequence number, and m is time phase number, and N is the data amount check that i-th time phase obtains.

In the present embodiment, in 4 time phases, the changing conditions of bearing vibration performance variation rate is as shown in Figure 5, in 4 time phases, the relation of raceway groove lesion diameter and bearing vibration performance variation rate is as shown in Figure 6, therefrom can see, when raceway groove lesion diameter is 0mm, aberration rate is very little, only has 10%, shows that rolling bearing military service performance is in standard state, there is no performance degradation sign, the possibility that bearing did not almost lose efficacy; When raceway groove lesion diameter is 0.1778mm, aberration rate increases a lot, reaches 59%, shows that rolling bearing military service performance enters abnomal condition, and performance starts to degenerate, and bearing has inefficacy sign, should pay close attention to bearing operation conditions or change bearing; When raceway groove lesion diameter is 0.5334mm, aberration rate increases gradually, reaches 74%, shows that the abnomal condition of rolling bearing military service performance is aggravated gradually, and performance degradation phenomenon worsens gradually, and bearing failure hidden danger is aggravated, it is necessary to out of service, changes bearing; When raceway groove lesion diameter is 0.7112mm, aberration rate increases rapidly, reaches 89%, shows that the abnomal condition of rolling bearing military service performance is aggravated rapidly, and performance degradation phenomenon worsens rapidly, and bearing lost efficacy, it is possible to serious accident can occur.

The embodiment of the detection system of a kind of bearing vibration performance variation of the present invention

Detection system in the present embodiment comprises measures module, series processing module, HuberM estimation module, absolute difference computation module, intrinsic interval computation module and aberration rate calculating module, wherein measure module to be used for the vibration of rolling bearing during one's term of military service in the different time stage being measured, obtain the bearing vibration data in different time stage, and formed the data sequence of m time phase; Series processing module is used for bearing vibration data fetch absolute value, according to order from small to large, obtains absolute value collating sequence Y_i, and determine the median of this sequence; HuberM estimation module is used for absolute value collating sequence Y_iCarry out HuberM estimation, the data that are improved sequence, and the mean value of computed improved sequence; Absolute difference computation module is used for the absolute difference of computed improved data sequence average value and absolute value collating sequence median; Intrinsic interval computation module is between the intrinsic region, absolute difference computation office territory according to improvement data sequence average value and absolute value collating sequence median and between overall intrinsic region; Aberration rate calculates module and is used for according to overall intrinsic interval computation bearing vibration performance variation rate, can detect out the variation situation of bearing vibration performance according to aberration rate. The specific implementation of each module is described in detail in the embodiment of method, repeats no more here.

Under the thinking that the present invention provides; the mode easily expected to those skilled in the art is adopted the technique means in above-described embodiment to be converted, replace, revise; and the goal of the invention substantially identical, that realize of the relevant art means in the effect played and the present invention is also substantially identical; above-described embodiment is carried out fine setting and is formed by the technical scheme formed like this, and this kind of technical scheme still falls within the scope of protection of the present invention.

Claims (10)

1. the detection method of a bearing vibration performance variation, it is characterised in that, the step of this detection method is as follows:

1) vibration of rolling bearing during one's term of military service in the different time stage is measured, obtain the bearing vibration data in different time stage, and formed the data sequence of m time phase;

2) by bearing vibration data fetch absolute value, according to order from small to large, absolute value collating sequence Y is obtained_i, and determine the median of this sequence;

3) to absolute value collating sequence Y_iCarry out HuberM estimation, the data that are improved sequence, and the mean value of computed improved sequence;

4) absolute difference of computed improved data sequence average value and absolute value collating sequence median;

5) by improving between the intrinsic region, absolute difference computation office territory of data sequence average value and absolute value collating sequence median and between overall intrinsic region;

6) by overall intrinsic interval computation bearing vibration performance variation rate, the variation situation of bearing vibration performance can be detected out according to aberration rate.

2. the detection method of bearing vibration performance variation according to claim 1, it is characterised in that, described step 3) the improvement data sequence that obtains is Z_i(n₁,n₂) it is:

Z_i(n₁,n₂)={ z_i(n; n₁,n₂); I=1,2 ..., m; N=1,2 ..., N

Wherein Z_i(n₁,n₂) for improving data sequence, z_i(n; n₁,n₂) for improving the n-th data of data sequence, i is time phase sequence number, and n is data sequence number, N is the data amount check that i-th time phase obtains, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

3. the detection method of bearing vibration performance variation according to claim 1, it is characterised in that, described step 5) in deterministic process between intrinsic region, office territory as follows:

A. the absolute difference D improving data sequence average value and absolute value collating sequence median is found_i(n₁,n₂) minimum value D_imin;

B. D is calculated_iminThe first data y of corresponding left sequence_iB () and right sequence mantissa are according to y_iE () is respectively K_i1And K_i2, [K_i1,K_i2] be between the intrinsic region, office territory of i-th time phase.

4. the detection method of bearing vibration performance variation according to claim 3, it is characterised in that, described step 5) in [K between overall intrinsic region_min1,K_min2] it is [K between the intrinsic region, office territory by i-th time phase_i1,K_i2] obtain, K_min1It is K_i1Minimum value, K_min2It is K_i2Minimum value; I is time phase sequence number; I=1,2 ..., m; M is time phase number.

5. the detection method of bearing vibration performance variation according to claim 1, it is characterised in that, described step 6) in aberration rate v_iFor:

$v_i=\frac{n_{vi}}{N}\×100\%;i=1,2,...,m$

Wherein v_iFor bearing vibration performance variation rate, n_viIt is i-th time phase bear vibration data absolute value not [K between overall intrinsic region_min1,K_min2] in data amount check, K_min1For floor value between overall intrinsic region, K_min2For upper bound value between overall intrinsic region, i is time phase sequence number, and m is time phase number, and N is the data amount check that i-th time phase obtains.

6. the detection system of a bearing vibration performance variation, it is characterised in that, this detection system comprises measures module, series processing module, HuberM estimation module, absolute difference computation module, intrinsic interval computation module and aberration rate calculating module,

Described measurement module is used for the vibration of rolling bearing during one's term of military service in the different time stage being measured, and obtains the bearing vibration data in different time stage, and is formed the data sequence of m time phase;

Described series processing module is used for bearing vibration data fetch absolute value, according to order from small to large, obtains absolute value collating sequence Y_i, and determine the median of this sequence;

Described HuberM estimation module is used for absolute value collating sequence Y_iCarry out HuberM estimation, the data that are improved sequence, and the mean value of computed improved sequence;

Described absolute difference computation module is used for the absolute difference of computed improved data sequence average value and absolute value collating sequence median;

Described intrinsic interval computation module is between the intrinsic region, absolute difference computation office territory according to improvement data sequence average value and absolute value collating sequence median and between overall intrinsic region;

Described aberration rate calculates module and is used for according to overall intrinsic interval computation bearing vibration performance variation rate, can detect out the variation situation of bearing vibration performance according to aberration rate.

7. the detection system of bearing vibration performance variation according to claim 6, it is characterised in that, the improvement data sequence that described HuberM estimation module obtains is Z_i(n₁,n₂) it is:

Z_i(n₁,n₂)={ z_i(n; n₁,n₂); I=1,2 ..., m; N=1,2 ..., N

Wherein Z_i(n₁,n₂) for improving data sequence, z_i(n; n₁,n₂) for improving the n-th data of data sequence, i is time phase sequence number, and n is data sequence number, N is the data amount check that i-th time phase obtains, and m is time phase number, n₁For the data amount check of left sequence, n₂For the data amount check of right sequence.

8. the detection system of bearing vibration performance variation according to claim 6, it is characterised in that, the process between intrinsic region, described intrinsic interval computation module calculating office territory is as follows:

A. the absolute difference D improving data sequence average value and absolute value collating sequence median is found_i(n₁,n₂) minimum value D_imin;

B. D is calculated_iminThe first data y of corresponding left sequence_iB () and right sequence mantissa are according to y_iE () is respectively K_i1And K_i2, [K_i1,K_i2] be between the intrinsic region, office territory of i-th time phase.

9. the detection system of bearing vibration performance variation according to claim 8, it is characterised in that, [K between described overall intrinsic region_min1,K_min2] it is [K between the intrinsic region, office territory by i-th time phase_i1,K_i2] obtain, K_min1It is K_i1Minimum value, K_min2It is K_i2Minimum value; I is time phase sequence number; I=1,2 ..., m; M is time phase number.

10. the detection system of bearing vibration performance variation according to claim 6, it is characterised in that, described bearing vibration performance variation rate v_iFor:

$v_i=\frac{n_{vi}}{N}\×100\%;i=1,2,...,m$

Wherein v_iFor bearing vibration performance variation rate, n_viIt is i-th time phase bear vibration data absolute value not [K between overall intrinsic region_min1,K_min2] in data amount check, K_min1For floor value between overall intrinsic region, K_min2For upper bound value between overall intrinsic region, i is time phase sequence number, and m is time phase number, and N is the data amount check that i-th time phase obtains.