CN102759397B - Efficient extraction method of friction fault characteristics in vibration signal of rotating shaft - Google Patents

Abstract

The invention discloses an efficient extraction method of friction fault characteristics in a vibration signal of a rotating shaft, comprising the following steps of: selecting a plurality of monitoring sections along the direction of the rotating shaft; mounting an eddy-current transducer to monitor the vibration signal (t) of the rotating shaft; carrying out two times of differential continuously on time by virtue of the actually-monitored vibration signal and carrying out burr point enhancement operation on the signal processed by the two times of differential to obtain Z(t); calculating statistic characteristics of the Z(t) signal to obtain a sample average, a sample variance and a signal Z'(t) without an average value; calculating a signal distortion amplitude fault degree coefficient and a distortion frequency rate fault degree coefficient; calculating average values of the signal distortion amplitude fault degree coefficients and the distortion frequency rate fault degree coefficients in a plurality of periods, and taking the maximum value umax in the two average values as friction fault degree coefficients to judge the friction fault degree; and judging a friction position according to the friction fault degree coefficient of each measuring point of the rotating shaft. The method disclosed by the invention can effectively amplify the early-period friction fault characteristics and improve the diagnosis accuracy of early-period friction faults.

Description

Tribological failure feature highly effective extraction method in shaft vibration signal

Technical field

The present invention relates to tribological failure feature extracting method in a kind of shaft vibration signal.

Background technology

In order to prevent that steam, pressurized air, lubricated wet goods actuating medium from leaking outside, all kinds of rotating machineries such as steam turbine, generator, gas turbine, compressor, pump, blower fan have all been installed all kinds of sealings in rotating shaft, blade tip and bearing both sides, gap between sound parts is less, is in servicely easy to occur the friction between sound parts.After tribological failure occurs, unit vibration can increase, and affect unit safety stable operation, will cause the generation of the serious accidents such as permanent bending of rotor, bearing shell be cracked in the time of seriously.According to incompletely statistics, the more than 70% cambered axle accident of domestic electric system Turbo-generator Set is because tribological failure is caused.Efficient monitoring, analysis and the diagnostic method of tribological failure are most important for the safe operation of rotating machinery.

Monitoring and the analytical approach of tribological failure mainly contain at present: (1) thermal effect method.After friction occurs, the one week friction light and heavy degree difference in rotating shaft surface, can form thus the temperature difference and cause rotor to occur thermal deformation.The vibration variable quantity that monitoring thermal deformation causes can help to analyze and judge tribological failure.This method is used widely in Turbo-generator Set.The degree of functioning of this method is very relevant with friction light and heavy degree, and fault is difficult to accurately judgement in early days.The rotating machineries such as Turbo-generator Set also exist due to the caused thermal deformation fault of other factors, and the feature between friction and these factors is very similar, are difficult to make a distinction, thereby have affected the accuracy of method.(2) time domain method.According to waveform and the judgement of orbit of shaft center feature.Under friction impact force action, on waveform, likely there will be the phenomenons such as burr, it is disorderly that orbit of shaft center likely can become.When friction force is very large, above-mentioned phenomenon likely occurs, but now friction has entered middle and advanced stage, has lost the best opportunity of tribological failure diagnosis.(3) Spectrum Method.Under large impact force action, system becomes non-linear, there will be the high fdrequency components such as two frequencys multiplication and frequency tripling in vibration signal, according to the variation of vibration signal frequency spectrum medium-high frequency component, can judge tribological failure.When friction force is larger, said frequencies feature likely occurs.Under early stage Frotteurism, frequecy characteristic is not clearly.(4) power sensor method.At the back of friction member installing force sensor, during friction, power sensor can be experienced impulsive force signal, judges thus tribological failure.This method is mainly used in laboratory, cannot be applied to engineering reality.

In tribological failure, late period, friction characteristic is obvious, the large multipotency of said method is judged fault.While rubbing in early days or slightly, friction force is smaller, and thermal deformation is less, and the impact of countershaft vibrational waveform is also smaller, and the features such as wave form distortion and frequency spectrum are also not obvious.

Summary of the invention

The present invention proposes tribological failure feature highly effective extraction method in a kind of shaft vibration signal, and the method can be amplified early stage tribological failure feature effectively, improves the accuracy rate of diagnosis of early stage tribological failure.

In order to realize above object, the present invention adopts following technical scheme: rotating machinery sound tribological failure feature highly effective extraction method, comprises the steps:

1) in rotating shaft, fix reflecting strips, aim at the fixing photoelectric sensor of reflecting strips and be used for measuring rotational speed pulse signal; In axial direction select multiple monitorings cross section, eddy current sensor is installed respectively, eddy current sensor detects shaft vibration signal, and shaft vibration signal is designated as: y (t); Rotational speed pulse signal is as the analysis benchmark of the shaft vibration signal of multiple measuring points;

2) will survey shaft vibration signal y (t) time will be done to two subdifferentials, obtain

$\stackrel{\·}{y}\left(t\right)=\frac{y(t+1)-y\left(t\right)}{\mathrm{\Δt}},$ $\stackrel{\·\·}{y}\left(t\right)=\frac{\stackrel{\·}{y}(t+1)-\stackrel{\·}{y}\left(t\right)}{\mathrm{\Δt}};$

Wherein, Δ t is sampling time interval;

3) signal after second differential is made to burr point enhance operation:

$Z\left(t\right)={\stackrel{\·\·}{y}}^2\left(t\right)-\stackrel{\·\·}{y}(t-1)\stackrel{\·\·}{y}(t+1);$

4) statistical nature of calculating Z (t) signal, remove mean value:

Sample average $\stackrel{\‾}{Z}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}Z\left(t\right);$

Sample variance $\mathrm{\σ}=\sqrt{\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{[Z\left(t\right)-\stackrel{\‾}{Z}]}^2};$

Remove the signal after average $Z^{\′}\left(t\right)=Z\left(t\right)-\stackrel{\‾}{Z};$

5) in definition sampling period Z ' (t) in signal the point of amplitude > 3 σ be distortional point, maximal value Z ' _max=max[Z ' is (t)], calculate the distortion n that counts and account for the ratio lambda of sample number N:

$\mathrm{\λ}=\frac{n}{N};$

6) calculate signal distortion amplitude fault degree coefficient u in arbitrary sampling period _1j:

$u_{1j}=\frac{2k{Z^{\′2}}_{\max }}{1+k{Z^{\′2}}_{\max }}-1,$ $k=\frac{1}{{\left(3\mathrm{\σ}\right)}^2},$ u _1j∈(-1,1)

This formula is known technology, is not described further;

7) calculate signal distortion frequency fault degree coefficient u in arbitrary sampling period _2j:

$u_{2j}=\frac{2m{\mathrm{\&lambda;}}^2}{1+m{\mathrm{\&lambda;}}^2}-1,$ 100<m<20000,u _2j∈(-1,1)

This formula is known technology, is not described further;

8) mean value of distortion amplitude fault degree coefficient and aberration frequency fault degree coefficient in L the sampling period of calculating:

$\stackrel{\&OverBar;}{u_1}=\frac{\underset{j=1}{\overset{L}{\mathrm{\&Sigma;}}}{u}_{1j}}{L},$ $\stackrel{\&OverBar;}{u_2}=\frac{\underset{j=1}{\overset{L}{\mathrm{\&Sigma;}}}{u}_{2j}}{L};$

9) get

with

in maximal value as tribological failure degree coefficient u _max:

$u_{\max }=\max (\stackrel{\&OverBar;}{u_1},\stackrel{\&OverBar;}{u_2});$

10) according to measuring point tribological failure degree coefficient, judge tribological failure degree, tribological failure degree coefficient value is larger, represents that tribological failure degree is more serious; According to the tribological failure degree coefficient of each measuring point in rotating shaft, judge frictional position, this measuring point tribological failure degree coefficient value is larger, represents the closer to friction point place.

Tribological failure feature highly effective extraction method in shaft vibration signal, wherein signal analysis frequency f _a>=10KHz, signals collecting frequency f _s>=2.56f _a, the sampling period is counted L>=8.

Beneficial effect: compared with prior art, tool of the present invention has the following advantages:

(1) original signal is done after second differential and burr enhance operation, the small distortional point in signal will be exaggerated, and can effectively amplify early stage tribological failure feature, improves the accuracy rate of diagnosis of early stage tribological failure;

(2) the tribological failure degree coefficient value calculating according to axial multiple measuring points distributes can judge frictional position;

(3) when tribological failure judges, considered the impact of distortional point quantity and distortion amplitude simultaneously;

(4) provide tribological failure and diagnose quantitative determination methods, make friction diagnosis quantitative from qualitative trend.

Sound friction detection method proposed by the invention can be monitored tribological failure and friction position effectively; the method can be embedded in all kinds of rotating machinery vibrating state protection TDM systems such as Turbo-generator Set, can effectively help technician to carry out the condition monitoring for rotating machinery such as Turbo-generator Set and fault diagnosis work.

Accompanying drawing explanation

Fig. 1 is tribological failure feature highly effective extraction method schematic flow sheet in shaft vibration signal of the present invention.

Fig. 2 is the rotor experiment table friction monitoring schematic diagram of the embodiment of the present invention.

Wherein, the 1st, motor; The 2nd, shaft coupling; The 3rd, photoelectric sensor; The 4th, bearing seat; The 5th, eddy current sensor; The 6th, friction screw and support; The 7th, rotor; The 8th, base.

Fig. 3 is without original signal waveform under Frotteurism.

Fig. 4 is original signal waveform under Frotteurism.

Fig. 5 is without under Frotteurism, original vibration signal being carried out to the waveform after second differential computing.

Fig. 6 is without under Frotteurism, the waveform after second differential being made to the waveform after burr enhance operation again.

Fig. 7 carries out the waveform after second differential computing to original vibration signal under Frotteurism.

Fig. 8 makes the waveform after burr enhance operation again to the waveform after second differential under Frotteurism.

Embodiment

The present embodiment is take the rotor experiment table shown in Fig. 1 as example, the early stage tribological failure highly effective extraction method analysis of carrying out.

The axis friction fault high efficiency extraction analytical approach that the present embodiment relates to is:

(1) on the shaft part exposing, paste reflecting strips, photoelectric sensor is aimed to reflecting strips, measure rotational speed pulse signal, the benchmark using this as the synchronous integer-period sampled analysis of multi-measuring point.

(2) at rotating shaft different cross section place, arrange that sensitivity is the non-contact turbulent flow sensor of 7.87mV/ μ m, monitoring shaft vibration signal y (t).(3) signalization collection, analytical parameters:

Analysis frequency f _a=20KHz

Frequency acquisition f _s=5.12KHz

Sampling period is counted L=20

(4) original signal is once differentiated:

$\stackrel{\&CenterDot;}{y}\left(t\right)=\frac{y(t+1)-y\left(t\right)}{\mathrm{\&Delta;t}}$

(5) signal after a subdifferential is remake to a subdifferential:

$\stackrel{\&CenterDot;\&CenterDot;}{y}\left(t\right)=\frac{\stackrel{\&CenterDot;}{y}(t+1)-\stackrel{\&CenterDot;}{y}\left(t\right)}{\mathrm{\&Delta;t}}$

(6) signal after second differential is made to burr enhance operation:

$Z\left(t\right)={\stackrel{\&CenterDot;\&CenterDot;}{y}}^2\left(t\right)-\stackrel{\&CenterDot;\&CenterDot;}{y}(t-1)\stackrel{\&CenterDot;\&CenterDot;}{y}(t+1)$

(7) statistical nature of calculating signal Z (t), remove mean value:

$\stackrel{\&OverBar;}{Z}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}Z\left(t\right)$

$\mathrm{\&sigma;}=\sqrt{\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{[Z\left(t\right)-\stackrel{\&OverBar;}{Z}]}^2}$

$Z^{\&prime;}\left(t\right)=Z\left(t\right)-\stackrel{\&OverBar;}{Z}$

(8) definition distortional point is the point of amplitude > 3 σ in one-period.The n that counts by distorting in one-period accounts for the ratio lambda of sample number N and calculates distortional point frequency fault degree coefficient:

$u_{2j}=\frac{2m{\mathrm{\&lambda;}}^2}{1+m{\mathrm{\&lambda;}}^2}-1,$ u _2j∈(-1,1),100<m<20000, $\mathrm{\&lambda;}=\frac{n}{N}$

(9) by maximum distortion amplitude Z ' in one-period _max=max[Z ' is (t)] calculating distortion amplitude fault degree coefficient:

$u_{1j}=\frac{2k{Z^{\&prime;2}}_{\mathrm{<figure-callout\; id="1"\; label="max"\; filenames="HDA00001870676100011.png,HDA00001870676100032.png"\; state="\{\{state\}\}">max</figure-callout>}}}{1+k{Z^{\&prime;2}}_{\max }}-1,$ $k=\frac{1}{{\left(3\mathrm{\&sigma;}\right)}^2},$ u _1j∈(-1,1)

(10) calculate u in L cycle _1jand u _2jmean value:

$\stackrel{\&OverBar;}{{\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="HDA00001870676100011.png,HDA00001870676100032.png"\; state="\{\{state\}\}">u</figure-callout>}}_1}=\frac{\underset{j=1}{\overset{L}{\mathrm{\&Sigma;}}}{u}_{1j}}{L},$ $\stackrel{\&OverBar;}{{\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="HDA00001870676100051.png"\; state="\{\{state\}\}">u</figure-callout>}}_2}=\frac{\underset{j=1}{\overset{L}{\mathrm{\&Sigma;}}}{u}_{2j}}{L}$

(11) get

with

in maximal value u _maxas tribological failure degree coefficient:

$u_{\max }=\max (\stackrel{\&OverBar;}{{\mathrm{<figure-callout\; id="1"\; label="u"\; filenames="HDA00001870676100011.png,HDA00001870676100032.png"\; state="\{\{state\}\}">u</figure-callout>}}_1},\stackrel{\&OverBar;}{{\mathrm{<figure-callout\; id="2"\; label="u"\; filenames="HDA00001870676100051.png"\; state="\{\{state\}\}">u</figure-callout>}}_2})$

(12) tribological failure criterion is as follows:

1) tribological failure degree

The larger expression tribological failure of the tribological failure degree coefficient value degree of measuring point is more serious.

2) friction position

In axial each measuring point, the cross section, some place of tribological failure degree coefficient value maximum is the most close tribological failure cross section.

Claims (2)

1. rotating machinery sound tribological failure feature highly effective extraction method, is characterized in that, comprises the steps:

1) in rotating shaft, fix reflecting strips, on the shaft part exposing, paste reflecting strips, aim at the fixing photoelectric sensor of reflecting strips and be used for measuring rotational speed pulse signal, described reflecting strips is to paste in rotating shaft along the axial direction of rotating shaft; In axial direction select multiple monitorings cross section, eddy current sensor is installed respectively, eddy current sensor detects shaft vibration signal, and shaft vibration signal is designated as: y (t); Rotational speed pulse signal is as the analysis benchmark of the shaft vibration signal of multiple measuring points:

2) will survey shaft vibration signal y (t) time will be done to two subdifferentials, obtain

$\stackrel{\&CenterDot;}{y}\left(t\right)=\frac{y(t+1)-y\left(t\right)}{\mathrm{\&Delta;t}},\stackrel{\&CenterDot;\&CenterDot;}{y}\left(t\right)=\frac{\stackrel{\&CenterDot;}{y}(t+1)-\stackrel{\&CenterDot;}{y}\left(t\right)}{\mathrm{\&Delta;t}};$

Wherein, Δ t is sampling time interval;

3) signal after second differential is made to burr point enhance operation:

$Z\left(t\right)={\stackrel{\&CenterDot;\&CenterDot;}{y}}^2\left(t\right)-\stackrel{\&CenterDot;\&CenterDot;}{y}(t-1)\stackrel{\&CenterDot;\&CenterDot;}{y}(t+1);$

4) calculate the statistical nature of Z (t) signal, and remove mean value:

Sample average $\stackrel{\&OverBar;}{Z}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}Z\left(t\right);$

Sample variance $\mathrm{\&sigma;}=\sqrt{\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{[Z\left(t\right)-\stackrel{\&OverBar;}{Z}]}^2};$

Remove the signal after average

;

Wherein N is sample number;

5) in definition sampling period Z ' (t) in signal the point of amplitude > 3 σ be distortional point, maximal value

Z ' _max=max[Z ' is (t)], calculate the distortion n that counts and account for the ratio lambda of sample number N:

$\mathrm{\&lambda;}=\frac{n}{N};$

6) calculate signal distortion amplitude fault degree coefficient u in arbitrary sampling period _1j:

$u_{1.j}=\frac{{{2\mathrm{kZ}}^{\&prime;2}}_{\max }}{{{1+\mathrm{kZ}}^{\&prime;2}}_{\max }}-1,k=\frac{1}{{\left(3\mathrm{\&sigma;}\right)}^2},u_{1j}\&Element;(-\mathrm{1,1});$

7) calculate signal distortion frequency fault degree coefficient u in arbitrary sampling period _2j:

$u_{2j}=\frac{2m{\mathrm{\&lambda;}}^2}{1+m{\mathrm{\&lambda;}}^2}-\mathrm{1,100}<m<1000,u_{2j}\&Element;(-\mathrm{1,1});$

8) mean value of distortion amplitude fault degree coefficient and aberration frequency fault degree coefficient in L the sampling period of calculating:

$\stackrel{\&OverBar;}{u_1}=\frac{\underset{j=1}{\overset{L}{\mathrm{\&Sigma;}}}{u}_{1j}}{L},\stackrel{\&OverBar;}{u_2}=\frac{\underset{j=1}{\overset{L}{\mathrm{\&Sigma;}}}{u}_{2j}}{L};$

9) get

with in maximal value as tribological failure degree coefficient u _max:

$u_{\max }=\max (\stackrel{\&OverBar;}{u_1},\stackrel{\&OverBar;}{u_2});$

10) first, according to measuring point tribological failure degree coefficient, judge tribological failure degree, tribological failure degree coefficient value is larger, represents that tribological failure degree is more serious; Then, according to the tribological failure degree coefficient of each measuring point in rotating shaft, judge frictional position, this measuring point tribological failure degree coefficient value is larger, represents the closer to friction point place.

2. rotating machinery sound tribological failure feature highly effective extraction method according to claim 1, is characterized in that signal analysis frequency f _a>=10KHz, signals collecting frequency f _s>=2.56.f _a, the sampling period is counted L>=8.

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