CN101354312B - Bearing failure diagnosis system - Google Patents

Abstract

The invention provides a bearing fault diagnosis system which comprises an intelligent bearing provided with six output ports with a first output port and a second output port outputting vibration acceleration signals, a third output port and a fourth output port speed signals and a fifth output port and a sixth output temperature signals. The system is characterized in that: the six groups of signals output by the intelligent bearing are sent to the input port of an A/D conversion module, six groups of digital signals output by the A/D conversion module are sent to a processor internally provided with a status monitor and a fault recognizer, wherein, the status monitor monitors the status of the bearing according to the vibration acceleration digital signals, the speed digital signals and the temperature digital signals, and the fault recognizer utilizes a signal processing tool to get a fault judgment result. The system of the invention has the advantages of being capable of monitoring the status of the bearing in an on-line manner according to the three types of signals of the intelligent bearing on the basis of the current intelligent bearing provided with a compound sensor soas to judge which part a fault takes place in.

Description

The intelligent bearing fault diagnosis system

Technical field

The present invention relates to sensor, specifically, relate to the wheel shaft, wheel box of a kind of wheel shaft that is applied in high-speed railway vehicle (bullet train etc.) and sedan limousine, large truck and some other adopts the rotating machinery on-line monitoring and the fault diagnosis system of intelligent bearing supporting way.

Background technology

Bearing, as one of vital part in the plant equipment, the quality of its running status will directly influence equipment running status and usability.To bearing, the monitoring of the bearing running status on particularly large-scale dynamoelectric equipment axis system and the hot-short and fault detect have become the important research content and the application of fault diagnosis technology.Through facts have proved, the quality of bearing diagnosis system performance depends on its detectability to the early stage fault in service of bearing, promptly detects abnormal conditions before catastrophic failure takes place.A host of facts prove that many major accidents are all owing to mechanical disorder caused with regard to appearance before expected life.These accidents have illustrated the potential danger that bearing fault brought that is difficult to predict, development intelligent bearing technology, and creating online bearing diagnosis and early warning system is current bearing failure diagnosis Developing Trend in Technology.

The intelligent bearing technology also can be described as under the background of technology develop rapidlys such as machinery, electronics, communication and produces.Because the continuous development of science and technology, improving constantly of the measure of precision of machinery and automaticity, early stage bearing fault detection method has fallen behind, and melts Modern Transducer Technology, signal transmission and treatment technology and computer technology is arisen at the historic moment in " intellectuality " diagnostic techniques of one.The performance monitoring and the method for diagnosing faults of therefore, the primary element that rotates freely as providing of widespread use in the mechanical system---bearing also develop towards the direction of " intellectuality ".Definition for " intelligent bearing ", current a kind of representative saying is, the sensing device of integrated different purposes on the basis of traditional bearing, it is combined into one and forms the particular structure unit, carry out information processing by microcomputer again, reach the purpose of real time on-line monitoring.

Compare with traditional bearing, a remarkable advantage that is integrated with the intelligent bearing of microsensor is exactly the serviceability that can monitor oneself in real time, and the signal to noise ratio (S/N ratio) height.Secondly because intelligent bearing centre bearer and sensor are combined into an one-piece construction, thereby the product that can be used as an independent completion produce and buy, make things convenient for user's practical application.

The combination of bearing and sensor at present comprises external hanging type and embedded two kinds of versions.External hanging type is meant that sensor is not in inner ring, outer ring or the rolling body that is embedded into bearing, but is attached on the bearing.This structure can not destroyed the integrality (being that maximum stress and the distortion that bearing allows do not change) of bearing.Traditional external hanging type is attached to sensory package around the bearing, and the object of monitoring and scope are very limited.More difficult in practice widespread use.And do not change bearing contour dimension, and the embedded intelligence bearing that can carry out multiple parameter testing is a better developing direction of intelligent bearing.The embedded intelligence bearing unit then is that sensor is embedded in the bearing body, the advantage of this method be sensing device can be very near the generation source of measured signal.The intermediate interface of signal transmission reduces, and the signal of collection more can reflect the practical working situation of bearing, signal to noise ratio (S/N ratio) height truly.

But because where sensing element is embedded into bearing actually, and sensing device these key issues such as reasonable Arrangement on compound sensor, make Embedded application be restricted.Currently used damascene structures is that sensing device is concentrated on the bearing, and this can produce stress and concentrate, and the bad layout of lead, brings difficulty to assembling.In addition, the sensing device of existing intelligent bearing only adopts a kind of mostly, and modal is the intelligent bearing unit that has the intelligent bearing unit of acceleration (vibration) sensing device and have speed sensing device.At high speed vehicles such as bullet train, bullet trains, because the speed of a motor vehicle is too high, the bearing vibration aggravation must detect vibration signal, with the huge person and the economic loss of preventing to cause.For preventing the generation of hot-short locking phenomenon, need to detect in real time tach signal.In addition, in order to prevent since bearing fault cause cut an accident, and owing to the wearing and tearing that the bearing self-heating causes, burn and need detect the temperature signal of bearing inner race (axle), outer ring simultaneously.So just must design vibration acceleration sensing device, temperature sensing device, the integrated intelligent bearing unit of revolution speed sensing device.

The inventor has developed a kind of (application number: 2007100925746) of intelligent bearing with compound sensor, this intelligent bearing is provided with six road delivery outlets, wherein first and second road delivery outlet AI0, AI1 respectively export one group of vibration acceleration signal, third and fourth road delivery outlet AI2, AI3 respectively export one group of tach signal, and the 5th, six road delivery outlet AI4, AI5 respectively export one group of temperature signal.Vibration acceleration sensing device, temperature sensing device, revolution speed sensing device and bearing is integrated, can extract the fault-signal of bearing effectively.

But also lack how the state of bearing to be carried out on-line monitoring, the concrete technical method that fault is discerned according to vibration acceleration signal, temperature signal, tach signal.

Summary of the invention

The purpose of this invention is to provide a kind of intelligent bearing fault diagnosis system, can be on the basis of the intelligent bearing that has the band compound sensor now, vibration acceleration signal, temperature signal, tach signal according to intelligent bearing carry out on-line monitoring to the state of bearing, and fault is discerned.

For achieving the above object, a kind of intelligent bearing fault diagnosis system of the present invention, comprise intelligent bearing, this intelligent bearing is provided with six road delivery outlets, wherein first, two road delivery outlets are respectively exported one group of vibration acceleration signal, the 3rd, four road delivery outlets are respectively exported one group of tach signal, the 5th, six road delivery outlets are respectively exported one group of temperature signal, its key is: six groups of signals of described intelligent bearing output send to the input port of A/D modular converter, this A/D modular converter is a digital signal with six groups of conversion of signals, six groups of digital signals of A/D modular converter output send to processor, be provided with state monitor and Fault Identification device in this processor, wherein state monitor is according to described first, two groups of vibration acceleration digital signals, the 3rd, four groups of rotating speed digital signals and the 5th, six groups of temperature digital signals are monitored the state of bearing, and generation failure alarm signal, state monitor is exported this alerting signal and is driven described Fault Identification device, this Fault Identification device utilizes the signal Processing instrument, comprehensive described vibration acceleration digital signal and rotating speed digital signal draw the fault judgement result.

This diagnostic system utilizes the intelligent bearing technology, gather vibration acceleration, speed and the temperature signal of bullet train hub bearing, treatment circuit by intelligent bearing inside amplifies vibration acceleration signal, tach signal, and temperature signal amplifies and compensates.Conversion enters monitoring of software analysis to pretreated 6 tunnel simulating signals through A/D.Rely on temperature value, velocity amplitude and vibration acceleration statistic to carry out status monitoring, when monitoring variable surpasses preset threshold, the proof bearing breaks down, at this moment state monitor fault alarm, start the Fault Identification function of Fault Identification device simultaneously, failure judgement occurs on which parts of bearing.The Fault Identification function relies on method for processing signals that digital signal is analyzed and handled and realizes.

Need to prove: the collection of intelligent bearing data is a collection of finishing, and the number of the sampled point that each batch data held is relevant with the cache size of A/D modular converter.After a batch data reads in by the A/D modular converter, to carry out multiple operation,, carry out digital demonstration, graphic presentation, also will realize multiple functions such as status monitoring and Fault Identification by calculating such as to comprising a batch data of 8192 sampling point informations.Only finished all operations, the A/D modular converter just can read in the next group data does repetitive operation.

Be provided with in the described state monitor:

Be used for the device that commencing signal is gathered;

Be used to obtain the time domain statistical parameter threshold value S of vibration acceleration signal _R, S _KDevice;

Be used for device with channel number CH, the first variable N1, the second variable N2 zero setting;

Be used to calculate root-mean-square value RMS, the kurtosis COEFFICIENT K of AI0 passage vibration acceleration _FDevice with temperature data value W;

Owing to can't directly obtain vibration performance, use vibration acceleration time domain statistic to reflect the size of vibrational energy.The RMS value has reflected the body vibration energy, and it can estimate the health status of bearing and more stable, but this parameter is responsive inadequately to the initial failure of bearing.The kurtosis COEFFICIENT K _FBe dimensionless group, reflected the size of impact shock, can be used for the initial failure diagnosis, but it can reduce gradually along with the intensification of fault.This diagnostic system adopts the method for two time domain parameter comprehensive evaluations to carry out the monitoring of vibrational state.

Be used to judge that temperature data value W is whether greater than 120 device;

If W is greater than 120 for the temperature data value, then be introduced into the device that is used to generate heat alarm;

Enter again and be used to judge whether RMS surpasses its threshold value S _RDevice;

If temperature data value W is not more than 120, then directly enters and describedly be used to judge whether RMS surpasses the device of its threshold value SR;

If RMS does not surpass its threshold value S _R, then directly enter and be used to judge the kurtosis COEFFICIENT K _FWhether surpass its threshold value S _KDevice;

If RMS surpasses its threshold value S _R, then enter and be used for the first variable N1 is added 1 device;

Be used to judge that the first variable N1 is whether greater than 5 device;

If greater than 5, then entering, the first variable N1 is used to generate first alerting signal, and to the device of the first variable N1 zero clearing;

Enter the described kurtosis COEFFICIENT K that is used to judge again _FWhether surpass its threshold value S _KDevice;

If the first variable N1 is not more than 5, then directly enter the described kurtosis COEFFICIENT K that is used to judge _FWhether surpass its threshold value S _KDevice;

If K _FDo not surpass its threshold value S _K, then directly enter and be used for channel number CH added 1 device;

If K _FSurpass its threshold value S _K, then enter and be used for the second variable N2 is added 1 device;

Be used to judge that the second variable N2 is whether greater than 5 device;

If greater than 5, then entering, the second variable N2 is used to generate second alerting signal, and to the device of the second variable N2 zero clearing;

Enter described 1 the device that is used for channel number CH added again;

If the second variable N2 is not more than 5, then directly enter described 1 the device that is used for channel number CH added;

Enter again and be used to judge that channel number CH is whether greater than 1 device;

If CH is not more than 1, then directly enter the root-mean-square value RMS, the kurtosis COEFFICIENT K that are used to calculate AI1 passage vibration acceleration _FAnd the device of temperature data value W;

If CH greater than 1, then is introduced into the device that is used for channel number CH zero setting;

Return described root-mean-square value RMS, the kurtosis COEFFICIENT K that is used to calculate AI0 passage vibration acceleration again _FAnd the device of temperature data value W;

Wherein said

$\mathrm{RMS}={\left(\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{x_i}^2\right)}^{1/2},$

$K_F=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{x_i}^4/{\left(\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{x_i}^2\right)}^2$

The vibration acceleration signal of described intelligent bearing output is that the form with aanalogvoltage exists, and unit is mv; Through becoming digital voltage signal after the A/D conversion, unit is mv; In processor digital voltage signal is carried out conversion again, obtain the vibration acceleration value xi of sampled point, unit is g, and its conversion formula is:

$X_i=\frac{X_i}{\mathrm{sm}}$

x _i': digital voltage signal, unit are mv;

S: the sensitivity coefficient of vibrating sensing device, unit are mv/g;

M: the enlargement factor of intelligent bearing vibration acceleration signal;

N: bearing inner race rotates 2 and encloses counting of being collected, and is to be that basic calculation draws with the tach signal:

$N=\frac{120f}{\mathrm{nk}}$

F: the sample frequency of every batch data, unit is Hz;

K: port number;

N: rotating speed, unit are r/min;

Described temperature data value W is: $W=\left(\frac{k}{N_Z}\underset{i=1}{\overset{\frac{N_z}{k}}{\mathrm{\Σ}}}\frac{y_i}{t}\right)/S_W$

N _Z: total sampling number of every batch data;

K: port number;

y _i: the value of the temperature digital signal sampling point after amplification and compensation, unit is mv;

T: the enlargement factor of intelligent bearing temperature signal;

S _W: the temperature-sensitivity coefficient of intelligent bearing, unit are mv/ ℃.

Be provided with in the described Fault Identification device:

Be used to begin the device of Fault Identification;

Be used to obtain rolling body and on outer ring raceway, pass through frequency f _OpDevice;

Be used to obtain rolling body and on inner ring raceway, pass through frequency f _IpDevice;

Be used to obtain the gyrofrequency f of the relative retainer of rolling body _BcDevice;

Be used to read vibration acceleration value x _iDevice;

Be used to utilize Fourier transformer, draw vibration acceleration signal value x _iThe device of frequency spectrum;

The analytic function of data comprises multiple signal processing methods such as cepstrum, filtering, relevant, envelope, can choose suitable analytical approach according to the characteristic of signal, and wherein the frequency spectrum of vibration acceleration is that method by Fourier transform obtains.

Be used in the frequency range less than f/2k, choosing the device of the 1st resonance peak P=1 greater than 3000;

Be used for determining the device of filter bandwidht B=500;

Be used for bandpass filtering, obtain the device of filtering after vibration acceleration time domain signal;

Be used to obtain the device of signal envelope spectrum after the filtering;

Be used for finding out envelope spectrum maximum amplitude Y _mDevice;

Be used to judge Y _m-f _OpThe value device between-5～5 whether;

If Y _m-f _OpValue between-5～5, then enter the device that is used to generate the outer ring fault-signal;

If Y _m-f _OpValue outside-5～5, then enter and be used to judge Y _m-f _IpThe value device between-5～5 whether;

If Y _m-f _IpValue between-5～5, then enter the device that is used to generate the inner ring fault-signal;

If Y _m-f _IpValue outside-5～5, then enter and be used to judge Y _m-f _BcThe value device between-5～5 whether;

If Y _m-f _BcValue between-5～5, then enter the device that is used to generate the rolling body fault-signal;

If Y _m-f _BcValue outside-5～5, then enter and be used for filter bandwidht B and add 100 device;

Vibration acceleration signal is carried out the arrowband bandpass filtering treatment, do the Hilbert conversion then, the analytic signal Q (t) that signal after the conversion and filtered vibration acceleration signal constitute is:

Q(t)＝q(t)+jq ₁(t)

Q (t): filtered signal;

q ₁(t): the signal after the Hilbert conversion.

Right | Q (t) | remake Fourier transform and obtain envelope spectrum, find out the maximum amplitude Y of envelope spectrum _m, at first the fault characteristic frequency with bearing outer ring contrasts, if satisfy-5＜Y _m-f _Op＜5 condition is diagnosed as bearing outer ring and breaks down, and does not carry out the fault judgement of inner ring, rolling body more successively if do not satisfy condition, and Rule of judgment is respectively :-5＜Y _m-f _Ip＜5 ,-5＜Y _m-f _Bc＜5.If three conditions do not satisfy, illustrate the selection of filtering parameter improperly, the program redirect is so that reselect relevant filtering parameter, and same resonance peak is being increased progressively with the filtering bandwidth of 100Hz under as the prerequisite of analytic target, and promptly B adds 100.

Enter again and be used to judge that B is whether greater than 1000 device;

If B is less than or equal to 1000, then return the described bandpass filtering that is used for, obtain the device of filtering after vibration acceleration time domain signal;

If B greater than 1000, then enters the device that is used for choosing at frequency spectrum following 1 resonance peak P=P+1;

If still can't discern the generation of fault when bandwidth surpasses 1000Hz, next so that frequency is higher resonance peak judges again as analytic target, i.e. P=P+1.

Be used to judge that P is whether greater than the frequency sequence number P of high resonance peak _nDevice;

If P is less than or equal to P _n, then return the described device that is used for determining filter bandwidht B=500;

If P is greater than P _n, then enter the device that is used for the output safety signal;

If to all having carried out analyzing the generation that also can't discern fault, i.e. P less than all resonance peaks in the frequency range of f/2k greater than 3000〉P _n, judge the bearing non-fault so.

Wherein:

$f_{\mathrm{op}}=\frac{n}{2}{f}_r(1-\frac{d}{D}\cos \mathrm{\α}),$

$f_{\mathrm{ip}}=\frac{n}{2}{f}_r(1+\frac{d}{D}\cos \mathrm{\α}),$

$f_{\mathrm{bc}}=\frac{D}{2d}{f}_r(1+\frac{d^2}{{\mathrm{<figure-callout\; id="2"\; label="D"\; filenames="H2008100702352E00011.png"\; state="\{\{state\}\}">D</figure-callout>}}^2}\stackrel{2}{\cos \mathrm{\&alpha;}})$

In the formula, D is the pitch diameter of bearing, i.e. the circle at place, rolling body center, and d is the diameter of rolling body, α is a contact angle, f _r=f _i-f ₀Be the frequency that relatively rotates of Internal and external cycle, when outer ring fixedly the time, f _rBe the rotational frequency of axle.

Native system adopts the method for resonance and demodulation to carry out the Fault Identification of bearing, thereby which parts is failure judgement occur on.Resonance demodulation technique is low frequency to be impacted the high-frequency resonance ripple evoked carry out envelope detection, obtains one that impact corresponding to low frequency and amplify broadening also the resonance and demodulation ripple.By this resonance and demodulation ripple is carried out spectrum analysis, judge the value and the type of fault.

Remarkable result of the present invention is: utilize the intelligent bearing technology, gather bearing vibration acceleration, rotating speed and temperature signal, the treatment circuit by intelligent bearing inside amplifies vibration acceleration signal, tach signal, and temperature signal amplifies and compensates.Conversion enters monitoring of software analysis to pretreated 6 tunnel simulating signals through A/D.Rely on temperature value, velocity amplitude and vibration acceleration statistic to carry out status monitoring, when monitoring variable surpasses preset threshold, the proof bearing breaks down, at this moment state monitor fault alarm, start the Fault Identification function of Fault Identification device simultaneously, the Fault Identification device adopts the method for resonance and demodulation to carry out the Fault Identification of bearing, thereby which parts is failure judgement occur on.

Description of drawings

Accompanying drawing 1 is a connection block diagram of the present invention;

Accompanying drawing 2 is the workflow diagram of state monitor;

Accompanying drawing 3 is the workflow diagram of Fault Identification device.

Embodiment

Below in conjunction with the drawings and specific embodiments the present invention is described in further detail.

As shown in Figure 1, a kind of intelligent bearing fault diagnosis system, by intelligent bearing 1, A/D modular converter 2, processor, state monitor and Fault Identification device are formed, wherein intelligent bearing 1 is provided with six road delivery outlets, wherein first, two road delivery outlet AI0, AI1 respectively exports one group of vibration acceleration signal, the 3rd, four road delivery outlet AI2, AI3 respectively exports one group of tach signal, the 5th, six road delivery outlet AI4, AI5 respectively exports one group of temperature signal, six groups of signals of described intelligent bearing 1 output send to the input port of A/D modular converter 2, this A/D modular converter 2 is a digital signal with six groups of conversion of signals, six groups of digital signals of A/D modular converter 2 outputs send to processor, be provided with state monitor and Fault Identification device in this processor, wherein state monitor is according to described first, two groups of vibration acceleration digital signals, the 3rd, four groups of rotating speed digital signals and the 5th, six groups of temperature digital signals are monitored the state of bearing, and generation failure alarm signal, state monitor is exported this alerting signal and is driven described Fault Identification device, this Fault Identification device utilizes the signal Processing instrument, comprehensive described vibration acceleration digital signal and rotating speed digital signal draw the fault judgement result.

This diagnostic system utilizes the intelligent bearing technology, gather vibration acceleration, speed and the temperature signal of bullet train hub bearing, treatment circuit by intelligent bearing inside amplifies vibration acceleration signal, tach signal, and temperature signal amplifies and compensates.Conversion enters monitoring of software analysis to pretreated 6 tunnel simulating signals through A/D.Rely on temperature value, velocity amplitude and vibration acceleration statistic to carry out status monitoring, when monitoring variable surpasses preset threshold, the proof bearing breaks down, at this moment state monitor fault alarm, start the Fault Identification function of Fault Identification device simultaneously, failure judgement occurs on which parts of bearing.The Fault Identification function relies on method for processing signals that digital signal is analyzed and handled and realizes.

Need to prove: the collection of intelligent bearing data is a collection of finishing, and the number of the sampled point that each batch data held is relevant with the cache size of A/D modular converter 2.After a batch data reads in by A/D modular converter 2, to carry out multiple operation,, carry out digital demonstration, graphic presentation, also will realize multiple functions such as status monitoring and Fault Identification by calculating such as to comprising a batch data of 8192 sampling point informations.Only finished all operations, A/D modular converter 2 just can read in the next group data does repetitive operation.

As shown in Figure 2: be provided with in the described state monitor:

Be used for the device that commencing signal is gathered;

Be used to obtain the time domain statistical parameter threshold value S of vibration acceleration signal _R, S _KDevice; S _R, S _KAs predetermined value, be stored in the storer in the processor.

Be used for device with channel number CH, the first variable N1, the second variable N2 zero setting;

Be used to calculate root-mean-square value RMS, the kurtosis COEFFICIENT K of AI0 passage vibration acceleration _FDevice with temperature data value W;

Owing to can't directly obtain vibration performance, use vibration acceleration time domain statistic to reflect the size of vibrational energy.The RMS value has reflected the body vibration energy, and it can estimate the health status of bearing and more stable, but this parameter is responsive inadequately to the initial failure of bearing.The kurtosis COEFFICIENT K _FBe dimensionless group, reflected the size of impact shock, can be used for the initial failure diagnosis, but it can reduce gradually along with the intensification of fault.This diagnostic system adopts the method for two time domain parameter comprehensive evaluations to carry out the monitoring of vibrational state.

Wherein said $\mathrm{RMS}={\left(\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{x_i}^2\right)}^{1/2},$ $K_F=\frac{1}{N}\underset{i=1}{\overset{\mathrm{<figure-callout\; id="4"\; label="N\; x\; i"\; filenames="H2008100702352E00011.png"\; state="\{\{state\}\}">N</figure-callout>}}{\mathrm{\&Sigma;}}}{x_i}^{}{{}_{}}^4/{\left(\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{x_i}^2\right)}^2$

The vibration acceleration signal of described intelligent bearing output is that the form with aanalogvoltage exists, and unit is mv; Through becoming digital voltage signal after the A/D conversion, unit is mv; In processor, digital voltage signal is carried out conversion again, obtain the vibration acceleration value x of sampled point _i, unit is g, its conversion formula is:

$X_i=\frac{X_i^{\&prime;}}{\mathrm{sm}}$

x _i': digital voltage signal, unit are mv;

S: the sensitivity coefficient of vibrating sensing device, unit are mv/g;

M: the enlargement factor of intelligent bearing 1 vibration acceleration signal;

N: bearing inner race rotates 2 and encloses counting of being collected, and is to be that basic calculation draws with the tach signal:

$N=\frac{120f}{\mathrm{nk}}$

F: the sample frequency of every batch data, unit is Hz;

K: port number;

N: rotating speed, unit are r/min;

Be used to judge that temperature data value W is whether greater than 120 device;

If W is greater than 120 for the temperature data value, then be introduced into the device that is used to generate heat alarm;

Whether 120 ℃ be in an important indicator of safe work state as bearing, becomes the threshold value of temperature alarming.

Enter again and be used to judge whether RMS surpasses its threshold value S _RDevice;

If temperature data value W is not more than 120, then directly enters and describedly be used to judge that whether RMS surpasses its threshold value S _RDevice;

Described temperature data value W is: $W=\left(\frac{k}{N_z}\underset{i=1}{\overset{\frac{N_z}{k}}{\mathrm{\&Sigma;}}}\frac{y_i}{t}\right)/S_W$

N _z: total sampling number of every batch data;

K: port number;

y _i: the value of the temperature digital signal sampling point after amplification and compensation, unit is mv;

T: the enlargement factor of intelligent bearing 1 temperature signal;

s _w: the temperature-sensitivity coefficient of intelligent bearing 1, unit are mv/ ℃.

If RMS does not surpass its threshold value S _R, then directly enter and be used to judge the kurtosis COEFFICIENT K _FWhether surpass its threshold value S _KDevice;

If RMS surpasses its threshold value S _R, then enter and be used for the first variable N1 is added 1 device;

Be used to judge that the first variable N1 is whether greater than 5 device;

If greater than 5, then entering, the first variable N1 is used to generate first alerting signal, and to the device of the first variable N1 zero clearing;

Enter the described kurtosis COEFFICIENT K that is used to judge again _FWhether surpass its threshold value S _KDevice;

If the first variable N1 is not more than 5, then directly enter the described kurtosis COEFFICIENT K that is used to judge _FDo not surpass its threshold value S _KDevice;

If K _FDo not surpass its threshold value S _K, then directly enter and be used for channel number CH added 1 device;

If K _FSurpass its threshold value S _K, then enter and be used for the second variable N2 is added 1 device;

Be used to judge that the second variable N2 is whether greater than 5 device;

If greater than 5, then entering, the second variable N2 is used to generate second alerting signal, and to the device of the second variable N2 zero clearing;

Enter described 1 the device that is used for channel number CH added again;

If the second variable N2 is not more than 5, then directly enter described 1 the device that is used for channel number CH added;

Enter again and be used to judge that channel number CH is whether greater than 1 device;

If CH is not more than 1, then directly enter the root-mean-square value RMS, the kurtosis COEFFICIENT K that are used to calculate AI1 passage vibration acceleration _FAnd the device of temperature data value W;

If CH greater than 1, then is introduced into the device that is used for channel number CH zero setting;

Return described root-mean-square value RMS, the kurtosis COEFFICIENT K that is used to calculate AI0 passage vibration acceleration again _FAnd the device of temperature data value W;

As shown in Figure 3: be provided with in the described Fault Identification device:

Be used to begin the device of Fault Identification;

Be used to obtain rolling body and on outer ring raceway, pass through frequency f _OpDevice;

Be used to obtain rolling body and on inner ring raceway, pass through frequency f _IpDevice;

Be used to obtain the gyrofrequency f of the relative retainer of rolling body _BcDevice;

Rolling bearing has n rolling body, and then rolling body passes through frequency f on outer ring and inner ring raceway _OpAnd f _Ip, and the gyrofrequency f of the relative retainer of rolling body _BcBe expressed as respectively:

$f_{\mathrm{op}}=\frac{n}{2}{f}_r(1-\frac{d}{D}\cos \mathrm{\&alpha;}),$ $f_{i_p}=\frac{n}{2}{f}_r(1+\frac{d}{D}\cos \mathrm{\&alpha;}),$ $f_{\mathrm{bc}}=\frac{D}{2d}{f}_r(1+\frac{d^2}{{\mathrm{<figure-callout\; id="2"\; label="d"\; filenames="H2008100702352E00011.png"\; state="\{\{state\}\}">d</figure-callout>}}^2}\stackrel{2}{\cos \mathrm{\&alpha;}})$

D is the pitch diameter of bearing, i.e. the circle at place, rolling body center, and d is the diameter of rolling body, α is a contact angle, f _r=f _i-f ₀Be the frequency that relatively rotates of Internal and external cycle, when outer ring fixedly the time, f _rBe the rotational frequency of axle;

Be used to read vibration acceleration value x _iDevice;

Be used to utilize Fourier transformer, draw vibration acceleration value x _iThe device of frequency spectrum;

The analytic function of data comprises multiple signal processing methods such as cepstrum, filtering, relevant, envelope, can choose suitable analytical approach according to the characteristic of signal, and wherein the frequency spectrum of vibration acceleration is that method by Fourier transform obtains.

Be used in the frequency range less than f/2k, choosing the device of the 1st resonance peak P=1 greater than 3000;

Be used for determining the device of filter bandwidht B=500;

Be used for bandpass filtering, obtain the device of filtering after vibration acceleration time domain signal;

Be used to obtain the device of signal envelope spectrum after the filtering;

Be used for finding out envelope spectrum maximum amplitude Y _mDevice;

Be used to judge Y _m-f _OpThe value device between-5～5 whether;

If Y _m-f _OpValue between-5～5, then enter the device that is used to generate the outer ring fault-signal;

If Y _m-f _OpValue outside-5～5, then enter and be used to judge Y _m-f _IpThe value device between-5～5 whether;

If Y _m-f _IpValue between-5～5, then enter the device that is used to generate the inner ring fault-signal;

If Y _m-f _IpValue outside-5～5, then enter and be used to judge Y _m-f _BcThe value device between-5～5 whether;

If Y _m-f _BcValue between-5～5, then enter the device that is used to generate the rolling body fault-signal;

If Y _m-f _BcValue outside-5～5, then enter and be used to filter bandwidht B to add 100 device;

Vibration acceleration signal is carried out the arrowband bandpass filtering treatment, do the Hilbert conversion then, the analytic signal Q (t) that signal after the conversion and filtered vibration acceleration signal constitute is:

Q(t)＝q(t)+jq ₁(t)

Q (t): filtered signal;

q ₁(t): the signal after the Hilbert conversion.

Right | Q (t) | remake Fourier transform and obtain envelope spectrum, find out the maximum amplitude Y of envelope spectrum _m, at first the fault characteristic frequency with bearing outer ring contrasts, if satisfy-5＜Y _m-f _Op＜5 condition is diagnosed as bearing outer ring and breaks down, and does not carry out the fault judgement of inner ring, rolling body more successively if do not satisfy condition, and Rule of judgment is respectively :-5＜Y _m-f _Ip＜5 ,-5＜Y _m-f _Bc＜5.If three conditions do not satisfy, illustrate the selection of filtering parameter improperly, the program redirect is so that reselect relevant filtering parameter, and same resonance peak is being increased progressively with the filtering bandwidth of 100Hz under as the prerequisite of analytic target, and promptly B adds 100.

Enter again and be used to judge that B is whether greater than 1000 device;

If B is less than or equal to 1000, then return the described bandpass filtering that is used for, obtain the device of filtering after vibration acceleration time domain signal;

If B greater than 1000, then enters the device that is used for choosing at frequency spectrum following 1 resonance peak P=P+1;

If still can't discern the generation of fault when bandwidth surpasses 1000Hz, next so that frequency is higher resonance peak judges again as analytic target, i.e. P=P+1.

Be used to judge that P is whether greater than the frequency sequence number P of high resonance peak _nDevice;

If P is less than or equal to P _n, then return the described device that is used for determining filter bandwidht B=500;

If P is greater than P _n, then enter the device that is used for the output safety signal;

If to all having carried out analyzing the generation that also can't discern fault, i.e. P less than all resonance peaks in the frequency range of f/2k greater than 3000〉P _n, judge bearing safety so, non-fault.

Claims (2)

1. intelligent bearing fault diagnosis system, comprise intelligent bearing (1), this intelligent bearing (1) is provided with six road delivery outlets, wherein first, two road delivery outlet (AI0, AI1) respectively export one group of vibration acceleration signal, the 3rd, four road delivery outlet (AI2, AI3) respectively export one group of tach signal, the 5th, six road delivery outlet (AI4, AI5) respectively export one group of temperature signal, it is characterized in that: six groups of signals of described intelligent bearing (1) output send to the input port of A/D modular converter (2), this A/D modular converter (2) is a digital signal with six groups of conversion of signals, six groups of digital signals of A/D modular converter (2) output send to processor (3), be provided with state monitor (4) and Fault Identification device (5) in this processor (3), wherein state monitor (4) is according to described first, two groups of vibration acceleration digital signals, the 3rd, four groups of rotating speed digital signals and the 5th, six groups of temperature digital signals are monitored the state of bearing, and generation failure alarm signal, state monitor (4) is exported this alerting signal and is driven described Fault Identification device (5), this Fault Identification device (5) utilizes the signal Processing instrument, comprehensive described vibration acceleration digital signal and rotating speed digital signal draw the fault judgement result;

Described state monitor is provided with in (4):

Be used for the device that commencing signal is gathered;

Be used to obtain the time domain statistical parameter threshold value S of vibration acceleration signal _R, S _KDevice;

Be used for device with channel number CH, the first variable N1, the second variable N2 zero setting;

Be used to calculate root-mean-square value RMS, the kurtosis COEFFICIENT K of AI0 passage vibration acceleration _FDevice with temperature data value W;

Be used to judge that temperature data value W is whether greater than 120 device;

If W is greater than 120 for the temperature data value, then be introduced into the device that is used to generate heat alarm;

Enter again and be used to judge whether RMS surpasses its threshold value S _RDevice;

If temperature data value W is not more than 120, then directly enters and describedly be used to judge that whether RMS surpasses its threshold value S _RDevice;

If RMS does not surpass its threshold value S _R, then directly enter and be used to judge the kurtosis COEFFICIENT K _FWhether surpass its threshold value S _KDevice;

If RMS surpasses its threshold value S _R, then enter and be used for the first variable N1 is added 1 device;

Be used to judge that the first variable N1 is whether greater than 5 device;

If greater than 5, then entering, the first variable N1 is used to generate first alerting signal, and to the device of the first variable N1 zero clearing;

Enter the described kurtosis COEFFICIENT K that is used to judge again _FThe device that whether surpasses its threshold value SK;

If the first variable N1 is not more than 5, then directly enter the described kurtosis COEFFICIENT K that is used to judge _FWhether surpass its threshold value S _KDevice;

If K _FDo not surpass its threshold value S _K, then directly enter and be used for channel number CH added 1 device;

If K _FSurpass its threshold value S _K, then enter and be used for the second variable N2 is added 1 device;

Be used to judge that the second variable N2 is whether greater than 5 device;

If greater than 5, then entering, the second variable N2 is used to generate second alerting signal, and to the device of the second variable N2 zero clearing;

Enter described 1 the device that is used for channel number CH added again;

If the second variable N2 is not more than 5, then directly enter described 1 the device that is used for channel number CH added;

Enter again and be used to judge that channel number CH is whether greater than 1 device;

If CH is not more than 1, then directly enter the root-mean-square value RMS, the kurtosis COEFFICIENT K that are used to calculate AI1 passage vibration acceleration _FAnd the device of temperature data value W;

If CH greater than 1, then is introduced into the device that is used for channel number CH zero setting;

Return described root-mean-square value RMS, the kurtosis COEFFICIENT K that is used to calculate AI0 passage vibration acceleration again _FAnd the device of temperature data value W;

Wherein said

The vibration acceleration signal of described intelligent bearing output is that the form with aanalogvoltage exists, and unit is mv; Through becoming digital voltage signal after the A/D conversion, unit is mv; In processor (3), digital voltage signal is carried out conversion again, obtain the vibration acceleration value x of sampled point _i, unit is g, its conversion formula is:

x _i': digital voltage signal, unit are mv;

S: the sensitivity coefficient of vibrating sensing device, unit are mv/g;

M: the enlargement factor of intelligent bearing (1) vibration acceleration signal;

N: bearing inner race rotates 2 and encloses counting of being collected, and is to be that basic calculation draws with the tach signal:

F: the sample frequency of every batch data, unit is Hz;

K: port number;

N: rotating speed, unit are r/min;

Described temperature data value W is:

N _z: total sampling number of every batch data;

K: port number;

y _i: the value of the temperature digital signal sampling point after amplification and compensation, unit is mv;

T: the enlargement factor of intelligent bearing (1) temperature signal;

S _W: the temperature-sensitivity coefficient of intelligent bearing (1), unit are mv/ ℃.

2. intelligent bearing fault diagnosis system according to claim 1 is characterized in that:

Be provided with in the described Fault Identification device (5):

Be used to begin the device of Fault Identification;

Be used to obtain rolling body and on outer ring raceway, pass through frequency f _OpDevice;

Be used to obtain rolling body and on inner ring raceway, pass through frequency f _IpDevice;

Be used to obtain the gyrofrequency f of the relative retainer of rolling body _BcDevice;

Be used to read vibration acceleration value x _iDevice;

Be used to utilize Fourier transformer, draw vibration acceleration signal value x _iThe device of frequency spectrum;

Be used in the frequency range less than f/2k, choosing the device of the 1st resonance peak P=1 greater than 3000;

Be used for determining the device of filter bandwidht B=500;

Be used for bandpass filtering, obtain the device of filtering after vibration acceleration time domain signal;

Be used to obtain the device of signal envelope spectrum after the filtering;

Be used for finding out envelope spectrum maximum amplitude Y _mDevice;

Be used to judge Y _m-f _OpThe value device between-5～5 whether;

If Y _m-f _OpValue between-5～5, then enter the device that is used to generate the outer ring fault-signal;

If Y _m-f _OpValue outside-5～5, then enter and be used to judge Y _m-f _IpThe value device between-5～5 whether;

If Y _m-f _IpValue between-5～5, then enter the device that is used to generate the inner ring fault-signal;

If Y _m-f _IpValue outside-5～5, then enter and be used to judge Y _m-f _BcThe value device between-5～5 whether;

If Y _m-f _BcValue between-5～5, then enter the device that is used to generate the rolling body fault-signal;

If Y _m-f _BcValue outside-5～5, then enter and be used for filter bandwidht B and add 100 device;

Enter again and be used to judge that B is whether greater than 1000 device;

If B is less than or equal to 1000, then return the described bandpass filtering that is used for, obtain the device of filtering after vibration acceleration time domain signal;

If B greater than 1000, then enters the device that is used for choosing at frequency spectrum following 1 resonance peak P=P+1;

Be used to judge that P is whether greater than the frequency sequence number P of high resonance peak _nDevice;

If P is less than or equal to P _n, then return the described device that is used for determining filter bandwidht B=500;

If P is greater than P _n, then enter the device that is used for the output safety signal;

Wherein:

In the formula, D is the pitch diameter of bearing, i.e. the circle at place, rolling body center, and d is the diameter of rolling body, α is a contact angle, f _r=f _i-f ₀Be the frequency that relatively rotates of Internal and external cycle, when outer ring fixedly the time, f _rBe the rotational frequency of axle;

Vibration acceleration signal is carried out the arrowband bandpass filtering treatment, do the Hilbert conversion then, the analytic signal Q (t) that signal after the conversion and filtered vibration acceleration signal constitute is:

Q(t)＝q(t)+jq ₁(t)

Q (t): filtered signal;

q ₁(t): the signal after the Hilbert conversion;

Wherein envelope spectrum is that to remake Fourier transform behind the mould resulting by analytic signal Q (t) each point is asked.

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