CN102507186B - Characteristic parameter-based method for condition monitoring and fault identification of planetary gearbox - Google Patents

Characteristic parameter-based method for condition monitoring and fault identification of planetary gearbox Download PDF

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CN102507186B
CN102507186B CN201110340196.5A CN201110340196A CN102507186B CN 102507186 B CN102507186 B CN 102507186B CN 201110340196 A CN201110340196 A CN 201110340196A CN 102507186 B CN102507186 B CN 102507186B
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signal
sun gear
frequency
epicyclic gearbox
characteristic parameter
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CN102507186A (en
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雷亚国
林京
孔德同
韩冬
廖与禾
王琇峰
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Xian Jiaotong University
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Xian Jiaotong University
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Abstract

The invention discloses a characteristic parameter-based method for the condition monitoring and the fault identification of a planetary gearbox. According to the characteristic parameter-based method, two characteristic parameters, i.e. filtered root mean square (FRMS) and difference spectrum energy (DSE), are proposed, the running condition of the planetary gearbox is monitored respectively through a time domain and a frequency domain due to the two characteristic parameters, and the fault of the planetary gearbox is finally identified by combining the time domain with the frequency domain. The characteristic parameter-based method has the advantages that: the two characteristic parameters are proposed aiming at the problem of fault diagnosis of the planetary gearbox, the defects that the traditional parameters, such as root mean square, kurtosis, FM0, FM4 and the like, for the condition monitoring of a fixed-axle gearbox cannot used for effectively monitoring the running condition of the planetary gearbox, are overcome, and thus, the condition monitoring and the fault identification of the planetary gearbox can be accurately achieved.

Description

A kind of epicyclic gearbox status monitoring and fault identification method based on characteristic parameter
Technical field
The invention belongs to mechanical fault diagnosis field, relate to a kind of epicyclic gearbox status monitoring and fault identification method based on characteristic parameter, can to the running status of epicyclic gearbox, monitor accurately, effectively realize the fault identification of epicyclic gearbox.
Background technology
The plurality of advantages such as that epicyclic gearbox has is lightweight, volume is little, ratio of gear is large, load-bearing capacity is strong, transmission efficiency is high, have therefore been widely used in the machine driven system of the industries such as wind-power electricity generation, aviation, boats and ships, metallurgy, petrochemical industry, mine, lifting transportation.Epicyclic gearbox is usually operated under the rugged surroundings of low-speed heave-load, so the faults such as the heavy wear of the critical components such as sun gear, planetary gear, ring gear and planet carrier and fatigue crack happen occasionally.
Its inner structure of epicyclic gearbox is complicated, generally sun gear, planetary gear and ring gear, consists of.Once certain parts breaks down in epicyclic gearbox, just may cause chain reaction, cause the shutdown of whole kinematic train, cause huge economic loss and severe social influence.Therefore the condition monitoring and fault diagnosis of epicyclic gearbox is become to very important.Due to the complex internal structure of epicyclic gearbox, it is carried out to condition monitoring and fault diagnosis also very difficult.Epicyclic gearbox is different from each gear with the dead axle transmission gear case of its fixing central shaft rotation.Planetary transmission system is comprised of sun gear, a plurality of planetary gear, ring gear and planet carrier etc.Conventionally ring gear maintains static, and sun gear is around the central shaft rotation of self, and several planetary gear is not only around central shaft rotation separately, simultaneously around the central shaft revolution of sun gear, and meshes with sun gear and ring gear simultaneously.Therefore, the motion of epicyclic gearbox middle gear is typical compound motion, and its vibratory response is more more complicated than dead axle transmission gear case, and corresponding troubleshooting issue has feature and the difficult point of self.Therefore, some characteristic parameters for fixed axis gear case can not carry out status monitoring and fault identification to epicyclic gearbox effectively.Parameter for fixed axis gear case status monitoring comprises effective value (RMS), kurtosis (K), FM0, FM4 etc. at present.
Time-domain and frequency-domain is two importances of portraying plant equipment Dynamic Signal characteristic, by developing certain characteristic parameter in time domain or frequency domain, can realize effective monitoring and fault identification to mechanical equipment state.By describing the size conversion of spectrum energy and the increase and decrease of corresponding frequencies in frequency spectrum, failure message that can characterization device.In general, when calculated characteristics parameter, often to carry out filtering processing to signal, filter out the information irrelevant with fault, then characteristic parameter is processed and extracted to Fault-Sensitive information.
Summary of the invention
The object of the invention is to overcome above-mentioned the deficiencies in the prior art, a kind of epicyclic gearbox status monitoring and fault identification method based on characteristic parameter is provided.The method, from time domain and two characteristic parameters of frequency-domain calculations, is carried out status monitoring and fault identification to epicyclic gearbox, can comparatively comprehensively to the vibration information of epicyclic gearbox, extract like this.Effective value in time domain can reflected signal the power of vibration, normal information is filtered out, remaining composition is failure message.In frequency domain, the frequency spectrum of the frequency spectrum of measured signal and normal signal is made to poor spectrum, poor spectrum faults information.By the characteristic parameter combination of two time-domain and frequency-domains, can effectively carry out status monitoring and the fault identification of epicyclic gearbox.
Technical scheme of the present invention is carried out in accordance with the following steps:
(1) calculation of filtered signal effective value (FRMS), first carries out filtering to signal, then the effective value of signal after calculation of filtered;
(2) calculate poor spectrum energy (DSE), first calculate the poor spectrum of the vibration signal of collection and the normal vibration signal of this epicyclic gearbox, then calculate the poor corresponding energy of composing, finally above energy is normalized;
(3) 2 parameters of trying to achieve are above combined, epicyclic gearbox is carried out to fault identification.
In step (1):
The vibration signal filtering that sensor is gathered.The maximal value that finds spectral magnitude in each half planet carrier modulation frequency range of theoretical meshing frequency left and right, frequency corresponding to maximal value is actual meshing frequency.According to identical way, find 2 rank, 3 rank meshing frequencies.Signal within each 6 rank planet carrier modulation frequency range of 1-3 rank meshing frequency left and right is all filtered out, and the sun gear 1-5 simultaneously filtering out in vibration signal doubly turns frequently, finally the time-domain signal after filtering is calculated to effective value, obtains FRMS;
In step (2):
First vibration signal is carried out to Fourier transform, then calculate the poor spectrum of the historical normal signal of frequency spectrum and this epicyclic gearbox, to being greater than 0 amplitude in poor spectrum, add up afterwards, finally by gained cumulative sum divided by all frequency spectrum amplitudes of respective signal be normalized;
In step (3):
Take first parameter as horizontal ordinate, take second parameter as ordinate, the result of two parameters is plotted on a figure, epicyclic gearbox is carried out to fault identification.
Core of the present invention is to have realized the extraction of the characteristic parameter of reflection epicyclic gearbox running status and failure condition, combines the information of time-domain and frequency-domain, and Fault-Sensitive feature is provided.Can monitor the running status of epicyclic gearbox like this, realize the identification of epicyclic gearbox fault.
Accompanying drawing explanation
Fig. 1 is a kind of epicyclic gearbox status monitoring based on characteristic parameter and the process flow diagram of fault identification method;
Fig. 2 (a) be while having load FRMS and DSE to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 2 (b) is non-loaded, FRMS and DSE are to sun gear crackle, wearing and tearing, normal classification results.
Fig. 3 (a) be while having load RMS and K to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 3 (b) is non-loaded, RMS and K are to sun gear crackle, wearing and tearing, normal classification results.
Fig. 4 (a) be while having load RMS and FM0 to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 4 (b) is non-loaded, RMS and FM0 are to sun gear crackle, wearing and tearing, normal classification results.
Fig. 5 (a) be while having load RMS and FM4 to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 5 (b) is non-loaded, RMS and FM4 are to sun gear crackle, wearing and tearing, normal classification results.
Fig. 6 (a) be while having load K and FM0 to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 6 (b) is non-loaded, K and FM0 are to sun gear crackle, wearing and tearing, normal classification results.
Fig. 7 (a) be while having load K and FM4 to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 7 (b) is non-loaded, K and FM4 are to sun gear crackle, wearing and tearing, normal classification results.
Fig. 8 (a) be while having load FM0 and FM4 to sun gear crackle, wearing and tearing, normal classification results.
When Fig. 8 (b) is non-loaded, FM0 and FM4 are to sun gear crackle, wearing and tearing, normal classification results.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in further detail: shown in accompanying drawing 1, flow process of the present invention is as follows:
1) with acceleration transducer, gather the vibration signal of epicyclic gearbox;
2) to vibration signal filtering.In each half planet carrier modulation frequency range of theoretical meshing frequency left and right, find the maximal value of spectral magnitude, frequency corresponding to maximal value is actual meshing frequency, according to identical way, find 2 rank, 3 rank meshing frequencies, signal within each 6 rank planet carrier modulation frequency range of 1-3 rank meshing frequency left and right is all filtered out, the sun gear 1-5 simultaneously filtering out in vibration signal doubly turns frequently, finally the time-domain signal after filtering is calculated to effective value and just obtains first characteristic parametric filtering signal effective value (FRMS);
3) frequency spectrum of this signal and normal signal are made to poor spectrum, to being greater than 0 amplitude in poor spectrum, add up afterwards, finally by gained cumulative sum divided by all frequency spectrum amplitudes of respective signal be normalized and just obtain second characteristic parameter difference spectrum energy (DSE);
4) will be above step 2) with step 3) two characteristic parameter F RMS, DSE obtaining are plotted on a figure, take DSE as horizontal ordinate, take FRMS as ordinate, just obtain the classification results in conjunction with two parameters.
Epicyclic gearbox status monitoring according to above summary of the invention and Fig. 1 a kind of based on characteristic parameter and the process flow diagram of fault identification method, carry out status monitoring and fault identification to certain epicyclic gearbox.This epicyclic gearbox has gear for two stage planetary gear train transmission, and every one-level is all that sun gear rotates, and ring gear is fixed, and we are normal to this epicyclic gearbox first order sun gear, crackle, three kinds of operating modes of wearing and tearing carry out fault identification.First order Gear Planet Transmission has three planetary gears, and the number of teeth of each planetary gear is 40, and the sun gear number of teeth is 20, and the ring gear number of teeth is 100.Turning of sun gear is frequently respectively 35Hz, 40Hz, 45Hz, 50Hz, at every kind, is divided into again under turning frequently and loads and do not load two kinds of situations,, crackle normal to first order sun gear, three kinds of pattern fault identifications of wearing and tearing.With sensor gather its vertical diameter to vibration signal, sample frequency is set to 5120Hz, sampling length was 120 seconds, using every 4 second length data as two characteristic parameters of a sample calculation, under each operating mode, calculate 15 samples like this.According to foregoing invention content,, first order sun gear crackle normal to gear, first order sun gear abrasion condition are diagnosed respectively.Shown in Fig. 1, calculate first characteristic parameter, first the vibration signal of acceleration transducer collection is carried out to filtering, filtered data are calculated to RMS, obtain the characteristic parameter F RMS in time domain; Calculate second characteristic parameter, first this signal is carried out to FFT, then this signal and historical normal signal are made to poor spectrum, afterwards the amplitude that is greater than 0 in poor spectrum is added up, finally by gained cumulative sum divided by all frequency spectrum amplitudes of respective signal be normalized, obtain the characteristic parameter DSE in frequency domain; By two characteristic parameter F RMS, DSE combination, above sample is classified, result as shown in Figure 2, Fig. 2 (a) represents classification results when load is 13.5Nm, Fig. 2 (b) represents classification results when non-loaded, and wherein, △ represents normal sample, zero represents first order sun gear wearing and tearing ,+represent first order sun gear crackle.As can be seen from Figure 2 do not load and load in two kinds of situations, classification results is all more satisfactory, will be normal, first order sun gear crackle, three kinds of operating modes of first order sun gear wearing and tearing separate completely, 4 kinds turn and frequently have all samples of non-loaded 8 kinds of operating modes accurately to divide, fault identification is accurate.Normally, the classification results of three kinds of patterns of first order sun gear crackle, first order sun gear wearing and tearing, sample inter-object distance is little, between class distance is large, effective, fault identification is simple and reliable.
In order to prove the validity of foregoing invention content, adopt several conventional indexs equally above-mentioned operating mode to be classified, the index of selecting is effective value (RMS), kurtosis (K), FM0, FM4.By above parameter combination of two, for classification, result is as shown in Fig. 3-8, and △ represents normal sample, and zero represents first order sun gear wearing and tearing ,+represent first order sun gear crackle.Wherein Fig. 2 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, two kinds of characteristic parameter F RMS of first order sun gear crack fault, the wearing and tearing of first order sun gear and the classification results of DSE, (b) under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, two kinds of characteristic parameter F RMS of first order sun gear crack fault, the wearing and tearing of first order sun gear and the classification results of DSE; Fig. 3 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the RMS of sun gear wearing and tearing and the classification results of K, (b) be under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the RMS of sun gear wearing and tearing and the classification results of K; Fig. 4 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the RMS of sun gear wearing and tearing and the classification results of FM0, (b) be under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the RMS of sun gear wearing and tearing and the classification results of FM0; Fig. 5 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the RMS of sun gear wearing and tearing and the classification results of FM4, (b) be under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the RMS of sun gear wearing and tearing and the classification results of FM4; Fig. 6 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the K of sun gear wearing and tearing and the classification results of FM0, (b) be under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the K of sun gear wearing and tearing and the classification results of FM0; Fig. 7 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the K of sun gear wearing and tearing and the classification results of FM4, (b) be under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the K of sun gear wearing and tearing and the classification results of FM4; Fig. 8 (a) load is in 13.5Nm situation, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the FM0 of sun gear wearing and tearing and the classification results of FM4, (b) be under immunization with gD DNA vaccine, to three kinds of operating modes be that whole gears are normal, sun gear crack fault, the FM0 of sun gear wearing and tearing and the classification results of FM4.As can be seen from the figure, the result of the combination of two gained of above Common Parameters RMS, K, FM0, FM4, the sample in normal, first order sun gear crackle, three kinds of situations of first order sun gear wearing and tearing overlaps, and cannot carry out identification to fault.By contrast, can find out superiority of the present invention.
Above invention decomposition result is good, easy to operate simple, and status monitoring and fault identification that a kind of epicyclic gearbox status monitoring based on characteristic parameter and fault identification method can be realized epicyclic gearbox are better described.
Above content is in conjunction with concrete preferred implementation further description made for the present invention; can not assert that the specific embodiment of the present invention only limits to this; for general technical staff of the technical field of the invention; without departing from the inventive concept of the premise; can also make some simple deduction or replace, all should be considered as belonging to the present invention and determine scope of patent protection by submitted to claims.

Claims (1)

1. epicyclic gearbox status monitoring and the fault identification method based on characteristic parameter, is characterized in that, comprising:
(1) calculation of filtered signal effective value FRMS, first carries out filtering to signal, then the effective value of signal after calculation of filtered; Described calculation of filtered signal effective value FRMS, the vibration signal filtering that sensor is gathered, in each half planet carrier modulation frequency range of theoretical meshing frequency left and right, find the maximal value of spectral magnitude, frequency corresponding to maximal value is actual meshing frequency, according to identical way, find 2 rank, 3 rank meshing frequencies, signal within each 6 rank planet carrier modulation frequency range of 1-3 rank meshing frequency left and right is all filtered out, the sun gear 1-5 simultaneously filtering out in vibration signal doubly turns frequently, finally the time-domain signal after filtering is calculated to effective value, obtain FRMS;
(2) calculate poor spectrum energy DSE, first calculate the poor spectrum of the vibration signal of collection and the normal vibration signal of this epicyclic gearbox, then calculate the poor corresponding energy of composing, finally above energy is normalized; The poor spectrum energy DSE of described calculating, first be vibration signal to be carried out to Fourier transform obtain frequency spectrum, then calculate the poor spectrum of the normal signal of vibration signal frequency spectrum and this epicyclic gearbox, to being greater than 0 amplitude in poor spectrum, add up afterwards, finally by the poor spectrum cumulative sum of gained divided by all frequency spectrum amplitudes of this signal be normalized, obtain DSE;
(3) two parameters of trying to achieve are above combined, epicyclic gearbox is carried out to fault identification; First characteristic parameter F RMS of take is ordinate, and second the characteristic parameter DSE of take is horizontal ordinate, and the result of two characteristic parameters is plotted on a figure, and the fault of epicyclic gearbox is carried out to identification.
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