CN101813560A - Spectrum diagnosing and identifying method of early fault of momentum wheel - Google Patents
Spectrum diagnosing and identifying method of early fault of momentum wheel Download PDFInfo
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Abstract
The invention is used for analyzing spectrum characteristics and a change rule of a momentum wheel by analyzing a time domain and a frequency domain of the dynamic response of the momentum wheel in different running time and is also used for analyzing the causes of spectrum peak generation and spectrum peak change by combining the dynamic characteristic analysis of parts of the momentum wheel and the pulse frequency calculation analysis of bearing parts. Thereby, the early fault of the momentum wheel is identified more scientifically and accurately; and particularly, the cause of the fault is diagnosed in time. On one hand, effective remedial measures can be adopted in time for avoiding unnecessary momentum wheel discard; and on the other hand, the research of fault mode analysis and the like on the momentum wheel can be carried out. The invention can be used for accurately positioning fault points of the momentum wheel, providing more scientific, accurate and effective improving measures, and enhancing the reliability of subsequent products.
Description
Technical field
The present invention relates generally to the detection method that the initial failure reason of momenttum wheel is diagnosed.
Background technology
Is momenttum wheel widely used in utilizing it in the spacecrafts such as various satellites, airship at present? gyroscopic intertia? the attitude of satellite is stablized or changed to the moment of reaction that is produced with velocity variations; As the crucial unit of satellite, its performance directly influences the control accuracy and the reliability of satellite, and in a single day momenttum wheel breaks down and finish major function with having a strong impact on satellite, even causes the whole Star useless.And because the momenttum wheel product is paid the various ground environments test examinations that satellite assembly need carry out half a year to one year, its cycle is long, testing expenses are huge, and in a single day momenttum wheel breaks down, and single every test will be done again, even can cause satellite to delay to launch; Will be to economic benefit, particularly social benefit produces very big harmful effect.
The domestic and international at present identification to early fault of momentum wheel mainly is by the electric current of test momenttum wheel or the size of power consumption, analyze its variation tendency, rule of thumb carry out analysis-by-synthesis and judge whether momenttum wheel initial failure can occur, though this recognition methods is simple relatively, convenient, when ground experiment, can online check and analysis, but it also has following shortcoming:
(1) because momenttum wheel is the system of a relative complex, cause that electric current (power consumption) size and the reason that changes are a lot, sometimes be multiple reason combined action, prior art is just discerned fault, can't carry out scientific and rational diagnosis to the reason that causes fault, particularly can't the early stage reason that cause fault be positioned; When ground experiment, in a single day momenttum wheel breaks down, and can only decompose momenttum wheel, and each parts of momenttum wheel are carried out test analysis, just may find failure cause; Momenttum wheel is in case decompose, and just means that the part parts scrap, every detection in early stage and test irrevocably lost.
(2) when the size of momenttum wheel electric current with when changing at fault critical point, owing to being difficult to judge by empirical analysis whether reason and momenttum wheel will produce fault future, be to continue test mostly, when fault is obvious, the initial reason that fault produces positioned on the one hand with regard to being difficult to; Owing in time do not adopt an effective measure, often cause unnecessary momenttum wheel to scrap on the other hand.
Therefore, the early fault of momentum wheel reason is discerned and diagnosed just important unusually.
Summary of the invention
Task of the present invention is at above-mentioned defective, a kind of early fault of momentum wheel cause diagnosis recognition methods that can accurately find the initial failure and the failure cause of momenttum wheel is provided, to improve the reliability of momenttum wheel and even satellite, science, reasonably take effective innovative approach, reduce the development cost of product.
Technical scheme of the present invention is: spectrum diagnosing and identifying method of early fault of momentum wheel, and at first, detection computations draws the natural frequency of each parts in the static momenttum wheel down and the ripple frequency of momenttum wheel bearing; Then, the momenttum wheel assembling is also carried out running in, detects time-domain signal and the frequency-region signal of momenttum wheel integral body under dynamically; At last, utilize power spectrum analysis method to analyze the momenttum wheel time-domain signal and judge whether momenttum wheel has initial failure, change the ripple frequency that bearing whether occurs or the trouble spot of each parts natural frequency judgement momenttum wheel according to the spectrum peak of the frequency-region signal of momenttum wheel.
When analyzing momenttum wheel time-domain signal and frequency-region signal in the following several ways:
(1) if tangible " basic spectral ≠ 0 " and/or " the spectrum peak group of continuous spectrum " phenomenon can primitive decision be that momenttum wheel has initial failure; When the natural frequency of momenttum wheel parts appearred in the bigger spectrum peak in " the spectrum peak group of continuous spectrum ", it was defective to be defined as these parts;
(2), do not have between the momenttum wheel on-stream period to occur significantly " basic spectral ≠ 0 " and or " the spectrum peak group of continuous spectrum " phenomenon, when bigger spectrum peak that momenttum wheel parts natural frequency causes also not occurring, the decidable momenttum wheel is qualified, no initial failure;
(3), do not have between the momenttum wheel on-stream period to occur significantly " basic spectral ≠ 0 " and or " the spectrum peak group of continuous spectrum " phenomenon, but when bigger spectrum peak that momenttum wheel parts natural frequency causes occurring, prolong the seating time, if Gu the bigger spectrum peak that frequently causes becomes big and time-domain signal becomes big, decidable is that these parts are defective, and initial failure appears in momenttum wheel; Gu if the bigger spectrum peak and the time-domain signal that frequently cause diminish, prolong the seating time again, if the solid bigger spectrum peak that frequently causes and time-domain signal continues to diminish or stable, then being judged to be momenttum wheel does not have initial failure;
(4), only present cycle or the quasi-periodicity signal that the ripple frequency of momenttum wheel bearing causes when frequency-region signal, prolong the running-in test period, its time-domain signal is constant or improve, and the spectrum peak number of frequency-region signal reduces, spectrum peak magnitude descends or is constant, be that the decidable momenttum wheel does not have initial failure, otherwise be unacceptable product.
The described momenttum wheel running in time is 240 hours, and seating time of every prolongation also is 240 hours, and need detect two or more rotating speed in the momenttum wheel operation process and time-domain signal and the frequency-region signal under the plural frequency range.
Described two kinds of rotating speeds are 3000 rev/mins and 6000 rev/mins; Described two frequency ranges are 0～3906Hz and 0～5088Hz.
Before the time-domain signal and frequency-region signal that detect momenttum wheel, need momenttum wheel is carried out pre-running in, to reach the incipient stability state.
The described pre-seating time is 240 hours.
Natural frequency at described each parts of momenttum wheel adopts broadband transient excite method to test and acquisition as calculated by power hammer and sensor testing system.
Described sensor is a foil gauge, and foil gauge is connected with strainmeter, and the power hammer is connected with charge amplifier, and the signal of strainmeter and charge amplifier is simultaneously through the filtering of low pass anti alias filter, by analyzing with the DASP analytic system after the signal sampler collection.
Each parts of described momenttum wheel adopt rigid foam to support or elastic threads hangs two kinds of fixed forms, to imitate the free restrained condition of each parts.
During described momenttum wheel running in, degree of will speed up piezoelectric sensor is installed in momenttum wheel back shaft top, receive the axial response signal of momenttum wheel, charge amplifier amplifies response signal, through the filtering of low pass anti alias filter, gather the momenttum wheel response signal by signal sampler, analyze with the DASP analytic system.
The present invention adopts technique scheme, it is by carrying out time domain and frequency-domain analysis to the dynamic response of momenttum wheel in different working times, analyze its spectrum signature and Changing Pattern, in conjunction with momenttum wheel parts dynamic analysis and the computational analysis of bearing parts ripple frequency, the reason that the analytical spectra peak produces and the spectrum peak changes, thereby science more, find the initial failure of momenttum wheel exactly, particularly failure cause is in time diagnosed and discerned, can in to the maintenance of momenttum wheel, in time take effective remedial measures on the one hand, avoid unnecessary momenttum wheel to scrap, can carry out researchs such as failure mode analysis (FMA) on the other hand to momenttum wheel, accurately locate trouble spot to momenttum wheel, more science is provided, accurately, effectively innovative approach, the reliability of raising subsequent product.This method can also be applied to simultaneously other technical field, and the initial failure of various rotors and bearing is diagnosed and discerned, and improves combination properties such as reliability of products, durability.
Description of drawings
Fig. 1 is the system chart that adopts each parts fixed frequency of supporting way test momenttum wheel among the present invention;
Fig. 2 is the system chart that adopts each parts fixed frequency of sus-pension test momenttum wheel among the present invention;
Fig. 3 is the system chart of momenttum wheel time-domain signal and frequency-region signal among the present invention;
Fig. 4 is fault detect and reason recognition principle figure among the present invention;
Fig. 5 is the time-domain signal figure of specification product among the present invention;
Fig. 6 is the frequency domain signal diagrams of specification product among the present invention;
Fig. 7 is a kind of time-domain signal figure with initial failure product among the present invention;
Fig. 8 is a kind of frequency domain signal diagrams with initial failure product among the present invention.
Embodiment
The natural frequency of each parts of momenttum wheel plays an important role to the dynamic perfromance of momenttum wheel, be the primary work of the diagnosis identification of early fault of momentum wheel so test the natural frequency of each parts, wherein important with the dynamic perfromance of retainer again.In the present embodiment, the natural frequency employing power hammer method of each parts is tested, and as shown in Figure 1 and Figure 2, among the figure, 1 is that foil gauge, 2 is elastic threads for rigid foam, 4 for power hammer, 3.In the fixed frequency test of carrying out each parts, for eliminating is supported the natural frequency of rigid body mode to guarantee the accuracy of measurement result as far as possible, in the test according to the actual installation operating mode of each parts in the momenttum wheel, adopt rigid foam 3 to support or elastic threads 4 sus-pension respectively, to imitate the free restrained condition of each parts as much as possible; The test error that causes for fear of the sensor additional mass adopts foil gauge 1, dynamic strain indicator to receive response signal; In the test, the power hammer adopts broadband transient excite method or makes the pulse excitation method knock parts to be tried, be input in the signal sampler after the filtering of low pass anti alias filter through the power hammer data-signal of charge amplifier amplification and through induced signal (response signal) while of the foil gauge that the broadband strainmeter receives, the signal that signal sampler collects is input in the computing machine by DASP (data acquisition signal processing) analytic system, use power spectrum, the transfer function analysis response signal, with coherence function the transfer function analysis result is tested, each parts is carried out the natural frequency that model analysis calculates each parts by ANSYS software.
In the test, for guaranteeing the confidence level of measurement result, each parts is used with a kind of method and is repeated repeatedly to test, and the result's is repeated fine, and maximum reproducibility error is less than 3%.
In momenttum wheel, bearing vibration has the greatest impact to the flywheel body vibratory response in the momenttum wheel.The essence of bear vibration is to be caused by the excitation in the Contact Pair, and the factor that therefore influences the Contact Pair contact performance all can exert an influence to the bearing vibration characteristic.The defective of bearing parts can produce low frequency pulsating at the volley, and the vibration that pulsation evokes can be developed into progressive infinite simple harmonic quantity progression, and its fundamental frequency is ripple frequency, thereby need calculate the ripple frequency of each parts on the bearing.
When time-domain signal under the test momenttum wheel is dynamic and frequency-region signal, as shown in Figure 3, momenttum wheel is rotatably installed on the pedestal, and stabilized voltage supply provides burning voltage for the DC voltage velometer for momenttum wheel, and the flywheel body that drives momenttum wheel rotates.The acceleration piezoelectric sensor is installed in the top of flywheel body back shaft, receive the axial response letter of flywheel body, charge amplifier amplifies response signal, through the filtering of low pass anti alias filter, gather the flywheel response signal by signal sampler, analyze with the DASP analytic system.
Frequency-domain analysis refers to and obtains the analysis that concerns between amplitude and the frequency after the signal analysis, and its basis is spectrum analysis, promptly analyzes amplitude, phase place, power and the energy of the Dynamic Signal distribution relation with frequency.And fault is in the variation that frequency structure takes place and all can cause during development, thus frequency spectrum analysis method be use in the mechanical fault diagnosis one of signal processing method the most widely.Frequency spectrum analysis method mainly comprises: fft analysis is fast fourier transform analysis, power spectrumanalysis, cepstrum analysis etc.Wherein, power spectrum is an amount of describing the random vibration feature in frequency field.Power spectrum has reflected the energy of each harmonic component in the signal, the periodic signal in available its detection random signal.Thereby among the present invention analysis of experiments based on power spectrumanalysis.During analysis of experiments different time, rotating speed are carried out each frequency range point-to-point analysis.In the present embodiment, at first momenttum wheel is carried out 240 hours pre-running in, make flywheel and bearing unit reach the incipient stability state, to guarantee precision of test result, under 240 hours, 480 hours, 720 hours, 960 hours four time points of running and 3000 rev/mins, 6000 rev/mins two rotating speeds, flywheel is carried out the test of time domain and frequency-region signal respectively according to actual conditions then, main time domain and the frequency-region signal of analyzing in 0～3906Hz and two frequency ranges of 0～5088Hz, each segmentation frequency range is adopted four measuring points.
Usually, the athletic performance of system is divided 4 kinds of steady motion states: balance, periodic motion, quasi-periodic motion and chaos as shown in Figure 4.When reality is tested, the reason identification that divides following several states to carry out early fault of momentum wheel analysis and fault:
1. if significantly " basic spectral ≠ 0 " and or " the spectrum peak group of continuous spectrum " phenomenon, getting final product primitive decision be that momenttum wheel has initial failure; When the natural frequency of momenttum wheel parts appearred in the bigger spectrum peak in " the spectrum peak group of continuous spectrum ", it was defective to be defined as these parts;
2., do not have between the momenttum wheel on-stream period to occur significantly " basic spectral ≠ 0 " and or " the spectrum peak group of continuous spectrum " phenomenon, when bigger spectrum peak that momenttum wheel parts natural frequency causes also not occurring, the decidable momenttum wheel is qualified, no initial failure;
3., do not have between the momenttum wheel on-stream period to occur significantly " basic spectral ≠ 0 " and or " the spectrum peak group of continuous spectrum " phenomenon, but when bigger spectrum peak that momenttum wheel parts natural frequency causes occurring, prolong the seating time, if Gu the bigger spectrum peak that frequently causes becomes big and time-domain signal becomes big, decidable is that these parts are defective, and initial failure appears in momenttum wheel; Gu if the bigger spectrum peak and the time-domain signal that frequently cause diminish, prolong the seating time again, if the solid bigger spectrum peak that frequently causes and time-domain signal continues to diminish or stable, then being judged to be momenttum wheel does not have initial failure;
4., only present cycle or the quasi-periodicity signal that the ripple frequency of momenttum wheel bearing causes when frequency-region signal, prolong the running-in test period, its time-domain signal is constant or improve, and the spectrum peak number of frequency-region signal reduces, spectrum peak magnitude descends or is constant, be that the decidable momenttum wheel does not have initial failure, otherwise be unacceptable product.
In concrete enforcement, when 8 momenttum wheels were tested, as shown in Figure 5, wherein the time-domain signal of 7 momenttum wheels was less, and amplitude is about 30; As shown in Figure 6, its frequency-region signal is a discrete spectrum, and the bigger spectrum peak that the natural frequency of momenttum wheel parts, particularly retainer natural frequency cause do not occur, shows that 7 flywheels operate steadily all the time.But wherein the time-domain signal of 1 flywheel when running-in diagnosis in 240 hours is very big, and as shown in Figure 7, its amplitude is 256; Frequency-region signal its basic spectral as shown in Figure 8 is not 0, and continuous spectrum peak phenomenon occurs, and the natural frequency of retainer appears in bigger spectrum peak, a place wherein, judges that promptly this momenttum wheel has initial failure, and its trouble spot is a retainer.After this momenttum wheel decomposition, the empirical tests failure cause is that the retainer running is unstable, produces early stage excessive wear.Other momenttum wheels examine its fiduciary level to reach 99.49% through every performance test and life-span, much larger than 98% of existing regulation, have obtained good effect.
Because fault all can cause the variation of frequency structure when taking place and develop, the present invention is by carrying out time-domain analysis, frequency-domain analysis to the dynamic response of momenttum wheel in different working times, analyze its spectrum signature and Changing Pattern, in conjunction with momenttum wheel parts dynamic analysis and the computational analysis of bearing parts ripple frequency, the reason that the analytical spectra peak produces and the spectrum peak changes, thus can carry out the initial failure diagnostic analysis to momenttum wheel exactly.The method of the invention provides science more, exactly the initial failure of momenttum wheel being discerned, particularly failure cause is in time diagnosed, can in time take effectively not rescue measure on the one hand, avoid unnecessary momenttum wheel to scrap, can accurately locate fault on the other hand, take effective innovative approach, effectively improve the reliability of momenttum wheel.
The present invention not only can diagnose identification to the initial failure of momenttum wheel, simultaneously, can also be used to detect the diagnosis of the initial failure of other bearing parts or rotor, and analyzing failure cause is very helpful for the quality that improves product.
Claims (10)
1. spectrum diagnosing and identifying method of early fault of momentum wheel is characterized in that, at first, detection computations draws the natural frequency of each parts in the static momenttum wheel down and the ripple frequency of momenttum wheel bearing; Then, the momenttum wheel assembling is also carried out running in, detects time-domain signal and the frequency-region signal of momenttum wheel integral body under dynamically; At last, utilize power spectrum analysis method to analyze the momenttum wheel time-domain signal and judge whether momenttum wheel has initial failure, change the ripple frequency that bearing whether occurs or the trouble spot of each parts natural frequency judgement momenttum wheel according to the spectrum peak of the frequency-region signal of momenttum wheel.
2. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 1 is characterized in that, when analyzing momenttum wheel time-domain signal and frequency-region signal in the following several ways:
(1) if tangible " basic spectral ≠ 0 " and/or " the spectrum peak group of continuous spectrum " phenomenon can primitive decision be that momenttum wheel has initial failure; When the natural frequency of momenttum wheel parts appearred in the bigger spectrum peak in " the spectrum peak group of continuous spectrum ", it was defective to be defined as these parts;
(2), do not have to occur significantly " basic spectral ≠ 0 " and/or " the spectrum peak group of continuous spectrum " phenomenon between the momenttum wheel on-stream period, when bigger spectrum peak that momenttum wheel parts natural frequency causes also not occurring, the decidable momenttum wheel is qualified, no initial failure;
(3), there is not to occur significantly " basic spectral ≠ 0 " and/or " the spectrum peak group of continuous spectrum " phenomenon between the momenttum wheel on-stream period, but when bigger spectrum peak that momenttum wheel parts natural frequency causes occurring, prolong the seating time, if Gu the bigger spectrum peak that frequently causes becomes big and time-domain signal becomes big, decidable is that these parts are defective, and initial failure appears in momenttum wheel; Gu if the bigger spectrum peak and the time-domain signal that frequently cause diminish, prolong the seating time again, if the solid bigger spectrum peak that frequently causes and time-domain signal continues to diminish or stable, then being judged to be momenttum wheel does not have initial failure;
(4), only present cycle or the quasi-periodicity signal that the ripple frequency of momenttum wheel bearing causes when frequency-region signal, prolong the running-in test period, its time-domain signal is constant or improve, and the spectrum peak number of frequency-region signal reduces, spectrum peak magnitude descends or is constant, be that the decidable momenttum wheel does not have initial failure, otherwise be unacceptable product.
3. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 1 and 2, it is characterized in that, the described momenttum wheel running in time is 240 hours, seating time of every prolongation also is 240 hours, and need detect two or more rotating speed in the momenttum wheel operation process and time-domain signal and the frequency-region signal under the plural frequency range.
4. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 3 is characterized in that, described two kinds of rotating speeds are 3000 rev/mins and 6000 rev/mins; Described two frequency ranges are 0～3906Hz and 0～5088Hz.
5. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 1 and 2 is characterized in that, before the time-domain signal and frequency-region signal that detect momenttum wheel, needs momenttum wheel is carried out pre-running in, to reach the incipient stability state.
6. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 4 is characterized in that, the described pre-seating time is 240 hours.
7. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 1 is characterized in that, tests and acquisition as calculated by power hammer and sensor testing system employing broadband transient excite method in the natural frequency of described each parts of momenttum wheel.
8. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 6, it is characterized in that, described sensor is a foil gauge, foil gauge is connected with strainmeter, the power hammer is connected with charge amplifier, the signal of strainmeter and charge amplifier is simultaneously through the filtering of low pass anti alias filter, by analyzing with the DASP analytic system after the signal sampler collection.
9. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 7 is characterized in that, each parts of described momenttum wheel adopt rigid foam to support or elastic threads hangs two kinds of fixed forms, to imitate the free restrained condition of each parts.
10. spectrum diagnosing and identifying method of early fault of momentum wheel according to claim 1, it is characterized in that, during described momenttum wheel running in, degree of will speed up piezoelectric sensor is installed in momenttum wheel back shaft top, receive the axial response signal of momenttum wheel, charge amplifier amplifies response signal, through the filtering of low pass anti alias filter, gather the momenttum wheel response signal by signal sampler, analyze with the DASP analytic system.
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| CN103644966A (en) * | 2013-12-29 | 2014-03-19 | 中国科学技术大学 | Periodic signal enhancement detection device and method |
| CN104880303A (en) * | 2015-04-30 | 2015-09-02 | 北京控制工程研究所 | Comprehensive judging method for fault of space movable part shafting |
| CN105300675A (en) * | 2015-10-14 | 2016-02-03 | 哈尔滨工业大学 | Proportion coefficient analysis-based momentum wheel fault diagnosis method |
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| CN104880303A (en) * | 2015-04-30 | 2015-09-02 | 北京控制工程研究所 | Comprehensive judging method for fault of space movable part shafting |
| CN104880303B (en) * | 2015-04-30 | 2017-06-27 | 北京控制工程研究所 | A Comprehensive Judgment Method for Shafting Faults of Space Moving Parts |
| CN105300675A (en) * | 2015-10-14 | 2016-02-03 | 哈尔滨工业大学 | Proportion coefficient analysis-based momentum wheel fault diagnosis method |
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| CN109765426A (en) * | 2019-01-28 | 2019-05-17 | 哈尔滨工业大学 | A fast identification method of system model parameters based on wide-spectrum excitation signal |
| CN109765426B (en) * | 2019-01-28 | 2020-12-04 | 哈尔滨工业大学 | A fast identification method of system model parameters based on wide-spectrum excitation signal |
| CN111581762A (en) * | 2019-02-15 | 2020-08-25 | 中国航发商用航空发动机有限责任公司 | Early fault diagnosis method and system |
| CN111581762B (en) * | 2019-02-15 | 2023-04-14 | 中国航发商用航空发动机有限责任公司 | Early fault diagnosis method and system |
| CN111473750A (en) * | 2020-04-08 | 2020-07-31 | 江苏科技大学 | Device and method for monitoring lubricating wear state of main bearing of diesel engine |
| CN115380197A (en) * | 2020-04-13 | 2022-11-22 | 株式会社日立制作所 | Abnormal diagnosis device and maintenance management system |
| CN115380197B (en) * | 2020-04-13 | 2025-03-28 | 株式会社日立制作所 | Abnormal diagnosis equipment and maintenance management system |
| TWI741629B (en) * | 2020-06-01 | 2021-10-01 | 中華電信股份有限公司 | Machine spindle running-in pre-checking method and computer-readable medium |
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