CN103412057A - Weak oscillation attenuation signal parameter identification based on stochastic resonance and moving least square - Google Patents
Weak oscillation attenuation signal parameter identification based on stochastic resonance and moving least square Download PDFInfo
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Abstract
The invention relates to weak oscillation attenuation signal parameter identification based on stochastic resonance and moving least square. Firstly, directed at the characteristics of an oscillation attenuation shock signal, information entropy is employed as an immune optimization measure to perform algorithm improvement on parameter adjustment stochastic resonance, thus solving the problem of difficult calculation of the signal to noise ratio quantification measure of an oscillation attenuation signal. Then, two-step stochastic resonance and moving least squares fitting methods are employed to acquire the failure frequency, the oscillation frequency and damping of the weak oscillation attenuation signal and identify the primary fault of a rolling bearing. The technical scheme involved in the invention is of important significance to operating state monitoring and maintenance of rolling bearings and other rotating machineries, and also can be used for mode recognition and other applications.
Description
Technical field
The invention belongs to the mechanical fault diagnosis field, be specifically related to the weak oscillatory extinction signal parameter identification based on accidental resonance and Moving Least Squares.
Background technology
The oscillatory extinction signal is common rotating machinery such as rolling bearing, gear distress characterization signal.The detection of faint oscillatory extinction signal during for initial failure, accidental resonance is domestic and international main solution about the weak signal feature extraction at present, yet the research of accidental resonance is confined to the cosine signal that time domain is unlimited basically to be detected, and the oscillatory extinction signal has the advantages that time domain is tightly propped up, traditional accidental resonance is applied to the problem that faint oscillatory extinction signal demand solves quantitative evaluation parameter adjustment accidental resonance effect.The signal to noise ratio (S/N ratio) of estimating as cosine signal etc. is because the characteristics that the frequency domain of oscillatory extinction signal does not tightly prop up are difficult to calculate.On the other hand, what accidental resonance obtained is generally the failure-frequency of oscillatory extinction signal, thus judgement expression power fault.In order to obtain the quantification information of primary fault and fault degree, need further to obtain damping, oscillation frequency and the amplitude of oscillatory extinction signal.Yet after accidental resonance, signal has become rectangular signal, non-linear amplification has in various degree also been arranged simultaneously.Therefore the inversion method that needs research oscillatory extinction signal.
Summary of the invention
In order to overcome the shortcoming of above-mentioned prior art, the object of the present invention is to provide the weak oscillatory extinction signal parameter identification based on accidental resonance and Moving Least Squares, inverting obtains failure-frequency, oscillatory extinction frequency and the damping of oscillatory extinction signal, the primary fault of identification rolling bearing, significant to monitoring running state and the maintenance of the rotating machineries such as rolling bearing.
In order to achieve the above object, the technical solution used in the present invention is:
Weak oscillatory extinction signal parameter identification based on accidental resonance and Moving Least Squares comprises the following steps:
The first step, carry out the accidental resonance processing to the vibration acceleration signal gathered, and obtains the failure-frequency of vibration damping signal,
The failure-frequency of first pre-estimation vibration signal, in estimation range, select the parameter adjustment accidental resonance that is applicable to large parameter signal to process the vibration acceleration signal gathered,
Wherein, in parameter adjustment accidental resonance process, for the characteristics of oscillatory extinction impact signal, adopt and estimate and immune optimization algorithm based on information entropy, obtain optimum accidental resonance result;
Second step, according to the result of first step accidental resonance, intercept original vibration acceleration signal, and carry out secondary accidental resonance acquisition oscillatory extinction frequency,
According to the result of first step accidental resonance, obtain positional information and cycle information that each oscillatory extinction signal occurs, the vibration acceleration signal of acquired original is carried out to the windowing intercept operation,
Signal to intercepting carries out estimating with the second parameter of immune optimization algorithm and adjusting the accidental resonance operation based on information entropy, obtains the oscillatory extinction frequency of oscillatory extinction signal;
The 3rd step, utilize oscillatory extinction signal oscillating frequency of fadings that second step obtains as parameter, adopts the Moving Least Squares method be with ginseng signal retrieve, acquisition oscillatory extinction signal damping,
According to the result of second step accidental resonance, obtain positional information and cycle information that each oscillatory extinction signal occurs,
Long and the initial position of the window that Moving Least Squares is set according to the positional information obtained and cycle information, then carry out the match of Moving Least Squares method, obtains damping and the amplitude of oscillatory extinction signal.
Advantage of the present invention is: select information entropy to estimate as the immune optimization of parameter adjustment accidental resonance, solved the oscillatory extinction Signal-to-Noise and estimated the problem that is difficult to calculate, obtain accidental resonance effect accurately.By twice accidental resonance, can extract failure-frequency, oscillatory extinction frequency, damping and the amplitude information of signal, can provide diagnosing primary fault and quantification to pass judgment on the foundation of fault degree to the tester.
The accompanying drawing explanation
Fig. 1 is process flow diagram of the present invention.
The vibration acceleration signal figure of Fig. 2 for gathering.
Fig. 3 is the figure as a result of parameter adjustment accidental resonance for the first time.
Fig. 4 is the vibration acceleration signal figure of intercepting.
Fig. 5 is the figure as a result of parameter adjustment accidental resonance for the first time.
Fig. 6 is rolling bearing peak index design sketch.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in detail.
With reference to accompanying drawing 1, the weak oscillatory extinction signal parameter identification based on accidental resonance and Moving Least Squares comprises the following steps:
The first step, carry out the accidental resonance processing to the vibration acceleration signal gathered as shown in Figure 2, obtains failure-frequency, positional information and the oscillatory extinction signal number of vibration damping signal,
Start, reading out data, the failure-frequency of first pre-estimation vibration signal, carry out parameter initialization, in estimation range, selects the parameter adjustment accidental resonance that is applicable to large parameter signal to process the vibration acceleration signal gathered,
Wherein, in parameter adjustment accidental resonance process, characteristics for the oscillatory extinction impact signal, employing is estimated and immune optimization algorithm based on information entropy, obtain optimum accidental resonance result, thereby obtain failure-frequency, positional information and oscillatory extinction signal number information, the T as shown in Figure 3 of vibration damping signal
0For the inaction interval of vibration damping signal, τ
0Positional information for the vibration damping signal;
Second step, according to the result of first step accidental resonance, intercept original vibration acceleration signal, and carry out secondary accidental resonance acquisition oscillatory extinction frequency,
According to the result of first step accidental resonance, obtain positional information and cycle information that each oscillatory extinction signal occurs, the vibration acceleration signal of acquired original is carried out to intercept signal, intercept signal as shown in Figure 4,
Estimate the scope of oscillation frequency, and in this scope, intercept signal is carried out estimating with the second parameter of immune optimization algorithm and adjusting the accidental resonance operation based on information entropy, obtain the oscillatory extinction frequency of oscillatory extinction signal, result as shown in Figure 5;
The 3rd step, utilize oscillatory extinction signal oscillating frequency of fadings that second step obtains as parameter, adopts the Moving Least Squares method be with ginseng signal retrieve, acquisition oscillatory extinction signal damping, fitting result as shown in Figure 6,
Window length and the initial position of Moving Least Squares are set according to failure-frequency, positional information and the oscillatory extinction signal number information of first step accidental resonance result acquisition, utilize the oscillatory extinction signal oscillating frequency of fadings that second step obtains, as Moving Least Squares method known parameters, intercept signal is carried out to match, obtain damping and the amplitude of oscillatory extinction signal.
Claims (1)
1. based on the weak oscillatory extinction signal parameter identification of accidental resonance and Moving Least Squares, it is characterized in that, comprise the following steps:
The first step, carry out the accidental resonance processing to the vibration acceleration signal gathered, and obtains the failure-frequency of vibration damping signal,
The failure-frequency of first pre-estimation vibration signal, in estimation range, select the parameter adjustment accidental resonance that is applicable to large parameter signal to process the vibration acceleration signal gathered,
Wherein, in parameter adjustment accidental resonance process, for the characteristics of oscillatory extinction impact signal, adopt and estimate and immune optimization algorithm based on information entropy, obtain optimum accidental resonance result;
Second step, according to the result of first step accidental resonance, intercept original vibration acceleration signal, and carry out secondary accidental resonance acquisition oscillatory extinction frequency,
According to the result of first step accidental resonance, obtain positional information and cycle information that each oscillatory extinction signal occurs, the vibration acceleration signal of acquired original is carried out to the windowing intercept operation,
Signal to intercepting carries out estimating with the second parameter of immune optimization algorithm and adjusting the accidental resonance operation based on information entropy, obtains the oscillatory extinction frequency of oscillatory extinction signal;
The 3rd step, utilize oscillatory extinction signal oscillating frequency of fadings that second step obtains as parameter, adopts the Moving Least Squares method be with ginseng signal retrieve, acquisition oscillatory extinction signal damping,
According to the result of second step accidental resonance, obtain positional information and cycle information that each oscillatory extinction signal occurs,
Long and the initial position of the window that Moving Least Squares is set according to the positional information obtained and cycle information, then carry out the match of Moving Least Squares method, obtains damping and the amplitude of oscillatory extinction signal.
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| CN104298878A (en) * | 2014-10-14 | 2015-01-21 | 天津工业大学 | Self-adaptive searching method for obtaining optimal parameters of stochastic resonance system |
| CN105067105A (en) * | 2015-05-04 | 2015-11-18 | 西安交通大学 | Kinetic parameter identification method utilizing rotary machine start and stop transient signal feature |
| CN107666328A (en) * | 2017-10-09 | 2018-02-06 | 中国电子科技集团公司第二十研究所 | Low signal-to-noise ratio satellite communication signals method of reseptance |
| CN111220383A (en) * | 2019-11-14 | 2020-06-02 | 东华大学 | Transmission equipment weak fault detection method based on oscillation resonance theory |
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