CN109063668B - Impact signal envelope demodulation method based on peak value retention and down-sampling - Google Patents
Impact signal envelope demodulation method based on peak value retention and down-sampling Download PDFInfo
- Publication number
- CN109063668B CN109063668B CN201810922977.7A CN201810922977A CN109063668B CN 109063668 B CN109063668 B CN 109063668B CN 201810922977 A CN201810922977 A CN 201810922977A CN 109063668 B CN109063668 B CN 109063668B
- Authority
- CN
- China
- Prior art keywords
- signal
- envelope
- frequency
- sampling
- peak
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Theoretical Computer Science (AREA)
- Artificial Intelligence (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention provides an impulse signal envelope demodulation method based on peak value preserving and down-sampling, which realizes the acquisition of original signal envelope waveform through a peak value extraction algorithm, wherein the main calculation processes of the extraction algorithm are signal difference, multiplication and comparison, after the envelope waveform is acquired, the envelope waveform is down-sampled by using a peak value preserving and down-sampling method, the reduction of analysis frequency is realized, and finally, Fourier transform is carried out on down-sampled data to obtain the frequency spectrum characteristics of a fault signal, so as to obtain the related fault information of equipment. The invention better solves the following problems in the prior envelope demodulation method: the method is suitable for impact characteristic extraction in a rotary mechanical fault diagnosis system and is easy to integrate in a real-time online system.
Description
Technical Field
The invention relates to the field of mechanical fault diagnosis, in particular to an impact signal envelope demodulation method based on peak value retention downsampling.
Background
Rotating machines are widely used in various industrial fields, and the operation quality of the rotating machines, whether gears or bearings, directly affects the working performance of the whole equipment. Once the faults of the rotating parts are not discovered in time, the production accidents such as machine damage, production line shutdown and even personnel casualty can be caused. Therefore, the method has great significance for monitoring and analyzing early faults of related similar equipment.
In the field of mechanical failure diagnosis, when parts such as a rolling bearing or a gear have local damage or defects, attenuation impact is generated in the load operation process, and high-frequency natural vibration of the parts can be excited by the impact signal. The amplitude of the high-frequency natural vibration is modulated by fundamental waves generated by impact caused by physical defects as a carrier signal, so that the vibration waveform which can be collected from the outside presents a complex amplitude modulation phenomenon. The attenuation impact responses actually contain relevant fault information corresponding to the components.
For such modulation signals, especially when the frequency components are relatively complex and contain many signal components, the traditional frequency domain method cannot accurately locate the equipment fault. The modulation signal needs to be effectively extracted, and the envelope demodulation method can separate the fault information contained in the signal from the complex amplitude modulation vibration signal, and is one of the most widely applied diagnosis methods at present. There are many envelope demodulation methods, and currently, there are technologies commonly used in the art, such as those based on Hilbert Transform (HT: Hilbert Transform) (songxiang, rolling bearing fault diagnosis research based on envelope demodulation analysis, instrumentation and analysis monitoring, 2012), generalized detection envelope (li army, amplitude modulation signal envelope detection method and system, patent No. CN104218894B), and peak detection (hound, impulse signal demodulation method based on all-digital peak detection, patent No. CN 103308310B).
The main principle of the HT method is that firstly, band-pass filtering is utilized to filter low-frequency components in signals, modulated high-frequency components are obtained as much as possible, then, a test signal generates a 90-degree phase shift through HT, and the test signal and an original signal form an analytic signal, and the analytic signal forms an envelope signal; the bearing vibration signal with defects is converted into an envelope signal after Hilbert transform detection, and then the envelope signal is subjected to spectrum analysis, so that the frequency spectrum contains low-frequency excitation frequency, namely defect frequency. The generalized detection enveloping method comprises the steps of firstly obtaining an amplitude modulation signal and a corresponding carrier signal frequency, carrying out quarter-cycle time delay and half-cycle time delay after obtaining cycle time, multiplying a half-cycle time delay signal by a difference value of the half-cycle time delay signal and an original signal, and solving a square root value of the obtained signal and the quarter-cycle time delay signal to obtain an enveloping signal of the original amplitude modulation signal. The peak detection utilizesThe method for realizing impulse signal demodulation by digital peak detection simulates the RC charge-discharge process by using Ae-t/τFiltering for the morphological filtering algorithm of structural elements, firstly making an initial impact peak value A0According to A0e-t/τAttenuation is carried out to obtain an attenuation value AiThe next acquired impact peak A1And AiBy comparison, if A1≤AiThen abandon A1 and use AiAs one point in the waveform after peak detection and continuing to decay; otherwise, stopping attenuation, and converting A1As a new impact peak in the peak-detected waveform, and according to A1e-t/τThe decay process is restarted.
The three envelope demodulation methods have one or more of the following disadvantages and shortcomings:
the traditional HT demodulation method has poor real-time performance in the envelope solving process, is difficult to realize on line, needs to determine proper prior parameters (filtering frequency band and filter parameters) by different methods, has very unobvious demodulation effect if filtering range selection is not proper in low signal-to-noise ratio, and can not keep the peak value of the original actual signal under lower analysis frequency because the demodulated waveform amplitude is distorted.
The generalized detection envelope method needs to acquire a priori parameters (frequency information of an amplitude modulation signal and a carrier signal) in advance before processing so as to acquire a delay amount, and in the actual process of extracting the fault characteristics of the rotating machine, the characteristic frequency needs to be acquired through envelope demodulation, so that the parameter cannot be known in advance, and therefore the envelope demodulation method cannot be used in the field of mechanical fault diagnosis.
Although the peak detection method can keep the high peak part of the original waveform, the demodulation effect is poor under the condition of insignificant impact, the envelope signal is constructed by using exponentially attenuated structural elements, the attenuation characteristic and harmonic characteristic of the original signal can be lost, in the model, the selection of the prior parameter tau (time constant) can directly influence the result, and an inappropriate value can obtain a completely wrong envelope signal.
In addition, when the envelope spectrum of the signal is analyzed, since the characteristic frequency is often concentrated in a low frequency band, the analysis frequency is generally required to be reduced, thereby improving the resolution of the low frequency band and reducing the data amount and the operation amount. Interpolation resampling is generally used to realize the reduction of the analysis frequency, and in this case, no matter which method is used, in the resampling process, if the time corresponding to the peak of the original waveform does not have a time point corresponding to the peak on the new signal time sequence, the amplitude information of the envelope signal is lost.
Disclosure of Invention
Aiming at the problems and the defects of the existing method, the invention provides an impulse signal envelope demodulation method based on peak-preserving down-sampling. The method realizes the acquisition of the original signal envelope waveform through a peak extraction algorithm without any additional parameter, and overcomes the defect that the methods need to depend on prior parameters. After the envelope waveform is obtained, the analysis frequency is reduced by using a peak value retention and down-sampling method, and the low-frequency part of the envelope signal can be subjected to targeted analysis on the premise of fully retaining the original signal peak value. The invention has good real-time performance and is easy to transplant and realize on the embedded equipment. The extracted envelope waveform can well maintain the attenuation characteristics of the original signal.
To achieve the object of the present invention, the present invention provides an impulse signal envelope demodulation method based on peak-preserving down-sampling, comprising the steps of:
at a sampling frequency F during the rotary operation of a rotary machinesSampling to obtain an original vibration signal x (i);
calculating a differential signal d (i) ═ x (i) — x (i-1) of the original vibration signal x (i), obtaining two signals d1(i)＝d(1：n-1)，d2(i) D (2: n), where i is 0, 1, 2, …, n, n is the step size;
by judging the condition d1·d2＜0&d1Extracting peak information of the original vibration signal to obtain an envelope signal X (i) if the peak information is more than 0;
and carrying out Fourier transform on the envelope signal to obtain an envelope spectrum, and carrying out characteristic analysis on the envelope spectrum to obtain a corresponding fault diagnosis conclusion.
Wherein the sampling frequency Fs102.4kHz, and N-131068 sampling points.
Before the fourier transformation of the envelope signal, the following steps are also performed:
from the original signal sampling frequency FsRequired analysis frequency FaThe envelope signal X (i) is down-sampled by the sum of the spectral line number L to obtain a down-sampled signal Xres(j) (1-1). n +1 < j < l.n, wherein l is the serial number of a sampling window;
calculating the time t corresponding to the maximum value X (j) in each step length nl；
At Xres(j) Find all tlClosest time TlAnd update Xres(Tl) Has a value of X (t)l) Get updated Xres(j)；
Judging whether the updating of the whole section of signal is finished, namely, whether len (X (i)) is more than l x n is true or not, wherein len (X (i)) represents the length of the signal;
if the updating of the whole signal is completed, the updated X isres(j) The down-sampled envelope signal is retained as the final peak value;
if the updating of the whole section of signal is not finished, the time t corresponding to the maximum value X (j) in each step length n is calculatedlAnd continuing updating.
Wherein, the input parameters include: sampling frequency of Fs102.4kHz, the required analysis frequency is FaThe number of spectral lines is 3200 when the frequency is 1kHz, and the time length corresponding to the number of spectral lines 3200 is 1.25 s.
Wherein the step size n can be dependent on the frequency range of interest FaimAnd a sampling frequency FsMaking an estimate of where n is Fs/Faim。
Wherein the sampling frequency FsIs 256 Hz.
The variable parameter peak value preserving envelope demodulation method provided by the invention can well solve the problems in the prior art, and has the beneficial effects that:
1. the original signal envelope waveform is acquired by peak extraction without any additional parameter, the problem that the conventional method needs to rely on prior parameters is solved, the dependence on preset parameters is eliminated, the calculation process is very simple, the real-time performance is good, and the method is easy to transplant and implement on embedded equipment;
2. the envelope waveform extracted by the method can well keep the attenuation impulse response of the original signal, no assumption is made on the waveform characteristics, the reduction of the analysis frequency is realized by using a peak value preserving resampling method, and on the premise of fully preserving the peak value and the signal characteristics of the original signal, the low-frequency part of the envelope signal is subjected to targeted analysis, and the system operation amount and the data storage pressure are reduced.
The features and advantages of the present invention will become apparent by reference to the following drawings and detailed description of specific embodiments of the invention.
Drawings
FIG. 1 shows a schematic of the mechanical fault diagnosis system of the present invention;
FIG. 2 shows an acceleration waveform and a frequency spectrum of a vibration signal;
FIG. 3 illustrates a method flow diagram of the impulse signal envelope demodulation method of the present invention;
FIG. 4 shows an envelope waveform and spectrum obtained using peak extraction;
FIG. 5 shows an envelope waveform and spectrum obtained using the peak-preserving downsampling method of the present invention;
FIG. 6 shows the resulting envelope waveform and spectrum using the Hilbert transform and conventional resampling method at a sampling frequency of 256 Hz;
fig. 7 shows the envelope waveform and spectrum obtained using the peak-preserving downsampling method of the present invention at a sampling frequency of 256 Hz.
Detailed Description
The embodiment of the invention provides an impulse signal envelope demodulation method based on peak value preserving and down-sampling, which realizes the acquisition of an original signal envelope waveform through a peak value extraction algorithm, wherein the extraction algorithm mainly comprises the steps of signal difference, multiplication and comparison, after the envelope waveform is acquired, the envelope waveform is down-sampled by using a peak value preserving and down-sampling method, the reduction of analysis frequency is realized, and finally, Fourier transform is carried out on down-sampled data to obtain the frequency spectrum characteristics of a fault signal, so that the related fault information of equipment is obtained. In summary, the present invention better solves the following problems existing in the current envelope demodulation method: the method is suitable for impact characteristic extraction in a rotary mechanical fault diagnosis system and is easy to integrate in a real-time online system.
The following describes the embodiments and algorithmic processes of the present invention in detail with reference to the accompanying drawings.
Fig. 1 shows a schematic configuration of a mechanical failure diagnosis system of the present invention. The mechanical fault diagnosis system comprises a rolling bearing, a bearing seat and an acceleration sensor, wherein the rolling bearing is installed on the bearing seat, the acceleration sensor is installed on the bearing seat, sampling is carried out at a certain frequency during the rotating work of the rolling bearing, a vibration signal x (i) is obtained, the sampling frequency Fs is 102.4kHz, and the number N of sampling points is 131068. Fig. 2 shows an acceleration waveform and a frequency spectrum of a vibration signal, the upper graph is a time domain waveform of the signal, and the lower graph is a corresponding frequency spectrum thereof. From the frequency spectrum of the signal, it can be seen that the impact frequency (31.25Hz) generated by the bearing fault in the vibration signal is hardly found, and the 4-fold frequency is rather high in energy.
Fig. 3 shows a method flowchart of the impulse signal envelope demodulation method of the present invention.
Firstly, aiming at an original vibration signal x (i) acquired by a sensor, calculating a differential signal d (i) ═ x (i) — x (i-1) of the original vibration signal x (i) to obtain two paths of signals d1(i)＝d(1：n-1)，d2(i) D (2: n), where i is 0, 1, 2, …, n is the step size, i.e., the length of each sampling window. By judging the condition d1·d2＜0&d1The peak information of x (i) is extracted to obtain envelope signal X (i) (| x (i) | > Th is added to the judgment condition in the step, Th is based on the impact signalHard threshold set by peak). The corresponding envelope waveform and spectrum are shown in fig. 4. The obvious fault frequency of 31.25Hz and the higher harmonics thereof can be distinguished from the envelope spectrum, so that the corresponding fault characteristics of the measured bearing can be judged. The result shows that the envelope demodulation of the rotary mechanical fault signal (impact signal) can be realized by simple difference and comparison operation instead of the traditional Hilbert transform calculation process. And carrying out Fourier transform on the envelope signal to obtain an envelope spectrum, and carrying out characteristic analysis on the envelope spectrum to obtain a corresponding fault diagnosis conclusion. The simple algorithm process enables the system to be more easily used on embedded platforms such as field handheld instruments and monitoring equipment, and has better timeliness and timeliness.
However, in the practical engineering application process, in order to acquire the fault feature modulated to the high frequency band, the sampling frequency is relatively high, and the correlation processing is performed on the signal with the sampling frequency of 102.4kHz, particularly when the original signal rotates at a low speed, the corresponding fault frequency is low, and in the case that the sampling time has to be increased in order to acquire the sufficiently obvious fault feature, the storage and the computation amount are very challenging. In fact, the frequency of interest is often low (hundreds of Hz or even tens of Hz), and at this time, sufficient fault information can be retained and the calculation amount of hardware can be greatly reduced by a reasonable down-sampling means.
For the peak-preserving downsampling process of the present invention, the input parameters include: sampling frequency of Fs102.4kHz, the required analysis frequency is FaThe time length corresponding to the number of spectral lines 3200 is 1.25s, and the length of the original signal meets the requirement. For which the envelope signal x (i) needs to be processed as a down-sampled signal with a sampling frequency of 2560 Hz.
Specifically, first, according to the original signal sampling frequency FsRequired analysis frequency FaThe envelope signal X (i) is down-sampled by the sum of the spectral line number L to obtain a down-sampled signal Xres(j) And (l-1). n +1 < j < l.n, wherein l is the sampling window serial number. Conventional downsampling methods (either in the context of interpolation, bilinear interpolation or cubic convolution) may be usedInterpolation method such as interpolation) to calculate the envelope signal and obtain a down-sampled signal.
Then, the time t corresponding to the maximum value X (j) in each step length n is calculatedlThe step size n can be estimated from the frequency range of interest, assuming the frequency range of interest FaimWith F combined with frequency components below 200HzsCalculating to obtain n ═ Fs/Faim＝512。
Then, at Xres(j) Find all tlClosest time TlAnd update Xres(Tl) Has a value of X (t)l) Get updated Xres(j)。
Judging whether the updating of the whole segment of signal is completed, namely whether len (X (i)) is more than l x n, wherein len (X (i)) represents the length of the signal. If the updating of the whole signal is completed, the updated X isres(j) The down-sampled envelope signal is retained as the final peak value. If the updating of the whole section of signal is not finished, the time t corresponding to the maximum value X (j) in each step length n is calculatedlAnd continuing updating.
The final peak-preserving down-sampled envelope signal is then fourier transformed to obtain a frequency spectrum, as shown in fig. 5. Comparing fig. 4 and 5, it is found that the difference between the two is not great, but fig. 5 is calculated from the signal of which the data volume is reduced by 40 times, when the algorithm is integrally transplanted to the embedded system, the resource consumption can be greatly saved, and a more timely monitoring or diagnosis conclusion can be obtained.
In contrast, fig. 6 shows an envelope waveform and a frequency spectrum obtained by processing a vibration signal using a hilbert transform and by a conventional resampling method. In order to increase the contrast effect, the sampling frequency of the original signal is reduced to 256Hz, that is, the sampling frequency is reduced by 400 times compared with the original sampling frequency, and the number of the processed data points is also reduced by 400 times, and at this time, the envelope waveforms and the frequency spectrums obtained by the two methods are respectively as shown in fig. 6 (by using hilbert transform and through conventional resampling) and fig. 7 (by using the peak-preserving down-sampling method of the present invention).
Comparing the processing results shown in the two graphs, it can be seen that the time domain waveform impact characteristics in fig. 6 are obviously worse than the results in fig. 7, the periodicity in the time domain is difficult to judge, and the signal-to-noise ratio of the fault frequency is low as can be seen from the frequency spectrum. The results in fig. 7 show that the impact peak of the original vibration signal is well preserved in the down-sampling process, the periodic impact in the envelope waveform is still very obvious, and the characteristic frequency and the frequency multiplication thereof in the frequency spectrum are significant. It can be seen that the peak-preserving envelope demodulation and down-sampling method provided by the invention can well maintain the actual impact peak value of the signal at low sampling frequency, and the amplitude of the impact signal is hardly attenuated as can be seen by comparing the envelope waveforms in fig. 7, 5 and 4, so that the real impact waveform and energy can be obtained under the condition of reducing the operation requirement, and more accurate fault judgment can be obtained.
Finally, for the updated Xres(j) And performing characteristic analysis on the envelope spectrum obtained by Fourier transform to obtain a corresponding fault diagnosis conclusion.
The type of the processing signal of the method in the invention is not limited to vibration signal, but may be other types of signals (acoustic signals, etc.) capable of reflecting component faults, and accordingly, the sensor used may be an acceleration sensor, a vibration sensor, a displacement sensor, an acoustic sensor, etc. The data acquisition object mentioned in the invention can be a bearing, and can also be other rotating mechanical equipment such as a gear, a shaft and the like. The envelope decoding method involved in acquiring the envelope signal is not limited to the differential peak extraction algorithm provided by the invention, and can also be other envelope demodulation algorithms such as maximum envelope and phase-sensitive detection. In addition, the down-sampling algorithm and the required input conditions of the present invention are not limited to the interpolation method mentioned in the embodiment, and other down-sampling methods may be used.
The foregoing is illustrative only, and it is to be understood that modifications and variations in the arrangements and details described herein will be apparent to those skilled in the art, and that any obvious substitutions are within the scope of the present invention without departing from the inventive concepts thereof. It is therefore intended that the scope of the appended claims be limited only by the specific details presented by way of the foregoing description and explanation.
Claims (5)
1. A method for demodulating an envelope of an impulse signal based on peak-preserving downsampling, the method comprising the steps of:
at a sampling frequency F during the rotary operation of a rotary machinesSampling to obtain an original vibration signal x (i);
calculating a differential signal d (i) ═ x (i) — x (i-1) of the original vibration signal x (i), obtaining two signals d1(i)＝d(1：n-1)，d2(i) D (2: n), where i is 0, 1, 2,.. n, n is the step size;
by judging the condition d1·d2＜0&d1Extracting peak information of the original vibration signal to obtain an envelope signal X (i) if the peak information is more than 0;
from the original signal sampling frequency FsRequired analysis frequency FaThe envelope signal X (i) is down-sampled by the sum of the spectral line number L to obtain a down-sampled signal Xres(j) J is more than (l-1) · n +1 and less than l · n, wherein l is a sampling window serial number;
calculating the time t corresponding to the maximum value X (j) in each step length nl；
At Xres(j) Find all tlClosest time TlAnd update Xres(Tl) Has a value of X (t)l) Get updated Xres(j)；
Judging whether the updating of the whole section of signal is finished, namely, whether len (X (i)) is more than l x n is true or not, wherein len (X (i)) represents the length of the signal;
if the updating of the whole signal is completed, the updated X isres(j) The down-sampled envelope signal is retained as the final peak value;
if the updating of the whole section of signal is not finished, the time t corresponding to the maximum value X (j) in each step length n is calculatedlAnd continuing to update;
and carrying out Fourier transform on the envelope signal to obtain an envelope spectrum, and carrying out characteristic analysis on the envelope spectrum to obtain a corresponding fault diagnosis conclusion.
2. The method of claim 1, wherein the sampling frequency Fs102.4kHz, and N-131068 sampling points.
3. The method of claim 1, wherein inputting parameters comprises: sampling frequency of Fs102.4kHz, the required analysis frequency is FaThe number of spectral lines is 3200 when the frequency is 1kHz, and the time length corresponding to the number of spectral lines 3200 is 1.25 s.
4. The method of claim 1, wherein the step size n is determined according to the frequency range of interest FaimAnd a sampling frequency FsMaking an estimate of where n is Fs/Faim。
5. The method of claim 1, wherein the sampling frequency FsIs 256 Hz.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810922977.7A CN109063668B (en) | 2018-08-14 | 2018-08-14 | Impact signal envelope demodulation method based on peak value retention and down-sampling |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810922977.7A CN109063668B (en) | 2018-08-14 | 2018-08-14 | Impact signal envelope demodulation method based on peak value retention and down-sampling |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109063668A CN109063668A (en) | 2018-12-21 |
| CN109063668B true CN109063668B (en) | 2021-09-14 |
Family
ID=64678364
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810922977.7A Active CN109063668B (en) | 2018-08-14 | 2018-08-14 | Impact signal envelope demodulation method based on peak value retention and down-sampling |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109063668B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110160767B (en) * | 2019-06-14 | 2021-03-02 | 安徽智寰科技有限公司 | Impact period automatic identification and extraction method and system based on envelope analysis |
| CN110569812B (en) * | 2019-09-12 | 2022-11-01 | 天津工业大学 | Envelope demodulation method and envelope demodulation system for fault signals |
| CN110987435B (en) * | 2019-12-18 | 2021-10-01 | 北京化工大学 | Bearing fault diagnosis method based on improved K-SVD dictionary learning and compressed sensing |
| CN113297922B (en) * | 2021-04-30 | 2023-05-05 | 广西电网有限责任公司电力科学研究院 | High-voltage switch cabinet fault diagnosis method, device and storage medium |
| CN114754860B (en) * | 2022-04-13 | 2024-05-14 | 哈工大机器人（合肥）国际创新研究院 | Wireless vibration monitoring method, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5724002A (en) * | 1996-06-13 | 1998-03-03 | Acrodyne Industries, Inc. | Envelope detector including sample-and-hold circuit controlled by preceding carrier pulse peak(s) |
| CN103308310A (en) * | 2013-06-05 | 2013-09-18 | 西安交通大学 | Method for demodulating impact signals on basis of all-digital peak detection |
| CN105388012A (en) * | 2015-10-22 | 2016-03-09 | 兰州理工大学 | Order tracking method based on nonlinear frequency modulation wavelet transformation |
| CN107421435A (en) * | 2017-03-24 | 2017-12-01 | 浙江大学 | Homodyne orthogonal laser interference signal generation method based on digit shifter |
| CN107976304A (en) * | 2016-10-21 | 2018-05-01 | 计算系统有限公司 | The mechanical disorder prediction analyzed based on the periodical information to signal |
-
2018
- 2018-08-14 CN CN201810922977.7A patent/CN109063668B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5724002A (en) * | 1996-06-13 | 1998-03-03 | Acrodyne Industries, Inc. | Envelope detector including sample-and-hold circuit controlled by preceding carrier pulse peak(s) |
| CN103308310A (en) * | 2013-06-05 | 2013-09-18 | 西安交通大学 | Method for demodulating impact signals on basis of all-digital peak detection |
| CN105388012A (en) * | 2015-10-22 | 2016-03-09 | 兰州理工大学 | Order tracking method based on nonlinear frequency modulation wavelet transformation |
| CN107976304A (en) * | 2016-10-21 | 2018-05-01 | 计算系统有限公司 | The mechanical disorder prediction analyzed based on the periodical information to signal |
| CN107421435A (en) * | 2017-03-24 | 2017-12-01 | 浙江大学 | Homodyne orthogonal laser interference signal generation method based on digit shifter |
Non-Patent Citations (1)
| Title |
|---|
| 基于峰值保持降采样算法的中介轴承故障声发射数据缩减技术;田晶 等;《推进技术》;20180531;第38卷(第5期);第1157-1163页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109063668A (en) | 2018-12-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109063668B (en) | Impact signal envelope demodulation method based on peak value retention and down-sampling | |
| Shi et al. | Bearing fault diagnosis under variable rotational speed via the joint application of windowed fractal dimension transform and generalized demodulation: A method free from prefiltering and resampling | |
| Urbanek et al. | A two-step procedure for estimation of instantaneous rotational speed with large fluctuations | |
| Cheng et al. | Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis | |
| Wang et al. | Rolling element bearing fault diagnosis via fault characteristic order (FCO) analysis | |
| Tu et al. | Demodulated high-order synchrosqueezing transform with application to machine fault diagnosis | |
| Liu et al. | Bearing fault diagnosis method with unknown variable speed based on multi-curve extraction and selection | |
| Wang et al. | Sparse and low-rank decomposition of the time–frequency representation for bearing fault diagnosis under variable speed conditions | |
| CN110991564B (en) | Variable working condition bearing fault diagnosis method based on multiscale dispersion entropy deviation mean value and nonlinear mode decomposition | |
| Shao et al. | Multi‐Fault Feature Extraction and Diagnosis of Gear Transmission System Using Time‐Frequency Analysis and Wavelet Threshold De‐Noising Based on EMD | |
| Barbini et al. | Phase editing as a signal pre-processing step for automated bearing fault detection | |
| CN110084208B (en) | Calculation order tracking method capable of adaptively reducing noise and avoiding order aliasing | |
| Zhang et al. | Improved local cepstrum and its applications for gearbox and rolling bearing fault detection | |
| Lin et al. | A review and strategy for the diagnosis of speed-varying machinery | |
| CN112781709A (en) | Method for analyzing early failure and extracting characteristics of equipment vibration signal under variable speed working condition | |
| CN108398260B (en) | Method for quickly evaluating instantaneous angular speed of gearbox based on mixed probability method | |
| CN115795295A (en) | Rotating machinery characteristic frequency enhancement extraction method based on optimal weighted envelope spectrum | |
| CN111623968B (en) | Fault feature extraction method based on adaptive morphological filtering | |
| Sun et al. | Application of a novel improved adaptive CYCBD method in gearbox compound fault diagnosis | |
| CN114486263A (en) | Noise reduction and demodulation method for vibration signal of rolling bearing of rotary machine | |
| Lv et al. | Generalized synchroextracting-based stepwise demodulation transform and its application to fault diagnosis of rotating machinery | |
| CN107941511B (en) | A kind of implementation method of the frequency based on signal Time-frequency Decomposition-kurtosis figure | |
| Shang et al. | Rolling bearing fault diagnosis method based on MOMEDA and IEWT | |
| CN115436058B (en) | Bearing fault feature extraction method, device, equipment and storage medium | |
| Liu et al. | Rolling bearing fault diagnosis via ConceFT-based time-frequency reconfiguration order spectrum analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220713 Address after: Room 308, building 3, intelligent science park, No. 3963 Susong Road, Hefei Economic and Technological Development Zone, Anhui Province, 230000 Patentee after: Anhui Hagong Zhanlu Technology Equipment Co.,Ltd. Address before: 230601 intelligent equipment science and Technology Park, 3963 Susong Road, Hefei Economic and Technological Development Zone, Anhui Province Patentee before: HRG INTERNATIONAL INSTITUTE FOR RESEARCH & INNOVATION |
|
| TR01 | Transfer of patent right |