CN111900952B - Signal filtering denoising method, device and storage medium - Google Patents
Signal filtering denoising method, device and storage medium Download PDFInfo
- Publication number
- CN111900952B CN111900952B CN202010708992.9A CN202010708992A CN111900952B CN 111900952 B CN111900952 B CN 111900952B CN 202010708992 A CN202010708992 A CN 202010708992A CN 111900952 B CN111900952 B CN 111900952B
- Authority
- CN
- China
- Prior art keywords
- mode function
- intrinsic mode
- frequency
- imf
- imf intrinsic
- 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
- 238000000034 method Methods 0.000 title claims abstract description 52
- 238000001914 filtration Methods 0.000 title claims abstract description 51
- 230000001133 acceleration Effects 0.000 claims abstract description 12
- 230000006870 function Effects 0.000 claims description 147
- 238000000354 decomposition reaction Methods 0.000 claims description 31
- 238000004458 analytical method Methods 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 8
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003750 conditioning effect Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000002401 inhibitory effect Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03H—IMPEDANCE NETWORKS, e.g. RESONANT CIRCUITS; RESONATORS
- H03H9/00—Networks comprising electromechanical or electro-acoustic devices; Electromechanical resonators
- H03H9/46—Filters
Abstract
The application provides a signal filtering denoising method, a device and a storage medium, wherein the method comprises the following steps: obtaining a centrifugal pump vibration signal from the centrifugal pump through an acceleration sensor; performing signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal; and decomposing the improved signal to obtain an improved IMF intrinsic mode function. The application reduces modal aliasing, and simultaneously, compared with the original EMD method, the application overcomes the modal aliasing phenomenon existing in the prior art, inhibits the influence of impulse noise, retains the original information of the vibration signal to a greater extent, and has better performance.
Description
Technical Field
The application mainly relates to the field of signal analysis, in particular to a signal filtering denoising method, a device and a storage medium.
Background
Empirical Mode Decomposition (EMD) is a signal analysis method with a wide range of applications such as bearing failure detection, biomedical data analysis, power signal analysis, etc. Despite the wide application of EMD methods, there are problems associated with the methods that need to be addressed, such as modal aliasing, end effects, spline problems, and the like. When the EMD cannot successfully decompose the signal into unique frequency components, the different Intrinsic Mode Functions (IMFs) contain the same frequencies as the overlapping components, which is known as a mode aliasing problem. The modal aliasing phenomenon, once present, will affect the components of the subsequent decomposition. Finally, the decomposition result of EMD loses physical meaning, and the problem of modal aliasing is an unavoidable and well-solved important problem of EMD algorithm.
Disclosure of Invention
The application aims to solve the technical problem of providing a signal filtering denoising method, a device and a storage medium aiming at the defects of the prior art.
The technical scheme for solving the technical problems is as follows: a signal filtering denoising method comprises the following steps:
obtaining a centrifugal pump vibration signal from a centrifugal pump through an acceleration sensor;
performing signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal;
and decomposing the improved signal to obtain an improved IMF intrinsic mode function.
The other technical scheme for solving the technical problems is as follows: a signal filtering denoising apparatus comprising:
the vibration signal acquisition module is used for acquiring a centrifugal pump vibration signal from the centrifugal pump through the acceleration sensor;
the improved processing module is used for carrying out signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal;
and the decomposition processing module is used for carrying out decomposition processing on the improved signal to obtain an improved IMF intrinsic mode function.
The other technical scheme for solving the technical problems is as follows: a signal filtering denoising apparatus comprising a memory, a processor and a computer program stored in the memory and executable on the processor, which when executed by the processor implements a signal filtering denoising method as described above.
The other technical scheme for solving the technical problems is as follows: a computer readable storage medium storing a computer program which, when executed by a processor, implements a signal filtering denoising method as described above.
The beneficial effects of the application are as follows: the centrifugal pump vibration signal is obtained from the centrifugal pump through the acceleration sensor, the signal improvement processing of the centrifugal pump vibration signal is carried out to obtain an improved signal, the decomposition processing of the improved signal is carried out to obtain an improved IMF (intrinsic mode function), so that mode aliasing is reduced, meanwhile, compared with the original EMD method, the method overcomes the mode aliasing phenomenon in the prior art, suppresses the influence of impulse noise, retains the original information of the vibration signal to a greater extent, and has better performance.
Drawings
Fig. 1 is a schematic flow chart of a signal filtering denoising method according to an embodiment of the present application;
fig. 2 is a block diagram of a signal filtering denoising apparatus according to an embodiment of the present application.
Detailed Description
The principles and features of the present application are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the application and are not to be construed as limiting the scope of the application.
Fig. 1 is a schematic flow chart of a signal filtering denoising method according to an embodiment of the present application.
As shown in fig. 1, a signal filtering denoising method includes the following steps:
obtaining a centrifugal pump vibration signal from a centrifugal pump through an acceleration sensor;
performing signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal;
and decomposing the improved signal to obtain an improved IMF intrinsic mode function.
Preferably, the type of the acceleration sensor is a PCB352C67 type acceleration sensor.
It should be understood that the two acceleration sensors are respectively installed in the horizontal and vertical directions of the centrifugal pump, and a SpectraQuest type dynamic simulator is used to obtain the vibration signal of the centrifugal pump, and the obtained vibration signal is inputted through the DSP20-42 type signal analyzer and stored in a computer.
Specifically, the centrifugal pump with the model of Weir/Warman3/2CAH is selected, the data acquisition system adopts an SCXI signal conditioning system, the matched closed impeller is C2147, the diameter of the impeller is 8.5 inches and 5 blades are arranged, the sampling rate of the system in practical experiments is 9kHZ, the sampling time is 20s, the used rotating speed is 1797r/min, and the impeller in a normal state is marked as F1 for simplicity.
It should be appreciated that the control group is provided to reflect not only the effect of applying the median filter of the variable window to the EMD decomposition, but also to provide a reference for fault diagnosis.
It should be understood that this patent only analyzes the signals obtained in the vertical direction.
In the above embodiment, the centrifugal pump vibration signal is obtained from the centrifugal pump through the acceleration sensor, the signal improvement processing of the centrifugal pump vibration signal is performed to obtain an improved signal, the decomposition processing of the improved signal is performed to obtain an improved IMF intrinsic mode function, so that mode aliasing is reduced.
Optionally, as an embodiment of the present application, the process of performing signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal includes:
performing function analysis on the centrifugal pump vibration signal to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components;
respectively carrying out high-frequency filtering treatment on the plurality of high-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of high-frequency IMF intrinsic mode function filtering components;
respectively carrying out low-frequency filtering treatment on the plurality of low-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of low-frequency IMF intrinsic mode function filtering components;
and summing the plurality of low-frequency IMF intrinsic mode function filtering components according to the plurality of high-frequency IMF intrinsic mode function filtering components to obtain an improved signal.
It will be appreciated that a plurality of the high frequency IMF intrinsic mode function components and a plurality of the low frequency IMF intrinsic mode function components of different frequencies are filtered using median filters of different window sizes to generate a filtered IMF, wherein the higher the frequency IMF the larger the corresponding median filter window, the smaller the fraction.
Specifically, when the median filter window is large, the noise filtering capability is weak, but the loss of signal information is small, whereas when the median filter window is small, the noise filtering capability is strong, but the loss of signal information is serious. Two self-adaptive windows are defined by adopting a median filter of the variable window, so that noise can be effectively filtered, original information of signals can be stored to the greatest extent, and modal aliasing is reduced.
In the above embodiment, the function analysis of the vibration signal of the centrifugal pump obtains a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components; respectively carrying out high-frequency filtering treatment on the high-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of high-frequency IMF intrinsic mode function filtering components; respectively carrying out low-frequency filtering treatment on the plurality of low-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of low-frequency IMF intrinsic mode function filtering components; the improved signal is obtained by summing the high-frequency IMF intrinsic mode function filtering components and the low-frequency IMF intrinsic mode function filtering components, noise is effectively filtered, original information of the signal is saved to the greatest extent, mode aliasing is reduced, meanwhile, compared with an original EMD method, the mode aliasing phenomenon in the prior art is overcome, the influence of impulse noise is restrained, original information of a vibration signal is reserved to a greater extent, and better performance is achieved.
Optionally, as an embodiment of the present application, the process of performing function analysis on the vibration signal of the centrifugal pump to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components includes:
decomposing the centrifugal pump vibration signal by using an EMD empirical mode decomposition algorithm to obtain a plurality of original IMF intrinsic mode function components;
and carrying out frequency sorting on the plurality of original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components.
It will be appreciated that applying an EMD algorithm to the centrifugal pump vibration signal x (t) results in a number of the original IMF intrinsic modal function components c l (t) and residual r (t), and based on the original IMF intrinsic modal function component c l Ordering the frequency of (t) to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components.
In the above embodiment, the decomposition processing of the vibration signal of the centrifugal pump by using the EMD empirical mode decomposition algorithm obtains a plurality of original IMF intrinsic mode function components and a plurality of residuals; the frequency of the original IMF intrinsic mode function components is sequenced to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components, data support is provided for subsequent processing, noise is effectively filtered, original information of signals is saved to the greatest extent, mode aliasing is reduced, meanwhile, compared with an original EMD method, the method overcomes the mode aliasing phenomenon in the prior art, the influence of impulse noise is restrained, original information of vibration signals is reserved to a greater extent, and better performance is achieved.
Optionally, as an embodiment of the present application, the process of sorting the frequencies of the plurality of original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components includes:
respectively carrying out high-frequency judgment on a plurality of original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components;
and respectively carrying out low-frequency judgment on the plurality of original IMF intrinsic modal function components to obtain a plurality of low-frequency IMF intrinsic modal function components.
In the above embodiment, a plurality of high-frequency IMF intrinsic mode function components are obtained by respectively performing high-frequency judgment on a plurality of original IMF intrinsic mode function components; the low frequency judgment of the intrinsic modal function components of the original IMFs is carried out to obtain the intrinsic modal function components of the low frequency IMFs, compared with the original EMD method, the mode aliasing phenomenon in the prior art is overcome, the influence of impulse noise is restrained, the original information of the vibration signals is reserved to a greater extent, and the performance is better.
Optionally, as an embodiment of the present application, the process of respectively performing high-frequency judgment on the plurality of original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components includes:
the method comprises the steps of respectively carrying out high-frequency judgment on a plurality of original IMF intrinsic mode function components through a first formula to obtain a plurality of high-frequency IMF intrinsic mode function components, wherein the first formula is as follows:
wherein f IMFi Is the intrinsic modal function component of the original IMF, f IMF1 The first original IMF intrinsic mode function component decomposed by EMD empirical mode decomposition algorithm, f IMFL The last original IMF intrinsic mode function component decomposed by the EMD empirical mode decomposition algorithm.
In the above embodiment, the plurality of high-frequency IMF intrinsic mode function components are obtained by respectively performing the first equation on the plurality of high-frequency judgment on the plurality of original IMF intrinsic mode function components, so that the mode aliasing phenomenon existing in the prior art is overcome, the influence of impulse noise is inhibited, the original information of the vibration signal is reserved to a greater extent, and the performance is better.
Optionally, as an embodiment of the present application, the process of respectively performing low-frequency judgment on the plurality of original IMF intrinsic mode function components to obtain a plurality of low-frequency IMF intrinsic mode function components includes:
and respectively carrying out low-frequency judgment on the plurality of original IMF intrinsic mode function components through a second formula to obtain a plurality of low-frequency IMF intrinsic mode function components, wherein the second formula is as follows:
wherein f IMFi Is the intrinsic modal function component of the original IMF, f IMF1 The first original IMF intrinsic mode function component decomposed by EMD empirical mode decomposition algorithm, f IMFL The last original IMF intrinsic mode function component decomposed by the EMD empirical mode decomposition algorithm.
In the above embodiment, the second formula is used to determine the low frequencies of the plurality of original IMF intrinsic mode function components to obtain a plurality of low frequency IMF intrinsic mode function components, thereby overcoming the mode aliasing phenomenon existing in the prior art, inhibiting the influence of impulse noise, retaining the original information of the vibration signal to a greater extent, and having better performance.
Optionally, as an embodiment of the present application, the process of decomposing the improved signal to obtain an improved IMF intrinsic mode function includes:
and decomposing the improved signal by using an EMD empirical mode decomposition algorithm to obtain an improved IMF intrinsic mode function.
In the above embodiment, the improved IMF intrinsic mode function is obtained by using the decomposition processing of the improved signal by using the EMD empirical mode decomposition algorithm, so that the mode aliasing phenomenon existing in the prior art is overcome, the influence of impulse noise is inhibited, the original information of the vibration signal is reserved to a greater extent, and the performance is better.
Optionally, as another embodiment of the present application, the original IMF intrinsic mode function component and the improved IMF intrinsic mode function are compared respectively, and the result shows that the influence of impulse noise is effectively suppressed, and meanwhile, mode aliasing is reduced.
Fig. 2 is a block diagram of a signal filtering denoising apparatus according to an embodiment of the present application.
Alternatively, as another embodiment of the present application, as shown in fig. 2, a signal filtering denoising apparatus includes:
the vibration signal acquisition module is used for acquiring a centrifugal pump vibration signal from the centrifugal pump through the acceleration sensor;
the improved processing module is used for carrying out signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal;
and the decomposition processing module is used for carrying out decomposition processing on the improved signal to obtain an improved IMF intrinsic mode function.
Alternatively, another embodiment of the present application provides a signal filtering denoising apparatus, including a memory, a processor, and a computer program stored in the memory and executable on the processor, which when executed by the processor, implements the signal filtering denoising method as described above. The device may be a computer or the like.
Alternatively, another embodiment of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the signal filtering denoising method as described above.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the apparatus and units described above may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present application.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. For such understanding, the technical solution of the present application is essentially or part of what contributes to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the various embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The present application is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present application, and these modifications and substitutions are intended to be included in the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (6)
1. The signal filtering and denoising method is characterized by comprising the following steps of:
obtaining a centrifugal pump vibration signal from a centrifugal pump through an acceleration sensor;
performing signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal;
decomposing the improved signal to obtain an improved IMF intrinsic mode function;
the process for carrying out signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal comprises the following steps:
performing function analysis on the centrifugal pump vibration signal to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components;
respectively carrying out high-frequency filtering treatment on the plurality of high-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of high-frequency IMF intrinsic mode function filtering components;
respectively carrying out low-frequency filtering treatment on the plurality of low-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of low-frequency IMF intrinsic mode function filtering components;
summing the low-frequency IMF intrinsic mode function filtering components according to the high-frequency IMF intrinsic mode function filtering components to obtain an improved signal;
the process of performing function analysis on the centrifugal pump vibration signal to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components comprises the following steps:
decomposing the centrifugal pump vibration signal by using an EMD empirical mode decomposition algorithm to obtain a plurality of original IMF intrinsic mode function components;
frequency sorting is carried out on the original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components;
the process of sorting the frequencies of the original IMF intrinsic mode function components to obtain the high-frequency IMF intrinsic mode function components and the low-frequency IMF intrinsic mode function components comprises the following steps:
respectively carrying out high-frequency judgment on a plurality of original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components;
respectively carrying out low-frequency judgment on a plurality of original IMF intrinsic mode function components to obtain a plurality of low-frequency IMF intrinsic mode function components;
the process of respectively carrying out high-frequency judgment on the plurality of original IMF intrinsic mode function components to obtain the plurality of high-frequency IMF intrinsic mode function components comprises the following steps:
the method comprises the steps of respectively carrying out high-frequency judgment on a plurality of original IMF intrinsic mode function components through a first formula to obtain a plurality of high-frequency IMF intrinsic mode function components, wherein the first formula is as follows:
wherein f IMFi Is the intrinsic modal function component of the original IMF, f IMF1 The first original IMF intrinsic mode function component decomposed by EMD empirical mode decomposition algorithm, f IMFL The last original IMF intrinsic mode function component decomposed by the EMD empirical mode decomposition algorithm.
2. The method of signal filtering and denoising according to claim 1, wherein the process of respectively performing low-frequency judgment on the plurality of original IMF intrinsic mode function components to obtain a plurality of low-frequency IMF intrinsic mode function components includes:
and respectively carrying out low-frequency judgment on the plurality of original IMF intrinsic mode function components through a second formula to obtain a plurality of low-frequency IMF intrinsic mode function components, wherein the second formula is as follows:
wherein f IMFi Is the intrinsic modal function component of the original IMF, f IMF1 The first original IMF intrinsic mode function component decomposed by EMD empirical mode decomposition algorithm, f IMFL The last original IMF intrinsic mode function component decomposed by the EMD empirical mode decomposition algorithm.
3. The method according to any one of claims 1 to 2, wherein the process of decomposing the improved signal to obtain an improved IMF intrinsic mode function includes:
and decomposing the improved signal by using an EMD empirical mode decomposition algorithm to obtain an improved IMF intrinsic mode function.
4. A signal filtering denoising apparatus, comprising:
the vibration signal acquisition module is used for acquiring a centrifugal pump vibration signal from the centrifugal pump through the acceleration sensor;
the improved processing module is used for carrying out signal improvement processing on the vibration signal of the centrifugal pump to obtain an improved signal;
the decomposition processing module is used for carrying out decomposition processing on the improved signal to obtain an improved IMF intrinsic mode function;
in the improved processing module, the centrifugal pump vibration signal is subjected to signal improvement processing, and the process of obtaining an improved signal comprises the following steps:
performing function analysis on the centrifugal pump vibration signal to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components;
respectively carrying out high-frequency filtering treatment on the plurality of high-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of high-frequency IMF intrinsic mode function filtering components;
respectively carrying out low-frequency filtering treatment on the plurality of low-frequency IMF intrinsic mode function components through a preset variable window median filter to obtain a plurality of low-frequency IMF intrinsic mode function filtering components;
summing the low-frequency IMF intrinsic mode function filtering components according to the high-frequency IMF intrinsic mode function filtering components to obtain an improved signal;
in the improved processing module, the process of performing function analysis on the centrifugal pump vibration signal to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components comprises the following steps:
decomposing the centrifugal pump vibration signal by using an EMD empirical mode decomposition algorithm to obtain a plurality of original IMF intrinsic mode function components;
frequency sorting is carried out on the original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components and a plurality of low-frequency IMF intrinsic mode function components;
the process of sorting the frequencies of the original IMF intrinsic mode function components to obtain the high-frequency IMF intrinsic mode function components and the low-frequency IMF intrinsic mode function components comprises the following steps:
respectively carrying out high-frequency judgment on a plurality of original IMF intrinsic mode function components to obtain a plurality of high-frequency IMF intrinsic mode function components;
respectively carrying out low-frequency judgment on a plurality of original IMF intrinsic mode function components to obtain a plurality of low-frequency IMF intrinsic mode function components;
in the improved processing module, the process of respectively carrying out high-frequency judgment on the plurality of original IMF intrinsic mode function components to obtain the plurality of high-frequency IMF intrinsic mode function components comprises the following steps:
the method comprises the steps of respectively carrying out high-frequency judgment on a plurality of original IMF intrinsic mode function components through a first formula to obtain a plurality of high-frequency IMF intrinsic mode function components, wherein the first formula is as follows:
wherein f IMFi Is the intrinsic modal function component of the original IMF, f IMF1 The first original IMF intrinsic mode function component decomposed by EMD empirical mode decomposition algorithm, fI MFL The last original IMF intrinsic mode function component decomposed by the EMD empirical mode decomposition algorithm.
5. A signal filtering denoising apparatus comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the signal filtering denoising method of any one of claims 1 to 2 is implemented when the processor executes the computer program.
6. A computer readable storage medium storing a computer program, characterized in that the signal filtering denoising method according to any one of claims 1 to 2 is implemented when the computer program is executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010708992.9A CN111900952B (en) | 2020-07-22 | 2020-07-22 | Signal filtering denoising method, device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010708992.9A CN111900952B (en) | 2020-07-22 | 2020-07-22 | Signal filtering denoising method, device and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111900952A CN111900952A (en) | 2020-11-06 |
| CN111900952B true CN111900952B (en) | 2023-11-21 |
Family
ID=73189870
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010708992.9A Active CN111900952B (en) | 2020-07-22 | 2020-07-22 | Signal filtering denoising method, device and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111900952B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105275833A (en) * | 2015-10-30 | 2016-01-27 | 北京航空航天大学 | CEEMD (Complementary Empirical Mode Decomposition)-STFT (Short-Time Fourier Transform) time-frequency information entropy and multi-SVM (Support Vector Machine) based fault diagnosis method for centrifugal pump |
| CN105971901A (en) * | 2016-05-03 | 2016-09-28 | 北京航空航天大学 | Centrifugal pump fault diagnosis method based on complete ensemble empirical mode decomposition and random forest |
| CN109598152A (en) * | 2018-10-11 | 2019-04-09 | 天津大学 | Hardware Trojan horse inspection optimization method based on EMD noise reduction data prediction |
-
2020
- 2020-07-22 CN CN202010708992.9A patent/CN111900952B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105275833A (en) * | 2015-10-30 | 2016-01-27 | 北京航空航天大学 | CEEMD (Complementary Empirical Mode Decomposition)-STFT (Short-Time Fourier Transform) time-frequency information entropy and multi-SVM (Support Vector Machine) based fault diagnosis method for centrifugal pump |
| CN105971901A (en) * | 2016-05-03 | 2016-09-28 | 北京航空航天大学 | Centrifugal pump fault diagnosis method based on complete ensemble empirical mode decomposition and random forest |
| CN109598152A (en) * | 2018-10-11 | 2019-04-09 | 天津大学 | Hardware Trojan horse inspection optimization method based on EMD noise reduction data prediction |
Non-Patent Citations (2)
| Title |
|---|
| "基于EMD和FFT的齿轮箱故障诊断";陈汉新等;《武汉工程大学学报》;第33卷(第1期);第65-95页 * |
| 陈汉新等."基于EMD和FFT的齿轮箱故障诊断".《武汉工程大学学报》.2011,第33卷(第1期),第65-95页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111900952A (en) | 2020-11-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110659621A (en) | Combined noise reduction method based on variational modal decomposition and permutation entropy | |
| CN109765055B (en) | Rolling bearing fault detection method and system based on EWT, spectrum effective value and KNN | |
| CN112857804B (en) | Rolling bearing fault diagnosis method, device, medium and computer equipment | |
| CN111160090B (en) | BCG signal noise reduction method and system | |
| CN110619265A (en) | Ball mill cylinder vibration signal combined denoising method and device and storage medium | |
| CN111900952B (en) | Signal filtering denoising method, device and storage medium | |
| CN106651814B (en) | Image processing method and device | |
| Liu et al. | ECG signal denoising based on morphological filtering | |
| CN103784164B (en) | The preprocess method of ultrasonic signal and system | |
| CN112665857B (en) | Rolling bearing fault diagnosis method, device, equipment and storage medium | |
| CN112597958B (en) | Automatic identification method and system for rolling bearing fault | |
| CN109938725B (en) | Electroencephalogram signal processing method and system | |
| Lv et al. | Bearing fault signal analysis based on an adaptive multiscale combined morphological filter | |
| CN115655719A (en) | Bearing vibration signal staged noise reduction method and bearing fault identification method | |
| CN114659620A (en) | Acoustic signal extraction method and system of circuit breaker | |
| CN104156925A (en) | Processing method and system used for carrying out speckle removing and boundary enhancing on ultrasound image | |
| CN114441174A (en) | Diagnosis method, system, equipment and medium for composite fault of rolling bearing | |
| CN108201437B (en) | Signal processing method and device | |
| Ionita et al. | Automatic moiré pattern removal in microscopic images | |
| CN114047499A (en) | Signal normalization method and device for sensor array signal amplitude inconsistency | |
| CN112766203A (en) | Method and device for determining fault signal, storage medium and computer equipment | |
| CN115904791B (en) | Error code identification and self-adaptive repair method in momentum wheel rotating speed band jump process | |
| Liu et al. | The measurement and elimination of mode splitting: from the perspective of the partly ensemble empirical mode decomposition | |
| CN116400337B (en) | Ship noise modulation line spectrum extraction and axial frequency estimation method based on line segment detection | |
| CN114554029B (en) | Video processing method and device |
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 |