CN115659159A - Method and device for extracting vibration characteristics of pipeline - Google Patents
Method and device for extracting vibration characteristics of pipeline Download PDFInfo
- Publication number
- CN115659159A CN115659159A CN202211669262.8A CN202211669262A CN115659159A CN 115659159 A CN115659159 A CN 115659159A CN 202211669262 A CN202211669262 A CN 202211669262A CN 115659159 A CN115659159 A CN 115659159A
- Authority
- CN
- China
- Prior art keywords
- vibration
- time domain
- pipeline
- contribution degree
- vibration characteristics
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 46
- 238000001514 detection method Methods 0.000 claims abstract description 37
- 238000004458 analytical method Methods 0.000 claims abstract description 27
- 238000000546 chi-square test Methods 0.000 claims abstract description 21
- 238000000605 extraction Methods 0.000 claims abstract description 18
- 238000004364 calculation method Methods 0.000 claims abstract description 8
- 238000005070 sampling Methods 0.000 claims abstract description 7
- 238000004590 computer program Methods 0.000 claims description 12
- 238000010606 normalization Methods 0.000 claims description 7
- 230000003595 spectral effect Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 7
- 230000001133 acceleration Effects 0.000 description 6
- 230000006870 function Effects 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 238000012216 screening Methods 0.000 description 4
- 238000001228 spectrum Methods 0.000 description 4
- 238000000540 analysis of variance Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 239000012530 fluid Substances 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 238000001543 one-way ANOVA Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000000556 factor analysis Methods 0.000 description 1
- 230000014509 gene expression Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Landscapes
- Examining Or Testing Airtightness (AREA)
Abstract
The invention relates to a method and a device for extracting vibration characteristics of a pipeline, wherein the method comprises the following steps: acquiring time domain data and frequency domain data of a target pipeline in a leakage state and a non-leakage state in three axial directions respectively; calculating a plurality of vibration characteristics within a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features; calculating the contribution degree of each vibration characteristic to leakage detection based on a chi-square test method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree; calculating the contribution degree of each vibration characteristic to leakage detection based on a one-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers. According to the method, the vibration characteristics are screened from the multiple time domain characteristics and the frequency domain characteristics through a chi-square test and a single-factor variance analysis method, so that the dimension and the calculation cost of pipeline vibration characteristic extraction are reduced.
Description
Technical Field
The invention belongs to the technical field of pipeline vibration signal processing, and particularly relates to a method and a device for extracting pipeline vibration characteristics.
Background
The medium inside the pipeline is mostly fluid, i.e. gas or liquid, so the pipeline is divided into a gas pipeline and a liquid pipeline according to the type of the internal medium. Since fluid parameters tend to change over time within a conduit, conduit vibration is often the result. The vibration of the reciprocating mechanical related pipeline is one of the common abnormal phenomena because the characteristic fluctuation of the internal medium is common without reciprocating the mechanical connected pipeline.
The feature extraction is to extract features with high cohesiveness and low coupling in the original data to describe the original data through analysis and processing of the original data. Feature extraction is necessary for raw data, which is often high-dimensional, contains a lot of redundant information, and the direct use of raw data increases computational cost, and may make the entire sample space difficult to partition.
Disclosure of Invention
In order to reduce the dimensionality and the calculation cost of the pipeline vibration feature extraction data, the invention provides a pipeline vibration feature extraction method in a first aspect, which comprises the following steps: acquiring time domain data and frequency domain data of a target pipeline in a leakage state and a non-leakage state in three axial directions respectively; calculating a plurality of vibration characteristics within a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features; calculating the contribution degree of each vibration characteristic to leakage detection based on a chi-square test method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree; calculating the contribution degree of each vibration characteristic to leakage detection based on a one-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers.
In some embodiments of the invention, the calculating the contribution of each vibration feature to the leak detection based on the chi-square test method includes: respectively normalizing the multiple vibration characteristics according to the frequency domain characteristics and the time domain characteristics; and calculating the contribution degree of each normalized vibration characteristic to the leakage detection based on a chi-square test method.
Further, the step of calculating the contribution degree of each normalized vibration feature to the leakage detection includes the following steps:
wherein the content of the first and second substances,
the correlation coefficient is represented by a correlation coefficient,krepresenting a vibration feature number;nthe volume of the sample is represented by,pidenotes the firstiThe occurrence probability of each vibration feature;f i denotes the firstiFrequency of individual vibration characteristics.
In some embodiments of the present invention, the calculating the contribution degree of each vibration feature to the leak detection based on the one-way analysis of variance method includes: respectively normalizing the multiple vibration characteristics according to the frequency domain characteristics and the time domain characteristics; and calculating the contribution degree of each vibration characteristic after normalization to the leakage detection based on a one-factor variance analysis method.
In some embodiments of the invention, both M and N have values equal to or less than 8.
In the above embodiment, the time domain features include a time domain average value, a time domain absolute average value, a time domain variance, a time domain square root amplitude, and a time domain root mean square value; the time domain features include peak-to-peak, spectral mean, center frequency, mean square frequency, spectral root mean square value, frequency variance, and frequency domain amplitude skewness.
In a second aspect of the present invention, there is provided an apparatus for extracting vibration characteristics of a pipeline, comprising: the acquisition module is used for acquiring time domain data and frequency domain data of a target pipeline in a leakage state and a non-leakage state in three axial directions respectively; the calculation module is used for calculating a plurality of vibration characteristics in a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features; the first extraction module is used for calculating the contribution degree of each vibration characteristic to the leakage detection based on a chi-square detection method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree; the second extraction module is used for calculating the contribution degree of each vibration characteristic to the leakage detection based on a one-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers.
In a third aspect of the present invention, there is provided an electronic device comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of the present invention for providing extraction of vibration characteristics of a pipe in a first aspect.
In a fourth aspect of the present invention, there is provided a computer readable medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the method for extracting vibration characteristics of a pipeline provided by the first aspect of the present invention.
The beneficial effects of the invention are:
the invention preliminarily determines a plurality of discrete vibration characteristics by time domain analysis and frequency domain analysis of the pipeline vibration signal, and the steps of extraction or calculation are simple; and then calculating the contribution degree of each vibration feature through a chi-square test and a single-factor variance analysis method, and screening or reducing dimensions of a plurality of discrete vibration features, thereby realizing the reduction of the dimensions and the calculation cost of the pipeline vibration feature extraction data.
Drawings
FIG. 1 is a schematic flow diagram of a method for extracting vibration characteristics of a pipeline in some embodiments of the invention;
FIG. 2 is a time domain waveform of a pipeline in a leaking and non-leaking state in some embodiments of the present invention;
FIG. 3 is a frequency domain waveform of a pipeline in a leaking and non-leaking state in some embodiments of the present invention;
FIG. 4 is a schematic flow chart of a Chi-square test method for screening vibration signatures in some embodiments of the present invention;
FIG. 5 is a flow chart illustrating screening vibration characteristics of a single factor method in some embodiments of the invention;
FIG. 6 is a graphical illustration of the effect of Chi-Square test methods on screening vibration signatures in some embodiments of the present invention;
FIG. 7 is a schematic diagram of a device for extracting vibration characteristics of a pipeline in some embodiments of the invention;
fig. 8 is a schematic structural diagram of an electronic device in some embodiments of the invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, in a first aspect of the present invention, there is provided a method for extracting vibration characteristics of a pipeline, including: s100, acquiring time domain data and frequency domain data of a target pipeline in a leakage state and a non-leakage state in three axial directions respectively; s200, calculating a plurality of vibration characteristics in a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features; s300, calculating the contribution degree of each vibration characteristic to leakage detection based on a chi-square detection method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree; s400, calculating the contribution degree of each vibration characteristic to leakage detection based on a single-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers.
Referring to fig. 2 and 3, time and frequency domain waveforms of the pipe vibration signal in three axial directions (xyz axes) in two states are shown (an orange waveform in an upper portion of the figure is a leakage state, and a blue waveform in a lower portion of the figure is a non-leakage state). And the time domain observation shows that the vibration acceleration values of three axial directions of the pipeline greatly fluctuate when leakage occurs. The vibration change of the vibration acceleration of the pipeline in the X-axis direction and the Y-axis direction is larger in the leakage state than in the non-leakage state, and the average value of the vibration acceleration is shifted upwards integrally. And the energy of the vibration acceleration signal frequency spectrum of the pipeline in the leakage state is higher, and certain frequency spectrum offset exists in all three axial directions.
In view of this, in the embodiments of the present disclosure, based on the comparison between the leakage state and the non-leakage state of the pipeline and some common mechanical vibration characteristics, the following pipeline vibration characteristics are selected: the time domain average value (T1), the time domain absolute average value (T2), the time domain variance (T3), the time domain square root amplitude (T4), the time domain root mean square value (T5), the time domain peak-to-peak value (T6), the frequency spectrum average value (F1), the center frequency (F2), the root mean square frequency (F3), the frequency spectrum root mean square value (F4), the frequency variance (F5) and the frequency domain amplitude skewness (F6). The calculations specifically follow the formulas in the table.
Mathematical expressions for each vibration signature, see the following table:
in the formulai: time of day;n: total length of vibration signalt i : vibration data at each time;
f: frequency;s(f ): an amplitude at each frequency;
abs(t): absolute value processingmax(t): taking a maximum value;min(t): taking the minimum value;
since each feature has different influence degrees in the state classification, and different features are combined together to possibly influence the classification result, further analysis and research on the features are needed.
Referring to fig. 4, in step S300 of some embodiments of the present invention, the calculating the contribution degree of each vibration feature to the leak detection based on the chi-square test method includes: s301, normalizing the vibration characteristics according to frequency domain characteristics and time domain characteristics; s302, calculating the contribution degree of each normalized vibration feature to leakage detection based on a chi-square test method.
The specific procedure for the Chi-square Test is shown in the following table.
Further, in step S302, calculating the contribution degree of each vibration feature to be normalized to the leak detection includes the following steps:
wherein the content of the first and second substances,
the correlation coefficient is represented by a correlation coefficient,krepresenting a vibration characteristic number;nthe volume of the sample is represented by,piis shown asiThe occurrence probability of individual vibration characteristics;f i is shown asiFrequency of individual vibration characteristics. The correlation coefficient between each pipeline vibration characteristic and the pipeline leakage state sample label can be calculated by the formula
，
A larger value of (c) indicates a more pronounced vibration signature of the pipe.
Specifically, firstly, processing a data format, respectively extracting time domain and frequency domain vibration characteristics, then performing maximum and minimum normalization processing, then obtaining a characteristic contribution degree by using a Chi-square Test in a sklern library, and finally performing sequencing analysis on each characteristic.
Referring to fig. 5, in step S400 of some embodiments of the present invention, the calculating the contribution of each vibration feature to the leak detection based on the one-factor analysis of variance method includes:
s401, normalizing the vibration characteristics according to frequency domain characteristics and time domain characteristics;
s402, calculating the contribution degree of each normalized vibration feature to leakage detection based on a one-factor variance analysis method.
Specifically, the one-way ANOVA method operates as follows:
step 1: the establishment assumption is that:
step 2: calculating sample mean and sample variance:
in the formula
: first, thejThe mean of the samples in each of the dimensions,x ij : first, thejA dimension ofiThe number of the individual values is,
n j : first, thejIndividual levels of sample capacity;
in the formula
: first, thejIndividual levels of sample variance;
and step 3: calculate the variance between groups:
the variance between groups is denoted as MSB and is calculated as follows:
in the formula
: the sum of squares of the horizontal terms, denoted SSB;
c-1: degree of freedom of SSB
In the formula
: the average of the total number of samples,n: total number of samples.
And 4, step 4: intra-group variance estimation
The variance in the group is MSE, and the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
: the sum of the squares of the errors, recorded as SSE;n-crepresenting degrees of freedom of the SSE;
and 5: constructing F statistic for test:
,
if the c ensemble means are not equal, the MSB will be greater than the MSE. When in usefWhen the value reaches a certain critical value, it can be rejectedH 0 . The magnitude of the threshold being given by
And degree of freedom decisions.fThe larger the value is, the higher the correlation is, and the larger the correlation is used as the characteristic selection basis.
Referring to FIG. 6, the analysis results of Chi-square Test are shown, and the analysis results of ANOVA method are omitted. The two analysis results show that the time domain acceleration average value of the Y axis has the highest contribution degree in classification, and the vibration acceleration signals in the two states have obvious deviation; the frequency variance shows a very low degree of contribution in both analysis results.
The Chi-square Test analysis results in FIG. 6 show that the features in the X-axis direction have a higher contribution to the classification of the pipeline leakage detection, and the contribution in the Z-axis direction is relatively low; the overall degree of contribution of the time-domain feature is higher relative to the overall degree of contribution of the frequency-domain feature. The characteristics (invalid characteristics) with low contribution degree in two axial directions and above include a time domain absolute average value, a time domain square root amplitude value, a time domain mean square root value, and a center of gravity frequency, mean square frequency and frequency variance of a frequency domain.
Analysis results of the ANOVA method show that the contribution degree of the vibration characteristics in the Y axis direction is more prominent, the contribution degree of the vibration characteristics in the Z axis direction is the lowest, and the total contribution degree of the time-domain vibration characteristics is higher. The ANOVA method has a smaller number of ineffective vibration features and a smaller number of ineffective vibration features in both axial directions than the Chi-square Test.
In some embodiments of the invention, both M and N have values less than or equal to 8. And selecting the first eight items with contribution degree ranking from each analysis result as research data of subsequent pipeline leakage detection experiment analysis, and further researching the two groups of characteristics in the leakage detection analysis to obtain a characteristic vector capable of describing the pipeline leakage state.
Example 2
Referring to fig. 7, in a second aspect of the present invention, there is provided an apparatus 1 for extracting vibration characteristics of a pipeline, comprising: the acquisition module 11 is configured to acquire time domain data and frequency domain data of a target pipeline in a leakage state and an unleaky state in three axial directions; a calculating module 12, configured to calculate a plurality of vibration characteristics in a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features; a first extraction module 13, configured to calculate a contribution degree of each vibration feature to leak detection based on a chi-square test method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree; a second extraction module 14, configured to calculate a contribution degree of each vibration feature to leak detection based on a one-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers.
Further, the first extraction module 13 includes: the normalization unit is used for normalizing the vibration characteristics according to the frequency domain characteristics and the time domain characteristics; and the calculating unit is used for calculating the contribution degree of each vibration characteristic to be normalized to the leakage detection based on the chi-square test method.
Example 3
Referring to fig. 8, in a third aspect of the present invention, there is provided an electronic apparatus comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of the invention in the first aspect.
The electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following devices may be connected to the I/O interface 505 in general: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; a storage device 508 including, for example, a hard disk; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 8 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may be alternatively implemented or provided. Each block shown in fig. 8 may represent one device or may represent multiple devices as desired.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of the embodiments of the present disclosure. It should be noted that the computer readable medium described in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer-readable medium carries one or more computer programs which, when executed by the electronic device, cause the electronic device to:
computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, python, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A method for extracting vibration characteristics of a pipeline is characterized by comprising the following steps:
acquiring time domain data and frequency domain data of a target pipeline in a leakage state and a non-leakage state in three axial directions respectively;
calculating a plurality of vibration characteristics within a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features;
calculating the contribution degree of each vibration characteristic to leakage detection based on a chi-square test method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree;
calculating the contribution degree of each vibration characteristic to leakage detection based on a one-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers.
2. The method for extracting the pipeline vibration feature according to claim 1, wherein the calculating the contribution degree of each vibration feature to the leakage detection based on the chi-square test method comprises:
respectively normalizing the multiple vibration characteristics according to the frequency domain characteristics and the time domain characteristics;
and calculating the contribution degree of each vibration characteristic after normalization to the leakage detection based on a chi-square test method.
3. The method for extracting the pipeline vibration feature according to claim 2, wherein the calculating of the contribution degree of each vibration feature to the leakage detection after normalization comprises the following steps:
wherein, the first and the second end of the pipe are connected with each other,
representing a phaseThe coefficient of the connection is that,krepresenting a vibration feature number;nthe volume of the sample is represented by,pidenotes the firstiThe occurrence probability of individual vibration characteristics;f i denotes the firstiFrequency of individual vibration characteristics.
4. The method for extracting the pipeline vibration feature according to claim 1, wherein the calculating the contribution degree of each vibration feature to the leakage detection based on the one-way variance analysis method includes:
normalizing the plurality of vibration characteristics according to frequency domain characteristics and time domain characteristics respectively;
and calculating the contribution degree of each vibration characteristic after normalization to the leakage detection based on a one-factor variance analysis method.
5. The method for extracting the pipeline vibration feature according to claim 1, wherein the values of M and N are both less than or equal to 8.
6. The method for extracting the pipeline vibration feature according to any one of claims 1 to 5, wherein the time domain feature comprises a time domain average value, a time domain absolute average value, a time domain variance, a time domain square root amplitude and a time domain square root value;
the time domain features include peak-to-peak, spectral mean, center frequency, mean square frequency, spectral root mean square value, frequency variance, and frequency domain amplitude skewness.
7. An extraction device for vibration characteristics of a pipeline is characterized by comprising:
the acquisition module is used for acquiring time domain data and frequency domain data of a target pipeline in a leakage state and a non-leakage state in three axial directions;
the calculation module is used for calculating a plurality of vibration characteristics in a preset sampling period based on the time domain data and the frequency domain data; wherein the vibration features comprise time domain features and frequency domain features;
the first extraction module is used for calculating the contribution degree of each vibration characteristic to the leakage detection based on a chi-square detection method; extracting the first N vibration characteristics from the plurality of vibration characteristics according to the contribution degree;
the second extraction module is used for calculating the contribution degree of each vibration characteristic to leakage detection based on a one-factor variance analysis method; extracting the first M vibration characteristics from the plurality of vibration characteristics according to the contribution degree; wherein M and N are both positive integers.
8. The extraction device for the vibration characteristics of the pipeline according to claim 7, wherein the first extraction module comprises:
the normalization unit is used for normalizing the vibration characteristics according to the frequency domain characteristics and the time domain characteristics;
and the calculating unit is used for calculating the contribution degree of each vibration characteristic to be normalized to the leakage detection based on the chi-square test method.
9. An electronic device, comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of extracting vibration characteristics of a pipeline according to any one of claims 1 to 6.
10. A computer-readable medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the method of extracting vibration characteristics of a pipeline according to any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211669262.8A CN115659159A (en) | 2022-12-24 | 2022-12-24 | Method and device for extracting vibration characteristics of pipeline |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211669262.8A CN115659159A (en) | 2022-12-24 | 2022-12-24 | Method and device for extracting vibration characteristics of pipeline |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115659159A true CN115659159A (en) | 2023-01-31 |
Family
ID=85022921
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211669262.8A Pending CN115659159A (en) | 2022-12-24 | 2022-12-24 | Method and device for extracting vibration characteristics of pipeline |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115659159A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104132250A (en) * | 2014-07-14 | 2014-11-05 | 上海师范大学 | Pipeline leakage feature vector extraction method based on improved wavelet packet |
| CN105260371A (en) * | 2014-07-17 | 2016-01-20 | 华为技术有限公司 | Characteristic selection method and device |
| CN111899711A (en) * | 2020-07-30 | 2020-11-06 | 长沙神弓信息科技有限公司 | Vibration noise suppression method for unmanned aerial vehicle sensor |
-
2022
- 2022-12-24 CN CN202211669262.8A patent/CN115659159A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104132250A (en) * | 2014-07-14 | 2014-11-05 | 上海师范大学 | Pipeline leakage feature vector extraction method based on improved wavelet packet |
| CN105260371A (en) * | 2014-07-17 | 2016-01-20 | 华为技术有限公司 | Characteristic selection method and device |
| CN111899711A (en) * | 2020-07-30 | 2020-11-06 | 长沙神弓信息科技有限公司 | Vibration noise suppression method for unmanned aerial vehicle sensor |
Non-Patent Citations (2)
| Title |
|---|
| 余明东: "管道振动监测系统研究" * |
| 毕晓博: "基于振动信号特征的柴油机状态智能识别方法研究" * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20200294491A1 (en) | Method and apparatus for waking up device | |
| CN111883117B (en) | Voice wake-up method and device | |
| CN110334109A (en) | Relational database data query method, system, medium and electronic equipment | |
| WO2022135130A1 (en) | Voice extraction method and apparatus, and electronic device | |
| CN109961141A (en) | Method and apparatus for generating quantization neural network | |
| CN114648675A (en) | Countermeasure training method, image processing method, apparatus, device, and medium | |
| CN111367813B (en) | Automatic testing method and device for decision engine, server and storage medium | |
| CN115659159A (en) | Method and device for extracting vibration characteristics of pipeline | |
| CN117354055A (en) | Block chain twin Internet of things information data migration method and system | |
| CN114710173B (en) | Interference signal filtering method and device, electronic equipment and storage medium | |
| CN110069195B (en) | Image dragging deformation method and device | |
| CN111045634B (en) | Audio processing method and device | |
| CN116072108A (en) | Model generation method, voice recognition method, device, medium and equipment | |
| CN115272760A (en) | Small sample smoke image fine classification method suitable for forest fire smoke detection | |
| CN111754984B (en) | Text selection method, apparatus, device and computer readable medium | |
| CN111680754B (en) | Image classification method, device, electronic equipment and computer readable storage medium | |
| CN112734962B (en) | Attendance information generation method and device, computer equipment and readable storage medium | |
| CN112017685B (en) | Speech generation method, device, equipment and computer readable medium | |
| CN111898061B (en) | Method, apparatus, electronic device and computer readable medium for searching network | |
| CN112416911B (en) | Sample data acquisition method, device, equipment and storage medium | |
| WO2019235194A1 (en) | Acoustic signal separation device, learning device, methods therefor, and program | |
| CN112565979B (en) | Speaker frequency response numerical value calculation method and device, electronic equipment and storage medium | |
| CN110619537A (en) | Method and apparatus for generating information | |
| CN111145776B (en) | Audio processing method and device | |
| CN112039494B (en) | Low-pass filtering method, device, equipment and medium for overcoming azimuth zero crossing |
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 | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20230131 |