CN106501372A - Monitoring and positioning method based on wavelet packet analysis track switch crackle - Google Patents
Monitoring and positioning method based on wavelet packet analysis track switch crackle Download PDFInfo
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- CN106501372A CN106501372A CN201610959522.3A CN201610959522A CN106501372A CN 106501372 A CN106501372 A CN 106501372A CN 201610959522 A CN201610959522 A CN 201610959522A CN 106501372 A CN106501372 A CN 106501372A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/14—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object using acoustic emission techniques
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/10—Number of transducers
- G01N2291/101—Number of transducers one transducer
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2291/00—Indexing codes associated with group G01N29/00
- G01N2291/26—Scanned objects
- G01N2291/262—Linear objects
- G01N2291/2623—Rails; Railroads
Abstract
The invention discloses a kind of monitoring and positioning method based on wavelet packet analysis track switch crackle, comprises the steps：Formation of crack acoustic emission signal is gathered by being installed on the acoustic emission sensor of the end of track switch；Decompose the formation of crack acoustic emission signal using wavelet package transforms computing, obtain wavelet coefficient；To wavelet coefficient reconfiguration waveform；In the reconfiguration waveform, two wavelet signals for being used for positioning are chosen；Calculate the time difference Δ t that two wavelet signals reach the acoustic emission sensor；Obtain spread speed C of two wavelet signals in same mode1、C2；According to ranging formula, crackle is calculated with the acoustic emission sensor apart from S, determine the particular location of crackle.Using the present invention, in the case of only need to using single sensor, railroad turnout steel rail crackle, low cost is accurately positioned.
Description
Technical field
The invention belongs to track crack monitoring technical field, and in particular to a kind of prison based on wavelet packet analysis track switch crackle
Survey localization method.
Background technology
With China's science and technology rapid development of economy, track traffic has become the backbone of urban public transport.Track switch
It is important component part therein, under the repeat function of rolling stock dynamic loading, due in the material and construction of track switch itself
The reason for, track switch can be made to produce fatigue crack, crackle can make rail fracture cause train derailment once extending.Existing track
Detection meanss carry out health detection mainly by track detection vehicle or supersonic detecting vehicle to stock rail, but this inspection
Survey method cannot accurately be detected a flaw to the track of this complex section form of track switch.
Therefore, at present for turnout detection meanss still rely on manual method.For example, detected using acoustic emission sensor
Rail defects and failures, the frequency range for wherein commonly using acoustic emission signal is 100KHz-1000KHz, and the signal frequency of rail cracks exists
In the range of this.Crackle that some experimentatioies using acoustic emission method detected in rail is had at present, and they are not only from theory
On demonstrate the feasibility for detecting rail cracks using acoustic emission method, and examined by wheel track test equipment and actual field
Survey, further demonstrate the effectiveness that Rail Surface crackle is detected using acoustic emission.
However, these researchs mainly adopt characteristic parameter analytic process in the feature extraction of acoustic emission signal.Base in recent years
In the extractive technique of wave character, as the development of digital Acoustic radiating instrument shows its superiority, especially to complex geometry shape
Acoustic emission source in shape carries out feature extraction, compared to traditional parameters analysis method, can more accurately obtain crackle sound
The feature of emission source.In specific features extraction and position fixing process, generally existing problems with：
(1) using in Fourier transformation and wavelet-decomposing method, wavelet decomposition is poor in the frequency resolution of high band, and
Poor in the temporal resolution of low-frequency range, for the Analysis of Acoustic Emission Signal of high frequency slightly inadequate.
(2) on localization method, conventional sound localization is divided into two big class：Regional mapping method and time-of-arrival loaction：Region
The sound source position of positioning mode detection is a region, and degree of accuracy is relatively low；The most frequently used for time-of-arrival loaction, its precision is higher.
Generally, the diverse location of track switch is distributed in using multiple sensors according to certain way, is believed according to sound source
Number reach different sensors time difference, through the accurate location that geometric operation can determine that sound source.Positioning precision to be improved, it is necessary to
The acoustic emission wave signal of in sound-source signal same mode same frequency is accurately detected.As the length of railroad turnout steel rail is much larger than its section
Radius surface, so, sound localization belongs to the line positioning of the one-dimensional space, and it is fixed generally must to be carried out using two sensors
Position, so causes equipment cost and installation cost higher.
Content of the invention
In order to solve in prior art for Crack Acoustic Emission Signal high band frequency resolution poor, in low-frequency range
The problem that temporal resolution is poor and equipment cost is high, it is an object of the invention to provide a kind of be based on wavelet packet analysis track switch
The monitoring and positioning method of crackle, in the case of only need to using single sensor, is accurately positioned railroad turnout steel rail crackle, low cost.
For achieving the above object, the present invention is achieved by technical scheme below：
Monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention, it is characterised in that including following step
Suddenly：
Formation of crack acoustic emission signal is gathered by being installed on the acoustic emission sensor of the end of track switch；
Decompose the formation of crack acoustic emission signal using wavelet package transforms computing, obtain wavelet coefficient；
To wavelet coefficient reconfiguration waveform；
In the reconfiguration waveform, two wavelet signals for being used for positioning are chosen；
Calculate the time difference Δ t that two wavelet signals reach the acoustic emission sensor；
Obtain spread speed C of two wavelet signals in same mode1、C2；
According to ranging formula, crackle is calculated with the acoustic emission sensor apart from S, determine the particular location of crackle.
Further, the concrete formula of the wavelet package transforms analysis and utilization is：
Wherein, function wn(n ∈ N) is by orthogonal scaling function w0The wavelet packet that=φ determines；
hkAnd gkRespectively low pass and high pass filter coefficient.
Further, the step of the wavelet coefficient reconfiguration waveform, specific as follows：
In a series of wavelet packet coefficients, according to the frequency range that chooses, the corresponding wavelet packet coefficient of the frequency range is chosen, through too small
Reconstructed wave algorithm, the oscillogram of the selected frequency range after being reconstructed.
Further, the frequency of the frequency range is in 100kHz-180kHz.
Further, the step of calculating the time difference Δ t that two wavelet signals reach the acoustic emission sensor, tool
Body is：
In the frequency range, amplitude contour map is drawn, then according to the corresponding frequency values of wavelet signal that chooses, in institute
State in amplitude contour map, find the corresponding time, then twice done difference operation and obtained time difference Δ t.
Further, it is specially according to ranging formula：
Further, spread speed C of two wavelet signals in same mode is obtained1、C2The step of, specially：
By Rayleigh-Lan Mu equations, in group velocity curve, correspondingly in the same mode of the frequency selection purposes of the wavelet signal
Spread speed C1、C2.
Further, in the Rayleigh-Lan Mu equations, according to the characteristics of particle vibration, Lamb wave be divided into symmetric pattern and
Antisymmetric mode, the corresponding different order of each pattern Lamb wave.
Further, for Lamb wave is symmetric pattern, the Rayleigh-Lan Mu equations are：
Wherein：
CpLamb wave phase velocity；CsTransverse wave speed；ClLongitudinal wave velocity；
F Lamb wave frequencies；D thicknesss of slab.
Further, for Lamb wave is symmetric pattern, the Rayleigh-Lan Mu equations are：
Wherein：
CpLamb wave phase velocity；CsTransverse wave speed；ClLongitudinal wave velocity；
F Lamb wave frequencies；D thicknesss of slab.
Compared with prior art, the invention has the beneficial effects as follows：
(1) monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention, using wavelet package transforms come
Decompose acoustic emission Signal of Cracks, it is ensured that also have higher frequency resolution in high band, accurately extract the high frequency in Signal of Cracks
Rate signal.
(2) monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention, is solving acoustic emission crackle
On signal framing, an acoustic emission sensor is only used, reduced manufacturing cost and the installation cost of crack detection equipment.
Description of the drawings
Below in conjunction with the accompanying drawings the specific embodiment of the present invention is described in further detail, wherein：
Fig. 1 is the flow chart of the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention；
Fig. 2 is that track switch acoustic emission source is fixed in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Position schematic diagram；
Fig. 3 is using Rayleigh-Lan Mu in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
The group velocity figure of symmetrical wave and antisymmetry ripple in the track switch that equation is obtained；
Fig. 4 is acoustic emission Signal of Cracks in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Wavelet package transforms decomposition tree and source signal figure；
Fig. 5 (a) is wavelet package transforms in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Afterwards, the wavelet coefficient diagrams of the 110kHz of selection；
Fig. 5 (b) is wavelet package transforms in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Afterwards, the wavelet coefficient diagrams of the 122kHz of selection；
Fig. 6 (a) is wavelet package reconstruction in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Afterwards, the oscillogram of 110kHz；
Fig. 6 (b) is wavelet package reconstruction in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Afterwards, the oscillogram of 122kHz；
Fig. 7 is 100kHz-180kHz in the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention
Frequency range wavelet package reconstruction amplitude contour map.
Specific embodiment
The preferred embodiments of the present invention are illustrated below in conjunction with accompanying drawing, it will be appreciated that preferred reality described herein
Apply example to be merely to illustrate and explain the present invention, be not intended to limit the present invention.
As shown in Fig. 1～Fig. 7, the monitoring and positioning method based on wavelet packet analysis track switch crackle of the present invention, specifically
Step is as follows：
S01：Formation of crack acoustic emission signal is gathered by acoustic emission sensor；
The acoustic emission sensor is installed on the end of track switch, uniquely to determine the position of crackle.
S02：Decompose the formation of crack acoustic emission signal using wavelet package transforms computing, obtain wavelet coefficient；
The concrete formula of the wavelet package transforms analysis and utilization is：
Wherein, function wn(n ∈ N) is by orthogonal scaling function w0The wavelet packet that=φ determines；
hkAnd gkRespectively low pass and high pass filter coefficient.
Meanwhile, the power of the formation of crack acoustic emission signal is analyzed in 100kHz-180kHz.
S03：To wavelet coefficient reconfiguration waveform；
In a series of wavelet packet coefficients, according to the frequency range that chooses, the corresponding wavelet packet coefficient of the frequency range is chosen, through too small
Reconstructed wave algorithm, the oscillogram of the selected frequency range after being reconstructed.The frequency of the frequency range is in 100kHz-180kHz.
S04：In the reconfiguration waveform, two wavelet signals for being used for positioning are chosen；
Wherein this is used for the wavelet signal for positioning in reconfiguration waveform, chooses and concentrates prominent two waveform the most.
S05：Calculate the time difference Δ t that two wavelet signals reach the acoustic emission sensor；
In the frequency range, amplitude contour map is drawn, then according to the corresponding frequency values of wavelet signal that chooses, in institute
State in amplitude contour map, find the corresponding time, then twice done difference operation and obtained time difference Δ t.
Wherein, receipt amplitude contour map, specifically：
All wavelet packet coefficients after to decomposition seek absolute value, then according to frequency from low to high, successively each small echo
The coefficient of bag is plotted on figure.
S06：Obtain spread speed C of two wavelet signals in same mode1、C2；
By Rayleigh-Lan Mu equations, in group velocity curve, correspondingly in the same mode of the frequency selection purposes of the wavelet signal
Spread speed C1、C2；
Wherein, according to the characteristics of particle vibration, Lamb wave is divided into symmetric pattern and antisymmetric mode, each pattern Lamb wave
Corresponding different order.
For Lamb wave is symmetric pattern, the Rayleigh-Lan Mu equations are：
For Lamb wave is symmetric pattern, the Rayleigh-Lan Mu equations are：
Wherein：
CpLamb wave phase velocity；CsTransverse wave speed；ClLongitudinal wave velocity；
F Lamb wave frequencies；D thicknesss of slab.
S07：According to ranging formula, crackle is calculated with the acoustic emission sensor apart from S, determine the concrete position of crackle
Put.
It is specially according to ranging formula：
In conjunction with the track switch crack monitoring localization method based on wavelet packet analysis of the present invention above, specific to actual mistake
Used in journey, operate as follows：
1st, the installation of acoustic emission sensor and Selection of Wavelet Basis：
Adopt length for the rail of 15m, one end manually manufactures crackle breach wherein, tapped with weight and crack extension
Signal, is installing acoustic emission sensor, as shown in Figure 2 at breach 10m.
In wavelet packet, the selection of wavelet basiss can produce certain impact to analytical effect, in order to reach preferable analytical effect,
Suitable small echo should be selected.The small echo of symmetrical wavelet or near symmetrical is selected, to avoid phase distortion.For the typical sound of analysis
Transmission signal, selects db10 wavelet basiss herein.
2nd, acquisition parameter and the wavelet packet number of plies are arranged：
When carrying out wavelet packet analysis to formation of crack acoustic emission signal it may first have to the Decomposition order of wavelet packet to be determined, and
And Taiwan ADLINK high-speed collection card DAQ-2010 Real-time Collection track switch Crack Acoustic Emission Signals are used, sample frequency is 1MHz,
Sampling number is 20000, and according to Shannon (Shannon) sampling thheorem, its Nyquist (Nyquist) frequency is 500kHz.
By wavelet packet analysis, acoustic emission Signal of Cracks is decomposed the 9th layer, a total of 512 wavelet packets, that is to say by
The frequency domain of source signal is divided into 512 sub-bands, and a width of 976.5625Hz of the band of each sub-band, wherein peak low band be 0～
976.5625Hz, as shown in Figure 4.
3rd, choose the frequency of two high-frequency wavelets and calculate spread speed：
Due to during Signal of Cracks is judged, from the sensitivity that power spectral density map analysis shows track switch crackle acoustic emission
Frequency range is in more than 100kHz, therefore combines actual measured results, and the decomposition ripple of selection 110kHz and two frequencies of 122kHz is used as inspection
Framing signal is surveyed, respectively the 113rd wavelet packet and the 125th wavelet packet in the 9th layer of wavelet packet tree.
The track plate thickness of known track switch is 18mm, can be calculated the corresponding maximal rate difference of 110kHz and 122kHz
For 2543m/s and 3812m/s, the wavelet coefficient after its wavelet package transforms is as shown in Figure 5.
4th, location Calculation：
The all frequencies for choosing 100kHz～180kHz frequency ranges carry out wavelet package reconstruction, and are depicted as amplitude contour map,
As shown in fig. 7, can see that reaching time-difference is 1.39ms, according to formula by small echo figure(wherein, Δ
T reaches the time of sensor, C for sound-source signal1With C2The spread speed of respectively frequency a-signal and frequency B signal) can meter
Position location is calculated for 10.62m, actual crack signal location is 10m, and positional accuracy is 93%.
The above, is only presently preferred embodiments of the present invention, not makees any pro forma restriction to the present invention, therefore
Every any modification that without departing from technical solution of the present invention content, above example is made according to the technical spirit of the present invention,
Equivalent variations and modification, still fall within the range of technical solution of the present invention.
Claims (10)
1. a kind of monitoring and positioning method based on wavelet packet analysis track switch crackle, it is characterised in that comprise the steps：
Formation of crack acoustic emission signal is gathered by being installed on the acoustic emission sensor of the end of track switch；
Decompose the formation of crack acoustic emission signal using wavelet package transforms computing, obtain wavelet coefficient；
To wavelet coefficient reconfiguration waveform；
In the reconfiguration waveform, two wavelet signals for being used for positioning are chosen；
Calculate the time difference Δ t that two wavelet signals reach the acoustic emission sensor；
Obtain spread speed C of two wavelet signals in same mode1、C2；
According to ranging formula, crackle is calculated with the acoustic emission sensor apart from S, determine the particular location of crackle.
2. the monitoring and positioning method based on wavelet packet analysis track switch crackle according to claim 1, it is characterised in that：
The concrete formula of the wavelet package transforms analysis and utilization is：
Wherein, function wn(n ∈ N) is by orthogonal scaling function w0The wavelet packet that=φ determines；
hkAnd gkRespectively low pass and high pass filter coefficient.
3. the monitoring and positioning method based on wavelet packet analysis track switch crackle according to claim 1, it is characterised in that：
The step of wavelet coefficient reconfiguration waveform, specific as follows：
In a series of wavelet packet coefficients, according to the frequency range that chooses, the corresponding wavelet packet coefficient of the frequency range is chosen, through small echo weight
Structure algorithm, the oscillogram of the selected frequency range after being reconstructed.
4. the monitoring and positioning method based on wavelet packet analysis track switch crackle according to claim 3, it is characterised in that：
The frequency of the frequency range is in 100kHz-180kHz.
5. the monitoring and positioning method based on wavelet packet analysis track switch crackle according to claim 4, it is characterised in that：
The step of calculating the time difference Δ t that two wavelet signals reach the acoustic emission sensor, specifically：
In the frequency range, amplitude contour map is drawn, then according to the corresponding frequency values of wavelet signal that chooses, in the width
Value contour map in, find the corresponding time, then twice done difference operation and obtained time difference Δ t.
6. the monitoring and positioning method based on wavelet packet analysis track switch crackle according to claim 4, it is characterised in that：
It is specially according to ranging formula：
7. the monitoring and positioning method based on wavelet packet analysis track switch crackle according to right 1, it is characterised in that：
Obtain spread speed C of two wavelet signals in same mode1、C2The step of, specially：
Biography by Rayleigh-Lan Mu equations, in group velocity curve, in the same mode of the frequency selection purposes of the corresponding wavelet signal
Broadcast speed C1、C2.
8. the monitoring and positioning method based on wavelet packet analysis track switch crackle that states according to claim 7, it is characterised in that：
In the Rayleigh-Lan Mu equations, according to the characteristics of particle vibration, Lamb wave is divided into symmetric pattern and antisymmetric mode, per
The corresponding different orders of the pattern of kind Lamb wave.
9. the monitoring and positioning method based on wavelet packet analysis track switch crackle that states according to claim 8, it is characterised in that：
For Lamb wave is symmetric pattern, the Rayleigh-Lan Mu equations are：
Wherein：
CpLamb wave phase velocity；CsTransverse wave speed；ClLongitudinal wave velocity；
F Lamb wave frequencies；D thicknesss of slab.
10. the monitoring and positioning method based on wavelet packet analysis track switch crackle that claim 8 is stated, it is characterised in that：
For Lamb wave is symmetric pattern, the Rayleigh-Lan Mu equations are：
Wherein：
CpLamb wave phase velocity；CsTransverse wave speed；ClLongitudinal wave velocity；
F Lamb wave frequencies；D thicknesss of slab.
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| CN108132303A (en) * | 2017-11-28 | 2018-06-08 | 北京机电工程研究所 | A kind of near space vehicle thermal protection structure damage positioning method |
| CN109085248A (en) * | 2018-07-03 | 2018-12-25 | 内蒙古科技大学 | Localization method, the apparatus and system of bearing pipe wall impulse source |
| CN110568078A (en) * | 2019-06-20 | 2019-12-13 | 北京全路通信信号研究设计院集团有限公司 | Steel rail fracture detection method, device and system suitable for turnout zone |
| CN111301489A (en) * | 2020-03-31 | 2020-06-19 | 成都科锐传感技术有限公司 | Method for monitoring track cracks on line |
| CN114715222A (en) * | 2021-01-04 | 2022-07-08 | 北京全路通信信号研究设计院集团有限公司 | Steel rail online detection method and system |
| CN114715222B (en) * | 2021-01-04 | 2024-05-10 | 北京全路通信信号研究设计院集团有限公司 | Steel rail online detection method and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108132303A (en) * | 2017-11-28 | 2018-06-08 | 北京机电工程研究所 | A kind of near space vehicle thermal protection structure damage positioning method |
| CN109085248A (en) * | 2018-07-03 | 2018-12-25 | 内蒙古科技大学 | Localization method, the apparatus and system of bearing pipe wall impulse source |
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| CN110568078A (en) * | 2019-06-20 | 2019-12-13 | 北京全路通信信号研究设计院集团有限公司 | Steel rail fracture detection method, device and system suitable for turnout zone |
| CN110568078B (en) * | 2019-06-20 | 2022-04-22 | 北京全路通信信号研究设计院集团有限公司 | Steel rail fracture detection method, device and system suitable for turnout zone |
| CN111301489A (en) * | 2020-03-31 | 2020-06-19 | 成都科锐传感技术有限公司 | Method for monitoring track cracks on line |
| CN114715222A (en) * | 2021-01-04 | 2022-07-08 | 北京全路通信信号研究设计院集团有限公司 | Steel rail online detection method and system |
| CN114715222B (en) * | 2021-01-04 | 2024-05-10 | 北京全路通信信号研究设计院集团有限公司 | Steel rail online detection method and system |
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