CN110470742A - A kind of accurate detecting method of channel bend defect - Google Patents
A kind of accurate detecting method of channel bend defect Download PDFInfo
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Abstract
The present invention discloses a kind of accurate detecting method of channel bend defect, successively applies chirp signal to single stimulus sensor, obtains Chirp exciter response signal；Use narrow-band impulse extracting method, from the narrow-band ping for extracting guided wave under different center frequency in Chirp exciter response signal, and modal identification is carried out to the wave packet in the narrow-band ping of extraction, then for the purpose of obtaining pure S0 mode, confirm the centre frequency that narrowband extracts；Channel bend tomography forward model is established, and using the positive algorithm of second differnce, the guided wave flight time is calculated；Decline inversion method then in conjunction with steepest, flight time feature signal-based is extracted signal to narrow-band impulse and is analyzed and processed, and the identification and extraction of defect characteristic information are then carried out to the result of analysis processing；The depth and surface appearance feature of last display defect, complete the detection of channel bend defect.The present invention can be realized that channel bend defect is accurate and effective, comprehensive and quick detection.
Description
Technical field
The invention belongs to transport pipeline defects detection fields, are related to a kind of accurate detecting method of channel bend defect.
Background technique
As the fifth-largest transportation industry after railway, highway, water transport and aviation, pipeline transportation is because of its unique advantage, In
Extremely important effect is embodied in the industries such as petrochemical industry, power generation and daily life.But such pipeline usually high temperature, high pressure or
It works under the adverse circumstances such as person's galvano-cautery, in addition different degrees of damage, will inevitably occur in the aging of device structure itself
Wound, and then cause major accident, it will also cause casualties while bringing huge economic losses.Channel bend is as pipeline
The important component of network, effective detection of defect, the detection for improving transport pipeline are of great significance.
Since supersonic guide-wave propagation distance is long, detection speed is fast, decays small, high-efficient, and has and detect entire wall thickness side
The advantage in face has obtained great application and research in pipeline non-destructive testing field.Nowadays, more and more domestic and foreign scholars are right
Propagation characteristic of the supersonic guide-wave in channel bend has carried out emulation or experimental study.
The A.DEMMA of Imperial College, Britain has studied channel bend to guided wave transmission and anti-by finite element analysis
Penetrate the influence of coefficient, it was demonstrated that reflection and transmission performance of the supersonic guide-wave in channel bend is supersonic guide-wave in pipeline
Using providing Research Thinking.
Existing ultrasonic guided wave signals energisation mode is to be arranged circumferentially sensor respectively at channel bend both ends, and one end is
The actuated sensor of annular array arrangement, one end is the receiving sensor of annular array arrangement, if stimulus sensor applies simultaneously
Axial excitation can inspire S0 mode in channel bend, and stimulus sensor applies circumferential excitation simultaneously to swash in channel bend
T mode is issued, this kind of energisation mode single measurement can only obtain a kind of useful signal, therefore it is complete to limit acquisition elbow structure
Property information, cannot achieve the high resolution detection to elbow defect；On the other hand, studies have shown that passing through existing motivator
The supersonic guide-wave inspired either uses S0 mode or T mode, can not examine to the inside region of channel bend
It surveys, therefore, it is necessary to study new, effective guided wave exciting technique and signal processing method, realizes that channel bend defect is accurate, has
Effect comprehensively, quickly detects.
Summary of the invention
It is an object of the invention to overcome the above-mentioned prior art, a kind of accurate detection of channel bend defect is provided
Method, the detection method can be realized that defect in channel bend is accurate and effective, comprehensive and quick detection.
To achieve the above objectives, the technical solution of the present invention is as follows:
A kind of accurate detecting method of channel bend defect, comprising the following steps:
S1 builds channel bend ultrasonic guided wave detecting system；Using the channel bend ultrasonic guided wave detecting system built, according to
The secondary single stimulus sensor in channel bend ultrasonic guided wave detecting system applies chirp signal, channel bend supersonic guide-wave
Receiving sensor in detection system obtains Chirp exciter response signal；Using narrow-band impulse extracting method, motivated from Chirp
The narrow-band ping of guided wave under different center frequency is extracted in response signal, and to the wave packet in the narrow-band ping of extraction
Modal identification is carried out, then for the purpose of obtaining pure S0 mode, the centre frequency that narrowband extracts is confirmed, according to the center
Frequency obtains narrow-band impulse and extracts signal；
S2 establishes channel bend tomography forward model, and using the positive algorithm of second differnce, when to guided wave flight
Between calculated；Decline inversion method, the narrow-band impulse that flight time feature signal-based obtains S1 then in conjunction with steepest
It extracts signal to be analyzed and processed, the identification and extraction of defect characteristic information is then carried out to the result of analysis processing；Finally show
Show the depth and surface appearance feature of defect, completes the detection of channel bend defect.
In S1, from the process for extracting the narrow-band ping of guided wave under different center frequency in Chirp exciter response signal
It is as follows:
Determine that ideal pulse pumping signal is sd(t), ideal pulse pumping signal sd(t) response signal Rd(ω) are as follows:
Wherein, Rc(ω) is the frequency domain presentation form of Chirp exciter response signal, Sd(ω) is ideal pulse pumping signal
Fourier transformation, Sc(ω) is the Fourier transformation form of Chirp signal, and G (ω) is the bandpass filter in frequency domain；
Then to ideal pulse pumping signal sd(t) response signal Rd(ω) carries out inverse Fourier transform, obtains ideal arteries and veins
Rush pumping signal sd(t) narrow-band ping Rd(t)。
In S1, the process for carrying out modal identification to the wave packet in the narrow-band ping of extraction is as follows:
Time-frequency conversion is done to the narrow-band ping of extraction and obtains the arrival time of each Frequency point, in narrow-band ping
The flight time t of wave packetfAnd arrival time meets following formula:
tf=ta-te
Wherein, teFor the sending time of each Frequency point of ideal pulse pumping signal, taFor the arrival time of wave packet；
Then according to the flight time t of the wave packet in narrow-band pingfSeek the spread speed v of wave packet:
Wherein, larcFor the arc length of channel bend；
Then according to the spread speed v of wave packet and supersonic guide-wave dispersion curve, in the narrow-band ping of extraction
Wave packet carries out modal identification.
In S1, for the purpose of obtaining pure S0 mode, confirm that the process for the centre frequency that narrowband extracts is as follows:
Select S0 mode as the mode of channel bend ultrasound detection, the purity level ξ of S0 mode are as follows:
Wherein, A1For the wave packet amplitude of S0 mode, A2For the wave packet amplitude of A0 mode；
Then according to the relationship between purity level ξ and the centre frequency of narrowband extraction, the center frequency extracted narrowband is determined
Rate.
The Chirp signal is signal of the instantaneous frequency with Time Continuous linear change, the mathematical expression of Chirp signal
Formula are as follows:
In formula: w (t) is rectangular window function；f0For initial frequency；B is signal frequency domain width；T is signal duration；
The expression-form of Chirp exciter response signal in a frequency domain are as follows:
Rc(ω)=H (ω) Sc(ω)
Wherein, Rc(ω) is the frequency domain presentation form of Chirp exciter response signal；Sc(ω) is the Fourier of Chirp signal
Variation.
In S2, it is as follows to establish channel bend tomography forward model process:
Outside channel bend crestal line be unfolded, establish channel bend tomography forward model, obtain channel bend chromatography at
As forward model three-dimensional system of coordinate { O, x, y, z } and two-dimensional coordinate system the mapping relations of O, x', y'} are as follows:
Wherein, R is the bending radius of channel bend, and r is the internal diameter of the pipeline of channel bend.
In S2, using the positive algorithm of second differnce, the process calculated the guided wave flight time includes the following steps:
S2.1 acquires anisotropy velocity of sound field model c'(θ according to channel bend tomography forward model) are as follows:
Wherein, c is guided waves propagation speed,
S2.2 obtains eikonal equation according to the mapping relations and anisotropy velocity of sound field model are as follows:
S2.3 solves eikonal equation using second-order algorithm, obtains the flight time matrix of whole region, in which:
Solving eikonal equation uses entropy to meet the algorithm in uplink region, and eikonal equation is expressed are as follows:
WhereinIndicate backward difference operator in the x-direction,Indicate forward difference operator in the x-direction,Table
Show forward difference operator in the y-direction,Indicate backward difference operator in the y-direction；
The citation form of second-order differential operator are as follows:
In S2, decline inversion method in conjunction with steepest, flight time feature signal-based mentions the narrow-band impulse that S1 is obtained
The number of winning the confidence is analyzed and processed, and the identification and extraction of defect characteristic information are then carried out to the result of analysis processing；Finally show
The depth of defect and the process of surface appearance feature include the following steps:
S2.4 obtains matrix T when receiving sensor is walked according to flight time matrix；
S2.5 determines inversion problem are as follows:
D=A (T)
Wherein, A is nonlinear operator, and d is the wall thickness matrix of channel bend whole region；
S2.6 sets walking time error functional are as follows:
φ (d)=| | A (d)-T | |
S2.7 sets the gradient δ of walking time error functionaln, the optimized direction of steepest decline inversion method is determined, to pipeline
The wall thickness matrix d iteration of elbow whole region, Iteration are as follows:
dn+1=dn-ηnδn
Wherein, ηnFor step-size in search, ηnIt is calculate by the following formula:
ηn=arg { min [φ (dn+ηδn)]}
Wherein,
When error reaches given level, iterative process is terminated, and calculated result is mapped in threedimensional model, and display lacks
Sunken depth and surface appearance feature.
Compared with the prior art, the invention has the following beneficial effects:
In the accurate detecting method of channel bend defect of the invention, signal is detected using chirp signal, therefore improving
It can be improved detection efficiency while signal-to-noise ratio again, while by successively to single in channel bend ultrasonic guided wave detecting system
Stimulus sensor applies chirp signal, that is, the guided wave signals being subject to expand n compared with traditional array simultaneously motivator2
Times the quantity of sensor (n circumferentially), obtains the information more containing elbow shape characteristic.In terms of signal processing, mention
Guided wave S0 mode flight temporal characteristics are taken out, the second-order algorithm of proposition utilizes the flight-time information of grid node, can be more
Add and be accurately finally inversed by elbow topographical information, and defect detection result is more intuitive.It should be noted that the present invention is using ultrasound
Guided wave has the characteristics that all-wave field characteristic and spread speed are fast as detection means, based on supersonic guide-wave, and it is curved can to complete pipeline
Accurate and effective, comprehensive and quick detection of head defect.
Detailed description of the invention
Fig. 1 is the structural schematic diagram for the channel bend ultrasonic guided wave detecting system built in the present invention；
Fig. 2 is the time-domain diagram of the chirp signal in the present invention；
Fig. 3 is the frequency domain figure of the chirp signal in the present invention；
Fig. 4 is the time-frequency domain figure of the chirp signal in the present invention；
Fig. 5 is channel bend threedimensional model in the present invention to two dimensional model mapping graph；
Fig. 6 is the detailed process figure of channel bend detection in the present invention.
Specific embodiment
The present invention is further detailed with reference to the accompanying drawings and examples, to verify the present invention in the application
Validity, but this example is not intended to restrict the invention.
Referring to Fig. 6, the channel bend defect high-precision detecting method of the present invention based on supersonic guide-wave includes following
Step:
Step 1, channel bend ultrasonic guided wave detecting system as shown in Figure 1, the channel bend supersonic guide-wave are built first
Detection system includes guided wave excitation system, guided wave acquisition system and computer, wherein guided wave excitation system include waveform generator,
The stimulus sensor of amplifier and guided wave, stimulus sensor are connect with voltage amplifier, and amplifier is connect with waveform generator, are led to
It crosses guided wave excitation system and generates the supersonic guide-wave propagated along channel bend；Guided wave acquisition system includes receiving sensor, amplifier
That is data collector, receiving sensor are connect with amplifier, and amplifier is connected with data collector, pass through guided wave acquisition system
Acquisition and recording carries the guided wave signals of detection structure information, and data collector and waveform generator are connect with computer.
Successively apply chirp signal as shown in Figure 2 to single stimulus sensor, receiving sensor obtains Chirp excitation
Response signal, chirp signal are a kind of broadband excitation signals, and time-domain diagram, frequency domain figure and the time-frequency domain figure of chirp signal are respectively such as
Shown in Fig. 2, Fig. 3 and Fig. 4；Next narrow-band impulse extracting method is used, is expeditiously extracted from Chirp exciter response signal
Out under different center frequency guided wave narrow-band ping, and in the narrow-band ping of extraction wave packet carry out mode distinguish
Know, then for the purpose of obtaining pure S0 mode, confirms the centre frequency that narrowband extracts, obtained according to the centre frequency narrow
Tape pulse extracts signal.
Step 2, it establishes channel bend tomography forward model, and using the positive algorithm of second differnce, realizes to leading
The calculating of wave flight time declines inversion method then in conjunction with steepest, what flight time feature signal-based obtained step 1
Narrow-band impulse extracts signal and is analyzed and processed, and then carries out the identification of defect characteristic information to the result of analysis processing and mentions
It takes, the depth and surface appearance feature of last display defect, completes channel bend defects detection.
The detailed process of step 1 of the present invention are as follows:
The Chirp signal of use refers to instantaneous frequency with the signal of Time Continuous linear change, the mathematics of Chirp signal
Expression formula are as follows:
In formula: w (t) --- rectangular window function；f0--- initial frequency；B --- signal frequency domain width；T --- signal is held
The continuous time.
The expression-form of Chirp exciter response signal in a frequency domain are as follows:
Rc(ω)=H (ω) Sc(ω)
Wherein, Rc(ω) is the frequency domain presentation form of Chirp exciter response signal；Sc(ω) is the Fourier of Chirp signal
Variation.
Enable sdIt (t) is ideal pulse pumping signal, for the same Guided waves system, ideal pulse mechanism signal sd(t)
Response signal Rd(ω) are as follows:
Rd(ω)=H (ω) Sd(ω)
Wherein, response signal Rd(ω) uses frequency domain presentation form；Sd(ω) is ideal pulse pumping signal sd(t) Fu
In leaf transformation.
In ideal pulse excitation signal sd(t) in situation known to, response signal Rd(ω) frequency domain presentation form are as follows:
Wherein, G (ω) is considered as the bandpass filter in frequency domain；
Next, in the situation known to all parameters, to the result response signal R soughtdIt is inverse that (ω) carries out Fourier
Transformation, obtains ideal pulse pumping signal sd(t) response signal Rd(t), response signal RdIt (t) is narrow-band ping.
The response of 5 cycle sinusoidal signals of Hanning window modulation is set to extract object, ideal pulse pumping signal sd(t)
Expression formula are as follows:
Wherein, fcFor the centre frequency of extraction.
Time-frequency conversion is done to the narrow-band ping of extraction and obtains the arrival time of each Frequency point, the i.e. instantaneous frequency of signal
The arrival time of rate and each Frequency point corresponds respectively to projection of the crestal line in frequency and time shaft；
The flight time and arrival time of wave packet in narrow-band ping meet following formula:
tf=ta-te
Wherein, tfFor the flight time of wave packet, taFor the arrival time of wave packet, teFor each frequency of ideal pulse pumping signal
The sending time of point.
Then according to the flight time t of the wave packet in narrow-band pingfAcquire the spread speed of wave packet:
Wherein v is Wave packet propogation speed, larcFor the arc length of channel bend；
Next, according to the spread speed v and supersonic guide-wave dispersion curve of wave packet, in the narrow-band ping of extraction
Wave packet carry out modal identification；
Then select S0 mode as the mode of channel bend ultrasound detection, parameter ξ characterizes the purity level of S0 mode, pure
The expression formula of net degree ξ are as follows:
Wherein, A1For the wave packet amplitude of S0 mode, A2For the wave packet amplitude of A0 mode；
Then according to the relationship between purity level ξ and the centre frequency of narrowband extraction, the center frequency extracted narrowband is determined
Rate.
The detailed process of step 2 of the present invention are as follows:
As shown in figure 5, crestal line is unfolded outside channel bend, channel bend tomography forward model is established, pipeline is obtained
Elbow tomography forward model three-dimensional system of coordinate { O, x, y, z } and two-dimensional coordinate system the mapping relations of O, x', y'} are as follows:
Wherein, R and r is respectively the bending radius and internal diameter of the pipeline of elbow；
According to channel bend tomography forward model, it is based on differential geometric theory, acquires anisotropy velocity of sound field model
C'(θ) are as follows:
Wherein, c is guided waves propagation speed,
Eikonal equation is obtained according to the mapping relations and anisotropy velocity of sound field model are as follows:
Eikonal equation is solved using second-order algorithm, obtains the flight time matrix of whole region, in which:
Solving eikonal equation uses entropy to meet the algorithm in uplink region, and eikonal equation is expressed as are as follows:
Wherein,Indicate backward difference operator in the x-direction,Indicate forward difference operator in the x-direction,
Indicate forward difference operator in the y-direction,Indicate backward difference operator in the y-direction；
The citation form of second-order differential operator are as follows:
Matrix T when receiving sensor is walked is obtained according to flight time matrix；
Determine inversion problem are as follows:
D=A (T)
Wherein, A is nonlinear operator, and d is the wall thickness matrix of channel bend whole region；
Set walking time error functional are as follows:
φ (d)=| | A (d)-T | |
Set the gradient δ of walking time error functionaln, the optimized direction of steepest decline inversion method is determined, to channel bend
The wall thickness matrix d iteration of whole region, Iteration are as follows:
dn+1=dn-ηnδn
Wherein ηnFor step-size in search, ηnIt is calculate by the following formula:
ηn=arg { min [φ (dn+ηδn)]}
Wherein,
When error reaches the level of setting, iterative process is terminated, it may be assumed that φ (d)≤ε0When, iterative process terminates, ε0To set
Fixed level；
Finally calculated result is mapped in threedimensional model, intuitive aobvious pipeline shows the topographical information of elbow.
Claims (8)
1. a kind of accurate detecting method of channel bend defect, which comprises the following steps:
S1 builds channel bend ultrasonic guided wave detecting system；Using the channel bend ultrasonic guided wave detecting system built, successively give
Single stimulus sensor in channel bend ultrasonic guided wave detecting system applies chirp signal, channel bend ultrasonic guided wave detecting
Receiving sensor in system obtains Chirp exciter response signal；Using narrow-band impulse extracting method, from Chirp exciter response
The narrow-band ping of guided wave under different center frequency is extracted in signal, and to the wave Bao Jinhang in the narrow-band ping of extraction
Modal identification confirms the centre frequency that narrowband extracts, according to the centre frequency then for the purpose of obtaining pure S0 mode
It obtains narrow-band impulse and extracts signal；
S2, establishes channel bend tomography forward model, and using the positive algorithm of second differnce, to the guided wave flight time into
Row calculates；Decline inversion method then in conjunction with steepest, flight time feature signal-based extracts the narrow-band impulse that S1 is obtained
Signal is analyzed and processed, and the identification and extraction of defect characteristic information are then carried out to the result of analysis processing；Finally display lacks
Sunken depth and surface appearance feature completes the detection of channel bend defect.
2. a kind of accurate detecting method of channel bend defect according to claim 1, which is characterized in that in S1, from
The process that the narrow-band ping of guided wave under different center frequency is extracted in Chirp exciter response signal is as follows:
Determine that ideal pulse pumping signal is sd(t), ideal pulse pumping signal sd(t) response signal Rd(ω) are as follows:
Wherein, Rc(ω) is the frequency domain presentation form of Chirp exciter response signal, Sd(ω) is Fu of ideal pulse pumping signal
In leaf transformation, Sc(ω) is the Fourier transformation form of Chirp signal, and G (ω) is the bandpass filter in frequency domain；
Then to ideal pulse pumping signal sd(t) response signal Rd(ω) carries out inverse Fourier transform, obtains ideal pulse and swashs
Encourage signal sd(t) narrow-band ping Rd(t)。
3. a kind of accurate detecting method of channel bend defect according to claim 1, which is characterized in that in S1, to mentioning
The process that wave packet in the narrow-band ping taken carries out modal identification is as follows:
Time-frequency conversion is done to the narrow-band ping of extraction and obtains the arrival time of each Frequency point, narrow-band ping medium wave packet
Flight time tfAnd arrival time meets following formula:
tf=ta-te
Wherein, teFor the sending time of each Frequency point of ideal pulse pumping signal, taFor the arrival time of wave packet；
Then according to the flight time t of the wave packet in narrow-band pingfSeek the spread speed v of wave packet:
Wherein, larcFor the arc length of channel bend；
Then according to the spread speed v of wave packet and supersonic guide-wave dispersion curve, to the wave packet in the narrow-band ping of extraction
Carry out modal identification.
4. a kind of accurate detecting method of channel bend defect according to claim 1, which is characterized in that in S1, to obtain
For the purpose of obtaining pure S0 mode, confirm that the process for the centre frequency that narrowband extracts is as follows:
Select S0 mode as the mode of channel bend ultrasound detection, the purity level ξ of S0 mode are as follows:
Wherein, A1For the wave packet amplitude of S0 mode, A2For the wave packet amplitude of A0 mode；
Then according to the relationship between purity level ξ and the centre frequency of narrowband extraction, the centre frequency that narrowband extracts is determined.
5. a kind of accurate detecting method of channel bend defect according to claim 1, which is characterized in that the Chirp
Signal is signal of the instantaneous frequency with Time Continuous linear change, the mathematic(al) representation of Chirp signal are as follows:
In formula: w (t) is rectangular window function；f0For initial frequency；B is signal frequency domain width；T is signal duration；
The expression-form of Chirp exciter response signal in a frequency domain are as follows:
Rc(ω)=H (ω) Sc(ω)
Wherein, Rc(ω) is the frequency domain presentation form of Chirp exciter response signal；Sc(ω) is the Fourier transformation of Chirp signal
Form.
6. a kind of accurate detecting method of channel bend defect according to claim 1, which is characterized in that in S2, establish
Channel bend tomography forward model process is as follows:
Crestal line is unfolded outside channel bend, establishes channel bend tomography forward model, is obtaining channel bend tomography just
Drill model three-dimensional system of coordinate { O, x, y, z } and two-dimensional coordinate system the mapping relations of O, x', y'} are as follows:
Wherein, R is the bending radius of channel bend, and r is the internal diameter of the pipeline of channel bend.
7. a kind of accurate detecting method of channel bend defect according to claim 6, which is characterized in that in S2, utilize
The positive algorithm of second differnce, the process calculated the guided wave flight time include the following steps:
S2.1 acquires anisotropy velocity of sound field model c'(θ according to channel bend tomography forward model) are as follows:
Wherein, c is guided waves propagation speed,
S2.2 obtains eikonal equation according to the mapping relations and anisotropy velocity of sound field model are as follows:
S2.3 solves eikonal equation using second-order algorithm, obtains the flight time matrix of whole region, in which:
Solving eikonal equation uses entropy to meet the algorithm in uplink region, and eikonal equation is expressed are as follows:
WhereinIndicate backward difference operator in the x-direction,Indicate forward difference operator in the x-direction,Indicate edge
The forward difference operator in the direction y,Indicate backward difference operator in the y-direction；
The citation form of second-order differential operator are as follows:
8. a kind of accurate detecting method of channel bend defect according to claim 7, which is characterized in that in S2, in conjunction with
Steepest declines inversion method, and flight time feature signal-based is extracted signal to the narrow-band impulse that S1 is obtained and carried out at analysis
Then reason carries out the identification and extraction of defect characteristic information to the result of analysis processing；The depth of last display defect and surface
The process of shape characteristic includes the following steps:
S2.4 obtains matrix T when receiving sensor is walked according to flight time matrix；
S2.5 determines inversion problem are as follows:
D=A (T)
Wherein, A is nonlinear operator, and d is the wall thickness matrix of channel bend whole region；
S2.6 sets walking time error functional are as follows:
φ (d)=| | A (d)-T | |
S2.7 sets the gradient δ of walking time error functionaln, the optimized direction of steepest decline inversion method is determined, to channel bend
The wall thickness matrix d iteration of whole region, Iteration are as follows:
dn+1=dn-ηnδn
Wherein, ηnFor step-size in search, ηnIt is calculate by the following formula:
ηn=arg { min [φ (dn+ηδn)]}
Wherein,
When error reaches given level, iterative process is terminated, and calculated result is mapped in threedimensional model, display defect
Depth and surface appearance feature.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111189930A (en) * | 2020-02-07 | 2020-05-22 | 哈尔滨工业大学（威海） | Crack detection method, system and equipment based on pipe body and storage medium |
| CN117648594A (en) * | 2024-01-29 | 2024-03-05 | 长沙市海图科技有限公司 | Urban safety gas pipe network defect identification and management method |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0518943A (en) * | 1991-03-01 | 1993-01-26 | Mitsui Mining & Smelting Co Ltd | Method and device for detecting internal defect |
| JP2008304431A (en) * | 2007-06-11 | 2008-12-18 | Nichizou Tec:Kk | Scanning apparatus |
| CN102435674A (en) * | 2011-09-16 | 2012-05-02 | 新疆电力公司电力科学研究院 | Novel method for detecting crack and corrosion defects of metal part base material inner wall |
| CN102507734A (en) * | 2011-10-26 | 2012-06-20 | 河北省电力建设调整试验所 | Ultrasonic time-of-flight diffraction (TOFD) detection method for weld seam |
| CN202305480U (en) * | 2011-09-21 | 2012-07-04 | 北京工业大学 | Storage tank bottom plate corrosion detection system based on ultrasonic Lamb wave |
| JP2014062758A (en) * | 2012-09-20 | 2014-04-10 | Hitachi-Ge Nuclear Energy Ltd | Method and device for nondestructive inspection using guide wave |
| CN104374828A (en) * | 2014-11-18 | 2015-02-25 | 上海岩土工程勘察设计研究院有限公司 | Ultrasonic tomography imaging method of detection on hidden defect |
| CN105044212A (en) * | 2015-06-30 | 2015-11-11 | 清华大学 | Multimodal ultrasonic Lamb wave complex defect tomography method |
| WO2016161459A1 (en) * | 2015-04-02 | 2016-10-06 | Los Alamos National Security, Llc | Acoustic gas volume fraction measurement in a multiphase flowing liquid |
| CN107356677A (en) * | 2017-07-12 | 2017-11-17 | 厦门大学 | The supersonic damage-free detection method being imaged based on travel time tomography and reverse-time migration |
-
2019
- 2019-04-25 CN CN201910340435.3A patent/CN110470742B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0518943A (en) * | 1991-03-01 | 1993-01-26 | Mitsui Mining & Smelting Co Ltd | Method and device for detecting internal defect |
| JP2008304431A (en) * | 2007-06-11 | 2008-12-18 | Nichizou Tec:Kk | Scanning apparatus |
| CN102435674A (en) * | 2011-09-16 | 2012-05-02 | 新疆电力公司电力科学研究院 | Novel method for detecting crack and corrosion defects of metal part base material inner wall |
| CN202305480U (en) * | 2011-09-21 | 2012-07-04 | 北京工业大学 | Storage tank bottom plate corrosion detection system based on ultrasonic Lamb wave |
| CN102507734A (en) * | 2011-10-26 | 2012-06-20 | 河北省电力建设调整试验所 | Ultrasonic time-of-flight diffraction (TOFD) detection method for weld seam |
| JP2014062758A (en) * | 2012-09-20 | 2014-04-10 | Hitachi-Ge Nuclear Energy Ltd | Method and device for nondestructive inspection using guide wave |
| CN104374828A (en) * | 2014-11-18 | 2015-02-25 | 上海岩土工程勘察设计研究院有限公司 | Ultrasonic tomography imaging method of detection on hidden defect |
| WO2016161459A1 (en) * | 2015-04-02 | 2016-10-06 | Los Alamos National Security, Llc | Acoustic gas volume fraction measurement in a multiphase flowing liquid |
| CN105044212A (en) * | 2015-06-30 | 2015-11-11 | 清华大学 | Multimodal ultrasonic Lamb wave complex defect tomography method |
| CN107356677A (en) * | 2017-07-12 | 2017-11-17 | 厦门大学 | The supersonic damage-free detection method being imaged based on travel time tomography and reverse-time migration |
Non-Patent Citations (5)
| Title |
|---|
| SERGIO MALO 等: "Wave Mode Discrimination of Coded Ultrasonic Guided Waves Using Two-Dimensional Compressed Pulse Analysis", 《IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL》 * |
| 周邵萍 等: "基于导波的弯管裂纹缺陷的检测", 《机械工程学报》 * |
| 孙凯 等: "基于弹性导波的厚钢梁结构的损伤检测", 《振动与冲击》 * |
| 张吉 等: "超声波CT技术在混凝土无损检测中的应用现状及发展趋势", 《工程地球物理学报》 * |
| 郑阳 等: "Chirp信号及其在超声导波检测中的应用", 《仪器仪表学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111189930A (en) * | 2020-02-07 | 2020-05-22 | 哈尔滨工业大学（威海） | Crack detection method, system and equipment based on pipe body and storage medium |
| CN111189930B (en) * | 2020-02-07 | 2022-07-19 | 哈尔滨工业大学（威海） | Crack detection method, system and equipment based on pipe body and storage medium |
| CN117648594A (en) * | 2024-01-29 | 2024-03-05 | 长沙市海图科技有限公司 | Urban safety gas pipe network defect identification and management method |
| CN117648594B (en) * | 2024-01-29 | 2024-04-05 | 长沙市海图科技有限公司 | Urban safety gas pipe network defect identification and management method |
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