CN111458708B - Temperature deformation analysis method based on radar interferometry - Google Patents
Temperature deformation analysis method based on radar interferometry Download PDFInfo
- Publication number
- CN111458708B CN111458708B CN202010414496.2A CN202010414496A CN111458708B CN 111458708 B CN111458708 B CN 111458708B CN 202010414496 A CN202010414496 A CN 202010414496A CN 111458708 B CN111458708 B CN 111458708B
- Authority
- CN
- China
- Prior art keywords
- target
- image
- temperature deformation
- radar
- interferogram
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
Landscapes
- Engineering & Computer Science (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Radiation Pyrometers (AREA)
Abstract
The invention discloses a temperature deformation analysis method based on radar interferometry, which comprises the following steps: acquiring a radar image sequence of a target facility, and extracting a target image pair from the radar image sequence; acquiring a target interference image according to the target image pair; and determining the temperature deformation of the target facility according to the target interference pattern. According to the temperature deformation analysis method based on radar interferometry, the temperature deformation of the target facility is obtained by adopting the interference pattern generated by the target image pair in the radar image sequence of the target facility, and the temperature deformation in the facility deformation is analyzed independently, so that the accuracy of the facility deformation analysis can be improved.
Description
Technical Field
The invention relates to the technical field of facility monitoring, in particular to a temperature deformation analysis method based on radar interferometry.
Background
At present, various facilities such as bridges, buildings and the like are huge in quantity and play an important role in the development of the economic society, and after the facilities are built and used, the facilities can deform along with the continuous increase of operation time and environmental load, and the normal use of the facilities can be seriously influenced, so that not only is the economic loss caused, but also the safety of people is threatened, and therefore, the deformation analysis of the facilities is very necessary. However, the existing deformation analysis of the facility usually analyzes the overall deformation of the facility, the deformation caused by the temperature change has strong periodic tendency, even the magnitude of the temperature deformation exceeds the deformation caused by the structure of the facility, and when the deformation of the facility is analyzed, the temperature deformation needs to be analyzed separately.
Thus, there is a need for improvements and enhancements in the art.
Disclosure of Invention
The invention provides a temperature deformation analysis method based on radar interferometry, and aims to solve the problem that temperature deformation is not independently analyzed in facility deformation analysis in the prior art.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a temperature deformation analysis method based on radar interferometry is disclosed, wherein the temperature deformation analysis method based on radar interferometry comprises the following steps:
acquiring a radar image sequence of a target facility, and extracting a target image pair from the radar image sequence;
acquiring a target interference image according to the target image pair;
and determining the temperature deformation of the target facility according to the target interference pattern.
The temperature deformation analysis method based on radar interferometry, wherein the extracting of the target image pair from the radar image sequence comprises:
selecting a main image from the radar image sequence, and respectively calculating the image coherence of each radar image in the radar image sequence and the main image;
and acquiring each target radar image with image coherence larger than a preset threshold value, and forming a target image pair with the main image respectively.
The temperature deformation analysis method based on radar interferometry, wherein the calculating the image coherence of each radar image and the main image respectively comprises:
respectively acquiring the image coherence of each radar image and the main image according to a first preset formula;
the first preset formula is as follows:
where ρ istotalIs the image coherence between two images, ptemporalIs the temporal coherence between two images, pspatialIs the spatial coherence between two images, pdopplerIs the Doppler coherence between two images, pthermalFor thermal noise coherence, T is the time base line of two images, TcCritical time base line, B⊥Is the spatial baseline of the two images,
is a critical space baseline, FDCThe doppler frequencies of the two images are the doppler frequencies,
is the critical doppler frequency.
The temperature deformation analysis method based on radar interferometry, wherein the obtaining of the target interferogram according to the target image pair comprises:
generating corresponding differential interference patterns according to the target image pairs respectively;
screening the differential interferogram through a pre-trained interferogram screening model to obtain the target interferogram,
the interferogram screening model is trained according to multiple groups of sample data, and each group of sample data comprises a sample differential interferogram and a screening result corresponding to the sample differential interferogram.
The radar interferometry-based temperature deformation analysis method, wherein the determining the temperature deformation of the target facility according to the target interferogram comprises:
obtaining a coherence coefficient of each pixel point in the target interference graph, and determining a linear relation between temperature deformation and temperature difference corresponding to the target facility according to the coherence coefficient;
and determining the temperature deformation of the target facility according to the linear relation.
The temperature deformation analysis method based on radar interferometry, wherein the determining the linear relation between the temperature deformation and the temperature difference corresponding to the target facility according to the coherence coefficient includes:
determining a linear relation parameter of temperature deformation and temperature difference corresponding to the target facility according to a second preset formula;
determining the linear relationship according to the linear relationship parameter,
wherein the second preset formula is as follows:
where n is the total number of target interferograms, γjIs the jth target stemConcerning the maximum coherence coefficient, w, in the diagramjA, b are the linear relation parameters, delta T is the actual deformation measurement value of the time interval between two images in the target image pair corresponding to the jth target interferogram of the target facilityjThe temperature difference between two images in the target image pair corresponding to the jth target interferogram;
the linear relationship is as follows:
ΔD＝a·ΔT2+b(ΔT>0)
ΔD＝a·(-ΔT2)+b(ΔT<0)
and the delta D is the temperature deformation of the target facility generated when the temperature changes delta T.
The temperature deformation analysis method based on radar interferometry, wherein the determining the linear relationship according to the linear relationship parameter comprises:
and acquiring the thermal expansion coefficient of the target facility according to the linear relation, comparing the thermal expansion coefficient with the physical property of the material of the target facility, and verifying the linear relation.
The temperature deformation analysis method based on radar interferometry comprises the following steps of:
establishing a three-dimensional model of the target facility;
and carrying out data fusion on the temperature deformation and the three-dimensional model so as to realize visualization of the temperature deformation.
A terminal, wherein the terminal comprises: the temperature deformation analysis method based on radar interferometry comprises a processor and a storage medium which is in communication connection with the processor, wherein the storage medium is suitable for storing a plurality of instructions, and the processor is suitable for calling the instructions in the storage medium to execute the steps of realizing the temperature deformation analysis method based on radar interferometry.
A storage medium, wherein the storage medium stores one or more programs, which are executable by one or more processors to implement the steps of the above-mentioned radar interferometry-based temperature deformation analysis method.
Has the advantages that: compared with the prior art, the temperature deformation analysis method based on the radar interferometry obtains the temperature deformation of the target facility by adopting the interference pattern generated by the target image pair in the radar image sequence of the target facility, and the temperature deformation in the facility deformation is analyzed independently, so that the accuracy of the facility deformation analysis can be improved.
Drawings
FIG. 1 is a flow chart of an embodiment of a temperature deformation analysis method based on radar interferometry according to the present invention;
FIG. 2 is a schematic diagram of a radar image in a temperature deformation analysis method based on radar interferometry according to the present invention;
FIG. 3 is a schematic diagram of a target interferogram in a temperature deformation analysis method based on radar interferometry according to the present invention;
fig. 4 is a schematic structural diagram of an embodiment of a terminal provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The temperature deformation analysis method based on radar interferometry provided by the invention can be applied to terminals, including but not limited to various high-performance computers, personal computers, mobile terminals and the like.
Example one
Referring to fig. 1, fig. 1 is a flowchart illustrating a temperature deformation analysis method based on radar interferometry according to an embodiment of the present invention. The temperature deformation analysis method based on radar interferometry comprises the following steps:
s100, a radar image sequence of a target facility is obtained, and a target image pair is extracted from the radar image sequence.
The radar image is an image acquired by a radar micro-scale, and when deformation of a target facility is analyzed, a radar image sequence of the target facility is first obtained, specifically, each image in the radar image sequence may be obtained by cutting a radar image of an area where the target facility is located, as shown in fig. 2.
In order to remove the influence of the difference of the radar images caused by other factors on the analysis precision of the deformation of the target facility, in this embodiment, a target image pair is selected from the radar image sequence for deformation analysis, the target image pair includes two images, and the extracting the target image pair from the radar image sequence includes:
s110, selecting a main image from the radar image sequence, and respectively calculating the image coherence of each radar image in the radar image sequence and the main image.
And S120, acquiring each target radar image with image coherence larger than a preset threshold value, and forming a target image pair with the main image respectively.
In this embodiment, two images in the target image pair are interfered to generate a target interference pattern, deformation analysis is performed according to the target interference pattern, and the quality of the target interference pattern is related to the image coherence. Specifically, the separately calculating the image coherence of each radar image in the radar image sequence and the main image includes:
respectively acquiring the image coherence of each radar image and the main image according to a first preset formula;
the first preset formula is as follows:
where ρ istotalIs the image coherence between two images, ptemporalIs the temporal coherence between two images, pspatialIs the spatial coherence between two images, pdopplerIs the Doppler coherence between two images, pthermalFor thermal noise coherence, ρ for the same sensorthermalIs a constant, T is the time base line of two images, TcCritical time base line, B⊥Is the spatial baseline of the two images,
is a critical space baseline, FDCThe doppler frequencies of the two images are the doppler frequencies,
is the critical doppler frequency.
Referring to fig. 1 again, after the target image pair is extracted from the radar image sequence, the method for analyzing temperature deformation based on radar interferometry further includes:
and S200, acquiring a target interference pattern according to the target image pair.
Specifically, the acquiring a target interferogram according to the target image pair includes:
s210, generating corresponding differential interference patterns according to the target image pairs respectively;
s220, screening the differential interferogram through the interference pattern screening model trained in advance to obtain the target interferogram.
For each of the target image pairs, a corresponding differential interference pattern (as shown in fig. 3) may be generated, and in a possible implementation, the differential interference pattern corresponding to each of the target image pairs may be directly used as the target interference pattern, that is, deformation analysis may be directly performed according to the differential interference pattern. In this embodiment, in order to avoid the influence of errors such as orbit errors, ionospheric errors, and atmospheric errors in the interferogram on the result, after the corresponding differential interferogram is obtained according to the target image pair, the differential interferogram is further screened.
Specifically, in this embodiment, the differential interferogram is screened through an interferogram screening model trained in advance, the interferogram screening model is trained according to multiple sets of sample data, and each set of sample data includes a sample differential interferogram and a screening result corresponding to the sample differential interferogram. In specific implementation, a plurality of sample differential interferograms may be prepared, a screening result is marked on each sample differential interferogram in a manual labeling manner, if the difference is preserved or not preserved, to form the plurality of groups of sample data, then the interferogram screening model is trained through the plurality of groups of sample data, so that the interferogram screening model can screen the differential interferogram, one differential interferogram is input to the interferogram screening model, the interferogram screening model outputs the screening result of the differential interferogram, if the difference is preserved or not preserved, and the differential interferogram preserved after screening is used as the target interferogram.
S300, determining the temperature deformation of the target facility according to the target interference pattern.
Specifically, the deformation of the facility includes temperature deformation and structural deformation, the temperature deformation is deformation caused by temperature change, the structural deformation is deformation caused by the structure of the facility and the use condition, and after the temperature deformation of the target facility is determined according to the interferogram, the structural deformation of the target facility can be obtained according to the total deformation of the target facility.
The determining the temperature deformation of the target facility from the target interferogram comprises:
s310, obtaining a coherence coefficient of each pixel point in the target interference pattern, and determining a linear relation between temperature deformation and temperature difference corresponding to the target facility according to the coherence coefficient;
and S320, determining the temperature deformation of the target facility according to the linear relation.
A large number of earlier stage studies show that the temperature deformation of facility and temperature difference are positive correlation, and the temperature difference is bigger, and the temperature deformation that arouses is more violent, based on this experience, can establish the linear relation of temperature deformation and temperature difference to obtain corresponding temperature deformation according to the temperature difference.
Specifically, the coherence coefficient of each pixel in the target interferogram can be obtained according to the coherence coefficient map corresponding to the target interferogram, which is the prior art and is not described herein again. The determining the linear relation between the temperature deformation and the temperature difference corresponding to the target facility according to the coherence coefficient comprises:
s311, determining a linear relation parameter of temperature deformation and temperature difference corresponding to the target facility according to a second preset formula;
and S312, determining the linear relation according to the linear relation parameters.
Wherein the second preset formula is as follows:
where n is the total number of target interferograms, γjIs the maximum coherence coefficient, w, in the jth target interferogramjA, b are the linear relation parameters, delta T is the actual deformation measurement value of the time interval between two images in the target image pair corresponding to the jth target interferogram of the target facilityjIs the temperature difference between the two images in the target image pair corresponding to the jth target interferogram. That is, the respective a and b are obtained such that
And minimum.
The linear relationship is as follows:
ΔD＝a·ΔT2+b(ΔT>0)
ΔD＝a·(-ΔT2)+b(ΔT<0)
and the delta D is the temperature deformation of the target facility generated when the temperature changes delta T.
It is obvious that, when determining the linear relation parameter between the temperature deformation and the temperature difference, the present invention sets different weights for each target interferogram according to the coherence coefficient of each target interferogram, and specifically, for the target image pair corresponding to the target interferogram with higher coherence, the deformation value obtained by analysis is more reliable, so that γ is set in the second preset formulajThe data weight of the target interferogram with higher coherence is improved, so that the linear relationship is more accurate.
Further, in order to ensure the accuracy of the linear relationship, in this embodiment, the verifying the linear relationship further includes, specifically, after determining the linear relationship according to the linear relationship parameter:
and acquiring the thermal expansion coefficient of the target facility according to the linear relation, comparing the thermal expansion coefficient with the physical property of the material of the target facility, and verifying the linear relation.
Specifically, from the linear relationship, the thermal expansion coefficient α of the target facility can be obtainedT＝ΔD/(L·ΔT2) And D is the temperature deformation generated by the target facility when the temperature changes by delta T, and L is the effective length of temperature deformation transmission. When the coefficient of thermal expansion obtained from the linear relationship is consistent with the physical properties of the target facility material, the linear relationship can be considered to be more accurate.
Of course, those skilled in the art may also verify the linear relationship in other manners, for example, by comparing the temperature deformation obtained according to the linear relationship with the spatial distribution of the temperature deformation predicted based on the principle of structural mechanics, or, since there are multiple radar image datasets, such as an MSTR dataset, a shanghai Terra-X dataset, etc., the linear relationship may be obtained according to the above steps by radar images in different radar image datasets, and cross-validation may be performed according to the linear relationship obtained by different datasets, etc.
Referring to fig. 1 again, the method for analyzing temperature deformation based on radar interferometry further includes:
s300, determining the temperature deformation of the target facility according to the target interference pattern.
After the linear relation between the temperature deformation and the temperature difference corresponding to the target facility is determined, the temperature deformation of the target facility between two time points can be obtained only by obtaining the temperature difference between the two time points.
In a possible implementation manner, in order to facilitate analysis of deformation of the facility, the visualizing the temperature deformation is further performed, and specifically, after determining the temperature deformation of the target facility according to the target interferogram, the method includes:
and establishing a three-dimensional model of the target facility, and performing data fusion on the temperature deformation and the three-dimensional model to realize visualization of the temperature deformation.
After the temperature deformation of the target facility is determined according to the linear relationship, the temperature deformation data of the target facility can be correspondingly fused into the three-dimensional model of the target facility, so that an analyst can intuitively find the deformation propagation direction, the spatial distribution, the amplitude and the like through three-dimensional interactive operation such as rotation, translation, scaling, attribute coloring and the like, and provide more valuable information for knowing the deformation rule and safety analysis of the target facility by combining the self structure and material characteristics of the target facility, such as the correlation among the geometric shape, the structural stress characteristic, the material attribute and the like.
In summary, the present invention provides a temperature deformation analysis method based on radar interferometry, which obtains temperature deformation of a target facility by using an interferogram generated by a target image pair in a radar image sequence of the target facility, and separately analyzes the temperature deformation in the facility deformation, thereby improving accuracy of the facility deformation analysis.
It should be understood that, although the steps in the flowcharts shown in the figures of the present specification are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the sub-steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
Example two
Based on the above embodiments, the present invention further provides a terminal, and a schematic block diagram thereof may be as shown in fig. 4. The terminal comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein the processor of the terminal is configured to provide computing and control capabilities. The memory of the terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a method of temperature deformation analysis based on radar interferometry. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the terminal is arranged in the terminal in advance and used for monitoring the current operating temperature of internal equipment.
It will be understood by those skilled in the art that the block diagram of fig. 4 is a block diagram of only a portion of the structure associated with the inventive arrangements and is not intended to limit the terminals to which the inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may have some components combined, or may have a different arrangement of components.
In one embodiment, a terminal is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor when executing the computer program implementing at least the following steps:
acquiring a radar image sequence of a target facility, and extracting a target image pair from the radar image sequence;
acquiring a target interference image according to the target image pair;
and determining the temperature deformation of the target facility according to the target interference pattern.
Wherein the extracting of the target image pair from the radar image sequence comprises:
selecting a main image from the radar image sequence, and respectively calculating the image coherence of each radar image in the radar image sequence and the main image;
and acquiring each target radar image with image coherence larger than a preset threshold value, and forming a target image pair with the main image respectively.
Wherein the calculating the image coherence of each radar image and the main image respectively comprises:
respectively acquiring the image coherence of each radar image and the main image according to a first preset formula;
the first preset formula is as follows:
where ρ istotalIs the image coherence between two images, ptemporalIs the temporal coherence between two images, pspatialIs the spatial coherence between two images, pdopplerIs the Doppler coherence between two images, pthermalFor thermal noise coherence, T is the time base line of two images, TcCritical time base line, B⊥Is the spatial baseline of the two images,
is a critical space baseline, FDCThe doppler frequencies of the two images are the doppler frequencies,
is the critical doppler frequency.
Wherein the acquiring a target interferogram according to the target image pair comprises:
generating corresponding differential interference patterns according to the target image pairs respectively;
screening the differential interferogram through a pre-trained interferogram screening model to obtain the target interferogram,
the interferogram screening model is trained according to multiple groups of sample data, and each group of sample data comprises a sample differential interferogram and a screening result corresponding to the sample differential interferogram.
Wherein the determining the temperature deformation of the target facility from the target interferogram comprises:
obtaining a coherence coefficient of each pixel point in the target interference graph, and determining a linear relation between temperature deformation and temperature difference corresponding to the target facility according to the coherence coefficient;
and determining the temperature deformation of the target facility according to the linear relation.
Wherein the determining the linear relationship between the temperature deformation and the temperature difference corresponding to the target facility according to the coherence coefficient comprises:
determining a linear relation parameter of temperature deformation and temperature difference corresponding to the target facility according to a second preset formula;
determining the linear relationship according to the linear relationship parameter,
wherein the second preset formula is as follows:
where n is the total number of target interferograms, γjFor maximum coherence in the jth target interferogramCoefficient of performance, wjA, b are the linear relation parameters, delta T is the actual deformation measurement value of the time interval between two images in the target image pair corresponding to the jth target interferogram of the target facilityjThe temperature difference between two images in the target image pair corresponding to the jth target interferogram;
the linear relationship is as follows:
ΔD＝a·ΔT2+b(ΔT>0)
ΔD＝a·(-ΔT2)+b(ΔT<0)
and the delta D is the temperature deformation of the target facility generated when the temperature changes delta T.
Wherein determining the linear relationship according to the linear relationship parameter comprises:
and acquiring the thermal expansion coefficient of the target facility according to the linear relation, comparing the thermal expansion coefficient with the physical property of the material of the target facility, and verifying the linear relation.
Wherein the determining of the temperature deformation of the target facility from the target interferogram comprises:
establishing a three-dimensional model of the target facility;
and carrying out data fusion on the temperature deformation and the three-dimensional model so as to realize visualization of the temperature deformation.
EXAMPLE III
The present invention also provides a storage medium storing one or more programs, which are executable by one or more processors to implement the steps of the radar interferometry-based temperature deformation analysis method according to the first embodiment.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A temperature deformation analysis method based on radar interferometry is characterized by comprising the following steps:
acquiring a radar image sequence of a target facility, and extracting a target image pair from the radar image sequence;
acquiring a target interference image according to the target image pair;
determining the temperature deformation of the target facility according to the target interference pattern;
the determining the temperature deformation of the target facility from the target interferogram comprises:
obtaining a coherence coefficient of each pixel point in the target interference graph, and determining a linear relation between temperature deformation and temperature difference corresponding to the target facility according to the coherence coefficient;
and determining the temperature deformation of the target facility according to the linear relation.
2. The radar interferometry based temperature deformation analysis method of claim 1, wherein the extracting a target image pair from the radar image sequence comprises:
selecting a main image from the radar image sequence, and respectively calculating the image coherence of each radar image in the radar image sequence and the main image;
and acquiring each target radar image with image coherence larger than a preset threshold value, and forming a target image pair with the main image respectively.
3. The method of claim 2, wherein the separately calculating the image coherence of each radar image with the main image comprises:
respectively acquiring the image coherence of each radar image and the main image according to a first preset formula;
the first preset formula is as follows:
where ρ istotalIs the image coherence between two images, ptemporalIs the temporal coherence between two images, pspatialIs the spatial coherence between two images, pdopplerIs the Doppler coherence between two images, pthermalFor thermal noise coherence, T is the time base line of two images, TcCritical time base line, B⊥Is the spatial baseline of the two images, B⊥ cIs a critical space baseline, FDCThe doppler frequencies of the two images are the doppler frequencies,
is the critical doppler frequency.
4. The radar interferometry based temperature deformation analysis method of claim 1, wherein the obtaining a target interferogram from the target image pair comprises:
generating corresponding differential interference patterns according to the target image pairs respectively;
screening the differential interferogram through a pre-trained interferogram screening model to obtain the target interferogram,
the interferogram screening model is trained according to multiple groups of sample data, and each group of sample data comprises a sample differential interferogram and a screening result corresponding to the sample differential interferogram.
5. The radar interferometry based temperature deformation analysis method according to claim 1, wherein the determining the linear relationship between the temperature deformation and the temperature difference corresponding to the target facility according to the coherence coefficient comprises:
determining a linear relation parameter of temperature deformation and temperature difference corresponding to the target facility according to a second preset formula;
determining the linear relationship according to the linear relationship parameter,
wherein the second preset formula is as follows:
where n is the total number of target interferograms, γjIs the maximum coherence coefficient, w, in the jth target interferogramjA, b are the linear relation parameters, delta T is the actual deformation measurement value of the time interval between two images in the target image pair corresponding to the jth target interferogram of the target facilityjThe temperature difference between two images in the target image pair corresponding to the jth target interferogram;
the linear relationship is as follows:
ΔD＝a·ΔT2+b(ΔT>0)
ΔD＝a·(-ΔT2)+b(ΔT<0)
and the delta D is the temperature deformation of the target facility generated when the temperature changes delta T.
6. The radar interferometry based temperature deformation analysis method of claim 5, wherein the determining the linear relationship according to the linear relationship parameter comprises:
and acquiring the thermal expansion coefficient of the target facility according to the linear relation, comparing the thermal expansion coefficient with the physical property of the material of the target facility, and verifying the linear relation.
7. The radar interferometry based temperature deformation analysis method of claim 1, wherein the determining the temperature deformation of the target facility from the target interferogram comprises, after:
establishing a three-dimensional model of the target facility;
and carrying out data fusion on the temperature deformation and the three-dimensional model so as to realize visualization of the temperature deformation.
8. A terminal, characterized in that the terminal comprises: a processor, a storage medium communicatively connected to the processor, the storage medium adapted to store a plurality of instructions, the processor adapted to invoke the instructions in the storage medium to perform the steps of implementing the radar interferometry based temperature deformation analysis method according to any of claims 1-7.
9. A storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the steps of the radar interferometry based temperature deformation analysis method according to any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010414496.2A CN111458708B (en) | 2020-05-15 | 2020-05-15 | Temperature deformation analysis method based on radar interferometry |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010414496.2A CN111458708B (en) | 2020-05-15 | 2020-05-15 | Temperature deformation analysis method based on radar interferometry |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111458708A CN111458708A (en) | 2020-07-28 |
| CN111458708B true CN111458708B (en) | 2022-04-15 |
Family
ID=71686063
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010414496.2A Active CN111458708B (en) | 2020-05-15 | 2020-05-15 | Temperature deformation analysis method based on radar interferometry |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111458708B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106940443A (en) * | 2017-01-16 | 2017-07-11 | 洪都天顺（深圳）科技有限公司 | Complicated city infrastructure PSInSAR deformation methods of estimation under the conditions of cloud-prone and raining |
| CN107621636A (en) * | 2017-11-13 | 2018-01-23 | 河海大学 | A kind of Large-scale Railway Method of Bridge Health Monitoring based on PSI |
| CN108646244A (en) * | 2018-03-28 | 2018-10-12 | 中科卫星应用德清研究院 | Measure the analysis method and system of five dimension deformation of building |
| CN109341557A (en) * | 2018-09-13 | 2019-02-15 | 北京信息科技大学 | A kind of test method and system of piezo-electricity composite material temperature deformation |
| CN109471107A (en) * | 2018-11-27 | 2019-03-15 | 长沙理工大学 | Bridge permanent deformation analysis method based on PS-InSAR technology |
-
2020
- 2020-05-15 CN CN202010414496.2A patent/CN111458708B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106940443A (en) * | 2017-01-16 | 2017-07-11 | 洪都天顺（深圳）科技有限公司 | Complicated city infrastructure PSInSAR deformation methods of estimation under the conditions of cloud-prone and raining |
| CN107621636A (en) * | 2017-11-13 | 2018-01-23 | 河海大学 | A kind of Large-scale Railway Method of Bridge Health Monitoring based on PSI |
| CN108646244A (en) * | 2018-03-28 | 2018-10-12 | 中科卫星应用德清研究院 | Measure the analysis method and system of five dimension deformation of building |
| CN109341557A (en) * | 2018-09-13 | 2019-02-15 | 北京信息科技大学 | A kind of test method and system of piezo-electricity composite material temperature deformation |
| CN109471107A (en) * | 2018-11-27 | 2019-03-15 | 长沙理工大学 | Bridge permanent deformation analysis method based on PS-InSAR technology |
Non-Patent Citations (4)
| Title |
|---|
| Potential of satellite InSAR techniques for monitoring of bridge deformations;Milan Lazecky et al.;《2015 Joint Urban Remote Sensing Event (JURSE)》;20150611;第1—4页 * |
| Stability assessment of high-speed railway using advanced InSAR technique;Xiaoqiong QIN et al.;《2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)》;20161103;第6010—6013页 * |
| 基于路面变形速度的弯沉测量方法;张德津等;《上海交通大学学报》;20150228;第49卷(第2期);第220—226、231页 * |
| 应用PSInSAR技术分析上海道路网沉降时空特性;秦晓琼等;《武汉大学学报(信息科学版)》;20170228;第42卷(第2期);第170—177页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111458708A (en) | 2020-07-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sarmadi et al. | Bridge health monitoring in environmental variability by new clustering and threshold estimation methods | |
| Kaya et al. | Process capability analyses based on fuzzy measurements and fuzzy control charts | |
| Wang et al. | Investigation of the uncertainty of DIC under heterogeneous strain states with numerical tests | |
| Fouedjio et al. | Estimation of space deformation model for non-stationary random functions | |
| Liu et al. | Structural motion estimation via Hilbert transform enhanced phase-based video processing | |
| Shi et al. | Accuracy analysis of digital elevation model relating to spatial resolution and terrain slope by bilinear interpolation | |
| Iglesias et al. | Bayesian inversion in resin transfer molding | |
| Wang et al. | Kalman filter based fault detection for two-dimensional systems | |
| Blaysat et al. | Effect of interpolation on noise propagation from images to DIC displacement maps | |
| Gandino et al. | Covariance-driven subspace identification: A complete input–output approach | |
| CN112597577B (en) | High-precision dynamic measurement method and device for bridge cable force and computer equipment | |
| Pan et al. | Comparison of subset-based local and FE-based global digital image correlation: Theoretical error analysis and validation | |
| Carpio et al. | An anisotropic, fully adaptive algorithm for the solution of convection-dominated equations with semi-Lagrangian schemes | |
| Debruyne et al. | Identification of design parameter variability of honeycomb sandwich beams from a study of limited available experimental dynamic structural response data | |
| Estrada et al. | Intuitive interface for the quantitative evaluation of speckle patterns for use in digital image and volume correlation techniques | |
| Sur et al. | Influence of the analysis window on the metrological performance of the grid method | |
| De Marchi et al. | A rescaled method for RBF approximation | |
| CN111458708B (en) | Temperature deformation analysis method based on radar interferometry | |
| Emami | Local influence for Liu estimators in semiparametric linear models | |
| EP3351959B1 (en) | Apparatus and method for performing a consistency testing using non-linear filters that provide predictive probability density functions | |
| Broggiato et al. | Full‐field strain rate measurement by white‐light speckle image correlation | |
| Maquin et al. | Data reconciliation with uncertain models | |
| Yang et al. | Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study | |
| Liu et al. | Wind pressure field reconstruction based on unbiased conditional kernel density estimation | |
| Lima et al. | Robust simultaneous inference for the mean function of functional data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |