CN110261850B - Imaging algorithm for tree internal defect detection data - Google Patents
Imaging algorithm for tree internal defect detection data Download PDFInfo
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- CN110261850B CN110261850B CN201910584839.7A CN201910584839A CN110261850B CN 110261850 B CN110261850 B CN 110261850B CN 201910584839 A CN201910584839 A CN 201910584839A CN 110261850 B CN110261850 B CN 110261850B
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- 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
- G01S13/006—Theoretical aspects
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- 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
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- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/411—Identification of targets based on measurements of radar reflectivity
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- 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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/418—Theoretical aspects
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Abstract
The invention discloses an imaging algorithm of tree internal defect detection data, belongs to the technical field of tree internal defect detection, and aims to solve the problem that the influence of diffraction effect is ignored by the traditional detection technology and algorithm, and nondestructive detection of living standing tree cannot be met. Step a, equipment arrangement; step b, dividing grids; step c, calculating a time matrix of returning to the receiver after the signal sent by the transmitter reaches the sampling point by using a formula; step d, a linear interpolation method is applied, and electric fields corresponding to each element are accumulated on electric field values obtained by N sensors according to an accumulation formula, so that an electric field matrix is obtained; and e, representing the electric field matrix obtained by calculation aiming at each sampling point in a color cloud picture mode, thereby finishing detection and imaging of the internal defects of the standing tree. The imaging algorithm of the tree internal defect detection data can image the acquired signals and display the signals on a device display through an image display system.
Description
Technical Field
The invention relates to an imaging method, in particular to an imaging algorithm of tree internal defect detection data, and belongs to the technical field of tree internal defect detection.
Background
Compared with methods such as stress wave, ultrasonic wave, X-ray scanning and the like, the electromagnetic wave technology can be used for detecting a target object completely without damage, has high precision and no pollution, is safe to detect, and is increasingly used for detecting wood and trees. When an electromagnetic wave propagates in a medium, a part of the electromagnetic wave passes through a plane having a difference in electrical characteristics, is reflected, and is received by a receiving antenna. The direct wave and scattered wave of the electromagnetic wave in the propagation process are calculated and analyzed, so that the propagation condition of the electromagnetic wave in the medium inside the tree is obtained, the tree inside visual image is presented by combining the tree section profile information, the tree inside structure condition is accurately judged, and an important basis is provided for protecting rare ancient tree names and preventing and controlling plant diseases and insect pests in forest areas.
Nondestructive testing is carried out on the standing tree by adopting an electromagnetic wave technology to judge whether defects (cavities or decay) exist in the standing tree, and the main research difficulty is defect identification. The traditional electromagnetic wave nondestructive testing technology is based on the radar-sonar principle, and performs qualitative analysis on materials according to pulse echoes of defects. The technology only utilizes the scattering property of electromagnetic waves, ignores the influence of diffraction effect, is often limited by factors such as the shape of defects, the surface roughness of materials and the like in use, and cannot meet the requirement of nondestructive detection of standing tree, namely the inverse problem of electromagnetic wave scattering.
Disclosure of Invention
The invention aims to provide an imaging algorithm of tree internal defect detection data, so as to solve the problem that the traditional detection technology and algorithm neglect the influence of diffraction effect and cannot meet the requirement of nondestructive detection of standing tree. .
An imaging algorithm based on tree internal defect detection data, comprising the steps of:
step a, equipment arrangement; uniformly placing N transmitters and N receivers on the circumference of the tree, wherein each transmitter of the array transmits an electromagnetic pulse in one acquisition period, and each receiver receives an Ascan signal;
step b, dividing grids; taking the center of the air area as the center of a circle, taking the distance from the receiver to the center of the circle as the radius, and making an inscribed regular quadrangle of the circle to obtain vertex coordinates (x 1, y 1), (x 2, y 2) of the inscribed regular quadrangle, wherein the side length of the inscribed quadrangle divides the whole area according to a certain step to obtain N1×N2 coordinate points as sampling points;
step c, respectively calculating the sum of the distances from each sampling point to the transmitter and the receiver to obtain a three-dimensional matrix D N1×N2×N Calculating the time matrix t of the signal sent by the transmitter reaching the sampling point and returning to the receiver by using the formula N1×N2×N ；
Step d, a linear interpolation method is applied, and a time matrix t is found from the N groups of data obtained in the step 2 N1×N2×N The electric field E corresponding to each element S (x, t) applying an electric field E S (x, t) accumulating the electric field values obtained by N sensors according to an accumulation formula to obtain an electric field matrix I k (Z)；
Step e, calculating to obtain an electric field matrix I aiming at each sampling point k (Z) N1×N2 The method is expressed in a color cloud picture form, and the area with the bright spots in the picture is the internal defect of the standing tree, so that the internal defect of the standing tree is detected and imaged.
Preferably: the calculation formula in the step c is as follows:
wherein c=3×10 8 m/s, τ is a time constant related to wavelength, j=1, 2,...
Preferably: the accumulated formula in step d is:
wherein E is S (x, t) is a time matrix t N1×N2×N Electric field corresponding to each element of I k (Z) is an electric field matrix.
Compared with the existing products, the invention has the following effects:
when the main control processor controls, a control circuit is required to generate a continuous signal or a synchronous pulse signal and a device acquisition signal, the signal is transmitted into the tree through a transmitting antenna of the electromagnetic wave transmitter, and when the signal is subjected to targets with different dielectric constants, scattering is formed at an interface, so that an echo signal is formed. The equipment acquisition signal generated by the time sequence control circuit controls the data sampling circuit to acquire the signal at the receiving antenna, the signal is sent to the signal processing system through the main control processor to be amplified, filtered and the like, and the imaging algorithm is added in the signal processing system, so that the acquired signal can be imaged and displayed on the equipment display through the image display system.
Drawings
FIG. 1 is a block diagram of a tree internal defect imaging apparatus;
FIG. 2 is a schematic diagram of meshing operation;
fig. 3 is a schematic view of electromagnetic wave propagation inside a tree.
Detailed Description
Preferred embodiments of the present invention are described in detail below.
The imaging algorithm of the tree internal defect detection data comprises the following steps:
step a, equipment arrangement; uniformly placing N transmitters and N receivers on the circumference of the tree, wherein each transmitter of the array transmits an electromagnetic pulse in one acquisition period, and each receiver receives an Ascan signal;
step b, dividing grids; taking the center of the air area as the center of a circle, taking the distance from the receiver to the center of the circle as the radius, and making an inscribed regular quadrangle of the circle to obtain vertex coordinates (x 1, y 1), (x 2, y 2) of the inscribed regular quadrangle, wherein the side length of the inscribed quadrangle divides the whole area according to a certain step to obtain N1×N2 coordinate points as sampling points;
step c, respectively calculating the sum of the distances from each sampling point to the transmitter and the receiver to obtain a three-dimensional matrix D N1×N2×N Calculating the time matrix t of the signal sent by the transmitter reaching the sampling point and returning to the receiver by using the formula N1×N2×N ；
Step d, a linear interpolation method is applied, and a time matrix t is found from the N groups of data obtained in the step 2 N1×N2×N The electric field E corresponding to each element S (x, t) applying an electric field E S (x, t) accumulating the electric field values obtained by N sensors according to an accumulation formula to obtain an electric field matrix I k (Z)；
Step e, calculating to obtain an electric field matrix I aiming at each sampling point k (Z) N1×N2 The method is expressed in a color cloud picture form, and the area with the bright spots in the picture is the internal defect of the standing tree, so that the internal defect of the standing tree is detected and imaged.
Further: the calculation formula in the step c is as follows:
wherein c=3×10 8 m/s, τ is a time constant related to wavelength, j=1, 2,...
Further: the accumulated formula in step d is:
wherein E is S (x, t) is a time matrix t N1×N2×N Electric field corresponding to each element of I k (Z) is an electric field matrix.
Wherein, considering the normal incidence of electromagnetic waves to the trunk surface, the electric field can be written in the form of E (x) = (0; u (x)), with boundary conditions of
According to the formula:
Curl curl E(x)＝-ΔE(x)+grad div E(x)
a simplified wave equation for maxwell's equations can be derived as follows:
a schematic of the propagation of electromagnetic waves inside a tree is shown in fig. 3. The structural block diagram of the tree internal defect imaging device is shown in fig. 1. The main control processor is the core of the whole system, firstly, when the main control processor controls, a control circuit is required to generate a continuous signal or a synchronous pulse signal and a device acquisition signal, the signal is transmitted into the tree through a transmitting antenna of the electromagnetic wave transmitter, and when the signal is subjected to targets with different dielectric constants, scattering is formed at an interface, so that an echo signal is formed. The equipment acquisition signal generated by the time sequence control circuit controls the data sampling circuit to acquire the signal at the receiving antenna, the signal is sent to the signal processing system through the main control processor to be amplified, filtered and the like, and the imaging algorithm is added in the signal processing system, so that the acquired signal can be imaged and displayed on the equipment display through the image display system.
The working principle of inverting the internal defects of the tree is as follows: n transmitters and N receivers are uniformly arranged on the circumference of the tree, each transmitter of the array emits an electromagnetic pulse in one acquisition period, and each receiver receives an Ascan signal. After the transmission and the reception are completed, the imaging area to be performed is subjected to grid division, as shown in fig. 2, and electric field superposition calculation is performed on each sampling point on the grid according to an algorithm, and before summing the points on the grid, corresponding phase shift is required to be calculated on the received signal. After the reconstruction of each point of the grid is completed, the circulation is ended.
The present embodiment is only exemplary of the present patent, and does not limit the scope of protection thereof, and those skilled in the art may also change the part thereof, so long as the spirit of the present patent is not exceeded, and the present patent is within the scope of protection thereof.
Claims (3)
1. An imaging algorithm for detecting data of defects in a tree, comprising the steps of:
step a, equipment arrangement; uniformly placing N transmitters and N receivers on the circumference of the tree, wherein each transmitter of the array transmits an electromagnetic pulse in one acquisition period, and each receiver receives an Ascan signal;
step b, dividing grids; taking the center of the air area as the center of a circle, taking the distance from the receiver to the center of the circle as the radius, and making an inscribed regular quadrangle of the circle to obtain vertex coordinates (x 1, y 1), (x 2, y 2) of the inscribed regular quadrangle, wherein the side length of the inscribed quadrangle divides the whole area according to a certain step to obtain N1×N2 coordinate points as sampling points;
step c, respectively calculating the sum of the distances from each sampling point to the transmitter and the receiver to obtain a three-dimensional matrix D N1×N2×N Calculating the time matrix t of the signal sent by the transmitter reaching the sampling point and returning to the receiver by using the formula N1×N2×N ；
Step d, a linear interpolation method is applied, and a time matrix t is found from the N groups of data obtained in the step 2 N1×N2×N The electric field E corresponding to each element S (x, t) applying an electric field E S (x, t) accumulating the electric field values obtained by N sensors according to an accumulation formula to obtain an electric field matrix I k (Z)；
Step e, calculating to obtain an electric field matrix I aiming at each sampling point k (Z) N1×N2 The method is expressed in a color cloud picture form, and the area with the bright spots in the picture is the internal defect of the standing tree, so that the internal defect of the standing tree is detected and imaged.
2. An imaging algorithm for tree internal defect detection data according to claim 1, wherein: the calculation formula in the step c is as follows:
wherein c=3×10 8 m/s, τ is a time constant related to wavelength, j=1, 2,...
3. An imaging algorithm for tree internal defect detection data according to claim 1, wherein: the accumulation formula in the step d is as follows:
wherein E is S (x, t) is a time matrix t N1×N2×N Electric field corresponding to each element of I k (Z) is an electric field matrix.
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| CN115451861B (en) * | 2022-08-15 | 2023-09-01 | 中国水利水电科学研究院 | Nondestructive testing device and method for accurately obtaining areas of standing timber edges |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5841288A (en) * | 1996-02-12 | 1998-11-24 | Microwave Imaging System Technologies, Inc. | Two-dimensional microwave imaging apparatus and methods |
| WO2011047426A1 (en) * | 2009-10-21 | 2011-04-28 | J I Peston Pty Ltd | Wide area detection of insects using reflected microwaves |
| CN108732125A (en) * | 2018-06-05 | 2018-11-02 | 中国电子科技集团公司第四十研究所 | A kind of Terahertz material internal defect detection method based on gaussian iteration algorithm |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU4959400A (en) * | 1999-05-27 | 2000-12-18 | New Zealand Forest Research Institute Limited | Method for imaging logs or stems and apparatus |
| US20110188715A1 (en) * | 2010-02-01 | 2011-08-04 | Microsoft Corporation | Automatic Identification of Image Features |
| CN106405061B (en) * | 2016-09-22 | 2018-09-04 | 北京林业大学 | A kind of wooden body internal abnormality lossless detection system based on radar wave |
| CN107402257B (en) * | 2017-08-14 | 2019-11-08 | 浙江农林大学 | Timber radial longitudinal section defect imaging method based on path packet interpolation method |
| CN109900789B (en) * | 2019-03-22 | 2020-05-08 | 江南大学 | Imaging method for internal defects of longitudinal section of tree |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5841288A (en) * | 1996-02-12 | 1998-11-24 | Microwave Imaging System Technologies, Inc. | Two-dimensional microwave imaging apparatus and methods |
| WO2011047426A1 (en) * | 2009-10-21 | 2011-04-28 | J I Peston Pty Ltd | Wide area detection of insects using reflected microwaves |
| CN108732125A (en) * | 2018-06-05 | 2018-11-02 | 中国电子科技集团公司第四十研究所 | A kind of Terahertz material internal defect detection method based on gaussian iteration algorithm |
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