WO2023240939A1

WO2023240939A1 - Tree inspection method and apparatus and tree inspection device

Info

Publication number: WO2023240939A1
Application number: PCT/CN2022/135881
Authority: WO
Inventors: 王进; 沈泽昊; 施连敏; 谷飞; 李领治
Original assignee: 苏州大学
Priority date: 2022-06-14
Filing date: 2022-12-01
Publication date: 2023-12-21
Also published as: CN115047075A

Abstract

A tree inspection method and apparatus and a tree inspection device, which belong to the technical field of tree protection. The method comprises: firstly, uniformly attaching, in a surrounding manner, N patch-type ultrasonic modules in a tree inspection device to the periphery of a tree to be inspected; and acquiring an ultrasonic propagation speed between every two of the N patch-type ultrasonic modules, and forming a propagation speed matrix V between the patch-type ultrasonic modules. When there is a defect inside a tree, an ultrasonic propagation speed is affected, and therefore an internal defect image of a tree to be inspected can be generated according to a propagation speed matrix V between patch-type ultrasonic modules. By means of the method, the internal condition of a tree can be accurately measured; and patch-type ultrasonic modules have a low cost, and also do not cause damage to the tree itself.

Description

A tree detection method, device and tree detection equipment

This application requests the priority of the Chinese patent application submitted to the China Patent Office on June 14, 2022, with the application number 202210667854.X and the invention title "A tree detection method, device and tree detection equipment", and its entire content incorporated herein by reference.

Technical field

The present invention relates to the technical field of tree protection, and in particular to a tree detection method, device and tree detection equipment.

Background technique

As one of the four basic materials, wood has a wide range of uses in people's daily lives and has high economic value. At the same time, trees, as cultural carriers, also have ornamental and cultural value. Among them, precious trees have a special history. It has commemorative significance or scientific research value, so it is very necessary to detect the defect rate of wood. The defect rate refers to the degree of defects within the wood. By detecting the defect rate of wood, the immediate state of the wood can be understood.

Common methods for detecting internal defects of trees in the prior art include electromagnetic method, nuclear method and mechanical method. Among them, the electromagnetic method is based on the principle that electromagnetic waves will produce reflected waves of different amplitudes when passing through media with different dielectric constants. The differences in the amplitudes of the detected reflected waves are used to detect defects inside the trees. However, this detection method The required equipment is relatively expensive, the detection cost is high, and it is not suitable for widespread application; the nuclear method has many ways to detect internal defects in wood. One of the ways is to use neutron scanning imaging to measure the density changes of trees, which has high detection accuracy. Advantages, but also its testing equipment is expensive and very inconvenient to carry, which is not conducive to wide application; the mechanical method is to drill holes in wood. According to the principle that wood with different densities will produce different resistances when drilling, through comparison resistance to obtain the internal conditions of the wood, but this method has low measurement accuracy and can cause damage to the tree itself.

Contents of the invention

The purpose of the present invention is to provide a tree detection method, device and tree detection equipment, which can more accurately measure the internal conditions of the tree without damaging the tree itself, and at a low cost.

In order to solve the above technical problems, the present invention provides a tree detection method, which is applied to the processor in the tree detection equipment. The tree detection device also includes N chip-type ultrasonic modules, and N chip-type ultrasonic modules. Evenly surrounding the tree to be tested, it is used to emit and receive ultrasonic waves. N is an integer not less than 2. The tree detection method includes:

Obtain the ultrasonic propagation speed v _i,j between the N chip-type ultrasonic modules. v _i,j represents the difference between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module. The ultrasonic wave propagation speed between , i and j are both positive integers not greater than N;

According to all v _i,j, the propagation velocity matrix V between the patch ultrasonic modules is obtained;

The internal defect image of the tree to be tested is obtained according to the propagation velocity matrix V.

Preferably, the ultrasonic propagation velocity v _{i,j between N chip-type ultrasonic modules is obtained, and} the propagation velocity matrix V between the chip-type ultrasonic modules is obtained based on all vi _,j , including:

Obtain the circumference γ of the tree to be tested;

The straight-line distance d _i,j from the i-th chip-type ultrasonic module to the j-th chip-type ultrasonic module is calculated based on the perimeter γ;

The distance matrix D between the chip-type ultrasonic modules is formed according to all di _,j ;

Control the i-th chip-type ultrasonic module to emit ultrasonic waves every preset time and record the time t _i,j when the j-th chip-type ultrasonic module receives the ultrasonic wave, forming a gap between the chip-type ultrasonic modules. The propagation time matrix T;

The ultrasonic propagation speed v _i,j between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module is calculated according to the di _{,j and} the ti _,j . According to all The vi _,j constitute the propagation velocity matrix V between the patch-type ultrasonic modules.

Preferably, after forming the propagation velocity matrix V between the patch-type ultrasonic modules, it also includes:

Obtain the time error o _i of the respective positions of the N chip-type ultrasonic modules, o _i represents the time error of the position of the i-th chip-type ultrasonic module, and form a time error matrix O;

The propagation velocity matrix V is processed to eliminate time errors according to the time error matrix O, and the propagation velocity matrix V' after eliminating the time error is obtained;

Obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V includes:

The internal defect image of the tree to be tested is obtained according to the propagation velocity matrix V' after eliminating the time error.

Preferably, the time error o _i of each of the N chip-type ultrasonic modules is obtained, o _i represents the time error at the i-th chip-type ultrasonic module, and forms a time error matrix O, including:

Obtain the N _vi,j of adjacent chip-type ultrasonic modules;

Determine the d _i,j and the t i, _j corresponding to the above v _i,j as healthy ultrasound data;

Substitute all the healthy ultrasound data into the ultrasonic tangential velocity relationship to form a system of superlinear equations, and use the least squares method to solve the superlinear equations to obtain the time error matrix O;

The ultrasonic tangential velocity relationship is:

Where, di _,j is the distance between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module; d _r,s is the distance between the r-th chip-type ultrasonic module and the j-th chip-type ultrasonic module. The distance between s said patch-type ultrasonic modules;

Among them, θ _i,j is the tangential arc between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module, and k is the speed offset coefficient;

Among them, θ _r,s is the tangential arc between the r-th chip-type ultrasonic module and the s-th chip-type ultrasonic module, neither r nor s is greater than N, and k is the speed offset. Coefficient; o _i is the time error at the i-th patch ultrasonic module; o _j is the time error at the j-th patch ultrasonic module; o _r is the r-th patch ultrasonic module The time error at the module; o _s is the time error at the sth patch-type ultrasonic module.

Preferably, after obtaining the N _vi,j of adjacent chip-type ultrasonic modules, the method further includes:

Sort the v _i,j in the propagation velocity matrix V from large to small to obtain the first N vi _,j .

Preferably, after obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V', the method further includes:

Determine the defect rate of the tree to be tested based on the internal defect image;

Obtain the location information of the tree to be measured;

Upload the location information and defect rate of the trees to be tested to the network map system, and display the defect rate of the trees to be tested on the corresponding location mark on the map.

Preferably, after uploading the location information and defect rate of the tree to be tested to the network map system, and displaying the defect rate of the tree to be tested at the corresponding location mark on the map, the method further includes:

It is detected in real time whether the defect rate of the trees to be tested is lower than a threshold, and if so, the trees to be tested whose defect rate is lower than the threshold are marked on the map.

Preferably, obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V includes:

Divide the tree cross-section to be measured into a preset number of grids;

According to the distance and velocity between the straight line where the two patch-type ultrasonic modules are located and the pith center of the tree corresponding to each vi _,j in the propagation velocity matrix V, a cross-section of the tree to be measured is determined. In the influence range area, the speed of v _i,j is negatively correlated with the influence range area;

The grid corresponding to the influence range area of each v _i,j is assigned the speed value of v _i,j . When the grid is covered by multiple influence areas determined by v _i,j , the grid is Assign the value to the average value of multiple v _i,j ;

The grid whose assigned value is lower than the preset value is set as a defect grid, and an internal defect image of the tree to be tested is generated.

In order to solve the above technical problems, the present invention also provides a tree detection device, including:

memory for storing computer programs and calibration coefficients;

A processor, configured to execute the computer program to implement the steps of the above tree detection method.

In order to solve the above technical problems, the present invention also provides a tree detection equipment, which is characterized in that it includes N patch-type ultrasonic modules and the tree detection device as described above.

The invention provides a tree detection method, device and tree detection equipment, which are used in a processor in a tree detection equipment to evenly surround and fit N patch-type ultrasonic modules around the tree to be tested, and obtain N patches The ultrasonic propagation velocity between two ultrasonic modules forms the propagation velocity matrix V between the patch ultrasonic modules. Since there are defects inside the trees, the propagation speed of ultrasonic waves will be affected, so it can be based on the patch ultrasonic module. The propagation velocity matrix V between modules generates the internal defect image of the tree to be measured. It can be seen that in this way, the internal conditions of the tree can be measured more accurately, and the cost of the patch-type ultrasonic module is low, and it will not cause damage to the tree. itself causes damage.

Description of the drawings

In order to explain the technical solutions in the embodiments of the present invention more clearly, the prior art and the drawings needed to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the drawings of the present invention. Embodiments, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without exerting creative efforts.

Figure 1 is a flow chart of a tree detection method provided by the present invention;

Figure 2 is a schematic diagram of ultrasonic velocity distribution provided by the present invention;

Figure 3 is a schematic structural diagram of a tree detection device provided by the present invention.

Detailed ways

The core of the present invention is to provide a tree detection method, device and tree detection equipment, which can more accurately measure the internal conditions of the tree without damaging the tree itself, and at a lower cost.

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

Please refer to Figure 1. Figure 1 is a flow chart of a tree detection method provided by the present invention, which is applied to a processor in a tree detection equipment. The tree detection device also includes N chip-type ultrasonic modules, and N chip-type ultrasonic modules. The module is evenly wrapped around the tree to be tested and used to emit and receive ultrasonic waves. N is an integer not less than 2. The tree detection method includes:

S11: Obtain the ultrasonic propagation velocity v _i,j between N chip-type ultrasonic modules. v _i,j represents the ultrasonic propagation between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module. Speed, i and j are both positive integers not greater than N;

S12: Obtain the propagation velocity matrix V between chip ultrasonic modules based on all v _i,j ;

S13: Obtain the internal defect image of the tree to be tested according to the propagation velocity matrix V.

Considering that in the existing technology, most detection methods for the internal conditions of trees have problems such as high cost of detection instruments, difficulty in portability, and difficulty in deployment. Some detection methods can also cause damage to the trees themselves, so a lower-cost method is needed. , a tree detection method that is easy to carry and widely used, has high accuracy and does not damage trees.

In order to solve this problem, in this embodiment, non-destructive testing of trees is completed based on ultrasonic waves. Specifically, N patch-type ultrasonic modules are installed around the trees, and each patch-type ultrasonic module can emit And receive ultrasonic waves. When there are defects inside the tree, diffraction will occur when the ultrasonic waves encounter defects when propagating inside the tree, resulting in an increase in propagation time. Affected by the size of the defects inside the tree and the angle of ultrasonic wave propagation, the propagation time increases. The quantity will also be affected, so this scheme obtains the ultrasonic propagation velocity v _i,j between N chip-type ultrasonic modules, and obtains the propagation velocity matrix between chip-type ultrasonic modules based on all v _i,j V, where v _i,j represents the ultrasonic propagation speed between the i-th patch ultrasonic module and the j-th patch ultrasonic module, including all ultrasonic propagation from v _1,1 to v _N,N Velocity, the propagation velocity matrix V is defined as follows:

Then according to the propagation angle between two patch-type ultrasonic modules and the corresponding ultrasonic propagation speed, the defect image inside the tree to be tested can be obtained.

In addition, under normal circumstances, 6, 8, 10, or 12 chip-type ultrasonic modules are installed in tree detection equipment. The greater the number of chip-type ultrasonic modules, the more accurate the tree detection results will be. This application uses chip-type ultrasonic modules. The number of ultrasonic modules is not particularly limited and can be set according to actual conditions.

In addition, in a specific embodiment, the model of the ultrasonic module is AJ-SR04K, the accuracy is 10 μs, the model of the ultrasonic probe used is JS1640F2-W, and the operating frequency is 40 kHz.

In summary, the present invention provides a tree detection method, which is applied to the processor in the tree detection equipment. N chip-type ultrasonic modules are evenly placed around the tree to be measured, and N chip-type ultrasonic modules are obtained. The propagation speed of ultrasonic waves between two pairs constitutes the propagation velocity matrix V between chip-type ultrasonic modules. Since there are defects inside the trees, the propagation speed of ultrasonic waves will be affected, so it can be determined according to the distance between chip-type ultrasonic modules. The propagation velocity matrix V generates the internal defect image of the tree to be measured. It can be seen that in this way, the internal conditions of the tree can be measured more accurately, and the cost of the patch-type ultrasonic module is low, and it will not cause damage to the tree itself. .

Based on the above embodiments:

As a preferred embodiment, obtain the ultrasonic propagation velocity vi _{,j between N chip-type ultrasonic modules.} According to all _vi,j, obtain the propagation velocity matrix V between chip-type ultrasonic modules, including :

Get the perimeter γ of the tree to be measured;

Calculate the straight-line distance d _i,j from the i-th patch ultrasonic module to the j-th patch ultrasonic module based on the perimeter γ;

According to all d _{i, j,} the distance matrix D between the chip ultrasonic modules is formed;

Control the i-th chip-type ultrasonic module to emit ultrasonic waves every preset time and record the time t _i,j when the j-th chip-type ultrasonic module receives the ultrasonic wave, forming a propagation time matrix T between chip-type ultrasonic modules;

The ultrasonic propagation speed vi, _j between the i-th patch ultrasonic module and the j-th patch ultrasonic module is calculated based on di _,j and ti _{,j, and} a patch is formed based on all vi _,j Equation is the propagation velocity matrix V between ultrasonic modules.

In this embodiment, considering that the ultrasonic wave propagation speed between two chip-type ultrasonic modules can be calculated based on the distance between two chip-type ultrasonic modules and the ultrasonic wave propagation time, the perimeter of the tree to be measured is first obtained. γ. Since each patch-type ultrasonic module is evenly distributed around the tree to be measured, the distance between any two patch-type ultrasonic modules can be calculated according to the distance formula. Specifically, the distance formula is:

d _i,j represents the straight-line distance from the i-th patch ultrasonic module to the j-th patch ultrasonic module, and the distance matrix D is obtained based on all d _i,j . The distance matrix D is defined as follows:

Then use the acquisition subsystem to obtain the time t _i,j required to propagate ultrasonic waves between two chip-type ultrasonic modules. Specifically, considering that multiple chip-type ultrasonic modules collecting data at the same time may produce large data noise , so this program controls one chip-type ultrasonic module to emit ultrasonic waves every preset time, and another chip-type ultrasonic module to receive the ultrasonic wave and record the interval time until the ultrasonic wave propagation time data between all chip-type ultrasonic modules is After all are recorded, all ti _{, j} constitute the propagation time matrix T. The propagation time matrix T is defined as follows:

According to the distance matrix D and the propagation time matrix T, the propagation speed matrix V can be obtained. Specifically, the propagation speed matrix V is defined as follows:

As a preferred embodiment, after forming the propagation velocity matrix V between patch ultrasonic modules, it also includes:

Obtain the time error o _i of each position of N chip-type ultrasonic modules, o _i represents the time error of the position of the i-th chip-type ultrasonic module, and form a time error matrix O;

According to the time error matrix O, the propagation velocity matrix V is processed to eliminate the time error, and the propagation velocity matrix V' after eliminating the time error is obtained;

Obtain the internal defect image of the tree to be tested according to the propagation velocity matrix V, including:

According to the propagation velocity matrix V’ after eliminating the time error, the internal defect image of the tree to be tested is obtained.

In this embodiment, in order not to cause damage to the trees themselves, the intrusive sensors commonly used in the prior art are replaced with patch-type ultrasonic modules. However, due to reasons such as bark, paint, and cracks on the bark surface of the trees, the The patch-type ultrasonic module cannot fit closely with the trees to be tested, so additional data noise will be generated, which will increase the propagation time of ultrasonic waves and reduce the accuracy of defect detection. Therefore, in actual use, it should also be eliminated The time error caused by the inability of the chip-type ultrasonic module to fit closely with the bark improves the accuracy of detecting the internal conditions of the tree to be measured. Specifically, the time error o _i of the position of each chip-type ultrasonic module is obtained, in When calculating the ultrasonic propagation speed between two chip-type ultrasonic modules, the time error of the two ultrasonic modules can be eliminated by subtracting the time error of each of the two ultrasonic modules from the collected ultrasonic propagation time between the two chip-type ultrasonic modules. The final ultrasonic propagation velocity is obtained to obtain the propagation velocity matrix V' after eliminating the time error, and then the internal defect image of the tree to be tested is obtained based on the propagation velocity matrix V' after the time error is eliminated, which improves the accuracy of the internal defect image.

As a preferred embodiment, obtain the time error o _i of each of N chip-type ultrasonic modules, o _i represents the time error at the i-th chip-type ultrasonic module, and form a time error matrix O, including:

Obtain N vi _,j of adjacent chip-type ultrasonic modules;

Determine d _i,j and t i, _j corresponding to the above v i _,j as healthy ultrasound data;

Substitute all healthy ultrasound data into the ultrasonic tangential velocity relationship to form a system of superlinear equations, and use the least squares method to solve the superlinear equations to obtain the time error matrix O;

The relationship between ultrasonic tangential velocity is:

Among them, di _,j is the distance between the i-th chip ultrasonic module and the j-th chip ultrasonic module; d _r,s is the distance between the r-th chip ultrasonic module and the s-th chip ultrasonic module. distance between modules;

Among them, θ _i,j is the tangential arc between the i-th patch ultrasonic module and the j-th patch ultrasonic module, and k is the speed bias coefficient;

Among them, θ _r,s is the tangential arc between the r-th patch ultrasonic module and the s-th patch ultrasonic module, neither r nor s is greater than N, k is the speed bias coefficient; o _i is the The time error at the i chip-type ultrasonic module; o _j is the time error at the j-th chip-type ultrasonic module; o _r is the time error at the r-th chip-type ultrasonic module; o _s is the s-th chip ultrasonic module Time error at the chip-type ultrasonic module.

In this embodiment, as the tangential angle changes, the interference caused by the bark remains within a relatively small range, so we assume that the time error caused by each patch-type ultrasonic module not tightly fitting the tree is Fixed, according to the tangential velocity radial velocity relationship V _T ≈ V _R (1-kθ ² ), when there are no defects inside the tree, the tangential velocity V _T and the radial velocity V _R should satisfy the above relationship, where k is the velocity bias coefficient. k is determined by the characteristics of the tree itself and can be obtained through experimental measurement. Since the healthy ultrasonic data selected in this embodiment are all ultrasonic data that are not affected by the internal defects of the tree, these ultrasonic data should It is only affected by the time error caused by not tightly adhering to the bark. Therefore, after eliminating the time error, the propagation speed of the new ultrasonic wave should satisfy the above relationship, from which the ultrasonic tangential velocity relationship can be obtained:

Among them, o _i , o _j , o _r , and _os are respectively the time errors of the positions of the i-th, j-th, r-th, and s-th patch ultrasonic modules. After simplifying the relationship It can be obtained:d _r,s c _i,j o _i +d _r,s c _i,j o _j -d _i,j c _r,s o _r -d _i,j c _r,s o _s =d _{r, s} c _i,j t _i,j -d _i,j c _r,s t _r,s ,

Among them, k is the above-mentioned tree characteristic coefficient, θ _i,j is the tangential arc between the i-th patch ultrasonic module and the j-th patch ultrasonic module. Substitute the determined healthy ultrasonic data into the above simplified Relational expressions, multiple sets of relational expressions are obtained to form a superlinear equation:

Using the least squares method to solve the superlinear equation, the time error of the position of each patch ultrasonic module can be obtained. where a is generated by superposition calculation of d and c.

Specifically, the time correction algorithm based on the least squares method can be used to solve the superlinear equation. The time correction algorithm based on the least squares method is specifically:

Input C, T, L, γ, n, ι, where C is the ratio of the ultrasonic speed of the healthy tangential path to the radial path speed;

Output T, D;

1) Initialize A=0 _ι×n , B=0 _ι×1 , D=0 _n×n , S=0 _ι×(n+1) , e=l _1,1 , f=l _1,2 , where , e and l are used to calculate the coefficient matrix, due to the formula

It is necessary to calculate every two paths. For the convenience of calculation, the first ultrasonic path is fixed here, where e and f are the subscripts of the first ultrasonic path;

2)for i＝1 to n do

3)for j＝1 to n do

4)

5)for i＝1 toιdo

6) g=l _i,1 ;

7)h= _li,2 ;

8)a _i,e =a _i,e +d _g,h c _e,f ;

9)a _i,f =a _i,f +d _g,h c _e,f ;

10)a _i,g =a _i,g -d _e,f c _g,h ;

11)a _i,h =a _i,h -d _e,f c _g,h ;

12)b _i =d _g,h c _e,f t _e,f -d _e,f c _g,h t _g,h ;

13)for i＝1 toido;

14)forj＝1 to ndo;

15)s _i,j =a _i,j ;

16)s _i,13 = b _i ;

17) Use the least squares method to solve the system of superlinear equations S and store the results in the matrix O;

18) fori＝1 to ndo;

19)forj＝1 to ndo;

20)t _i,j =t _i,j -o _i -o _i ;

21) Return matrix T and matrix D;

Among them, the generation process of the ratio matrices A and B of the ultrasonic velocity of the healthy tangential path to the radial path velocity is described in lines 5-12, and it is cycled i times. Lines 13-16 loop ιn times, and the complexity of line 17 is O(ι2n). Lines 18-20 are looped n2 times. Therefore, the above complexity is O(ι2n).

As a preferred embodiment, after obtaining N vi _,j of adjacent patch ultrasonic modules, it also includes:

Sort the v _i,j in the propagation velocity matrix V from large to small, and obtain the first N v _i,j .

In this embodiment, in order to improve the accuracy of the time error, it is necessary to increase the amount of health data. Therefore, in addition to determining the data between adjacent chip-type ultrasonic modules as health data, it is also considered that when the ultrasonic wave propagation is affected by defects, the ultrasonic wave The propagation speed will slow down. Therefore, theoretically, the fastest ultrasonic propagation speed data in the propagation speed matrix should not be affected by defects. Therefore, this solution also sorts the v _{i, j} in the propagation speed matrix V from large to small, and The first N _vi,j are also determined as health data, thereby increasing the data volume of health data and further increasing the accuracy of the time error.

As a preferred embodiment, after obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V’, it also includes:

Determine the defect rate of the tree to be tested based on internal defect images;

Obtain the location information of the trees to be measured;

Upload the location information and defect rate of the trees to be tested to the network map system, and display the defect rate of the trees to be tested on the corresponding location marks on the map.

In this embodiment, after obtaining the internal defect image of the tree to be tested, the result will be uploaded to a subsystem implemented in the form of a website. According to the internal defect image, the defect rate of the tree to be tested can be obtained. As a specific embodiment , The network map system here can be based on the Spring and Vue frameworks, based on Baidu Map, and display the defect rate of the trees to be tested in real time on the map.

In addition, different icons can also be used on the map to represent trees with different defect rates, allowing users to more intuitively observe the defects of each tree.

As a preferred embodiment, after uploading the location information and defect rate of the tree to be tested to the network map system, and displaying the defect rate of the tree to be tested at the corresponding location mark on the map, it also includes:

It is detected in real time whether the defect rate of the trees to be tested is lower than the threshold. If so, the trees to be tested whose defect rate is lower than the threshold are marked on the map.

In this embodiment, considering that the purpose of defect detection on trees is to understand the internal conditions of the trees so as to take protective measures for the defective trees, this solution marks the defect rate of the trees to be tested on the map system and detects them in real time. Whether the defect rate of trees is lower than a threshold, when it is lower than a certain threshold, trees with a defect rate lower than the threshold will be marked on the map to facilitate subsequent protection measures.

As a preferred embodiment, obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V includes:

Divide the tree cross-section to be measured into a preset number of grids;

According to the distance and speed between the straight line of the two patch-type ultrasonic modules corresponding to each v _{i, j} in the propagation velocity matrix V and the pith center of the tree, an influence range area is determined for it in the cross section of the tree to be measured, v _{i , the speed of j} is negatively correlated with the area of influence;

Assign the grid value corresponding to the influence range area of each v _i,j to the speed value of v _i, j. When there is a grid covered by multiple influence areas determined by v _i,j , assign the grid value to multiple The average value of v _i,j ;

Set the grid with a value lower than the preset value as a defect grid to generate an internal defect image of the tree to be tested.

In this embodiment, in order to obtain the defect image inside the tree to be tested, the cross section of the tree is first gridded and divided into a preset number of grids, and then a value is determined for each v _{i, j} based on its velocity value. For the scope of influence, please refer to Figure 2. Figure 2 is a schematic diagram of an ultrasonic velocity distribution provided by the present invention. Between each two patch-type ultrasonic modules, one is determined based on the ultrasonic propagation speed between the two patch-type ultrasonic modules. The scope of influence, as shown in Figure 2, is larger on the side closer to the center of the marrow and smaller on the side farther away from the center of the marrow. Specifically, when determining the scope of influence of v _i,j , the formula w+ σ(δ-v)+ξα determines the width of the influence range, where w is one-eighth of the diameter of the tree,

δ is the maximum value in the velocity matrix V,

is the minimum value in the velocity matrix V. Considering that the part close to the center of the pith has a larger influence range than the part far from the center of the pith, ξα is also added, where ξ is the control coefficient and α is a Boolean value far away from or close to the center of the pith. When When it is close to the center of the marrow, α takes 1, and when it is far away from the center of the marrow, α takes -1. For example, when the k-th grid is in the influence range determined by the i-th patch ultrasonic module and the j-th patch ultrasonic module. When it is close to the medullary center side, α is set to 1 at this time, and then it is judged whether the straight-line distance between the i-th patch ultrasonic module and the j-th patch ultrasonic module and the length of the k-th grid is less than or equal to w+ σ(δ-v)+ξα, if so, it is determined that the k-th grid is affected by the influence range determined by the i-th patch ultrasonic module and the j-th patch ultrasonic module, so the k-th grid The value is assigned to the speed value of v _i,j . Similarly, when the k-th grid is affected by the influence range determined by multiple v _i,j , the k-th grid is assigned the speed of multiple v _i,j After completing the assignment of values to all grids in this way, the grids whose assignments are lower than the preset values are set as defective grids. Finally, the grids are convolved and transposed to improve the obtained results. Accuracy of defect images.

Input: T, D, U, n, m, w, σ, δ, ξ, where U is an n*n*m dimensional matrix, and the elements ui,j,k of U are the k-th unit and the i-th sensor The length intercepted by the straight line formed by the jth sensor;

Output:

1) Initialization X=0 _m×1 ;

2) δ is the maximum value in matrix V;

3)for k＝1 to m do;

4) Create an empty list Y;

5)for i＝1 to n do;

6)for j＝1 to n do;

7)

8)

9)

10)

11)

12) Assume

is the distance from the pith center to the k-th grid cell;

13)if

14)α=1;

15)else;

16)α=-1;

17)v＝d _i,j /t _i,j ;

18) Assume

is the length of the straight line between the i-th sensor and the j-th sensor in the k-th grid unit;

19)if

20) Add v to Y;

twenty one)

22) Return matrix X;

In the above algorithm, lines 3-20 are looped n ² m times, and the complexity of line 12 is o(1). Therefore, the complexity of TPSI is o(n ² m). Compared with TRRI, the time complexity of the above algorithm is smaller.

The present invention also provides a tree detection device. Please refer to Figure 3. Figure 3 is a schematic structural diagram of a tree detection device provided by the present invention. The device includes:

Memory 31 for storing computer programs and calibration coefficients;

The processor 32 is configured to execute a computer program to implement the steps of the above tree detection method.

For an introduction to the tree detection device provided by the present invention, please refer to the above method embodiments, and the present invention will not be described again here.

The invention also provides a tree detection equipment, which includes N chip-type ultrasonic modules and the above-mentioned tree detection device.

For an introduction to the tree detection equipment provided by the present invention, please refer to the above method embodiments, and the present invention will not be described again here.

It should also be noted that in this specification, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that these entities or operations There is no such actual relationship or sequence between operations. Furthermore, the terms "comprises," "comprises," or any other variation thereof are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but also those not expressly listed other elements, or elements inherent to the process, method, article or equipment. Without further limitation, an element qualified by the statement "comprises a..." does not exclude the presence of additional identical elements in the process, method, article, or device that includes the element.

The above description of the disclosed embodiments enables those skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be practiced in other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

A tree detection method, characterized in that it is applied to a processor in a tree detection device, and the tree detection device further includes N chip-type ultrasonic modules, and the N chip-type ultrasonic modules are evenly surrounded and attached to each other. Measuring the surroundings of trees for emitting and receiving ultrasonic waves, N is an integer not less than 2. The tree detection method includes:

Obtain the ultrasonic propagation speed v i,j between the N chip-type ultrasonic modules. v i,j represents the difference between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module. The ultrasonic wave propagation speed between , i and j are both positive integers not greater than N;

According to all v i,j, the propagation velocity matrix V between the patch ultrasonic modules is obtained;

The internal defect image of the tree to be tested is obtained according to the propagation velocity matrix V.
The tree detection method according to claim 1, characterized in that, obtaining the ultrasonic propagation speed v i,j between pairs of N said patch-type ultrasonic modules, and obtaining the said patch-type ultrasonic module based on all vi ,j The propagation velocity matrix V between ultrasonic modules includes:

Obtain the circumference γ of the tree to be tested;

The straight-line distance d i,j from the i-th chip-type ultrasonic module to the j-th chip-type ultrasonic module is calculated based on the perimeter γ;

The distance matrix D between the chip-type ultrasonic modules is formed according to all di ,j ;

Control the i-th chip-type ultrasonic module to emit ultrasonic waves every preset time and record the time t i,j when the j-th chip-type ultrasonic module receives the ultrasonic wave, forming a gap between the chip-type ultrasonic modules. The propagation time matrix T;

The ultrasonic propagation speed v i,j between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module is calculated according to the di ,j and the ti ,j . According to all The vi ,j constitute the propagation velocity matrix V between the patch-type ultrasonic modules.
The tree detection method according to claim 2, characterized in that after forming the propagation velocity matrix V between the patch-type ultrasonic modules, it also includes:

Obtain the time error o i of the respective positions of the N chip-type ultrasonic modules, o i represents the time error of the position of the i-th chip-type ultrasonic module, and form a time error matrix O;

Perform time error elimination processing on the propagation velocity matrix V according to the time error matrix O to obtain the propagation velocity matrix V' after eliminating the time error;

Obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V includes:

The internal defect image of the tree to be tested is obtained according to the propagation velocity matrix V' after eliminating the time error.
The tree detection method according to claim 3, characterized in that the time error o i of each of the N chip-type ultrasonic modules is obtained, o i represents the time error at the i-th chip-type ultrasonic module, And form the time error matrix O, including:

Obtain the N vi,j of adjacent chip-type ultrasonic modules;

Determine the d i,j and the t i, j corresponding to the above v i,j as healthy ultrasound data;

Substitute all the healthy ultrasound data into the ultrasonic tangential velocity relationship to form a system of superlinear equations, and use the least squares method to solve the superlinear equations to obtain the time error matrix O;

The ultrasonic tangential velocity relationship is:
Where, di ,j is the distance between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module; d r,s is the distance between the r-th chip-type ultrasonic module and the j-th chip-type ultrasonic module. The distance between s said patch-type ultrasonic modules;
Among them, θ i,j is the tangential arc between the i-th chip-type ultrasonic module and the j-th chip-type ultrasonic module, and k is the speed offset coefficient;
Among them, θ r,s is the tangential arc between the r-th chip-type ultrasonic module and the s-th chip-type ultrasonic module, neither r nor s is greater than N, and k is the speed offset. Coefficient; o i is the time error at the i-th patch ultrasonic module; o j is the time error at the j-th patch ultrasonic module; o r is the r-th patch ultrasonic module The time error at the module; o s is the time error at the sth patch-type ultrasonic module.
The tree detection method according to claim 4, characterized in that after obtaining the N vi,j of adjacent patch-type ultrasonic modules, it further includes:

Sort the v i,j in the propagation velocity matrix V from large to small to obtain the first N vi ,j .
The tree detection method according to claim 1, characterized in that after obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V', it further includes:

Determine the defect rate of the tree to be tested based on the internal defect image;

Obtain the location information of the tree to be measured;

Upload the location information and defect rate of the trees to be tested to the network map system, and display the defect rate of the trees to be tested on the corresponding location mark on the map.
The tree detection method according to claim 6, characterized in that the location information and defect rate of the tree to be tested are uploaded to a network map system, and the defect rate of the tree to be tested is displayed on the corresponding position mark in the map. ,Also includes:

It is detected in real time whether the defect rate of the trees to be tested is lower than a threshold, and if so, the trees to be tested whose defect rate is lower than the threshold are marked on the map.
The tree detection method according to any one of claims 1 to 7, characterized in that obtaining the internal defect image of the tree to be tested according to the propagation velocity matrix V includes:

Divide the tree cross-section to be measured into a preset number of grids;

According to the distance and velocity between the straight line where the two patch-type ultrasonic modules are located and the pith center of the tree corresponding to each vi ,j in the propagation velocity matrix V, a cross-section of the tree to be measured is determined. In the influence range area, the speed of v i,j is negatively correlated with the influence range area;

The grid corresponding to the influence range area of each v i,j is assigned the speed value of v i,j . When the grid is covered by multiple influence areas determined by v i,j , the grid is Assign the value to the average value of multiple v i,j ;

The grid whose assigned value is lower than the preset value is set as a defect grid, and an internal defect image of the tree to be tested is generated.
A tree detection device, characterized by including:

memory for storing computer programs and calibration coefficients;

A processor, configured to execute the computer program to implement the steps of the tree detection method in any one of 1 to 8 above.
A tree detection equipment, characterized in that it includes N chip-type ultrasonic modules, and also includes the tree detection device as claimed in claim 9.