A method and system for optimizing array observation space based on cutterhead rotation sparsity

Abstract

The application provides an array observation space optimization method and system based on cutter head rotation sparsity, constructs an initial surface array, selects a target survey line, randomly selects a survey point in the initial surface array and removes it, obtains the position of the remaining survey points on the survey line in one rotation of the cutter head, calculates the position of other survey points on the survey line in each rotation, counts the coverage and coverage times, judges whether the position of all survey points on the survey line meets the full coverage evaluation index, if yes, removes the survey point in the survey point surface array and updates the survey point position, repeats the above steps until the coverage times of the survey point position is 0, the cycle is terminated, and the sparse position based on the full coverage evaluation is obtained, the above steps are repeated, the sparse result meeting the full coverage is expanded, the most sparse probe on a single survey line and a single ring is considered, and the best optimization result is obtained. The application can provide an important prerequisite guarantee for realizing fine detection.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of observation optimization, and particularly relates to an array observation space optimization method and system based on cutter head rotation sparsity. BACKGROUND

[0002] The statements in this section merely provide background information related to the application and do not necessarily constitute prior art.

[0003] As an important device for geological exploration, the tunnel boring machine has high application value. However, the observation space of the tunneling face is narrow at present, and the constraint of the mechanical structure leads to limited positions of the probes that can be arranged on the cutter head, so that the number of the probes carried by the cutter head is small and the distribution is sparse. How to determine appropriate observation parameters and obtain sufficient wave field information by using a small number of probes is the first problem to be solved.

[0004] However, the existing observation system design method mainly aims at the optimization of the ground observation system involved in oil and gas exploration, and generally divides the ground into rectangular grid points, and then sparsifies the large rectangular grid point array. However, the cutter head of the tunnel boring machine is generally circular and can rotate freely, which is different from the optimization problem of the ground observation system. There is no observation system evaluation index and design method for the sparse observation of a small number of probes of the cutter head of the tunnel boring machine. It is difficult to realize the sufficient acquisition of wave field information under the sparse observation condition of the cutter head. SUMMARY

[0005] In order to solve the above problems, the application provides an array observation space optimization method and system based on cutter head rotation sparsity. The application learns from the observation form of three-dimensional seismic exploration to obtain an initial surface array observation form, and uses the rotation form of the cutter head to construct a sparse observation data combination, thereby providing an important prerequisite guarantee for realizing fine detection.

[0006] According to some embodiments, the application adopts the following technical scheme:

[0007] An array observation space optimization method based on cutter head rotation sparsity, comprising the following steps:

[0008] (1) constructing an initial surface array;

[0009] (2) selecting a target survey line, randomly selecting a survey point in the initial surface array and removing it;

[0010] (3) rotating the cutter head for one revolution to obtain the positions of the remaining survey points on the survey line;

[0011] (4) calculating the positions of other measuring points on the measuring line in each rotation, counting the coverage and the number of coverages, and judging whether all measuring point positions on the measuring line satisfy the full coverage evaluation index, and if so, removing the measuring point from the measuring point surface array and updating the measuring point position in the surface array;

[0012] (5) repeating steps (2)-(4) until the number of coverages of the measuring point position is 0, and the cycle is terminated to obtain sparse positions based on the full coverage evaluation;

[0013] (6) repeating steps (2)-(5) to expand the sparse results that satisfy the full coverage, considering the most sparse probes on a single measuring line and a single circular ring, and obtaining the best optimization result.

[0014] As an optional implementation, in step (1), the specific process of constructing the initial surface array includes: determining the value range of the trace interval and the offset under the premise of satisfying the longitudinal and lateral resolution of the acoustic wave signal, determining the basic parameters of the observation system, and taking the radial surface array as the initial surface array.

[0015] As an optional implementation, in step (2), the specific process of selecting a target measuring line and randomly selecting a measuring point in the surface array for removal includes: considering the limitation of the mechanical structure on the actual cutter head, the radial initial surface array has a specified position where the probe cannot be arranged, defining the missing position in advance, randomly selecting a measuring point from the remaining measuring points as the first sparse removal position, and obtaining the probe distribution probe coding map.

[0016] As an optional implementation, in step (3), the specific process of obtaining the positions of the remaining measuring points on the measuring line after one rotation of the cutter head includes: rotating the cutter head for one revolution, labeling the probe position code after one revolution of the measuring line, and analyzing the distribution of the measuring points on the measuring line.

[0017] As an optional implementation, in step (4), the specific process of judging whether all measuring point positions on the measuring line satisfy the full coverage evaluation index includes: determining the number of coverages of different probe excitation data at different receiving probe positions, and if the number of coverages is greater than a set value, then all measuring point positions on the measuring line satisfy the full coverage evaluation index.

[0018] As an optional implementation, in step (6), the specific process of expanding the sparse results that satisfy the full coverage and considering the most sparse probes on a single measuring line and a single circular ring includes: taking the sparse distribution of adjacent probes on the measuring line and the circular ring as further constraint conditions, constructing a probe sparse evaluation parameter, and obtaining the probe sparse observation position with the maximum probe spacing in the preliminary optimization position.

[0019] As a further implementation, the probe sparse evaluation parameter is the ratio of the total number of removed probes to the total number of initial probes.

[0020] An array observation space optimization system based on cutter head rotation sparsity, comprising:

[0021] A surface array construction module configured to construct an initial surface array;

[0022] A selection module configured to select a target survey line, randomly select a survey point in the initial surface array and remove it;

[0023] A rotation module configured to obtain the position of the remaining survey points on the survey line in one rotation of the cutter head;

[0024] An update optimization module configured to calculate the position of other survey points on the survey line each time the cutter head rotates, count the coverage and the number of coverages, determine whether all survey point positions on the survey line meet the full coverage evaluation index, and if so, remove the survey point from the surface array and update the survey point position in the surface array;

[0025] A first loop module configured to repeat the execution of the above modules until the number of coverages of a survey point position is 0, and the loop is terminated to obtain sparse positions based on the full coverage evaluation;

[0026] A second loop module configured to repeat the execution of the above modules to expand the sparse results that meet the full coverage and consider the most sparse probes on a single survey line and on a single circular ring to obtain the best optimization result.

[0027] A computer readable storage medium having a plurality of instructions stored therein, the instructions being adapted to be loaded and executed by a processor of a terminal device to perform the steps in the method.

[0028] A terminal device comprising a processor and a computer readable storage medium, the processor being configured to implement instructions, and the computer readable storage medium being configured to store a plurality of instructions, the instructions being adapted to be loaded and executed by the processor to perform the steps in the method.

[0029] Compared with the prior art, the beneficial effects of the present application are:

[0030] The present application is based on cutter head rotation sparsity optimization and obtains an optimal distribution position of the probe in a sparse observation system, can realize full coverage of all positions in a small probe position distribution observation aperture, and realizes full observation of the wave field information in front of the tunnel boring machine face with a small number of survey points.

[0031] The present application is based on the equivalent initial surface array observation system sparsity method, realizes sparse observation of the probe, and determines the sparse observation position. By utilizing the characteristics of the cutter head rotation, the sparse observation data are combined to realize full observation of the wave field information.

[0032] In order to make the above objectives, characteristics and advantages of the present application more apparent, comprehensible and easier to be understood, the following preferred embodiments are specifically described in detail below, together with the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0033] The drawings constituting a part of this disclosure serve to provide a further understanding of the present application, and the illustrative embodiments of the present application and their description serve the purpose of explaining the present application, and do not constitute an improper limitation of the present application.

[0034] Figure 1a , Figure 1b is a radiation surface array observation form of the present application;

[0035] Figure 2a is a schematic diagram of line and point position coding;

[0036] Figure 2b is a schematic diagram of coverage;

[0037] Figure 3a is a schematic diagram of full coverage of line 1;

[0038] Figure 3b is a schematic diagram of full coverage evaluation effect;

[0039] Figure 4 is a schematic diagram of the flow of the present application;

[0040] Figure 5a , Figure 5b is a position distribution diagram of a constraint sparse 1st array probe of the present application;

[0041] Figure 6 is a distribution of a 6-line constraint sparse 1st probe of the present application;

[0042] Figure 7a is a 0-11th rotation coverage of the present application;

[0043] Figure 7b is a schematic diagram of coverage number statistics of line 1 of the present application;

[0044] Figure 8 is a sparse intensity optimization diagram;

[0045] Figure 9 a is a sparse probe position of a constraint sparse array;

[0046] Figure 9 b is a sparse probe coding of a constraint sparse array;

[0047] Figure 10 is a distribution of probes on different lines of a constraint sparse 17th array;

[0048] Figure 11 is a probe distribution in a random constraint sparse process;

[0049] Figure 12a 0-11 rotation coverage case;

[0050] Figure 12b Line 1 coverage count. DETAILED DESCRIPTION

[0051] The application will be further described below in connection with the drawings and examples.

[0052] It should be noted that the following detailed description is illustrative only and is intended to provide further description of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0053] It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, elements, components, and / or groups thereof, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof.

[0054] In combination with the three-dimensional seismic exploration on the ground and the form of the tunnel boring machine cutter, the selected observation form is optimized, and the initial surface array distribution form for realizing sufficient observation is finally determined.

[0055] In combination with the circular shape of the cutter and the feature that it can rotate, the radial observation form is selected as the initial surface array observation form. However, how to fully utilize the observation form to propose a suitable observation system evaluation index is a problem to be solved in this section. From the initial observation system form, it can be found that when all positions of the surface array exist probes, the sufficient observation of the geological information of the abnormal body can be realized, and when the observation points are defaulted, the problem of insufficient coverage degree at certain positions will exist, which will bring acquisition artifacts to the observation data and reduce the imaging quality. Therefore, the observation system evaluation index based on the full coverage of the detection target area is proposed in this embodiment, which can be expressed as: any point on the survey line has an excitation position and a receiving position, that is, the observation data of all excitation positions can be obtained. The observation system evaluation index of the full coverage of the target area is explained in the form of observation system coding in this embodiment. Therefore, in order to explain the observation system evaluation index, the representation method of the observation system needs to be determined to code the observation positions.

[0056] In order to explain the observation system evaluation index proposed in this embodiment, the representation method of the observation system is first explained. The radial surface array observation form includes two parts: survey lines (as shown in Figure 1a ) and survey points (as shown in Figure 1b ).

[0057] The five-star mark position mark receiving position / excitation position. The survey line and the survey point are defined, wherein the survey line is represented as: different survey line numbers all pass through the center of the cutter head, and the survey line formed by the top to the bottom of the cutter head is marked as survey line 1, and in accordance with the clockwise principle, survey line 2, survey line 3, …, survey line 6 are in turn; therefore, most of the positions on the cutter head are covered by the survey lines. At the same time, the survey points are distributed at equal intervals on each survey line, and the outermost position at the top of the cutter head is 1# survey point. For example, for survey line 1, the survey point at the top of the cutter head is marked as 1-1, and the survey point at the bottom of the cutter head is marked as 1-7; similarly, the 1# survey point of survey line 6 is at the lower right side, and the 7# survey point is at the upper left side.

[0058] Figure 1b The corresponding probe position code is as follows Figure 2a , wherein the longitudinal direction represents different survey line numbers, and the transverse direction represents survey points on different survey lines. It can be found from the figure that there are observation points at the 2nd position of survey line 1 and the 5th position of survey point 1, so that the coded position can receive 1 time of coverage, and the coverage times for other survey lines and survey points are 0, wherein the coverage is as shown in Figure 2b , it can be found from the figure that when the full coverage condition is not met, the observation is insufficient, and only the observation of 2 positions can be realized.

[0059] All positions on the survey line are taken as the full coverage of the observation target area as the system evaluation index, and specifically, taking survey line 1 as an example for illustration, the corresponding position code characteristics are as shown in Figure 3a , all positions on survey line 1 have survey points, so it meets the full coverage evaluation index. Therefore, the coverage of survey line 1 is further illustrated in this embodiment, because survey point 4# is located at the center position of the cutter head, so survey point 4# is also on other survey lines. On this basis, the coverage of survey line 1 is calculated as Figure 3b , wherein the abscissa is the receiving point position, and the ordinate is the excitation point position, it can be found from the figure that all excitation positions and receiving positions can be covered. Therefore, the full coverage evaluation standard of this embodiment can fully observe the wave field.

[0060] Due to the reserved positions of the rolling cutter, the scraping cutter and the tearing cutter of the tunnel boring machine cutter head, the probe cannot observe in the initial surface array form. The sparse observation of the probe does not affect the excitation and reception of the acoustic wave signal. Direct processing of the sparse observation data may cause spatial false frequency and other problems. Therefore, the rotation of the cutter head is used to replenish the sparse signal to the regular signal. Therefore, how to achieve sufficient observation of the wave field information under the condition of using a small number of probes is a problem to be solved. Through the analysis of the initial surface array observation form, it can be found that the rotation of the cutter head can supplement the sparse probe observation data, and then realize the full coverage observation of all measurement lines and measurement points, and finally realize the sufficient observation of the wave field information. The equivalent initial surface array observation system design method of the sparse probe rotation observation is described in detail below:

[0061] For a given measurement line and measurement point (this embodiment takes 6 measurement lines and 7 measurement points on each measurement line as an example), the optimization of the observation system is realized by judging the coverage degree of the remaining measurement points through the random removal of the measurement points. The optimization process of the observation system mainly includes five stages, as shown in Figure 4

[0062] (i) Stage one: select a measurement line, randomly select a measurement point in the surface array and remove it;

[0063] (ii) Stage two: rotate the cutter head for one revolution to obtain the position of the remaining measurement points on the measurement line;

[0064] (iii) Stage three: calculate the position of the other measurement points on the measurement line each time, and count the coverage and the number of coverage. Then, it is judged whether the position of all measurement points on the measurement line meets the full coverage evaluation index. If it meets, the measurement point is removed in the measurement point surface array, and the measurement point position is updated;

[0065] (iv) Stage four: recalculate stages two to three until the number of coverage of the measurement point position is 0 and the measurement point cannot be removed any more. Then, the cycle is terminated, and the sparse position based on the full coverage evaluation is obtained;

[0066] (v) Stage five: multiple cycles of stages one to four are performed to expand the sparse results that meet the full coverage. The most sparse probe on a single measurement line and a single ring is considered to obtain the best optimization result.

[0067] Therefore, the position relationship of the observation system can be more clearly explained by encoding the measurement line and the measurement point. On this basis, the encoding form is used to compare and analyze the evaluation index proposed in this embodiment with the above non-full coverage observation, and the correctness of the method proposed in this embodiment is verified.

[0068] ​The array sparse observation system design based on the rotation of the cutter head is realized through the above steps. Next, taking the 6 lines shown in FIG. 1 and 7 measuring points on each line as an example, the cutter head sparse rotation observation system implementation process is demonstrated.

[0069] Phase one: considering the limitations of the mechanical structure of the actual cutter head, such as the rolling cutter and the tearing cutter, the initial radial surface array cannot be laid out at some positions. Taking the positions of measuring points 1-5, 2-6 and 3-1 as examples, the measuring point 4-3 is randomly selected as the first sparse elimination position, and the probe distribution code position is obtained as shown in FIG. 5.

[0070] Phase two: the positions of the remaining measuring points on the line are calculated. In order to facilitate the subsequent statistics, the probe position code of the 6 lines after one rotation is directly given as shown in FIG. 6. In the figure, the horizontal axis represents the measuring point number, and the vertical axis represents the rotation number. From the figure, it can be found that the measuring point distribution patterns obtained by different lines change from line 1 to line 6. The main difference is that as the cutter head rotates, the probe distribution at the measuring point position on the line shifts downward. Therefore, the measuring point distribution on each line presents a cyclic appearance rule. Therefore, only one line needs to be analyzed, and the rules of other lines can be obtained by rotating the cutter head. Figure 6 Phase three: the coverage and coverage times of the 6 lines after one rotation are counted as shown in FIG. 7a and FIG. 7b. From the figure, it can be found that the coverage information of different lines is close to consistent,

[0071] Figure 7a The middle frame line selects line 1 for key analysis, and the evaluation results are shown in FIG. 8. From the figure, it can be found that different probe excited data are covered at different receiving probe positions, and the coverage times are 12 times, and the minimum coverage times are 8 times. From FIG. 9, it can be found that the coverage times are dense, although the data quality obtained at this time is good, but too many probe distributions cannot meet the actual engineering sparse probe distribution requirements, so the seismic data still has strong redundancy. The measuring point position can be further sparse optimized. Figure 7a Figure 7b Figure 7b Phase four: through the cycle of phase one to phase three, the sparse probe position that meets the full coverage condition is obtained. Since the obtained sparse observation position is analytical, phase one to phase three need to be cycled multiple times to expand the preliminary optimization position of the sparse observation position that meets the full coverage condition.

[0072] Phase five: taking the sparse distribution of adjacent probes on the measuring line and the circular ring as further constraint conditions, the probe sparse evaluation parameter S is constructed, and the probe sparse observation position with the maximum probe spacing is obtained in the preliminary optimization position.

[0073]

[0074] ​​​​

[0075] wherein R(i,j) represents the position encoding value of the jth measurement point on the ith ring, L(m,n) represents the position encoding value of the nth measurement point on the mth measurement line, and index represents whether the probe exists or not, index = 1 indicates that the probe exists at the position, otherwise the probe does not exist at the position. To further evaluate the sparsity effect, the sparsity ratio is used as a quantitative evaluation parameter in this embodiment, which is defined as the ratio of the total number of removed probes to the total number of initial probes, wherein T_f represents the final total number of probes, and T_i represents the initial total number of probes:

[0076]

[0077] The sparsity constraint is performed on the 500 groups of probe positions satisfying the full coverage constraint, and the sparsity evaluation parameters of each sample are calculated, and the results are shown in Figure 8 It can be found from the figure that the sparsity of different samples is different, and the minimum and maximum sparsity parameters differ by nearly 4 times. Among them, for sample 299, the sparsity parameter S is the largest, indicating that the sample has strong sparsity under the premise of satisfying full coverage.

[0078] The sparse probe distribution of the 299th sample is shown in Figure 9 It can be found from the figure that the probe data is obviously reduced compared with before sparsity, and the probe sparsity on each side line is obviously improved and increased.

[0079] It can be found from Figure 9 a that the probe positions are more sparse, the probe distribution in space becomes more random, and the predefined area where the probe cannot be installed presents a large area of blank, which also provides protection for the safe operation of the cutter head and the stability of the probe. The total number of probes is reduced from 37 to 15, and the sparsity ratio is 59%. On this basis, the probe positions on the 6 measurement lines obtained according to the final sparse positions of the probes are shown in Figure 10 .

[0080] In order to show that the removal of each probe has strong randomness, this embodiment draws the probe sparsity process under random constraint. In the figure, the horizontal axis represents the measurement point number, and the vertical axis represents the rotation number. The same as the first sparsity, it can be seen from the figure that the measurement point distribution obtained by different measurement lines is consistent in the change process from measurement line 1 to measurement line 6, and the main difference is that the probe distribution at the measurement point position on the measurement line has been translated downward as the cutter head rotates. Therefore, the measurement point distribution on each measurement line presents a cyclic rule. Therefore, for multiple measurement lines, only one of them needs to be analyzed, and a certain delay is added to obtain the rule of other measurement lines. The random removal process of the probe is shown in Figure 11 .

[0081] The horizontal axis represents the probe's survey line number, and the vertical axis represents the probe distribution in each sparsity process. Due to spatial constraints on the probes, there were initially four probe positions. On the survey lines distinguished by black lines in the figure, the probes achieved random and conditional sparsity in each sparsity process. Ultimately, observations of all offset types were achieved with a relatively small number of probes. Based on this, the coverage after one rotation of the six survey lines is plotted as follows: Figure 12a As shown.

[0082] As can be seen from the figure, due to the rotating nature of the cutterhead, the coverage information of different measurement lines is consistent. Therefore, [the following is a selection / selection]... Figure 12a The middle frame line was selected for focused analysis based on survey line 1, and its evaluation results are shown below. Figure 12b As shown in the figure, it can be seen that data from different probes are covered at different receiving probe locations. Compared to the first sparsity, the number of coverage times decreases overall after 17 sparsity iterations, with an average of 4 coverage times, a maximum of 12 coverage times, and a minimum of 1 coverage time. Overall, the number of probes decreases significantly after sparsity, with half of the locations in the figure having no probes. Therefore, full coverage of all locations under a smaller probe location distribution aperture was obtained, revealing the probe distribution locations in a sparse observation system.

[0083] In summary, the sparse optimization process mainly consists of three parts: initial array construction, equivalent initial array, and combined observation with cutter head rotation. The first step is to select a suitable array layout. The second step ensures that all initial observation points have probes, and then uses the full coverage evaluation criterion to successively remove probes until the full coverage condition can no longer be met, thus establishing a large set of sparse probe solutions. The solution with the sparsest probe positions is then selected as the sparse probe distribution location. The third step uses a small number of probes to acquire sparse observation data, and then rotates the cutter head until it completes one full rotation. The observation data at different rotation angles of the cutter head are combined by sampling, achieving supplementary observation data based on cutter head rotation, ultimately achieving sufficient observation of the reflected signal.

[0084] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., that can be made by those skilled in the art without creative effort within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for optimizing the array observation space based on sparse cutterhead rotation, characterized in that, Includes the following steps: (1) Construct the initial array; (2) Select the target survey line, randomly select a survey point in the initial area array and remove it; (3) Rotate the cutter head one revolution to obtain the position of the remaining measuring points on the measuring line; (4) Calculate the position of other measuring points on the measuring line for each rotation, and statistically analyze the coverage and the number of coverages to determine whether the position of all measuring points on the measuring line meets the full coverage evaluation index. If it does, remove the measuring point from the measuring point array and update the measuring point position of the array. (5) Repeat steps (2)-(4) above until the number of times the measurement point is covered is 0, then the loop terminates and sparse locations based on the full coverage evaluation are obtained. (6) Repeat steps (2)-(5) above to expand the sparse results to fully cover the target area. Consider the sparsest probes on a single measurement line and a single ring to obtain the best optimization results.

2. The array observation space optimization method based on sparse cutterhead rotation as described in claim 1, characterized in that, In step (1), the specific process of constructing the initial array includes: determining the range of values ​​for the channel spacing and the shot-receiver distance under the premise of satisfying the longitudinal and lateral resolution of the acoustic signal, determining the basic parameters of the observation system, and using the radial array as the initial array.

3. The array observation space optimization method based on sparse tool disk rotation as described in claim 1, characterized in that, In step (2), the specific process of selecting the target measurement line, randomly selecting a measurement point in the array and removing it includes: considering the limitations of the mechanical structure on the actual cutter head, there are designated positions in the radial initial array where probes cannot be placed, the position of the missing observation is predefined, and the measurement point is randomly selected from the remaining measurement points as the first sparse removal position to obtain the probe distribution meter probe coding map.

4. The array observation space optimization method based on sparse cutterhead rotation as described in claim 1, characterized in that, In step (3), the specific process of obtaining the position of the remaining measuring points on the measuring line by rotating the cutter head once is as follows: the cutter head rotates once, the probe position code is marked after the measuring line has rotated once, and the distribution pattern of measuring points on the measuring line is analyzed.

5. The array observation space optimization method based on sparse tool disk rotation as described in claim 1, characterized in that, In step (4), the specific process of determining whether the full coverage evaluation index of all measurement points under the measurement line is met includes determining the number of times the data excited by different probes covers different receiving probe positions. If the number of coverages is greater than the set value, then the full coverage evaluation index of all measurement points under the measurement line is met.

6. The array observation space optimization method based on sparse tool disk rotation as described in claim 1, characterized in that, In step (6), the process of expanding the sparse results to fully cover the probes includes taking the sparse distribution of adjacent probes on the probe line and the ring as a further constraint, constructing probe sparse evaluation parameters, and obtaining the probe sparse observation position with the largest probe spacing in the preliminary optimization position.

7. The array observation space optimization method based on sparse tool disk rotation as described in claim 6, characterized in that, The probe sparsity evaluation parameter is the ratio of the total number of probes removed to the initial total number of probes.

8. A space optimization system for array observation based on sparse tool disk rotation, characterized in that, include: The array construction module is configured to construct the initial array; The selection module is configured to select a target survey line, randomly select a survey point in the initial area array, and then remove it; The rotary module is configured to rotate the cutter head one revolution to obtain the position of the remaining measuring points on the measuring line; The update and optimization module is configured to calculate the positions of other measuring points on the measuring line with each rotation, statistically analyze the coverage and the number of coverages, and determine whether the positions of all measuring points on the measuring line meet the full coverage evaluation index. If they do, the measuring point is removed from the measuring point array and the measuring point positions of the array are updated. The first loop module is configured to repeat the execution of the above selection module, rotation module and update optimization module until the coverage count of the measurement point location is 0, the loop terminates, and sparse locations based on the full coverage evaluation are obtained. The second loop module is configured to repeat the execution of the above selection module, rotation module, update optimization module and the first loop module, expanding the sparse results to full coverage, considering the sparsest probes on a single measurement line and a single ring, to obtain the best optimization results.

9. A computer-readable storage medium, characterized in that, It stores multiple instructions adapted for loading by the processor of a terminal device and executing the steps of the method according to any one of claims 1-7.

10. A terminal device, characterized in that, It includes a processor and a computer-readable storage medium, the processor being used to implement various instructions; the computer-readable storage medium being used to store a plurality of instructions adapted to be loaded by the processor and executed in the steps of the method of any one of claims 1-7.

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