Earth material construction compaction degree evaluation method and related device

Abstract

The invention provides a soil material construction compaction degree evaluation method and a related device. The soil material construction compaction degree evaluation method comprises the following steps: obtaining compaction degree evaluation index information at a sampling position; performing data preprocessing on the obtained compaction degree evaluation index information so as to standardize the compaction degree evaluation index; performing data fusion on the compaction degree evaluation index information based on a D-S evidence theory so as to determine the compaction degree qualification probability of the soil material at the sampling position; and according to the compaction degree qualification probability of the soil material at the sampling position, carrying out spatial interpolation on the compaction degree qualification probability values at other sampling positions through a spatial interpolation method so as to obtain a full-working-face compaction degree qualification probability value distribution cloud picture, and evaluating the compaction quality of the soil material by taking a probability threshold supporting compaction degree qualification as an evaluation reference. According to the method, the limitation that the compaction quality is represented by a single index is overcome, and the accuracy and reliability of soil material compaction degree evaluation are improved.

Description

Technical Field

[0001] The present application belongs to the technical field of rolling quality control in earth-rock dam construction, and in particular to a method for evaluating the compaction degree of earth material construction and a related device. Background Art

[0002] In the process of soil rolling construction, compaction is a key indicator to measure the quality of the project. Conventional soil compaction testing uses manual test pit sampling, which has the disadvantages of low testing efficiency, time-consuming and labor-intensive sampling, few sample points, difficulty in reflecting the entire warehouse surface, difficulty in timely feedback control, and interference with subsequent construction operations.

[0003] In recent years, with the development of intelligent rolling technology, methods based on real-time monitoring indicators to evaluate soil compaction quality have been widely used, including frequency domain indicators CV, CCV, THD based on the spectrum analysis of roller vibration acceleration, and compaction indicators such as stiffness and compaction work per unit volume derived with the help of the roller-soil dynamics model.

[0004] The above indicators can characterize the compaction quality to a certain extent, but they all have their own limitations. For example, the frequency domain compaction index indirectly evaluates the compaction quality of soil by the different vibration responses of the roller to the different density states of the soil, but it is easily affected by the hardness of the bottom layer of the soil and the compaction uniformity of the bottom layer; the compaction stiffness index can directly characterize the hardness of the compacted soil during the rolling process, but it cannot reflect the dynamic response of the soil to the roller during the compaction process; the compaction work per unit volume can objectively reflect the compaction effect of the roller on the soil and the effect of the soil on the external pressure, but it cannot reflect the uniformity of the compaction effect of different soils.

[0005] Therefore, there are obvious limitations in using a single indicator to characterize compaction quality, and the resulting evaluation results have obvious deviations, leading to poor construction quality. In addition, the existing evaluation methods are time-consuming and labor-intensive, which seriously restricts the construction progress. Summary of the invention

[0006] In view of this, the present application aims to propose a method for evaluating the compaction degree of soil construction and a related device to solve at least one of the above problems.

[0007] To achieve the above purpose, the technical solution of this application is implemented as follows: In a first aspect, the present application provides a method for evaluating the compaction degree of soil materials during construction, comprising: Acquire compaction evaluation index information at the sampling position, wherein the compaction evaluation index information includes compaction stiffness, frequency domain compaction index and unit volume compaction work; Performing data preprocessing on the acquired compaction evaluation index information to standardize the compaction evaluation index; Based on the DS evidence theory, data fusion is performed on the compaction evaluation index information to determine the probability of qualified compaction of the soil material at the sampling location; According to the qualified probability of compaction of soil at the sampling position, the qualified probability values ​​of compaction at other sampling positions are spatially interpolated by spatial interpolation method to obtain the distribution cloud map of the qualified probability values ​​of compaction of the entire working surface. The probability threshold that supports qualified compaction is used as the evaluation benchmark to evaluate the compaction quality of soil.

[0008] In the second aspect, based on the same inventive concept, the present application also provides a soil construction compaction evaluation device, comprising: An information acquisition module is configured to acquire compaction evaluation index information at a sampling position, wherein the compaction evaluation index information includes compaction stiffness, frequency domain compaction index, and unit volume compaction work; A preprocessing module is configured to perform data preprocessing on the acquired compaction evaluation index information to standardize the compaction evaluation index; A data fusion module is configured to perform data fusion on the compaction evaluation index information based on DS evidence theory to determine the probability of a qualified compaction of the soil material at the sampling location; The compaction evaluation module is configured to perform spatial interpolation on the compaction probability values ​​at other sampling locations based on the compaction probability of the soil at the sampling location through the spatial interpolation method, so as to obtain a distribution cloud map of the compaction probability values ​​of the entire working surface, and use the probability threshold that supports the compaction quality as the evaluation benchmark to evaluate the compaction quality of the soil.

[0009] In a third aspect, based on the same inventive concept, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in the first aspect is implemented.

[0010] In a fourth aspect, based on the same inventive concept, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0011] Compared with the prior art, the soil construction compaction evaluation method and related device described in this application have the following beneficial effects: The soil construction compaction evaluation method and related devices described in the present application obtain multi-source information and perform information fusion evaluation based on DS evidence theory, thereby overcoming the limitation of a single indicator in representing the compaction quality, improving the accuracy and reliability of soil compaction evaluation, and achieving rapid and accurate judgment of soil compaction, which provides a new way to control the compaction quality of soil construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 This is a flow chart of a method for evaluating the compaction degree of soil materials during construction described in an embodiment of the present application; Figure 2 This is a schematic diagram of the structure of a soil material construction compaction evaluation device described in an embodiment of the present application; Figure 3 This is a schematic diagram of the hardware structure of the electronic device described in the embodiment of the present application. DETAILED DESCRIPTION

[0013] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0014] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0015] In order to solve the limitation of a single indicator to characterize the compaction degree of soil, this application proposes a method for rapid evaluation of the compaction degree of soil during rolling under multi-source information fusion. This method combines multiple time domain and frequency domain evaluation indicator information, and performs information fusion evaluation through DS evidence theory, thereby achieving rapid and accurate judgment of the compaction degree of soil.

[0016] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0017] See also Figure 1 As shown, this embodiment provides a method for evaluating the compaction degree of soil construction, which specifically includes the following steps: Step S101, obtaining compaction evaluation index information at a sampling position, wherein the compaction evaluation index information includes compaction stiffness, frequency domain compaction index and unit volume compaction work.

[0018] Specifically, in this embodiment, the intelligent rolling technology is used to collect data such as roller acceleration, travel speed, number of passes, compaction thickness, etc. in real time during the rolling process, and the data of each collected position can be calculated. The stiffness at , compaction work per unit volume And CV index (frequency domain compaction index), the calculation formula is as follows: (1) In the formula, For the collection location CV value of and For the collection location The fundamental frequency harmonic amplitude and double fundamental frequency harmonic amplitude of acceleration after Fourier transform.

[0019] (2) In the formula, Indicates the amplitude of the exciting force, in N; Indicates the mass of the roller, in kg; For the collection location The time domain acceleration of the roller vibration, in m / s 2 ; Indicates the maximum displacement of the roller, in m; It means that in the actual soil rolling process, due to the influence of damping, the The phase difference caused by the roller displacement lagging behind the exciting force.

[0020] (3) In the formula, Indicates the collection location The compaction work per unit volume at the location is expressed in J / m 3 ; Indicates the collection location The vibration frequency at , in Hz; Indicates the width of the roller, m; Indicates the collection location The rolling thickness at , in m; Indicates the collection location The speed at the point, in m / s; Indicates the radial load of the roller, in N; Indicates the collection location The amplitude at , in m; Indicates the collection location The formula exciting force at is in N; Same as above.

[0021] These indicators respectively reflect the hardness of the compacted soil, the compaction effect of the roller on the soil, and the vibration response of the roller to the different compaction states of the soil.

[0022] Step S102: preprocess the acquired compaction evaluation index information to standardize the compaction evaluation index.

[0023] Specifically, in this embodiment, for the different dimensions and value ranges of stiffness, unit volume compaction work and CV indicators, a linear normalization method is used to convert the values ​​of different evaluation indicators into dimensionless values. The linear normalization formula is as follows: (4) In the formula, and They represent the minimum and maximum values ​​of the evaluation indicators respectively.

[0024] Step S103: Based on the DS evidence theory, data fusion is performed on the compaction evaluation index information to determine the probability of a qualified compaction of the soil material at the sampling location.

[0025] Step S301: Calculate the basic probability distribution value of the indicator at any sampling position.

[0026] Each compaction evaluation indicator is regarded as an independent body of evidence, and each body of evidence assigns a basic probability assignment (BPA) to two hypotheses (compaction qualified and compaction unqualified). Based on each evaluation indicator, its support for the two hypotheses (compaction qualified and compaction unqualified) is calculated, that is, the probability value of each compaction evaluation indicator supporting the two hypotheses and .

[0027] The basic probability distribution value of stiffness is calculated as follows: Assuming that under given working conditions, the stiffness index under different compaction conditions is measured multiple times, and its value range is ,in represents the minimum stiffness, Represents the maximum stiffness. The greater the stiffness, the higher the probability of supporting qualified compaction. Combined with the compaction control requirements, the control threshold of the stiffness index is , then the BPA of the stiffness at the acquisition location can be calculated according to the linear distribution: (5) (6) In the formula, and They represent the probability values ​​of the stiffness index at the collection location supporting the compaction degree to be qualified and unqualified respectively.

[0028] Similarly, the probability values ​​of the unit volume compaction work supporting qualified compaction and unqualified compaction at the collection location are expressed as and ; The probability values ​​of the CV index supporting the qualified compaction degree and the unqualified compaction degree at the sampling location are respectively represented by and .

[0029] Step S302: Conflict reduction processing of indicator evidence body.

[0030] In order to resolve the possible conflicts between different indicator evidence bodies and improve the reliability of multi-source information fusion results, Murphy's rule is used to weaken the conflicts of indicator evidence bodies. Calculate the weighted average probability value of all indicator evidence bodies supporting the same hypothesis and , the formula is as follows: (7) (8) In the formula, Indicates the weighted average probability value of qualified compaction at the sampling location; It represents the weighted average probability value of unqualified compaction at the sampling location.

[0031] Furthermore, the probability values ​​of all indicator evidence bodies are weighted to make the support probability values ​​of each indicator evidence body consistent, reducing the impact of conflicts on the results. The formula for adjusting the indicator probability value distribution is as follows: (9) (10) (11) (12) (13) (14) In the formula, represents the adjustment factor; , and They represent the probability values ​​of the stiffness, compaction work per unit volume and CV index at the sampling location supporting the qualified compaction degree; , and They respectively represent the probability values ​​of unqualified compaction degree supported by stiffness, compaction work per unit volume and CV index at the collection location.

[0032] Step S303, after integrating multiple indicators, the probability value of passing the compaction is calculated.

[0033] The adjusted BPA is obtained using formulas (9)-(14), and the DS evidence theory rule is used for iterative fusion to obtain the final fusion probability values ​​at each acquisition position: and , the specific calculation formula is as follows: (15) (16) (17) (18) (19) (20) In the formula, and They represent the probability values ​​of qualified and unqualified compaction after the stiffness index and the unit volume compaction work index at the collection location are integrated; and They represent the probability values ​​of qualified and unqualified compaction at the collection location after the three indicators are integrated; and They represent the conflict factors of the two fusions and are used to describe the conflict between the evidences. The larger the value, the greater the conflict between the evidences, which also means that the reliability of the decision result after fusion is worse.

[0034] The above steps are used to calculate the probability values ​​of qualified and unqualified compaction at each sampling position under real-time monitoring.

[0035] Step S104: Based on the qualified compaction probability of the soil at the sampling position, the qualified compaction probability values ​​at other sampling positions are spatially interpolated by the spatial interpolation method to obtain a distribution cloud diagram of the qualified compaction probability values ​​of the entire working surface, and the probability threshold that supports the qualified compaction is used as an evaluation benchmark to evaluate the compaction quality of the soil.

[0036] Specifically, in this embodiment, taking into account the discreteness of the data at the sampling position, the probability of qualified compaction at the sampling position obtained in step S103 and the spatial interpolation method (such as Kriging interpolation) are used to interpolate the probability value of qualified compaction at any other position, and a probability value distribution cloud map of qualified compaction supported by the entire working face can be obtained.

[0037] To support the probability threshold of qualified compaction As an evaluation benchmark, When the compaction degree is qualified, The value is 0.5.

[0038] In addition, several test points can be randomly selected on site, and the fusion evaluation results of each point can be compared and analyzed with the actual compaction test results.

[0039] Specifically, if the fusion result is consistent with the actual test result, it is recorded as a correct judgment; if the result is inconsistent, it is recorded as a misjudgment (including misjudgment of qualified and unqualified). Dynamically adjust the probability threshold according to the misjudgment situation: if there are many points misjudged as qualified, the threshold needs to be appropriately increased. ; If there are many points that are misjudged as unqualified, the threshold needs to be appropriately lowered It should be noted that the threshold value should strike a balance between the correct judgment rates of qualified and unqualified, so as to achieve rapid and accurate judgment of soil compaction.

[0040] Areas judged to have unsatisfactory compaction degree shall be re-rolled to ensure the quality of soil compaction.

[0041] The method described in this embodiment obtains multi-source information and performs information fusion evaluation based on DS evidence theory, thereby overcoming the limitation of a single indicator in representing compaction quality, improving the accuracy and reliability of soil compaction evaluation, and achieving rapid and accurate judgment of soil compaction, which provides a new way to control the compaction quality of soil construction.

[0042] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0043] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, an embodiment of the present application also provides a soil construction compaction evaluation device.

[0044] like Figure 2 As shown, the soil construction compaction evaluation device comprises: The information acquisition module 11 is configured to acquire compaction evaluation index information at the sampling position, wherein the compaction evaluation index information includes compaction stiffness, frequency domain compaction index and unit volume compaction work; A preprocessing module 12 is configured to perform data preprocessing on the acquired compaction evaluation index information to standardize the compaction evaluation index; The data fusion module 13 is configured to perform data fusion on the compaction evaluation index information based on the DS evidence theory to determine the probability of a qualified compaction of the soil material at the sampling location; The compaction evaluation module 14 is configured to perform spatial interpolation on the compaction probability values ​​at other sampling positions according to the compaction probability of the soil at the sampling position by means of the spatial interpolation method, so as to obtain a distribution cloud diagram of the compaction probability values ​​of the entire working surface, and to evaluate the compaction quality of the soil using the probability threshold supporting the compaction as the evaluation benchmark.

[0045] For the convenience of description, the above devices are described in terms of functions and are divided into various modules. Of course, when implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0046] The device of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0047] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method described in any of the above embodiments is implemented.

[0048] Figure 3 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0049] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0050] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0051] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0052] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0053] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 ).

[0054] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0055] The electronic device of the above embodiment is used to implement the corresponding method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0056] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method described in any of the above embodiments.

[0057] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0058] The computer instructions stored in the storage medium of the above embodiments are used to enable the computer to execute the method described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0059] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0060] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the well-known power / ground connections to the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device may be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present application are to be implemented (that is, these details should be fully within the scope of understanding of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or with changes in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0061] Although the present application has been described in conjunction with specific embodiments of the present application, many alternatives, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the discussed embodiments.

[0062] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A method for evaluating the compaction degree of soil materials during construction, characterized in that: include: Acquire compaction evaluation index information at the sampling position, wherein the compaction evaluation index information includes compaction stiffness, frequency domain compaction index and unit volume compaction work; Performing data preprocessing on the acquired compaction evaluation index information to standardize the compaction evaluation index; Based on the DS evidence theory, data fusion is performed on the compaction evaluation index information to determine the probability of qualified compaction of the soil material at the sampling location; According to the qualified probability of compaction of soil at the sampling position, the qualified probability values ​​of compaction at other sampling positions are spatially interpolated by spatial interpolation method to obtain the distribution cloud map of the qualified probability values ​​of compaction of the entire working surface. The probability threshold that supports qualified compaction is used as the evaluation benchmark to evaluate the compaction quality of soil.

2. The method according to claim 1, characterized in that The obtaining of compaction evaluation index information at the sampling position during rolling includes: Calculate compaction stiffness, frequency domain compaction index and unit volume compaction work based on the rolling process parameters collected in real time; Wherein, the compaction stiffness formula is: ； In the formula, Indicates the amplitude of the exciting force; Indicates the quality of the roller; For the collection location The time domain acceleration of the roller vibration; is the maximum displacement of the roller; It is the phase difference caused by the displacement of the roller lagging behind the exciting force at the collection position due to the influence of damping in the actual soil rolling process; The frequency domain compaction index formula is: ； In the formula, For collection location Compaction monitoring value at; and For collection location The fundamental harmonic amplitude and double fundamental harmonic amplitude of the acceleration at the Fourier transform; The formula for compaction work per unit volume is: ； In the formula, For collection location The compaction work per unit volume at ; For collection location The vibration frequency at is the width of the roller; For collection location The rolling thickness at For collection location The speed at which is the radial load of the roller; For collection location The amplitude at For collection location The exciting force at the place.

3. The method according to claim 1, characterized in that The data preprocessing of the acquired compaction evaluation index information to standardize the compaction evaluation index includes: The compaction stiffness, frequency domain compaction index and unit volume compaction work values ​​are converted into dimensionless values ​​by using a linear normalization method.

4. The method according to claim 1, characterized in that: The data fusion of the compaction evaluation index information based on the DS evidence theory to determine the qualified probability of the soil compaction at the sampling position includes: respectively calculating the basic probability distribution values ​​of the compaction stiffness, the frequency domain compaction index and the unit volume compaction work value; The conflict of indicator evidence is weakened by Murphy rule to obtain the qualified probability value of each indicator and the inappropriate probability value of each indicator. The qualified probability values ​​of the compaction degree and the unqualified probability values ​​of the compaction degree are iteratively fused through the DS evidence theory rule to obtain the qualified probability value of the compaction degree and the unqualified probability value of the compaction degree at the fused sampling position.

5. The method according to claim 4, characterized in that The soil compaction quality is evaluated by taking the probability threshold of supporting the qualified compaction degree as the evaluation benchmark, including: The probability threshold of supporting the qualified compaction degree is used as the evaluation benchmark, and the qualified compaction degree probability value obtained after fusion is compared with the probability threshold to obtain the evaluation result, including: In response to the compaction degree qualified probability value being greater than or equal to the probability threshold, determining that the compaction degree at the sampling position is qualified; In response to the compaction degree qualified probability value being less than the probability threshold, the compaction degree at the sampling location is determined to be unqualified.

6. The method according to claim 5, characterized in that Also includes: Areas judged to have unsatisfactory compaction degree shall be re-rolled to compact the soil in that area.

7. The method according to claim 1, characterized in that Also includes: Randomly select several test points and compare and analyze the fusion evaluation results of each point with the actual compaction test results; In response to the fusion evaluation result and the actual compaction degree detection result being determined to be consistent, it is recorded as a correct judgment; In response to the inconsistency between the fusion evaluation result and the actual compaction detection result, it is recorded as a misjudgment, and the probability threshold is dynamically adjusted according to the misjudgment situation.

8. A soil material construction compaction evaluation device, characterized in that: include: An information acquisition module is configured to acquire compaction evaluation index information at a sampling position, wherein the compaction evaluation index information includes compaction stiffness, frequency domain compaction index, and unit volume compaction work; A preprocessing module is configured to perform data preprocessing on the acquired compaction evaluation index information to standardize the compaction evaluation index; A data fusion module is configured to perform data fusion on the compaction evaluation index information based on DS evidence theory to determine the probability of a qualified compaction of the soil material at the sampling location; The compaction evaluation module is configured to perform spatial interpolation on the compaction probability values ​​at other sampling locations based on the compaction probability of the soil at the sampling location through the spatial interpolation method, so as to obtain a distribution cloud map of the compaction probability values ​​of the entire working surface, and use the probability threshold that supports the compaction quality as the evaluation benchmark to evaluate the compaction quality of the soil.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium, characterized in that: in, The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 7.

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