A method and related device for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample

Abstract

The present application discloses a method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample and a related device, which relates to the field of geotechnical engineering testing technology. The method includes obtaining the target stiffness of a designed adjustable stiffness spring assembly and a sample to be loaded; the adjustable stiffness spring assembly includes a main spring and an auxiliary spring; the auxiliary springs are centered on the main spring and are evenly spaced; and the stiffness value and effective number of turns of the main spring and the auxiliary spring in the adjustable stiffness spring assembly are determined according to the target stiffness. The present application can intelligently adapt the stiffness value and effective number of turns of the main spring and the auxiliary spring in the adjustable stiffness spring assembly according to the target stiffness, and then derive an adjustable stiffness spring assembly adapted to the sample to be loaded. Based on the component, a constant stiffness boundary that is the same as the actual stiffness of the sample to be loaded is provided when pressure is applied to the sample to be loaded, which can more realistically simulate the real environment in which the sample is located.

Description

Technical Field

[0001] The present application relates to the field of geotechnical engineering testing technology, and in particular to a method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample and a related device. Background Art

[0002] The various natural geological bodies and structural materials involved in geotechnical engineering construction are situated in complex geological environments, where their strength and deformation properties are influenced by their surroundings. In engineering, the performance of various materials is primarily studied through laboratory testing, which requires creating the in-situ environment in which the materials reside to obtain accurate and reliable material parameters. The influence of geostress on materials in underground structures cannot be ignored. In laboratory testing, this is often simulated by applying pressure to the materials using a loading device. Furthermore, when materials are subjected to pressure, they deform and are constrained by adjacent materials. This constraint depends on the stiffness of these adjacent materials. Current laboratory testing devices often fail to effectively simulate these boundary conditions that constrain material deformation. Most testing devices only consider the application of pressure and completely ignore deformation. A small number of testing devices incorporate springs on the loading head to control the stiffness and achieve constant stiffness loading. However, the stiffness of the loading head in existing devices is fixed, determined by the spring, and cannot be adjusted to the actual stiffness of the material environment. Summary of the Invention

[0003] The purpose of this application is to provide a method and related device for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample, which can accurately control the actual stiffness of the environment in which the sample is located when the sample is loaded and tested.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample, comprising:

[0006] Obtaining the target stiffness of the designed adjustable stiffness spring assembly and the sample to be loaded; the adjustable stiffness spring assembly includes a main spring and auxiliary springs; the auxiliary springs are centered on the main spring and are evenly spaced;

[0007] The stiffness values ​​and effective numbers of turns of the main spring and the auxiliary spring in the adjustable stiffness spring assembly are determined according to the target stiffness.

[0008] In a second aspect, the present application provides a sample loading device, comprising: a hydraulic loader, a pressure sensor, a loading base, an adjustable stiffness spring assembly, a loading plate, a sample box, a sample stiffness measuring element, and a control system;

[0009] Connection between hydraulic loading machine, pressure sensor, sample stiffness measuring element and control system;

[0010] The pressure sensor is arranged between the loading end and the loading base of the hydraulic loader;

[0011] The adjustable stiffness spring assembly is arranged between the loading base and the loading plate;

[0012] The sample box is used to hold the sample to be loaded;

[0013] The sample stiffness measuring element is used to measure the target stiffness of the sample to be loaded in the actual environment;

[0014] The control system is used to obtain the target stiffness output by the sample stiffness measuring element and execute the above-mentioned intelligent control optimization method for the spring group stiffness of the adapted sample to determine the stiffness value and effective number of turns of the main spring and auxiliary spring in the adjustable stiffness spring assembly; it is also used to control the hydraulic loader according to the pressure data detected by the pressure sensor to control the pressure applied to the sample to be loaded.

[0015] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned method for intelligently controlling and optimizing the stiffness of a spring group of an adaptive sample.

[0016] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for intelligently controlling and optimizing the stiffness of the spring group of the adaptive sample.

[0017] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0018] The present application provides a method and related device for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample, and obtains the target stiffness of a designed adjustable stiffness spring assembly and a loaded sample; the adjustable stiffness spring assembly includes a main spring and an auxiliary spring; the auxiliary springs are evenly spaced and centered around the main spring; and the stiffness value and effective number of turns of the main spring and the auxiliary spring in the adjustable stiffness spring assembly are determined based on the target stiffness. The present application can intelligently adapt the stiffness value and effective number of turns of the main spring and the auxiliary spring in the adjustable stiffness spring assembly based on the target stiffness, and then derive an adjustable stiffness spring assembly adapted to the sample to be loaded. Based on this assembly, a constant stiffness boundary identical to the actual stiffness of the sample to be loaded is provided when pressure is applied to the sample to be loaded, which can more realistically simulate the real environment in which the sample is located. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 This is a diagram of the application environment of a method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample in one embodiment of the present application;

[0021] Figure 2 A schematic diagram of a flow chart of a method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample according to one embodiment of the present application;

[0022] Figure 3 A schematic structural diagram of an adjustable stiffness spring assembly provided in one embodiment of the present application;

[0023] Figure 4 A schematic diagram of a flow chart for determining the model and effective number of coils of an adjustable stiffness spring assembly according to an embodiment of the present application;

[0024] Figure 5 A schematic structural diagram of a sample loading device provided in one embodiment of the present application;

[0025] Figure 6 A schematic diagram of the structure of a computer device provided in one embodiment of the present application.

[0026] Reference numerals:

[0027] 1-reaction frame; 2-sample box; 3-hydraulic loader; 4-pressure sensor; 5-loading base; 6-adjustable stiffness spring assembly; 7-loading plate; 8-sample stiffness measuring element; 9-control system; 61-main spring; 62-auxiliary spring. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0029] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0030] The intelligent control and optimization method of the spring group stiffness of the adaptive sample provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. The terminal communicates with the server through the network. The data storage system can store data that the server needs to process. The data storage system can be set up separately, integrated on the server, or placed on the cloud or other servers. The terminal can send the designed adjustable stiffness spring assembly 6 and the target stiffness of the sample to be loaded to the server. After the server receives the designed adjustable stiffness spring assembly 6 and the target stiffness of the sample to be loaded, the server obtains the designed adjustable stiffness spring assembly 6 and the target stiffness of the loaded sample; the adjustable stiffness spring assembly 6 includes a main spring 61 and an auxiliary spring 62; the auxiliary spring 62 is centered on the main spring 61 and is evenly spaced. The stiffness value and effective number of turns of the main spring 61 and the auxiliary spring 62 in the adjustable stiffness spring assembly 6 are determined according to the target stiffness. The server can feedback the obtained stiffness value and effective number of turns of the main spring 61 and the auxiliary spring 62 to the terminal. In addition, in some embodiments, the intelligent control and optimization method of the spring group stiffness of the adaptation sample can also be implemented separately by the server or the terminal. For example, the terminal can directly perform intelligent control and optimization of the spring group stiffness of the adaptation sample for the video to be processed, or the server can obtain the video to be processed from the data storage system and perform intelligent control and optimization of the spring group stiffness of the adaptation sample for the video to be processed.

[0031] The terminals may be, but are not limited to, various desktop computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The server may be implemented as an independent server or a server cluster consisting of multiple servers, or as a cloud server.

[0032] In an exemplary embodiment, Figure 2 As shown, a method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The server in is used as an example for description, including the following steps 101 to 102.

[0033] Step 101, obtaining the designed adjustable stiffness spring assembly 6 and the target stiffness of the loaded sample; the adjustable stiffness spring assembly 6 includes a main spring 61 and an auxiliary spring 62; the auxiliary springs 62 are centered on the main spring 61 and are evenly spaced.

[0034] In this step, it is known that the designed adjustable stiffness spring assembly 6 includes a main spring 61 and an auxiliary spring 62, wherein the specific number of springs can be predetermined, and the preset number of spring stiffness and effective coils can be directly determined later, or the number of main springs and auxiliary springs of the adjustable stiffness spring assembly can be preliminarily estimated, for example, a numerical range is given, and then the stiffness values ​​of each model in the benchmark spring database are combined with the target stiffness value to specifically determine the final number of springs.

[0035] Step 102 : determining the stiffness value and effective number of turns of the main spring 61 and the auxiliary spring 62 in the adjustable stiffness spring assembly 6 according to the target stiffness.

[0036] The stiffness values ​​and effective numbers of turns of the main spring 61 and the auxiliary spring 62 in the adjustable stiffness spring assembly 6 are determined. When the sample (rock and soil sample) is loaded based on the adjustable stiffness spring assembly 6, a real and reasonable constant stiffness boundary condition is provided during the loading process of the rock and soil sample, and a constant normal stiffness boundary is provided.

[0037] By implementing steps 101 and 102 above, and by designing the adjustable spring assembly 6 and determining the stiffness of each spring, a constant stiffness boundary equal to the sample's actual stiffness is provided when pressure is applied to the sample, thereby more realistically simulating the sample's actual environment. Furthermore, by designing different adjustable spring assembly 6 structures for different target stiffnesses, the process of adjusting the spring assembly stiffness is more convenient and rapid. Once the stiffness values ​​and effective number of coils for the main spring 61 and auxiliary spring 62 are determined, the adjustable spring assembly 6 can be retrofitted to existing loading equipment to achieve the most realistic simulation of the sample's natural environment.

[0038] As an example, Figure 3 As shown, the adjustable stiffness spring assembly 6 includes a main spring 61 and six auxiliary springs 62. The six auxiliary springs 62 surround the main spring 61 and are evenly distributed at 120° intervals. It is optimal if all six auxiliary springs 62 have the same stiffness. If this is not possible, two symmetrically positioned springs must have the same stiffness to ensure uniform stiffness distribution on the loading plate 7.

[0039] In another exemplary embodiment of the present application, each auxiliary spring 62 in the adjustable stiffness spring assembly 6 is equipped with a length-adjustable limit rod; the limit rod is used to adjust the effective number of coils of the corresponding auxiliary spring 62, thereby arbitrarily fine-tuning the stiffness of each auxiliary spring 62. The limit rod penetrates the center of the spring and has a limit plate at the end. By adjusting the height of the limit rod end and fixing it, the limit plate can be fixed to the position of any coil in the spring, thereby fixing all springs above the limit plate, allowing fine-tuning of the spring stiffness.

[0040] In another exemplary embodiment of the present application, the stiffness value and effective number of coils of the main spring 61 and the auxiliary spring 62 in the adjustable stiffness spring assembly 6 are determined according to the target stiffness, specifically including:

[0041] (1) Selecting an appropriate reference spring element model from a reference spring database according to the target stiffness; different reference spring elements have different stiffness values.

[0042] The reference spring database is equipped with a series of reference spring elements. Each reference spring element has the same length, but different materials, wire diameters, diameters, and numbers of coils, resulting in different stiffness. The stiffness calculation formula for a single spring is:

[0043]

[0044] Where: k is the spring stiffness (N / m), G is the shear modulus of the spring material (MPa), d is the spring wire diameter (mm), D is the average diameter of the spring (mm), and n is the number of effective coils.

[0045] (2) The main spring 61 model and the auxiliary spring 62 model are determined from the adapted reference spring element models; the total stiffness value corresponding to the main spring 61 model and the auxiliary spring 62 model is less than the target stiffness, and the difference from the target stiffness is less than a preset difference.

[0046] by Figure 3 Taking the example of one main spring 61 and six auxiliary springs 62, the stiffness of the main spring 61 is k0, and the auxiliary springs 62 are numbered sequentially from ① to ⑥. Here, ① and ④ have the same stiffness, k1; ② and ⑤ have the same stiffness, k2; and ③ and ⑥ have the same stiffness, k3. The overall stiffness K of the adjustable stiffness spring assembly 6 is calculated as follows:

[0047] ;

[0048] After determining the target stiffness, the overall stiffness K of the adjustable-stiffness spring assembly 6 is set equal to or slightly less than the target stiffness. Based on the initial stiffness of each reference spring element, a spring combination with a total stiffness slightly less than the target stiffness is selected as the main spring 61 and auxiliary spring 62. The effective number of coils of each auxiliary spring 62 is fine-tuned to achieve a total stiffness of the adjustable-stiffness spring assembly 6 equal to the target stiffness. By adjusting the limit rod to control the effective number of coils of each auxiliary spring 62, the overall stiffness of the adjustable-stiffness spring assembly 6 can be brought to the target stiffness.

[0049] (3) Taking the maximum number of coils of the spring as the initial effective number of coils, the effective number of coils of the auxiliary spring 62 is optimized to determine the effective number of coils of each auxiliary spring 62.

[0050] This step fine-tunes the total spring group rate to compensate for the difference from the target rate.

[0051] (4) When the absolute values ​​of the differences between the total spring group stiffness corresponding to various effective coil number combinations under the current auxiliary spring model and the target stiffness are not less than the preset error value, return to the step of "selecting an adapted reference spring element model from the reference spring database according to the target stiffness" to adapt the new reference spring element model.

[0052] Because adjusting the number of effective coils may not bring the total spring assembly stiffness closer to the target stiffness in various situations, a new spring model needs to be selected. For example, if the target stiffness is 950 and the required error cannot exceed 10, one main spring (500 stiffness) and six auxiliary springs (50 stiffness, total length 10 coils) are selected. When the auxiliary springs have 7 coils, the total stiffness is 500 + 6 × (50 × 10 / 7) = 928.57. When the number of coils is 6, the total stiffness is 500 + 6 × (50 × 10 / 6) = 1000. Therefore, the closest stiffness to the target achieved with this set of springs is 928.57. The minimum error is 950 - 928.57 = 21.43, which is greater than 10. This spring set does not meet the requirements and needs to be re-selected.

[0053] In another exemplary embodiment of the present application, in the above step (3), if Figure 4 As shown, taking the maximum number of coils of the spring as the initial effective number of coils, optimizing the effective number of coils of the auxiliary spring 62 is performed to determine the effective number of coils of each auxiliary spring 62, specifically including:

[0054] (3-1) Taking the maximum number of spring turns as the initial effective number of turns, determine the total spring group stiffness corresponding to each auxiliary spring 62 and the main spring 61 under the current effective number of turns.

[0055] (3-2) Calculate the absolute value of the difference between the total spring group stiffness and the target stiffness.

[0056] (3-3) Determine whether the absolute value of the difference is less than the preset error value.

[0057] If so, the optimal effective number of coils of each auxiliary spring 62 is output.

[0058] If not, adjust the effective number of turns of each auxiliary spring 62, and use the adjusted effective number of turns as the current effective number of turns, and return to the step of "determining the total spring group stiffness corresponding to each auxiliary spring 62 and the main spring 61 under the current effective number of turns".

[0059] In this application, an intelligent control algorithm for the stiffness of the spring group is applied. According to the target stiffness, a suitable combination of reference spring elements is selected as the main spring 61 and the auxiliary spring 62, and the effective number of turns to be used for each spring is calculated. By intelligently designing the specific structure of the adjustable stiffness spring assembly 6, the stiffness of the adjustable stiffness spring assembly 6 is adjusted to be the same as that of the sample, which can ensure that a constant normal stiffness boundary is provided during the sample loading process, and can most realistically simulate the natural environment in which the sample is located, so that the loading test experimental results of the sample are more reasonable and in line with reality.

[0060] In another exemplary embodiment of the present application, a sample loading device is provided, such as Figure 5 As shown, it includes: a hydraulic loader 3, a pressure sensor 4, a loading base 5, an adjustable stiffness spring assembly 6, a loading plate 7, a sample box 2, a sample stiffness measuring element 8 and a control system 9 (such as a host computer).

[0061] The hydraulic loading machine 3, the pressure sensor 4, the sample stiffness measuring element 8 and the control system 9 are connected.

[0062] The pressure sensor 4 is provided between the loading end of the hydraulic loader 3 and the loading base 5 .

[0063] The adjustable stiffness spring assembly 6 is provided between the loading base 5 and the loading plate 7 .

[0064] The sample box 2 is used to hold and secure the sample to be loaded. The sample box 2 can be modified into a box, a flat plate, a shear box, a confining pressure chamber, etc. to meet different test requirements.

[0065] Sample stiffness measurement element 8 is used to measure the target stiffness of the sample under actual conditions. Installed in sample box 2, after the sample is installed, it measures the target stiffness of the sample to ensure the measurement results best reflect the actual state of the sample during the test. The adjustable stiffness spring assembly 6 and sample stiffness measurement element 8 are installed in the sample loading device.

[0066] The hydraulic loader 3 provides the pressure required for loading. The pressure sensor 4 measures the pressure applied by the device. The loading base 5 transmits the pressure provided by the hydraulic loader 3 to the sample and maintains constant stiffness during loading. The loading plate 7 evenly distributes the loading pressure across the sample surface.

[0067] The control system 9 is used to obtain the target stiffness output by the sample stiffness measuring element 8 and execute the intelligent control optimization method for the spring group stiffness adapted to the sample to determine the stiffness value and effective number of turns of the main spring 61 and the auxiliary spring 62 in the adjustable stiffness spring assembly 6; it is also used to control the hydraulic loader 3 according to the pressure data detected by the pressure sensor 4 to control the pressure applied to the sample to be loaded.

[0068] like Figure 5 As shown, the sample loading device further includes: a reaction frame 1, which is the main body of the loading device, used for fixing and installing various equipment and providing reaction force for the loading device.

[0069] In the present application, before loading the sample, the target stiffness of the sample is measured by the sample stiffness measuring element 8, and the spring group stiffness intelligent control algorithm (i.e., the spring group stiffness intelligent control optimization method adapted to the sample) is applied. The algorithm selects a suitable spring combination and calculates the required effective number of turns of each auxiliary spring 62. The spring is replaced in the adjustable stiffness spring assembly 6, and the effective number of turns of each auxiliary spring 62 is adjusted by the limit rod, so that the overall stiffness of the adjustable stiffness spring assembly 6 is adjusted to be as similar as possible to the target stiffness of the sample, which can most realistically simulate the natural environment in which the sample is located, making the experimental results of the test more reasonable and in line with reality.

[0070] In another exemplary embodiment of the present application, one end of the main spring 61 and one end of the auxiliary spring 62 of the adjustable stiffness spring assembly 6 are detachably connected to the loading plate 7. Each spring can be detached and replaced to arbitrarily adjust the adjustable stiffness.

[0071] by Figure 3 Taking one main spring 61 and six auxiliary springs 62 as an example, the main spring 61 is located at the center of the loading plate 7, and the six auxiliary springs 62 are evenly distributed around the main spring 61 at intervals of 120°. The auxiliary springs 62 are close to the edge of the loading plate 7 to make the area enclosed by the adjustable stiffness spring group as large as possible to ensure uniform stiffness distribution on the loading plate 7.

[0072] In another exemplary embodiment of the present application, the adjustable stiffness spring assembly 6 also includes a limit rod with adjustable length; each auxiliary spring 62 is correspondingly provided with a limit rod; one end of the limit rod is fixed on the loading plate 7, and the other end is provided with a limit plate; the limit rod is used to adjust the effective number of turns of the corresponding auxiliary spring 62.

[0073] On the loading plate 7, there is an opening at the center of the installation position of each auxiliary spring 62, and a limit rod with adjustable position up and down (i.e. adjustable length) is inserted and fixed, which is used to fix the number of turns of any auxiliary spring 62, thereby arbitrarily fine-tuning the stiffness of each auxiliary spring 62.

[0074] The present application also provides an application scenario, which applies the above-mentioned intelligent control and optimization method for the stiffness of the spring group of the adaptive sample. Specifically: the intelligent control and optimization method for the stiffness of the spring group of the adaptive sample provided in this embodiment can be applied in the rock and soil sample loading test scenario. The scenario includes an adjustable spring component control and optimization link and a loading test link; the adjustable spring component control and optimization link is used to select a suitable spring combination based on the target stiffness of the sample, determine the model of the main spring and the auxiliary spring, and the effective number of coils; the loading test link is used to design the corresponding spring component based on the model of the main spring and the auxiliary spring and the effective number of coils, and install the spring component into the loading equipment for sample loading test. The intelligent control and optimization method for the stiffness of the spring group of the adaptive sample provided in this embodiment belongs to the adjustable spring component control and optimization link.

[0075] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store the intelligent control optimization data of the spring group stiffness of the adaptive sample. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for intelligent control optimization of the spring group stiffness of the adaptive sample is implemented.

[0076] Those skilled in the art will understand that Figure 6 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application and does not constitute a limitation on the computer device to which the solution of the present application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps of the above-mentioned method embodiments when executing the computer program.

[0077] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0078] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0079] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0080] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0081] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0082] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for intelligently controlling and optimizing the stiffness of a spring group adapted to a sample, characterized in that: include: Obtaining the target stiffness of the designed adjustable stiffness spring assembly and the sample to be loaded, including measuring the target stiffness of the sample to ensure that the measurement results best match the actual state of the sample during the test; the adjustable stiffness spring assembly includes a main spring and auxiliary springs; the auxiliary springs are centered around the main spring and are evenly spaced; Determining the stiffness value and effective number of coils of the main spring and the auxiliary spring in the adjustable stiffness spring assembly according to the target stiffness; specifically comprising: Screening out an adapted reference spring element model from a reference spring database according to the target stiffness; reference spring elements of different models have different stiffness values; Determining a main spring model and an auxiliary spring model from the adapted reference spring element model; the total stiffness value corresponding to the main spring model and the auxiliary spring model is less than the target stiffness, and the difference from the target stiffness is less than a preset difference; Taking the maximum number of coils of the spring as the initial effective number of coils, the effective number of coils of the auxiliary springs is optimized to determine the effective number of coils of each auxiliary spring; If the absolute values ​​of the differences between the total spring assembly stiffness corresponding to various effective coil number combinations under the current auxiliary spring model and the target stiffness are not less than the preset error value, return to step "selecting an adapted reference spring element model from the reference spring database according to the target stiffness" to adapt the new reference spring element model; The method of optimizing the effective number of coils of the auxiliary springs by taking the maximum number of coils of the spring as the initial effective number of coils and determining the effective number of coils of each auxiliary spring specifically includes: Taking the maximum number of spring coils as the initial effective number of coils, determine the total spring group stiffness corresponding to each auxiliary spring and main spring under the current effective number of coils; Calculate the absolute value of the difference between the total spring group stiffness and the target stiffness; Determine whether the absolute value of the difference is less than the preset error value; If so, output the optimal effective number of coils of each auxiliary spring; If not, adjust the effective number of coils of each auxiliary spring, take the adjusted effective number of coils as the current effective number of coils, and return to step "Determine the total spring group stiffness corresponding to each auxiliary spring and main spring under the current effective number of coils".

2. The method for intelligently controlling and optimizing the spring group stiffness of the adapted sample according to claim 1, characterized in that: The symmetrical auxiliary springs in the adjustable-rate spring assembly provide the same rate of spring stiffness.

3. The method for intelligently controlling and optimizing the spring group stiffness of the adapted sample according to claim 1, characterized in that: Each auxiliary spring in the adjustable stiffness spring assembly is provided with a length-adjustable limit rod; the limit rod is used to adjust the effective number of coils of the corresponding auxiliary spring.

4. A sample loading device, characterized in that: include: Hydraulic loader, pressure sensor, loading base, adjustable stiffness spring assembly, loading plate, sample box, sample stiffness measurement element and control system; Connection between hydraulic loading machine, pressure sensor, sample stiffness measuring element and control system; The pressure sensor is arranged between the loading end and the loading base of the hydraulic loader; The adjustable stiffness spring assembly is arranged between the loading base and the loading plate; The sample box is used to hold the sample to be loaded; The sample stiffness measuring element is used to measure the target stiffness of the sample to be loaded in the actual environment; A control system for obtaining the target stiffness output by a sample stiffness measuring element and executing the intelligent control optimization method for the stiffness of a spring group adapted to the sample as described in any one of claims 1 to 3 to determine the stiffness value and effective number of turns of a main spring and an auxiliary spring in an adjustable stiffness spring assembly; and for controlling a hydraulic loader according to pressure data detected by a pressure sensor to control the pressure applied to the sample to be loaded.

5. The sample loading device according to claim 4, characterized in that: One end of a main spring and one end of an auxiliary spring of the adjustable rate spring assembly are detachably connected to the loading plate.

6. The sample loading device according to claim 5, characterized in that: The adjustable stiffness spring assembly also includes a length-adjustable limit rod; each auxiliary spring is provided with a corresponding limit rod; one end of the limit rod is fixed to the loading plate, and the other end is provided with a limit plate; the limit rod is used to adjust the effective number of turns of the corresponding auxiliary spring.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for intelligently controlling and optimizing the spring group stiffness of the adaptation sample according to any one of claims 1 to 3.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for intelligently controlling and optimizing the spring group stiffness of the adaptation sample according to any one of claims 1 to 3 is implemented.

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