Soft rock disintegration test system and method for multi-cycle hydrolysis of acid-base solution

Abstract

The invention relates to the technical field of soft rock testing, and particularly discloses a soft rock disintegration testing system and a soft rock disintegration testing method for multi-cycle hydrolysis of an acid-base solution. According to the system, a target soft rock sample is finely processed, the processing quality coefficient of the target soft rock sample is evaluated in real time, and it is ensured that each soft rock sample meets the testing standard as much as possible; the processing quality of the target soft rock sample is improved, the material waste is reduced, the test effectiveness is further ensured by collecting and analyzing the apparent parameters of the soft rock sample and screening out the compliant sample, the compliant soft rock sample is uniformly grouped and subjected to the multi-cycle hydrolysis test, the disintegration characteristics of the soft rock under different conditions can be deeply known, and the test efficiency is improved. By collecting parameters of the soaking process and analyzing compliance indexes of the soaking process, testing conditions are flexibly adjusted, testing efficiency is improved, all combination gauge soft rock samples are dried, experimental result parameters are collected, whether testing needs to be conducted again or not is scientifically judged, and comprehensiveness and accuracy of testing results are ensured.

Description

Technical Field

[0001] This invention relates to the field of soft rock testing technology, specifically to a soft rock disintegration testing system and method based on multi-cycle hydrolysis with acid and alkali solutions. Background Technology

[0002] Soft rock constitutes an indispensable and complex component of soil and rock mass in civil engineering construction. Exploring accurate and efficient testing methods for its disintegration characteristics is of vital practical significance and reference value for engineering projects in areas where soft rock is widely distributed. In view of this, intelligent in-depth testing and scientific research on the disintegration characteristics of soft rock have emerged, aiming to achieve more accurate and efficient exploration and analysis of soft rock disintegration behavior through advanced technical means.

[0003] For example, invention patent CN118190772A discloses a soft rock disintegration apparatus and test method for simulating wet-dry cycles. The soft rock disintegration apparatus includes an experimental chamber, in which the sample is placed. The experimental chamber is a transparent, enclosed structure. The side wall of the experimental chamber is equipped with a water inlet and an air drying device to simulate a wet-dry cycle environment. A test controller is placed on the top of the experimental chamber, and a support frame is placed inside the experimental chamber. The support frame is suspended from the measuring end of the test controller to measure the mass of the support frame in real time. The support frame includes a base and a hanging net. The base is installed inside the hanging net, and a rotating platform is installed on the base. The rotating platform rotates by a bottom rotating shaft, and the sample is placed on the rotating platform. A humidity detection sensor is installed inside the sample to measure the humidity of the sample in real time.

[0004] For example, the invention patent with announcement number CN107560963B announces a method for single-sided dehydration disintegration test of extremely soft rock, which belongs to the field of extremely soft rock disintegration, including the following steps: (1) on-site sampling; (2) making a single-sided sample sealed on all four sides and bottom; (3) air-drying the sample; (4) after air-drying, placing the air-dried sample on a sieve and immersing it in water to disintegrate naturally; (5) observing the disintegration phenomenon and removing the disintegration material on the upper surface by manual pouring. After stabilizing for 24 hours, the remaining sample is taken out and dried at low temperature. The sealing material of the sample is removed, and the disintegration depth after the dry-wet cycle is determined; (6) the disintegration material on the 2mm sieve is dried and sieved through standard sieves with sieve hole diameters of 60mm, 40mm, 20mm, 10mm, 5mm and 2mm respectively, and the disintegration rate of the disintegration material is calculated.

[0005] However, in the process of implementing the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems: In the current soft rock disintegration experiment, the control of key variable parameters is relatively general. Even small changes in key variable parameters may have a significant impact on the experimental results, which may lead to the experimental results being easily interfered with, thereby affecting the accuracy of the experimental results. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a soft rock disintegration testing system and method based on multi-cycle hydrolysis with acid and alkali solutions, which can effectively solve the problems mentioned in the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of the present invention provides a soft rock disintegration testing system based on multi-cycle hydrolysis with acid and alkali solutions, comprising: a soft rock processing module for processing target soft rock samples, acquiring processing parameters of the target soft rock samples, evaluating the processing quality coefficient of the target soft rock samples, comparing it with a processing quality threshold, determining whether to adjust the processing parameters of the target soft rock samples, until the processing of the target soft rock samples is completed, and obtaining each soft rock sample; and a soft rock selection module for collecting apparent parameters of each soft rock sample and analyzing the apparent compliance factor of each soft rock sample. This process identifies compliant soft rock samples, which are then uniformly grouped to form compliant soft rock sample groups. Each group undergoes a disintegration test using multiple cycles of acid-base hydrolysis. A soft rock soaking module collects soaking process parameters for each group and analyzes their compliance index, determining whether adjustments to the soaking process parameters are necessary. A data collection module dries each group of compliant soft rock samples, collects experimental results, and determines whether another disintegration test using multiple cycles of acid-base hydrolysis is required.

[0008] As a further solution, the determination of whether to adjust the processing parameters of the target soft rock sample is as follows: the processing quality coefficient of the target soft rock sample is compared with the processing quality threshold. If the processing quality coefficient of the target soft rock sample is greater than the processing quality threshold, it is determined that the processing parameters of the target soft rock sample will not be adjusted. If the processing quality coefficient of the target soft rock sample is less than or equal to the processing quality threshold, it is determined that the processing parameters of the target soft rock sample will be adjusted. The adjustment process is as follows: the processing quality coefficient of the target soft rock sample is matched with the processing parameter adjustment set corresponding to each processing quality coefficient interval stored in the test database, thereby obtaining and executing the processing parameter adjustment set of the target soft rock sample. After the adjustment is completed, the processing quality coefficient of the target soft rock sample in the next adjacent processing monitoring sub-cycle is evaluated, and it is determined whether to adjust the processing parameters of the target soft rock sample, until the processing of the target soft rock sample is completed and each soft rock sample is obtained.

[0009] As a further solution, the labeling of each compliant soft rock sample is specifically carried out as follows: extract the apparent compliance threshold from the test database, compare the apparent compliance factor of each soft rock sample with the apparent compliance threshold, and label several soft rock samples with apparent compliance factors greater than the apparent compliance threshold as compliant soft rock samples, thereby grouping each compliant soft rock sample according to preset grouping requirements.

[0010] As a further solution, the determination of whether to adjust the soaking process parameters of each group of soft rock samples is as follows: The soaking process compliance index of each group of compliant soft rock samples is compared with the soaking process compliance threshold. If the soaking process compliance index of a group of compliant soft rock samples is greater than the soaking process compliance threshold, it is determined that the soaking process parameters of that group of compliant soft rock samples will not be adjusted. If the soaking process compliance index of a group of compliant soft rock samples is less than or equal to the soaking process compliance threshold, it is determined that the soaking process parameters of that group of compliant soft rock samples will be adjusted. The adjustment process is as follows: The determination criteria for the soaking process compliance index of the group of compliant soft rock samples are obtained, and the soaking process parameters of the group of compliant soft rock samples are adjusted comprehensively based on the soaking process compliance index, the soaking process compliance threshold, and the determination criteria for the soaking process compliance index of the group of compliant soft rock samples. After the adjustment is completed, the soaking process compliance index of each group of compliant soft rock samples in the next adjacent soaking detection sub-cycle is evaluated, and it is determined whether to adjust the soaking process parameters of each group of soft rock samples, until the soaking process of each group of soft rock samples is completed.

[0011] As a further solution, the specific process for determining whether to conduct a disintegration test involving multiple cycles of acid-base hydrolysis is as follows: The experimental result parameters of each group of compliant soft rock samples include the average particle size of each group of compliant soft rock samples; the historical adjacent experimental result parameters of each group of compliant soft rock samples are obtained, i.e., the historical adjacent average particle size of each group of compliant soft rock samples; the historical adjacent average particle size of each group of compliant soft rock samples is compared with the corresponding average particle size of each group of compliant soft rock samples; the result is then compared with the historical adjacent average particle size of each group of compliant soft rock samples to obtain the particle size change rate of each group of compliant soft rock samples; the particle size change rate of each group of compliant soft rock samples is compared with the reference particle size change rate; if the particle size change rate of a certain group of compliant soft rock samples is greater than the reference particle size change rate, then it is determined that the group of compliant soft rock samples will undergo a disintegration test involving multiple cycles of acid-base hydrolysis again; if the particle size change rate of a certain group of compliant soft rock samples is less than or equal to the reference particle size change rate, then it is determined that the group of compliant soft rock samples will not undergo a disintegration test involving multiple cycles of acid-base hydrolysis again.

[0012] The second aspect of this invention provides a method for testing the disintegration of soft rock through multi-cycle hydrolysis with acid and alkali solutions, comprising: Step 1, processing a target soft rock sample, obtaining processing parameters of the target soft rock sample, evaluating the processing quality coefficient of the target soft rock sample, comparing it with a processing quality threshold, and determining whether to adjust the processing parameters of the target soft rock sample, until the processing of the target soft rock sample is completed, thereby obtaining each soft rock sample; Step 2, collecting the apparent parameters of each soft rock sample, analyzing the apparent compliance factor of each soft rock sample, thereby marking each compliant soft rock sample. The compliant soft rock samples were uniformly grouped to obtain each group of compliant soft rock samples. A disintegration test using multiple cycles of acid and alkali hydrolysis was then conducted on each group of compliant soft rock samples. Step three: The soaking process parameters of each group of compliant soft rock samples were collected, and the compliance index of the soaking process of each group of compliant soft rock samples was analyzed to determine whether the soaking process parameters of each group of soft rock samples needed to be adjusted. Step four: Each group of compliant soft rock samples was dried, and the experimental results parameters of each group of compliant soft rock samples were collected to determine whether another disintegration test using multiple cycles of acid and alkali hydrolysis was necessary.

[0013] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) This invention provides a soft rock disintegration test system and method for multi-cycle hydrolysis of acid and alkali solutions. It can not only accurately evaluate the processing quality of soft rock samples, but also effectively optimize the disintegration test process. By refining the processing of the target soft rock samples and evaluating their processing quality coefficient in real time, it ensures that each soft rock sample meets the test standards as much as possible, thereby improving the processing quality of the target soft rock samples and reducing material waste. Furthermore, by collecting and analyzing the apparent parameters of the soft rock samples, compliant samples are screened out, further ensuring the effectiveness of the test. In addition, by uniformly grouping the compliant soft rock samples and conducting multi-cycle hydrolysis tests, it not only helps to gain a deeper understanding of the disintegration characteristics of soft rock under different conditions, but also allows for the analysis of the compliance index of the soaking process by collecting soaking process parameters, thereby flexibly adjusting the test conditions and improving the test efficiency. Finally, each group of compliant soft rock samples is dried and the experimental result parameters are collected to scientifically determine whether the test needs to be conducted again, so as to ensure the comprehensiveness and accuracy of the test results.

[0014] (2) This invention collects the apparent parameters of each soft rock sample, analyzes the apparent compliance factor of each soft rock sample, thereby marking each compliant soft rock sample, and uniformly groups each compliant soft rock sample to obtain each group of compliant soft rock samples. This ensures that only compliant soft rock samples that meet the standards are included in subsequent tests, effectively avoiding experimental errors caused by unqualified samples, and greatly improving the accuracy and reliability of the experiment. This makes the subsequent acid and alkali solution multi-cycle hydrolysis and disintegration test experiment more comprehensive and representative.

[0015] (3) This invention collects the soaking process parameters of each group of compliant soft rock samples and analyzes the compliance index of the soaking process of each group of compliant soft rock samples. Based on this, it determines whether the soaking process parameters of each group of soft rock samples need to be adjusted. This process not only ensures the high stability and controllability of the experimental conditions and lays a solid foundation for the accuracy and reliability of the experimental results, but also provides a clear and definite guiding idea for the subsequent precise adjustment of the soaking process parameters based on the compliance index. This fine control of key variable parameters effectively avoids the interference that may be introduced due to abnormal changes in parameters during the experiment, thereby ensuring the smooth progress of the entire experimental process and the accuracy of the experimental results. Attached Figure Description

[0016] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0018] Figure 2 This is a schematic diagram of the method steps of the present invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0020] Reference Figure 1 As shown, the first aspect of the present invention provides a soft rock disintegration test system based on multi-cycle hydrolysis of acid and alkali solutions, comprising: a soft rock processing module, a soft rock selection module, a soft rock soaking module, and a data collection module.

[0021] The first aspect of this invention provides a soft rock disintegration test system based on multi-cycle hydrolysis of acid and alkali solutions, and further includes a test database. The test database stores the following parameters: defined cutting speed fluctuation value, reference average coolant supply rate, defined average vibration amplitude, influence coefficient of cutting speed fluctuation value, influence coefficient of average coolant supply rate, influence coefficient of average vibration amplitude, soft rock reference cutting speed, average machining quality coefficient weighting factor, apparent density reference value, defined average porosity, apparent density influence value, influence value of average porosity, influence value of profile curve deviation rate, reference profile curve, weighting factor of average machining quality coefficient, weighting factor of average apparent compliance factor, influence coefficient of maximum pH deviation value, influence coefficient of maximum pH change rate, influence coefficient of pH compliance duration, influence coefficient of minimum pH deviation value, machining quality threshold, immersion process compliance threshold, apparent compliance threshold, and machining parameter adjustment set corresponding to each machining quality coefficient interval.

[0022] The soft rock processing module is connected to the soft rock selection module, the soft rock selection module is connected to the soft rock soaking module, the soft rock soaking module is connected to the data collection module, and the soft rock processing module, soft rock selection module, soft rock soaking module and data collection module are all connected to the test database.

[0023] The soft rock processing module is used to process the target soft rock sample, obtain the processing parameters of the target soft rock sample, evaluate the processing quality coefficient of the target soft rock sample, compare it with the processing quality threshold, and determine whether to adjust the processing parameters of the target soft rock sample until the processing of the target soft rock sample is completed, and obtain each soft rock sample.

[0024] The target soft rock samples were selected by the experimenters from fresh rocks, marked as target soft rock samples, and then wrapped in plastic wrap and transported back to the laboratory. The retrieved target soft rock samples were processed into various soft rock samples. However, since deviations may occur during the processing and cutting of the target soft rock samples, it is necessary to select compliant soft rock samples that meet the requirements of the experimenters from each soft rock sample to ensure the rigor of the experiment.

[0025] Specifically, the determination of whether to adjust the processing parameters of the target soft rock sample is as follows: the processing quality coefficient of the target soft rock sample is compared with the processing quality threshold. If the processing quality coefficient of the target soft rock sample is greater than the processing quality threshold, it is determined that the processing parameters of the target soft rock sample will not be adjusted. The aforementioned processing quality threshold represents the minimum value of the reasonable range of the processing quality coefficient of the target soft rock sample, which is extracted from the test database.

[0026] If the processing quality coefficient of the target soft rock sample is less than or equal to the processing quality threshold, it is determined that the processing parameters of the target soft rock sample should be adjusted. The specific adjustment process is as follows: the processing quality coefficient of the target soft rock sample is matched with the processing parameter adjustment set corresponding to each processing quality coefficient interval stored in the test database, thereby obtaining and executing the processing parameter adjustment set of the target soft rock sample; after the adjustment is completed, the processing quality coefficient of the target soft rock sample in the next adjacent processing monitoring sub-cycle is evaluated, and it is determined whether to adjust the processing parameters of the target soft rock sample, until the processing of the target soft rock sample is completed and each soft rock sample is obtained; in an example embodiment, it is assumed that the processing quality coefficient of the target soft rock sample is YU, which belongs to the processing quality coefficient interval [YU-10%, YU+] stored in the test database. Assuming the processing quality threshold is YO, the processing parameter adjustment set corresponding to the processing quality coefficient range [YU-10%, YU+10%) is the processing parameter adjustment set for the target soft rock sample matched with the processing quality coefficient YU. This processing parameter adjustment set for the target soft rock sample includes: averaging the real-time cutting speed of the processing equipment to which the target soft rock sample belongs within the processing monitoring sub-cycle to obtain the average cutting speed of the processing equipment to which the target soft rock sample belongs within the processing monitoring sub-cycle; extracting the soft rock reference cutting speed from the test database; if the average cutting speed of the processing equipment to which the target soft rock sample belongs within the processing monitoring sub-cycle is greater than the soft rock reference cutting speed, then reducing the average cutting speed of the processing equipment to which the target soft rock sample belongs in the next adjacent processing monitoring sub-cycle. If the average cutting speed of the processing equipment used to process the target soft rock sample is less than the reference cutting speed for soft rock during the processing monitoring sub-cycle, then the average cutting speed of the processing equipment used to process the target soft rock sample during the next adjacent processing monitoring sub-cycle will be increased by [number]. The average coolant supply rate of the processing equipment for the target soft rock sample during the processing monitoring sub-cycle is compared with the average coolant supply rate of the reference coolant. If the average coolant supply rate of the processing equipment for the target soft rock sample during the processing monitoring sub-cycle is greater than the average coolant supply rate of the reference coolant, then the average coolant supply rate of the processing equipment for the target soft rock sample in the next adjacent processing monitoring sub-cycle is reduced. If the average coolant supply rate of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle is less than the reference average coolant supply rate, then the average coolant supply rate of the processing equipment to which the target soft rock sample belongs during the next adjacent processing monitoring sub-cycle will be increased. times.

[0027] It should be explained that if the processing quality coefficient of the target soft rock sample is less than or equal to the processing quality threshold, it usually means that the cutting speed or average coolant supply rate is not set properly during processing. A rapid response is needed to adjust the cutting speed and average coolant supply rate of the processing equipment for the target soft rock sample in the next adjacent processing monitoring sub-cycle. Since the processing monitoring sub-cycle is short, the adjustment of the processing parameters for the target soft rock sample can be considered real-time. This real-time parameter adjustment strategy aims to quickly correct any deviations in the cutting speed and coolant supply rate, thereby adjusting the processing state to within the range required by the experiment. It should also be noted that the reference cutting speed and reference average coolant supply rate for soft rock primarily serve as a benchmark to determine whether the current processing parameters are too high or too low, thus determining the direction of adjustment. The specific adjustment range still needs to be determined based on the processing quality coefficient and processing quality threshold of the target soft rock sample.

[0028] Furthermore, the processing quality coefficient of the target soft rock sample is evaluated, and the specific evaluation process is as follows: The processing parameters of the target soft rock sample include the real-time spindle speed of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle, the average coolant supply rate of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle, and the average vibration amplitude of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle. The aforementioned processing monitoring sub-cycle represents the time period for monitoring the processing of the target soft rock sample, and the specific duration is determined by the processing equipment management personnel. It should be explained that the time period for monitoring the processing of the target soft rock sample is divided into several processing monitoring sub-cycles, and one soft rock sample is processed in each processing monitoring sub-cycle. The aforementioned real-time spindle speed represents the rotational speed of the spindle of the processing equipment used to process the target soft rock sample at any time during the processing monitoring sub-cycle, which is measured by a speed sensor. The aforementioned average coolant supply rate represents the average value of the coolant supply rate of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle, which can be monitored by a flow sensor. The aforementioned average vibration amplitude represents the average value of the overall vibration amplitude of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle, which can be monitored by a vibration sensor.

[0029] The circumference of the blade of the processing equipment to which the target soft rock sample belongs is obtained and multiplied with the real-time spindle speed of the processing equipment during the processing monitoring sub-cycle to obtain the real-time cutting speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. The blade circumference of the processing equipment to which the target soft rock sample belongs refers to the circumference of the blade used to directly cut the target soft rock sample in the processing equipment, which can be extracted from the specifications of the processing equipment. The blade type includes, but is not limited to, circular saw blades. The real-time cutting speed refers to the cutting speed of the processing equipment to which the target soft rock sample belongs at any time during the processing monitoring sub-cycle.

[0030] Each sampled cutting speed is located from the real-time cutting speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. The standard deviation of each sampled cutting speed is processed, and the result is marked as the cutting speed fluctuation value of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. Each sampled cutting speed refers to a number of real-time cutting speeds located from the real-time cutting speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle using a random algorithm (e.g., a linear congruential algorithm). The cutting speed fluctuation value is used to quantify the degree of fluctuation of the cutting speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle.

[0031] By comprehensively analyzing the cutting speed fluctuation value, the average coolant supply rate, and the average vibration amplitude of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle, a processing quality coefficient for the target soft rock sample is obtained. This processing quality coefficient is used to comprehensively quantify the degree of stability and high quality achieved by the processing equipment during the processing of the target soft rock sample.

[0032] The processing quality coefficient of the target soft rock sample is specifically evaluated using the following method: ; In the formula, The processing quality coefficient of the target soft rock sample. This represents the cutting speed fluctuation value of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle. The average coolant supply rate of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle. The average vibration amplitude of the processing equipment used to process the target soft rock sample during the processing monitoring sub-cycle. To test the preset cut speed fluctuation values ​​in the database, To test the preset reference average coolant supply rate in the database, To test the predefined average vibration amplitude in the database, To test the influence coefficient of the preset cutting speed fluctuation value in the database, To test the influence coefficient of the average coolant supply rate preset in the database, The average vibration amplitude influence coefficient is preset in the test database.

[0033] The aforementioned definition of cutting speed fluctuation value represents the maximum allowable value of cutting speed fluctuation value of the processing equipment to which the target soft rock sample belongs within the processing monitoring sub-cycle. The aforementioned reference average coolant supply rate represents the reference value of the average coolant supply rate of the processing equipment to which the target soft rock sample belongs within the processing monitoring sub-cycle. The main purpose of this reference value is to serve as a benchmark to assess whether the coolant supply rate is too high or too low during actual processing. However, it should be noted that simply adjusting the coolant supply rate to the reference value does not directly guarantee a reduction in cutting speed fluctuation value and average vibration amplitude. It is necessary to comprehensively optimize and determine the optimal coolant supply rate based on actual operation to achieve the purpose of reducing cutting speed fluctuation value and average vibration amplitude. The aforementioned definition of average vibration amplitude represents the maximum allowable value of average vibration amplitude of the processing equipment to which the target soft rock sample belongs within the processing monitoring sub-cycle.

[0034] The aforementioned cutting speed fluctuation value influence coefficient represents the degree of influence of the unit value of cutting speed fluctuation value on the machining quality coefficient of the target soft rock sample; the aforementioned coolant average supply rate influence coefficient represents the degree of influence of the unit value of coolant average supply rate on the machining quality coefficient of the target soft rock sample; the aforementioned average vibration amplitude influence coefficient represents the degree of influence of the unit value of average vibration amplitude on the machining quality coefficient of the target soft rock sample. The test database stores the correspondence between cutting speed fluctuation value and its corresponding influence coefficient, the correspondence between coolant average supply rate and its corresponding influence coefficient, and the correspondence between average vibration amplitude and its corresponding influence coefficient. For example, by inputting the cutting speed fluctuation value, coolant average supply rate, and average vibration amplitude into the test database, the test database can match the cutting speed fluctuation value influence coefficient, coolant average supply rate influence coefficient, and average vibration amplitude influence coefficient, all of which have values ​​between 0 and 1.

[0035] It should be explained that an increase in cutting speed fluctuations often has adverse effects on the machining process. It can lead to instability in cutting forces, which in turn intensifies vibrations in the machining equipment, manifesting as an increase in the average vibration amplitude. This increased vibration not only reduces the machining accuracy and surface quality of the target soft rock sample but may also accelerate tool wear and shorten its lifespan. Simultaneously, if the average coolant supply rate is significantly lower than the corresponding reference value, the machining equipment will not receive sufficient cooling and lubrication. This will prevent the heat generated during cutting from dissipating in time, causing the cutting temperature to rise and resulting in thermal deformation of the cutting tool and workpiece. Thermal deformation alters the relative positional relationship between the cutting tool and the target soft rock sample, increasing instability during the cutting process and thus triggering or exacerbating [the problem]. The vibration amplitude of the processing equipment, and excessive coolant may also change the lubrication state of the cutting area, resulting in uneven distribution of cutting force, which may also increase the vibration amplitude of the processing equipment. Therefore, the interaction between the cutting speed fluctuation value, the average coolant supply rate and the average vibration amplitude parameter during processing has a negative impact, which may cause the target soft rock sample to generate more cracks and pores during processing. These defects will not only damage the structural integrity of the soft rock sample, but may also affect its performance in subsequent acid and alkali solution multi-cycle hydrolysis and disintegration tests. Specifically, due to the cracks and pores introduced during processing, the soft rock sample may not be able to accurately simulate the disintegration behavior under real environment in the test experiment, thereby reducing the accuracy and reliability of the test results.

[0036] The soft rock selection module is used to collect the apparent parameters of each soft rock sample, analyze the apparent compliance factor of each soft rock sample, thereby marking each compliant soft rock sample, uniformly grouping each compliant soft rock sample to obtain each group of compliant soft rock samples, and conducting a disintegration test experiment of acid and alkali solution multi-cycle hydrolysis on each group of compliant soft rock samples.

[0037] In one example embodiment, the disintegration test experiment of the above-mentioned acid-base solution multi-cycle hydrolysis is carried out in the following steps: 1. Prepare soaking solution for each group of compliant soft rock samples using sulfuric acid and sodium hydroxide; 2. Weigh each group of compliant soft rock samples and place them in a transparent container, pour in the pre-prepared soaking solution until the rock samples are submerged, label the corresponding pH value, and place the container in a constant temperature chamber. The constant temperature chamber is set to the target constant temperature (in one example embodiment, the target constant temperature can be 25 degrees Celsius). In the experiment, an acid-base titrator is used to maintain the pH of the soaking solution between the corresponding reference maximum pH and reference minimum pH; 3. Soak for the target time (in one example embodiment, the target time can be 48 hours), pour out the supernatant of the corresponding container of each group of compliant soft rock samples, and then transfer the remaining liquid along with the sample into the test chamber. 4. Place each group of containers in an oven and dry them to the target weight at the target drying temperature (in one example embodiment, the target drying temperature can be 105 degrees Celsius) for no less than 8 hours; 5. After drying, take out the samples from each group of containers and place them in a desiccator to cool to room temperature. Based on the coarse sieving requirements and the characteristics of the test samples, select each sieve (e.g., particle size distribution of 100 mm, 50 mm, 10 mm, 5 mm, 2 mm, and 1 mm) to sieve each group of compliant soft rock samples; 6. Summarize the samples on each sieve corresponding to each group of compliant soft rock samples to obtain the average particle size of each group of compliant soft rock samples. According to the disintegration situation, the test is carried out in cycles of hydrolysis until the particle size change rate of each group of compliant soft rock samples is greater than the reference particle size change rate.

[0038] The target constant temperature, target duration, target drying temperature, and each sample sieve mentioned above were all determined by the experimenters based on the purpose and requirements of the experiment, the properties of the experimental materials, and the physicochemical changes during the experiment.

[0039] In one specific embodiment, the present invention collects the apparent parameters of each soft rock sample, analyzes the apparent compliance factor of each soft rock sample, thereby marking each compliant soft rock sample, and uniformly groups the compliant soft rock samples to obtain each group of compliant soft rock samples. This ensures that only compliant soft rock samples that meet the standards are included in subsequent tests, effectively avoiding experimental errors caused by unqualified samples, and greatly improving the accuracy and reliability of the experiment. As a result, the subsequent acid and alkali solution multi-cycle hydrolysis and disintegration test experiments are more comprehensive and representative.

[0040] Specifically, the marking process for each compliant soft rock sample is as follows: An apparent compliance threshold is extracted from the test database, and the apparent compliance factor of each soft rock sample is compared with the apparent compliance threshold. Several soft rock samples with apparent compliance factors greater than the apparent compliance threshold are marked as compliant soft rock samples. The compliant soft rock samples are then grouped according to preset grouping requirements. The aforementioned apparent compliance threshold represents the minimum reasonable range of the apparent compliance factor for each soft rock sample, extracted from the test database. It should be explained that by adjusting the processing parameters of the target soft rock samples, it can be ensured that most (over 90%) of the soft rock samples are compliant samples. However, for the rigor of the experiment, further screening is required. Several soft rock samples with apparent compliance factors less than or equal to the apparent compliance threshold are recycled. In one example embodiment, the aforementioned preset grouping requirements refer to dividing each compliant soft rock sample equally into several groups. This means that each group of samples is similar in quantity, quality, or representativeness to ensure the fairness and accuracy of the experimental results. Equal grouping helps eliminate the influence of differences between samples on the experimental results, making comparisons between different groups more meaningful.

[0041] By setting different pH values ​​from acidic to alkaline, the performance of soft rock samples under different acidic and alkaline environments can be comprehensively evaluated, thereby gaining a more accurate understanding of the properties and application potential of soft rock samples. Therefore, in an example embodiment, the experimenter sets the target number of compliant soft rock samples, such as 7 groups, and the pH value of each group corresponds to different target pH values, such as 4, 5, 6, 7, 8, 9 and 10.

[0042] Specifically, the apparent compliance factors of each soft rock sample were analyzed, and the specific analysis process is as follows: The apparent parameters of each soft rock sample include its apparent volume, mass, porosity of each detection location region, and profile curve. The apparent volume refers to the total volume of each soft rock sample including all its voids (such as pores and cracks), which can be measured using 3D scanning technology (such as a 3D scanner). The mass of each soft rock sample refers to its weight. The porosity refers to the ratio of the area occupied by pores to the total area of ​​the detection region within each detection location region. The mass of each soft rock sample and the porosity of each detection location region can be obtained by the experimenter through upload, and each detection region is determined by the experimenter. The profile curve represents the shape curve of the surface of each soft rock sample, which can be measured using 3D scanning technology (such as a 3D scanner).

[0043] The apparent volume of each soft rock sample is compared with the mass of the corresponding soft rock sample to obtain the apparent density of each soft rock sample. The apparent density refers to the mass of each soft rock sample per unit external volume (including internal closed pores), which describes the density of each soft rock sample including its internal voids.

[0044] The porosity of each soft rock sample at each detection location is averaged to obtain the average porosity of each soft rock sample, which represents the average porosity of the detection location area of ​​each soft rock sample.

[0045] The total number of processing monitoring sub-cycles and the processing quality coefficient of the target soft rock sample corresponding to each processing monitoring sub-cycle are obtained. The processing quality coefficients of the target soft rock sample corresponding to each processing monitoring sub-cycle are accumulated and divided by the total number of processing monitoring sub-cycles to obtain the average processing quality coefficient of the target soft rock sample. This average coefficient is used to comprehensively quantify the stability and high quality achieved by the processing equipment in the process of processing the target soft rock sample. The total number of processing monitoring sub-cycles and the processing quality coefficient of the target soft rock sample corresponding to each processing monitoring sub-cycle can be extracted from the data analysis and processing log. Each time a processing monitoring sub-cycle and the corresponding processing quality coefficient of the target soft rock sample are analyzed, they are immediately recorded in the data analysis and processing log.

[0046] The contour curves of each soft rock sample are compared with a reference contour curve to obtain the contour curve deviation rate of each soft rock sample. This rate is used to quantify the degree of deviation between the contour curves of each soft rock sample and the reference contour curve. By inputting the contour curves of each soft rock sample and the reference contour curve into image processing software (such as Matrix Lab), operations such as translation, rotation, and scaling can be used to make the contour curves of each soft rock sample as close to the reference contour curve as possible. After the comparison, the deviation value between the contour curve of each soft rock sample and the reference contour curve is calculated point by point. The deviation value can be the shortest straight-line distance between corresponding points on the contour curve of each soft rock sample and the reference contour curve. By obtaining the deviation values ​​of each point on the contour curve of each soft rock sample and accumulating them, the accumulated result is compared with the total length of the reference contour curve to obtain the contour curve deviation rate of each soft rock sample. The aforementioned reference contour curve represents the reference standard for the contour curves of each soft rock sample, which is established by the experimenters and stored in the test database.

[0047] By comprehensively analyzing the apparent density, average porosity, profile curve deviation rate, and average processing quality coefficient of each soft rock sample, the apparent compliance factor of each soft rock sample is obtained. The apparent compliance factor of each soft rock sample is used to comprehensively quantify the compliance degree of the surface state of each soft rock sample after processing and cutting.

[0048] Furthermore, the apparent compliance factor of each soft rock sample is analyzed using the following specific method: ; In the formula, Let p be the apparent compliance factor for the p-th soft rock sample. The average processing quality coefficient of the target soft rock sample. The average processing quality coefficient weighting factor is preset in the test database. Let p be the apparent density of the p-th soft rock sample. Let p be the average porosity of the p-th soft rock sample. Let be the profile curve deviation rate of the p-th soft rock sample. To test the preset apparent density reference value in the database, To test the predefined average porosity in the database, To test the effect value of the pre-defined apparent density in the database, To test the influence value of the preset average porosity in the database, The influence value of the profile curve deviation rate preset in the test database is used, where p is the number of each soft rock sample. x is the total number of soft rock samples, and e is a natural constant.

[0049] The aforementioned apparent density reference value represents the reference value of the apparent density of the p-th soft rock sample; the aforementioned defined average porosity represents the maximum allowable average porosity of the p-th soft rock sample; based on the expected processing and application requirements, the experimenter will set a target apparent density reference value; based on historical performance statistical analysis and expected processing quality, the experimenter will set a maximum allowable average porosity, which is usually determined based on the minimum requirements to ensure the performance of the soft rock sample, in order to identify large deviations that may occur during the processing.

[0050] The aforementioned average processing quality coefficient weighting factor represents the proportion of the average processing quality coefficient in the apparent compliance factor. The test database stores the correspondence between the average processing quality coefficient and its corresponding weighting factor. For example, by inputting the average processing quality coefficient into the test database, the test database can match the average processing quality coefficient weighting factor, with values ​​ranging from 0 to 1. The aforementioned apparent density influence value represents the degree of influence of the unit value of apparent density on the apparent compliance factor. The aforementioned average porosity influence value represents the degree of influence of the unit value of average porosity on the apparent compliance factor. The aforementioned profile curve deviation rate influence value represents the degree of influence of the unit value of profile curve deviation rate on the apparent compliance factor. The test database stores the correspondence between apparent density and its corresponding influence value, the correspondence between average porosity and its corresponding influence value, and the correspondence between profile curve deviation rate and its corresponding influence value. For example, by inputting apparent density, average porosity, and profile curve deviation rate into the test database, the test database can match the influence values ​​of apparent density, average porosity, and profile curve deviation rate, with values ​​ranging from 0 to 1.

[0051] It needs to be explained that if the average processing quality coefficient of the target soft rock sample is at a low level, this will directly lead to the generation of more cracks and pores inside each soft rock sample during processing. The introduction of these defects not only affects the overall structural integrity of the soft rock sample, but also significantly changes its physical properties under the same volume conditions. Here, it is emphasized that "same volume" is used by the experimenters to ensure the principle of controlled variables in the experiment, keeping the size of the soft rock sample (such as volume and profile curve) consistent, so as to accurately assess the impact of processing quality on sample performance. Under the same volume, due to the presence of cracks and pores, the apparent density of the soft rock sample will deviate significantly from its preset reference value. This is because apparent density is the ratio of mass to volume, and cracks and pores reduce the actual mass of the material, but the volume remains unchanged, thus leading to a decrease in apparent density. At the same time, cracks and pores... An increase in porosity also signifies a significant rise in average porosity. This increase alters the profile of the soft rock sample, causing it to deviate significantly from the expected reference curve. This deviation reflects the irregularity and inaccuracy of the soft rock sample. As both average porosity and profile deviation rate reach high levels, the apparent compliance of the soft rock sample decreases significantly. This makes the hydrolysis reaction of the soft rock sample in acidic and alkaline solutions more complex and unpredictable. These defects may become preferential pathways for hydrolysis, accelerating the sample disintegration process or causing the disintegration pattern to deviate from expectations. Therefore, when using these poorly processed soft rock samples for experiments, the data obtained will be difficult to accurately reflect the hydrolysis and disintegration behavior of soft rock under actual conditions. Consequently, soft rock samples with apparent compliance factors less than the apparent compliance threshold are not suitable for further experiments.

[0052] The soft rock soaking module is used to collect soaking process parameters of each group of compliant soft rock samples and analyze the soaking process compliance index of each group of compliant soft rock samples, thereby determining whether to adjust the soaking process parameters of each group of soft rock samples.

[0053] In one specific embodiment, the present invention collects the soaking process parameters of each group of compliant soft rock samples and analyzes the compliance index of the soaking process of each group of compliant soft rock samples. Based on this, it determines whether the soaking process parameters of each group of soft rock samples need to be adjusted. This process not only ensures the high stability and controllability of experimental conditions, laying a solid foundation for the accuracy and reliability of experimental results, but also provides a clear and explicit guiding approach for subsequent precise adjustment of soaking process parameters based on the compliance index. This fine control of key variable parameters effectively avoids interference that may be introduced due to abnormal changes in parameters during the experiment, thereby ensuring the smooth progress of the entire experimental process and the accuracy of the experimental results.

[0054] Specifically, the determination of whether to adjust the soaking process parameters of each group of soft rock samples is as follows: the soaking process compliance index of each group of compliant soft rock samples is compared with the soaking process compliance threshold. If the soaking process compliance index of a certain group of compliant soft rock samples is greater than the soaking process compliance threshold, it is determined that the soaking process parameters of that group of compliant soft rock samples will not be adjusted. The aforementioned soaking process compliance threshold represents the minimum value of the reasonable range of the soaking process compliance index of each group of compliant soft rock samples, and is extracted from the test database.

[0055] If the compliance index of a certain group of compliant soft rock samples during the soaking process is less than or equal to the compliance threshold, then the soaking process parameters of that group of compliant soft rock samples are determined to be adjusted. The specific adjustment process is as follows: Obtain the criteria for determining the compliance index of the soaking process of that group of compliant soft rock samples, and adjust the soaking process parameters of that group of compliant soft rock samples comprehensively based on the compliance index, the compliance threshold, and the criteria for determining the compliance index. The criteria for determining the compliance index of the soaking process of that group of compliant soft rock samples are the maximum pH deviation value of that group of compliant soft rock samples within the soaking detection sub-cycle and the pH deviation value of that group of compliant soft rock samples. The relationship between the minimum pH deviation of the samples during the soaking and testing sub-cycle; in an example embodiment, if the compliance index of a certain group of compliant soft rock samples during the soaking process is less than or equal to the compliance threshold of the soaking process, assuming the compliance index of the g-th group of compliant soft rock samples is GH and the compliance threshold of the soaking process is GHJT, if the maximum pH deviation of the g-th group of compliant soft rock samples during the soaking and testing sub-cycle is greater than the minimum pH deviation of the g-th group of compliant soft rock samples during the soaking and testing sub-cycle, it indicates that the pH of the soaking solution of the g-th group of compliant soft rock samples is increasing during the soaking and testing sub-cycle. Therefore, it is necessary to reduce the titration rate of the alkaline solution in the acid-base titrator, reducing the existing speed. If the maximum pH deviation of the compliant soft rock sample in group g during the immersion testing sub-cycle is less than the minimum pH deviation, it indicates that the immersion solution of the compliant soft rock sample in group g shows a decreasing pH trend during the immersion testing sub-cycle. Therefore, it is necessary to reduce the titration rate of the acidic solution in the acid-base titrator, lowering the existing rate. If the maximum pH deviation of the compliant soft rock sample in group g during the immersion testing sub-cycle is equal to the minimum pH deviation of the compliant soft rock sample in group g during the immersion testing sub-cycle, it indicates that the titration rates of both acidic and alkaline solutions in the acid-base titrator are too high, making it impossible to stabilize the pH of the immersion solution. Therefore, the titration rates of both acidic and alkaline solutions in the acid-base titrator should be reduced to their current rates. times.

[0056] After the adjustment is completed, the compliance index of the soaking process of each group of compliant soft rock samples in the next adjacent soaking test sub-cycle is evaluated, and it is determined whether the soaking process parameters of each group of soft rock samples should be adjusted until the soaking process of each group of soft rock samples is completed.

[0057] Furthermore, the analysis of the compliance index of the soaking process of each group of compliant soft rock samples is as follows: The soaking process parameters of each group of compliant soft rock samples include the pH change curve of each group of compliant soft rock samples during the soaking detection sub-cycle. This curve represents the change of pH of each group of compliant soft rock samples over time during the soaking detection sub-cycle. The pH of the soaking solution of each group of compliant soft rock samples detected by the acid-base titrator during the soaking detection sub-cycle, along with the corresponding timestamp, can be input into data processing software (such as Matrix Laboratory) to plot the pH change curve of each group of compliant soft rock samples during the soaking detection sub-cycle. The aforementioned soaking detection sub-cycle represents the time period for monitoring the soaking process of each group of compliant soft rock samples. The specific duration is determined by the experimenters. It should be explained that the time period for monitoring the soaking process of each group of compliant soft rock samples is evenly divided into several soaking detection sub-cycles.

[0058] The maximum and minimum values ​​of the pH change curves of each group of compliant soft rock samples during the immersion testing sub-cycle were located and marked as the maximum and minimum pH values ​​of each group of compliant soft rock samples during the immersion testing sub-cycle, respectively. These values ​​can be obtained using data processing software (such as Matrix Laboratory). The maximum pH value represents the maximum pH value of the immersion solution for each group of compliant soft rock samples during the immersion testing sub-cycle; the minimum pH value represents the minimum pH value of the immersion solution for each group of compliant soft rock samples during the immersion testing sub-cycle.

[0059] Obtain the reference maximum and minimum pH values ​​for each group of compliant soft rock samples. Compare the maximum pH value of each group of compliant soft rock samples within the immersion testing sub-cycle with the corresponding reference maximum pH value to obtain the maximum pH deviation value for each group of compliant soft rock samples within the immersion testing sub-cycle. The aforementioned reference maximum pH value represents the maximum permissible pH value of the immersion solution for each group of compliant soft rock samples within the immersion testing sub-cycle. The aforementioned reference minimum pH value represents the maximum permissible pH value of the immersion solution for each group of compliant soft rock samples within the immersion testing sub-cycle. The minimum pH value is set. For example, if the pH value of the soaking solution for a certain combination is set to 8, and the soaking solution is allowed to fluctuate within 0.5 above or below the corresponding pH value, then the reference maximum pH value for that group is 8.5, and the reference minimum pH value is 7.5. The reference maximum pH value and the reference minimum pH value for each group of compliant soft rock samples are determined by the experimenters. The maximum pH value deviation of each group of compliant soft rock samples within the soaking test sub-cycle represents the difference between the maximum pH value of each group of compliant soft rock samples within the soaking test sub-cycle and the reference maximum pH value. If the maximum pH value deviation is large, it indicates that the titration rate of the alkaline solution needs to be reduced.

[0060] The reference minimum pH of each group of compliant soft rock samples is compared with the minimum pH of each group of compliant soft rock samples during the immersion test sub-cycle. The difference is then processed to obtain the minimum pH deviation value of each group of compliant soft rock samples during the immersion test sub-cycle. This value represents the difference between the reference minimum pH and the minimum pH of each group of compliant soft rock samples during the immersion test sub-cycle. If the minimum pH deviation value is large, it indicates that the titration rate of the acidic solution needs to be reduced.

[0061] Data processing was performed on the pH change curves of each group of compliant soft rock samples during the immersion testing sub-cycle to obtain the maximum pH change rate and the pH compliance duration for each group of compliant soft rock samples during the immersion testing sub-cycle. The specific data processing procedure for the maximum pH change rate of each group of compliant soft rock samples during the immersion testing sub-cycle was as follows: Data processing software (such as Matrix Laboratory) was used to process the absolute value of the difference between the pH at each time point and the pH at the previous adjacent time point on the pH change curve of each group of compliant soft rock samples during the immersion testing sub-cycle. This value was then divided by the interval between the corresponding adjacent time points to obtain the pH value at any time point within the immersion testing sub-cycle for each group of compliant soft rock samples. The pH change rate represents the rate of pH change of each group of compliant soft rock samples at any time point within the immersion testing sub-cycle. The maximum value extracted from the pH change rate of each group of compliant soft rock samples at any time point within the immersion testing sub-cycle is the maximum pH change rate of each group of compliant soft rock samples within the immersion testing sub-cycle, representing the maximum level of pH change rate of each group of compliant soft rock samples within the immersion testing sub-cycle. The pH compliance duration of each group of compliant soft rock samples within the immersion testing sub-cycle represents the duration for which the pH of each group of compliant soft rock samples is controlled between the corresponding maximum and minimum reference pH within the immersion testing sub-cycle, which can be obtained through data processing software (such as Matrix Laboratory).

[0062] The average apparent compliance factor of each group of compliant soft rock samples is obtained, which represents the average compliance degree of the surface state of each group of soft rock samples after processing and cutting. It is obtained by averaging the apparent compliance factors of each compliant soft rock sample in each group of compliant soft rock samples. The apparent compliance factor of the compliant soft rock sample can be obtained from the apparent compliance factor of each soft rock sample.

[0063] By comprehensively analyzing the average processing quality coefficient of the target soft rock samples, the average apparent compliance factor of each group of compliant soft rock samples, the maximum pH deviation of each group of compliant soft rock samples during the immersion testing sub-cycle, the minimum pH deviation of each group of compliant soft rock samples during the immersion testing sub-cycle, the maximum pH change rate of each group of compliant soft rock samples during the immersion testing sub-cycle, and the pH compliance time of each group of compliant soft rock samples during the immersion testing sub-cycle, the immersion process compliance index of each group of compliant soft rock samples is obtained. The immersion process compliance index of each group of compliant soft rock samples is used to comprehensively quantify the degree of compliance of the immersion process of each group of compliant soft rock samples.

[0064] The compliance index of the soaking process for each group of compliant soft rock samples was analyzed using the following method: ; In the formula, Let be the compliance index of the soaking process for the k-th compliant soft rock sample, where k is the sample number of each compliant soft rock sample group. f is the total number of compliant soft rock samples. The average processing quality coefficient of the target soft rock sample. Let be the average apparent compliance factor of the k-th compliant soft rock sample. The weighting coefficients are the preset average processing quality coefficients in the test database. The average apparent compliance factor weighting coefficients are preset in the test database. This represents the maximum pH deviation value of the k-th compliant soft rock sample during the immersion testing sub-cycle. The maximum rate of change in pH of the k-th compliant soft rock sample during the immersion testing sub-cycle is given. The duration of pH compliance for the k-th compliant soft rock sample during the immersion testing sub-cycle. This represents the minimum pH deviation value of the k-th compliant soft rock sample during the immersion testing sub-cycle. The influence coefficient of the maximum pH deviation value preset in the test database. The influence coefficient of the maximum rate of change of pH value preset in the test database. To test the impact coefficient of pH compliance time preset in the database, The influence coefficient of the minimum pH deviation value preset in the test database.

[0065] The aforementioned average processing quality coefficient weighting coefficient represents the proportion of the average processing quality coefficient in the immersion process compliance index; the aforementioned average apparent compliance factor weighting coefficient represents the proportion of the average apparent compliance factor in the immersion process compliance index. The test database stores the correspondence between the average processing quality coefficient and its corresponding weighting coefficient, as well as the correspondence between the average apparent compliance factor and its corresponding weighting coefficient. For example, by inputting the average processing quality coefficient and the average apparent compliance factor into the test database, the test database can match the average processing quality coefficient weighting coefficient and the average apparent compliance factor weighting coefficient, both ranging from 0 to 1; the aforementioned maximum pH deviation value influence coefficient represents the numerical value of the influence of the unit value of the maximum pH deviation value on the immersion process compliance index; the aforementioned maximum pH change rate influence coefficient represents the numerical value of the influence of the unit value of the maximum pH change rate on the immersion process compliance index; the aforementioned pH... The pH compliance time influence coefficient represents the degree of influence of a unit value of pH compliance time on the compliance index of the soaking process; the minimum pH deviation value influence coefficient represents the degree of influence of a unit value of the minimum pH deviation value on the compliance index of the soaking process. The test database stores the correspondence between the maximum pH deviation value and its corresponding influence coefficient, the maximum pH change rate and its corresponding influence coefficient, the pH compliance time and its corresponding influence coefficient, and the minimum pH deviation value and its corresponding influence coefficient. For example, by inputting the maximum pH deviation value, the maximum pH change rate, the pH compliance time, and the minimum pH deviation value into the test database, the test database can match the influence coefficients of the maximum pH deviation value, the maximum pH change rate, the pH compliance time, and the minimum pH deviation value, all of which have values ​​between 0 and 1.

[0066] It should be explained that the compliance of the processing procedure plays a crucial role in the soaking of soft rock samples. Specifically, if the compliance of the processing procedure is low, the apparent compliance of the soft rock sample will also be reduced accordingly. When the apparent compliance of the soft rock sample is reduced, its internal structure and chemical composition may also be affected, making the sample more susceptible to abnormal erosion during subsequent soaking. This abnormal erosion not only leads to a decline in the physical properties of the soft rock sample, but may also trigger a series of chemical reactions, making it extremely difficult to control the pH of the soaking solution. In order to comprehensively evaluate the compliance of the soaking process of soft rock samples, the average processing quality coefficient, the average apparent compliance factor, and the compliance index of the soaking process are analyzed in a comprehensive manner.

[0067] It should also be explained that the pH of the soaking solution for each group of compliant soft rock samples is a crucial control parameter during the immersion testing process. To ensure the accuracy and reliability of the experiment, the pH of the soaking solution needs to be strictly controlled between the corresponding maximum and minimum reference pH, i.e., maintained within a reasonable range. When the pH of the soaking solution is within this reasonable range, pH changes will be relatively stable, and the maximum rate of pH change will remain at a low level. This stability not only helps to accurately assess the chemical stability of soft rock samples but also reduces experimental errors caused by pH fluctuations. However, in practice, the pH of the soaking solution may sometimes deviate from this reasonable range. When it is found that the pH of the soaking solution deviates from the reasonable range, it is necessary to adjust it by adding acidic or alkaline solutions to restore pH balance. The titration process of acidic or alkaline solutions is not always smooth. If the titration rate is abnormal, such as too fast or too slow, it may lead to rapid changes in pH, thereby increasing the pH deviation. An increase in pH deviation means that the pH of the soaking solution has been fluctuating over a period of time. If the pH value cannot be stabilized within the preset reasonable range, it will directly affect the pH compliance time. Specifically, an increase in pH deviation will shorten the pH compliance time, meaning that the soaking solution cannot continuously meet the pH compliance requirements for a period of time. Therefore, in order to maintain the stability of the pH of the soaking solution and ensure the accuracy and reliability of the experiment, it is necessary to strictly control the titration rate of acidic or alkaline solutions to avoid abnormal pH fluctuations caused by being too fast or too slow. At the same time, it is also necessary to monitor the pH of the soaking solution regularly in order to promptly detect and correct deviations from the reasonable range. Through these measures, the accuracy and reliability of the experimental results can be improved.

[0068] The data collection module is used to dry each group of compliant soft rock samples, collect the experimental result parameters of each group of compliant soft rock samples, and determine whether to conduct a disintegration test experiment with multiple cycles of acid and alkali hydrolysis again.

[0069] Specifically, the determination process for whether to conduct a disintegration test involving multiple cycles of acid-base hydrolysis is as follows: The experimental result parameters for each group of compliant soft rock samples include the average particle size of each group of compliant soft rock samples, which represents the average diameter of the soft rock particles after hydrolysis. This value is obtained by the experimenters. For example, if a particle with a diameter of 100 mm weighs 2 grams and a particle with a diameter of 50 mm weighs 3 grams, the contribution value of the particle with a diameter of 100 mm is calculated using a weighted average method as 100 mm × 2 g = 200 mm·g; similarly, the contribution value of the particle with a diameter of 50 mm is 50 mm × 3 g = 150 mm·g. Then, these two contribution values ​​are added together to obtain a total of 350 mm·g. Finally, the total is divided by the total weight of the particles, 5 grams, to obtain an average particle size of 70 mm.

[0070] Historical adjacent experimental results parameters for each group of compliant soft rock samples were obtained, namely, the historical adjacent average particle size of each group of compliant soft rock samples. The historical adjacent average particle size of each group of compliant soft rock samples was then compared with the average particle size of the corresponding group of compliant soft rock samples. The result was then compared with the historical adjacent average particle size of each group of compliant soft rock samples to obtain the particle size change rate of each group of compliant soft rock samples. This rate is used to quantify the degree of change in the average diameter of the soft rock particles after hydrolysis of each group of compliant soft rock samples relative to the historical adjacent average particle size. The aforementioned historical adjacent experimental results parameters for each group of compliant soft rock samples can be obtained from the data recorded by the experimenters during the overall experiment. The historical adjacent average particle size of each group of compliant soft rock samples represents the average particle size of the soft rock particles after hydrolysis of each group of compliant soft rock samples in the historical adjacent experimental results.

[0071] The particle size change rate of each group of compliant soft rock samples is compared with the reference particle size change rate. If the particle size change rate of a certain group of compliant soft rock samples is greater than the reference particle size change rate, then the compliant soft rock samples of that group will be subject to a disintegration test of acid-base solution multi-cycle hydrolysis again. If the particle size change rate of a certain group of compliant soft rock samples is less than or equal to the reference particle size change rate, then the compliant soft rock samples of that group will not be subject to a disintegration test of acid-base solution multi-cycle hydrolysis again. The aforementioned reference particle size change rate represents a reference value for the particle size change rate, which is determined by the experimenters.

[0072] In one specific embodiment, the present invention provides a soft rock disintegration test system based on multi-cycle hydrolysis with acid and alkali solutions. This system not only accurately assesses the processing quality of soft rock samples but also effectively optimizes the disintegration test process. By refining the processing of target soft rock samples and evaluating their processing quality coefficient in real time, it ensures that each soft rock sample meets the test standards as closely as possible, thereby improving the processing quality of target soft rock samples and reducing material waste. Furthermore, by collecting and analyzing the apparent parameters of soft rock samples, compliant samples are screened out, further ensuring the validity of the test. In addition, uniformly grouping compliant soft rock samples and conducting multi-cycle hydrolysis tests not only helps to gain a deeper understanding of the disintegration characteristics of soft rock under different conditions but also allows for the analysis of the soaking process compliance index by collecting soaking process parameters, thereby flexibly adjusting test conditions and improving test efficiency. Finally, each group of compliant soft rock samples is dried, and experimental result parameters are collected to scientifically determine whether further testing is necessary, ensuring the comprehensiveness and accuracy of the test results.

[0073] Reference Figure 2As shown, the second aspect of the present invention provides a method for testing the disintegration of soft rock by multi-cycle hydrolysis with acid and alkali solutions, comprising: Step 1, processing a target soft rock sample, obtaining processing parameters of the target soft rock sample, evaluating the processing quality coefficient of the target soft rock sample, comparing it with a processing quality threshold, and determining whether to adjust the processing parameters of the target soft rock sample, until the processing of the target soft rock sample is completed, thereby obtaining each soft rock sample; Step 2, collecting the apparent parameters of each soft rock sample, analyzing the apparent compliance factor of each soft rock sample, thereby marking each compliant soft rock sample. The samples were divided into uniform groups to obtain each group of compliant soft rock samples. A disintegration test using multiple cycles of acid and alkali hydrolysis was then performed on each group of compliant soft rock samples. Step three: The soaking process parameters of each group of compliant soft rock samples were collected, and the compliance index of the soaking process was analyzed to determine whether the soaking process parameters of each group of soft rock samples needed adjustment. Step four: Each group of compliant soft rock samples was dried, and the experimental results parameters of each group of compliant soft rock samples were collected to determine whether another disintegration test using multiple cycles of acid and alkali hydrolysis was necessary.

[0074] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A soft rock disintegration testing system based on multi-cycle hydrolysis with acid and alkali solutions, characterized in that, include: The soft rock processing module is used to process the target soft rock sample, obtain the processing parameters of the target soft rock sample, evaluate the processing quality coefficient of the target soft rock sample, compare it with the processing quality threshold, and determine whether to adjust the processing parameters of the target soft rock sample until the processing of the target soft rock sample is completed, and obtain each soft rock sample. The soft rock selection module is used to collect the apparent parameters of each soft rock sample, analyze the apparent compliance factor of each soft rock sample, thereby marking each compliant soft rock sample, uniformly grouping each compliant soft rock sample to obtain each group of compliant soft rock samples, and conducting a disintegration test experiment of acid and alkali solution multi-cycle hydrolysis on each group of compliant soft rock samples. The soft rock soaking module is used to collect soaking process parameters of each group of compliant soft rock samples and analyze the soaking process compliance index of each group of compliant soft rock samples, thereby determining whether to adjust the soaking process parameters of each group of soft rock samples. The data collection module is used to dry each group of compliant soft rock samples, collect the experimental result parameters of each group of compliant soft rock samples, and determine whether to conduct a disintegration test experiment with multiple cycles of acid and alkali hydrolysis again.

2. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The processing quality coefficient of the target soft rock sample was evaluated, and the specific evaluation process is as follows: The processing parameters of the target soft rock sample include the real-time spindle speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle, the average coolant supply rate of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle, and the average vibration amplitude of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. The circumference of the cutting tool of the processing equipment to which the target soft rock sample belongs is obtained, and multiplied with the real-time spindle speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle to finally obtain the real-time cutting speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. Each sampled cutting speed was located from the real-time cutting speed of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. The standard deviation of each sampled cutting speed was processed, and the processing result was marked as the cutting speed fluctuation value of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle. By comprehensively analyzing the cutting speed fluctuation value, the average coolant supply rate, and the average vibration amplitude of the processing equipment to which the target soft rock sample belongs during the processing monitoring sub-cycle, a processing quality coefficient for the target soft rock sample is obtained. This processing quality coefficient is used to comprehensively quantify the degree of stability and high quality achieved by the processing equipment during the processing of the target soft rock sample.

3. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The determination process for whether to adjust the processing parameters of the target soft rock sample is as follows: The processing quality coefficient of the target soft rock sample is compared with the processing quality threshold. If the processing quality coefficient of the target soft rock sample is greater than the processing quality threshold, it is determined that the processing parameters of the target soft rock sample will not be adjusted. If the processing quality coefficient of the target soft rock sample is less than or equal to the processing quality threshold, it is determined that the processing parameters of the target soft rock sample should be adjusted. The specific adjustment process is as follows: the processing quality coefficient of the target soft rock sample is matched with the processing parameter adjustment set corresponding to each processing quality coefficient interval stored in the test database, thereby obtaining and executing the processing parameter adjustment set of the target soft rock sample. After the adjustment is completed, the processing quality coefficient of the target soft rock sample in the next adjacent processing monitoring sub-cycle is evaluated, and it is determined whether the processing parameters of the target soft rock sample should be adjusted until the processing of the target soft rock sample is completed, and each soft rock sample is obtained.

4. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The apparent compliance factors of each soft rock sample were analyzed, and the specific analysis process is as follows: The apparent parameters of each soft rock sample include the apparent volume of each soft rock sample, the mass of each soft rock sample, the porosity of each detection location region of each soft rock sample, and the profile curve of each soft rock sample. The apparent density of each soft rock sample is obtained by comparing its apparent volume with its corresponding mass. The porosity of each soft rock sample at each detection location is averaged to obtain the average porosity of each soft rock sample. The total number of processing monitoring sub-cycles and the processing quality coefficient of the target soft rock sample corresponding to each processing monitoring sub-cycle are obtained. The processing quality coefficients of the target soft rock sample corresponding to each processing monitoring sub-cycle are accumulated and divided by the total number of processing monitoring sub-cycles to obtain the average processing quality coefficient of the target soft rock sample. The profile curves of each soft rock sample were compared with the reference profile curve to obtain the profile curve deviation rate of each soft rock sample. By comprehensively analyzing the apparent density, average porosity, profile curve deviation rate, and average processing quality coefficient of each soft rock sample, the apparent compliance factor of each soft rock sample is obtained. The apparent compliance factor of each soft rock sample is used to comprehensively quantify the compliance degree of the surface state of each soft rock sample after processing and cutting.

5. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 4, characterized in that: The apparent compliance factors of each soft rock sample were analyzed using the following methods: ； In the formula, Let p be the apparent compliance factor for the p-th soft rock sample. The average processing quality coefficient of the target soft rock sample. The average processing quality coefficient weighting factor is preset in the test database. Let p be the apparent density of the p-th soft rock sample. Let p be the average porosity of the p-th soft rock sample. Let be the profile curve deviation rate of the p-th soft rock sample. To test the preset apparent density reference value in the database, To test the predefined average porosity in the database, To test the effect value of the pre-defined apparent density in the database, To test the influence value of the preset average porosity in the database, The influence value of the profile curve deviation rate preset in the test database is used, where p is the number of each soft rock sample. x is the total number of soft rock samples, and e is a natural constant.

6. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The specific marking process for each compliant soft rock sample is as follows: Apparent compliance thresholds are extracted from the test database, and the apparent compliance factors of each soft rock sample are compared with the apparent compliance thresholds. Several soft rock samples with apparent compliance factors greater than the apparent compliance thresholds are marked as compliant soft rock samples. Thus, the compliant soft rock samples are grouped according to preset grouping requirements.

7. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The analysis determined the compliance index of the soaking process for each group of compliant soft rock samples. The specific analysis process is as follows: The soaking process parameters for each group of compliant soft rock samples include the pH change curves of each group of compliant soft rock samples during the soaking detection sub-cycle. The maximum and minimum values ​​were located on the pH change curves of each group of compliant soft rock samples during the immersion test sub-cycle, and were marked as the maximum pH and minimum pH of each group of compliant soft rock samples during the immersion test sub-cycle, respectively. Obtain the reference maximum pH and reference minimum pH of each group of compliant soft rock samples. Then, perform difference processing on the maximum pH of each group of compliant soft rock samples during the immersion test sub-cycle and the corresponding reference maximum pH of each group of compliant soft rock samples to obtain the maximum pH deviation value of each group of compliant soft rock samples during the immersion test sub-cycle. The minimum reference pH of each group of compliant soft rock samples is compared with the minimum pH of each group of compliant soft rock samples during the immersion test sub-cycle to obtain the minimum pH deviation value of each group of compliant soft rock samples during the immersion test sub-cycle. Data processing was performed on the pH change curves of each group of compliant soft rock samples during the immersion test sub-cycle to obtain the maximum pH change rate of each group of compliant soft rock samples during the immersion test sub-cycle and the pH compliance duration of each group of compliant soft rock samples during the immersion test sub-cycle. The average apparent compliance factor of each group of compliant soft rock samples is obtained. The average processing quality coefficient of the target soft rock samples, the average apparent compliance factor of each group of compliant soft rock samples, the maximum pH deviation of each group of compliant soft rock samples during the soaking test sub-cycle, the minimum pH deviation of each group of compliant soft rock samples during the soaking test sub-cycle, the maximum pH change rate of each group of compliant soft rock samples during the soaking test sub-cycle, and the pH compliance time of each group of compliant soft rock samples during the soaking test sub-cycle are analyzed to obtain the soaking process compliance index of each group of compliant soft rock samples. The soaking process compliance index of each group of compliant soft rock samples is used to comprehensively quantify the degree of compliance of the soaking process of each group of compliant soft rock samples.

8. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The determination process for whether to adjust the soaking parameters of each group of soft rock samples is as follows: The soaking process compliance index of each group of compliant soft rock samples is compared with the soaking process compliance threshold. If the soaking process compliance index of a certain group of compliant soft rock samples is greater than the soaking process compliance threshold, it is determined that the soaking process parameters of that group of compliant soft rock samples will not be adjusted. If the compliance index of the soaking process of a certain group of compliant soft rock samples is less than or equal to the compliance threshold of the soaking process, it is determined that the soaking process parameters of the group of compliant soft rock samples should be adjusted. The specific adjustment process is as follows: obtain the judgment conditions of the compliance index of the soaking process of the group of compliant soft rock samples, and adjust the soaking process parameters of the group of compliant soft rock samples based on the compliance index of the soaking process, the compliance threshold of the soaking process, and the judgment conditions of the compliance index of the soaking process of the group of compliant soft rock samples. After the adjustment is completed, the compliance index of the soaking process of each group of compliant soft rock samples in the next adjacent soaking test sub-cycle is evaluated, and it is determined whether the soaking process parameters of each group of soft rock samples should be adjusted until the soaking process of each group of soft rock samples is completed.

9. The soft rock disintegration testing system based on multi-cycle hydrolysis of acid and alkali solutions according to claim 1, characterized in that: The specific determination process for deciding whether to perform the disintegration test of multiple cycles of acid-base solution hydrolysis again is as follows: The experimental results parameters for each group of compliant soft rock samples include the average grain size of each group of compliant soft rock samples. The historical adjacent experimental results parameters of each group of compliant soft rock samples were obtained, namely the historical adjacent average particle size of each group of compliant soft rock samples. The historical adjacent average particle size of each group of compliant soft rock samples was compared with the average particle size of the corresponding group of compliant soft rock samples. The result was then compared with the historical adjacent average particle size of each group of compliant soft rock samples to obtain the particle size change rate of each group of compliant soft rock samples. The particle size change rate of each group of compliant soft rock samples is compared with the reference particle size change rate. If the particle size change rate of a certain group of compliant soft rock samples is greater than the reference particle size change rate, it is determined that the compliant soft rock samples of that group will be subjected to the disintegration test experiment of acid-base solution multi-cycle hydrolysis again. If the particle size change rate of a certain group of compliant soft rock samples is less than or equal to the reference particle size change rate, it is determined that the compliant soft rock samples of that group will not be subjected to the disintegration test experiment of acid-base solution multi-cycle hydrolysis again.

10. A method for testing the soft rock disintegration using a multi-cycle hydrolysis system of acid-base solution as described in any one of claims 1-9, characterized in that: include: Step 1: Process the target soft rock sample, obtain the processing parameters of the target soft rock sample, evaluate the processing quality coefficient of the target soft rock sample, compare it with the processing quality threshold, and determine whether to adjust the processing parameters of the target soft rock sample until the processing of the target soft rock sample is completed, and obtain each soft rock sample. Step 2: Collect the apparent parameters of each soft rock sample, analyze the apparent compliance factor of each soft rock sample, mark each compliant soft rock sample, divide each compliant soft rock sample into uniform groups, obtain each group of compliant soft rock samples, and conduct a disintegration test experiment of acid and alkali solution multi-cycle hydrolysis on each group of compliant soft rock samples. Step 3: Collect the soaking process parameters of each group of compliant soft rock samples and analyze the compliance index of the soaking process of each group of compliant soft rock samples to determine whether the soaking process parameters of each group of soft rock samples need to be adjusted; Step 4: Dry each group of compliant soft rock samples, collect the experimental result parameters of each group of compliant soft rock samples, and determine whether to conduct the disintegration test experiment of acid and alkali solution multi-cycle hydrolysis again.

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