Additive selection method and selection device
By combining additive selection methods and devices, and using computer equipment to acquire and analyze filling operation data, the problem of neglecting the influence of seasons and other factors in the selection of additives in the existing technology has been solved, and more accurate control of filling strength and material saving have been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHENZHEN ZHONGJIN LINGNAN NONFERROUS METALS CO LTD FANKOU LEAD-ZINC MINE
- Filing Date
- 2022-12-12
- Publication Date
- 2026-06-05
AI Technical Summary
The existing technology ignores the influence of other factors during actual filling operations when selecting additives, resulting in the strength of the filling body not meeting safety requirements.
By obtaining selection test data of various types of additives, combined with planned filling operation time and actual filling operation data, and taking into account different seasonal factors, the target additives were determined to match the filling operation requirements.
It improves the accuracy of filling strength, reduces the amount of filling material used, and ensures the safety of filling operations.
Smart Images
Figure CN115822699B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of mining technology, and in particular to an additive selection method and device. Background Technology
[0002] The open spaces created after ore mining need to be filled in order to ensure that they do not pose a safety risk to the surrounding ore bodies.
[0003] Void filling typically involves mixing sand, gravel, cement, and other filling materials to form a filling slurry. This slurry is then injected into the void, where it settles over time to form a solid filling body. To ensure that the strength of the filling body formed by the slurry meets the requirements for void filling, additives can be added during the slurry formation process to enhance the strength of the subsequent filling body.
[0004] In existing technologies, the selection of additives is often determined through multiple experiments based on the test data. However, this selection method ignores the influence of other factors on the strength of the filling body during actual filling operations. Summary of the Invention
[0005] In view of this, embodiments of this application provide an additive selection method and device, which can take into account the actual filling operation time and the influence of additives on the strength of the filling body formed by the filling operation under different seasonal factors, so as to facilitate the determination of more suitable additives for the filling operation.
[0006] The first aspect of this application provides a method for selecting additives, including:
[0007] Obtain test data for the selection of various types of additives, including test strength data for each type of filler obtained by adding each type of additive to the filler sample material;
[0008] Determine the planned filling operation time;
[0009] Based on the planned filling operation time, obtain the actual filling operation data for the matching target filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season;
[0010] Based on the actual filling operation data, determine the expected strength data for each type of filling body;
[0011] Based on the test strength data and the expected strength data for each of the filling materials, a target additive is selected from a variety of additive types.
[0012] Optionally, obtaining the actual filling operation data matching the target filling operation time based on the planned filling operation time includes:
[0013] Determine the target season to which the planned filling operation time belongs;
[0014] Inquire about the actual filling operations carried out during the target season;
[0015] Obtain the actual filling operation data of the actual filling operation.
[0016] Optionally, the number of actual filling operations includes multiple items, and obtaining the actual filling operation data of the actual filling operation items includes:
[0017] Determine the volume of the void to be filled;
[0018] Determine the volume of the filled void corresponding to each of the actual filling operations;
[0019] Based on the volume of the void to be filled and the volumes of the multiple filled voids, the target filling operation is determined from the multiple actual filling operation items;
[0020] Obtain the actual filling operation data for the target filling operation.
[0021] Optionally, determining the target filling operation from multiple actual filling operations based on the volume of the void to be filled and the volumes of multiple filled voids includes:
[0022] Calculate the ratio of the volume of the void to be filled to the volume of each of the filled voids;
[0023] The actual filling operation item corresponding to the minimum difference between the ratio and the value 1 is taken as the target filling operation item.
[0024] Optionally, determining the expected strength data for each type of infill based on the actual filling operation data includes:
[0025] Obtain the detection data of the actual filling operation items corresponding to the actual filling operation data;
[0026] The actual filling operation data is corrected based on the detection data to obtain the expected strength data.
[0027] Optionally, the selection of a target additive from a variety of additives based on the test strength data and the expected strength data for each type of filling material includes:
[0028] Determine the data difference between the test strength data and the expected strength data for each type of filling material at different ages;
[0029] Based on the data difference, a target additive is selected from a variety of additive models.
[0030] Optionally, selecting the target additive from a variety of additives based on the data difference includes:
[0031] Determine the geological conditions of the void to be filled;
[0032] The weights for different ages are determined based on the geological conditions described.
[0033] The target value is obtained by weighting the data differences corresponding to different age groups;
[0034] The additive corresponding to the smallest target value is taken as the target additive.
[0035] A second aspect of this application provides an additive selection device, comprising:
[0036] The optional test data acquisition module is used to acquire optional test data of various types of additives. The optional test data includes test strength data of each type of filler obtained by adding each type of additive to the filler sample material.
[0037] The module for determining the planned filling operation time is used to determine the planned filling operation time.
[0038] The actual filling operation data acquisition module is used to acquire actual filling operation data matching the target filling operation time based on the planned filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season;
[0039] The expected strength data determination module is used to determine the expected strength data of each type of filling body based on the actual filling operation data.
[0040] A target additive selection module is used to select a target additive from a variety of additives based on the test strength data and the expected strength data for each type of filling material.
[0041] Optionally, the real filling operation data acquisition module includes:
[0042] The target season determination submodule is used to determine the target season to which the planned filling operation time belongs;
[0043] The Actual Filling Operation Items Query Submodule is used to query actual filling operations carried out in the target season.
[0044] The actual filling operation data acquisition submodule is used to acquire the actual filling operation data of the actual filling operation item.
[0045] Optionally, the number of actual filling operations may include multiple items, and the actual filling operation data acquisition submodule includes:
[0046] The unit for determining the volume of the void to be filled is used to determine the volume of the void to be filled.
[0047] The filled void volume determination unit is used to determine the volume of the filled void corresponding to each of the actual filling operations.
[0048] The target filling operation item determination unit is used to determine the target filling operation item from multiple actual filling operation items based on the volume of the void to be filled and the volumes of multiple filled voids.
[0049] The actual filling operation data acquisition unit is used to acquire the actual filling operation data of the target filling operation.
[0050] Optionally, the target filling operation determination unit includes:
[0051] The volume ratio calculation subunit is used to calculate the ratio of the volume of the void to be filled to the volume of each of the filled voids;
[0052] The target filling operation item determination subunit is used to take the actual filling operation item corresponding to the minimum value of the difference between the ratio and the value 1 as the target filling operation item.
[0053] Optionally, the desired intensity data determination module includes:
[0054] The detection data acquisition submodule is used to acquire detection data of the actual filling operation items corresponding to the actual filling operation data;
[0055] The expected intensity data determination submodule is used to correct the actual filling operation data based on the detection data to obtain the expected intensity data.
[0056] Optionally, the target additive selection module includes:
[0057] The data difference determination submodule is used to determine the data difference between the test strength data and the expected strength data of each type of filling material at different ages;
[0058] The target additive selection submodule is used to select a target additive from a variety of additives based on the data difference.
[0059] Optionally, the target additive selection submodule includes:
[0060] The geological condition determination unit is used to determine the geological condition of the void to be filled.
[0061] The weight determination unit is used to determine the weights of different ages based on the geological conditions.
[0062] The target value calculation unit is used to weight the data differences corresponding to different age groups to obtain the target value;
[0063] The target additive selection unit is used to select the additive corresponding to the smallest target value as the target additive.
[0064] A third aspect of this application provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the additive selection method as described in any of the first aspects above.
[0065] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the additive selection method as described in any of the first aspects above.
[0066] A fifth aspect of this application provides a computer program product that, when run on a computer, causes the computer to execute the additive selection method described in any of the first aspects above.
[0067] Compared with the prior art, the embodiments of this application have the following advantages:
[0068] In this embodiment, the computer device can first acquire selection test data for various types of additives. This selection test data may include test strength data for each type of filler obtained by adding each type of additive to the filler sample material. Based on this, by determining the planned filling operation time, actual filling operation data matching the target filling operation time can be obtained. This target filling operation time and the planned filling operation time belong to the same season. Then, the computer device can determine the expected strength data for each type of filler based on the actual filling operation data. After obtaining the test strength data and expected strength data, the computer device can select a target additive from various types of additives that is more suitable for the current season and matches the actual needs of the void to be filled, based on the test strength data and expected strength data for each type of filler. This embodiment, considering the actual filling operation time and the influence of additives on the strength of the filler formed under different seasonal factors, facilitates the determination of more suitable additives for the filling operation, helps ensure that the strength of the filler obtained from the actual filling operation meets safety requirements, and reduces the amount of filling material used. Attached Figure Description
[0069] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0070] Figure 1 This is a schematic diagram of an additive selection method provided in an embodiment of this application;
[0071] Figure 2 This is a schematic diagram of one implementation of S103 in an additive selection method provided in this application embodiment;
[0072] Figure 3 This is a schematic diagram of one implementation of S1033 in an additive selection method provided in this application embodiment;
[0073] Figure 4 This is a schematic diagram of one implementation of S104 in an additive selection method provided in an embodiment of this application;
[0074] Figure 5 This is a schematic diagram of one implementation of S105 in an additive selection method provided in an embodiment of this application;
[0075] Figure 6 This is a schematic diagram of one implementation of S1052 in an additive selection method provided in this application embodiment;
[0076] Figure 7 This is a schematic diagram of an additive selection device provided in an embodiment of this application;
[0077] Figure 8 This is a schematic diagram of a computer device provided in an embodiment of this application. Detailed Implementation
[0078] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.
[0079] The technical solution of this application will be described below through specific embodiments.
[0080] Reference Figure 1 The diagram illustrates an additive selection method provided in an embodiment of this application, which may specifically include the following steps:
[0081] S101. Obtain test data for the selection of various types of additives, wherein the test data includes test strength data for each type of filler obtained by adding each type of additive to the filler sample material.
[0082] This method can be applied to computer equipment, that is, the execution subject of this application embodiment is computer equipment. By executing the additive selection method provided in this application embodiment, the computer equipment can select suitable additives for open-field filling operations.
[0083] In this embodiment, the additives that can be used for filling operations may include a variety of additives, each of which can be distinguished by different models. When selecting a suitable additive, the computer device can first obtain selection test data for multiple models of additives. This selection test data may include test strength data for each type of filler obtained by adding each model of additive to the filling sample material.
[0084] In practice, after each type of additive is purchased, staff can test it according to the corresponding testing methods to obtain selection test data. During the testing, staff can add the newly purchased additive to the preparation of various filling sample materials. After a period of time, the compressive strength of the resulting fillings is tested, and this compressive strength can be used as the test strength data for the corresponding additive. The selection test data can be stored in a database for reference in subsequent actual filling operations.
[0085] S102. Determine the planned filling operation time.
[0086] The planned filling operation time can be the actual date or time period for filling operations determined according to the project schedule. For example, the planned filling operation time could be December 25th, which means that, according to the project schedule, workers plan to fill a certain vacant site on December 25th.
[0087] S103. Based on the planned filling operation time, obtain the actual filling operation data of the matching target filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season.
[0088] In this embodiment of the application, the target filling operation time can be a time within the same season as the planned filling operation time. For example, in the aforementioned example, the planned filling operation time is December 25th, which is winter. Accordingly, the target filling operation time should also be a time within winter, and the filling operation corresponding to the target filling operation time is the filling operation carried out during winter.
[0089] After the target filling operation time is determined, the computer equipment can obtain the actual filling operation data corresponding to the target filling operation time. This actual filling operation data is the operation data of a completed filling operation.
[0090] In one possible implementation of the embodiments of this application, such as Figure 2 As shown, in step S103, obtaining the actual filling operation data matching the planned filling operation time based on the planned filling operation time can specifically include the following steps S1031-S1033:
[0091] S1031. Determine the target season to which the planned filling operation time belongs.
[0092] The target season for the planned filling operation is the same as the season in which the planned filling operation takes place. For example, in the previous example, the planned filling operation date was December 25th, which is winter. Therefore, the target season is winter.
[0093] S1032. Inquire about the actual filling operations carried out in the target season.
[0094] Typically, the data for each completed filling operation can be archived in a database for retrospective analysis or other processing. In this embodiment, the computer device can query the database for actual filling operations performed during the target season. These actual filling operations are those that have already been completed.
[0095] For example, if the target season is winter, then the actual filling operations can be various filling operations carried out in winter.
[0096] S1033. Obtain the actual filling operation data of the actual filling operation.
[0097] Computer equipment can retrieve operational data from a database of actual filling operations completed during the target season, i.e., actual filling operation data.
[0098] In one possible implementation of the embodiments of this application, such as Figure 3As shown, obtaining the actual filling operation data for the actual filling operation item in S1033 may specifically include the following steps S1331-S1334:
[0099] S1331. Determine the volume of the void to be filled.
[0100] S1332. Determine the volume of the filled void corresponding to each of the actual filling operations.
[0101] S1333. Based on the volume of the void to be filled and the volumes of the multiple filled voids, determine the target filling operation from the multiple actual filling operation items.
[0102] Generally, the number of actual filling operations belonging to the target season may include multiple items. For example, in the aforementioned example, there may be multiple actual filling operations completed in winter.
[0103] In this embodiment of the application, a target filling operation that matches the currently planned filling operation can be determined from multiple actual filling operation items based on volume factors.
[0104] In practice, the volume of the void to be filled and the volume of the filled void corresponding to each actual filling operation can be determined. The volume of the void to be filled can be determined by measurement before the operation, and the measured volume data can be stored in a computer. The volume of the filled void can be obtained from the actual filling operation data of the corresponding void.
[0105] Based on the identified voids to be filled and the volume of each filled void, the computer equipment can determine the target filling operation from multiple real filling operations.
[0106] In this embodiment, the computer device can calculate the ratio of the volume of the void to be filled to the volume of each filled void, and take the actual filling operation corresponding to the minimum difference between the multiple ratios and the value 1 as the target filling operation. The minimum difference between the above ratios and the value 1 indicates that the volume of the filled void corresponding to the actual filling operation is closest to the volume of the void to be filled currently planned. That is, the target filling operation and the planned filling operation belong to the same season, and the volume of the void corresponding to the target filling operation is comparable to the volume of the void to be filled.
[0107] S1334. Obtain the actual filling operation data of the target filling operation.
[0108] Once the target filling operation is identified, it is equivalent to determining a unique filling operation from multiple actual filling operation items. The computer equipment can then obtain the filling operation data for this unique actual filling operation.
[0109] S104. Based on the actual filling operation data, determine the expected strength data for each type of filling body.
[0110] In this embodiment of the application, the actual strength data of the filling body formed after filling the void can be recorded in the actual filling operation data. Based on the actual strength data of the filling body, the expected strength data of each type of filling body can be determined.
[0111] In one possible implementation of the embodiments of this application, such as Figure 4 As shown, determining the expected strength data for each type of filling material based on actual filling operation data in S104 may specifically include the following steps S1041-S1042:
[0112] S1041. Obtain the detection data of the actual filling operation items corresponding to the actual filling operation data.
[0113] In this embodiment of the application, the test data can be the data obtained by testing the strength of the actual filled body after the void has been filled, that is, the actual strength data of the filled body. The actual strength data can be obtained from the actual filling operation data.
[0114] S1042. Correct the actual filling operation data based on the detection data to obtain the expected strength data.
[0115] Since the test data is actual strength data obtained by measuring the filling material during actual filling operations, this data may not necessarily meet expectations. Therefore, computer equipment can correct the actual filling operation data to obtain the desired strength data. The desired strength data is the actual strength data of the filling material expected to be obtained before filling the already filled voids.
[0116] S105. Based on the test strength data and the expected strength data of each of the filling materials, select a target additive from a variety of additives.
[0117] After determining the desired strength data and the test strength data of the filler obtained from each filler sample material, the computer equipment can select a target additive from a variety of additive types based on the desired strength data and the test strength data. The target additive is the type of additive that, when added to the filler sample material to form the filler, produces test strength data of the filler that is closest to the desired strength data.
[0118] In one possible implementation of the embodiments of this application, such as Figure 5 As shown, in S105, selecting the target additive from a variety of additives based on the test strength data and expected strength data of each type of filler may specifically include the following steps S1051-S1052:
[0119] S1051. Determine the data difference between the test strength data and the expected strength data for each type of filling material at different ages.
[0120] S1052. Based on the data difference, select a target additive from a variety of additive models.
[0121] In this embodiment of the application, the test strength data may include the strength data of the filling material at different ages. For example, the age of the filling material may include 3 days, 7 days, 14 days, 21 days, 28 days, etc. These strength data at different ages can be obtained by conducting strength tests on the filling material at the corresponding number of days after its formation.
[0122] When selecting target additives based on test strength data and expected strength data, the computer equipment can determine the data difference between the test strength data and the expected strength data for each type of filling material at different ages. For example, the computer equipment can determine the data difference between the test strength data and the expected strength data for filling materials at 3 days, 7 days, 14 days, 21 days, and 28 days of age, respectively. This yields five data difference values.
[0123] Computer equipment can select target additives from a variety of additive models based on determined differences in multiple data points.
[0124] In another possible implementation of this application embodiment, as shown in the figure, step S1052, selecting the target additive from multiple types of additives based on the data difference, may specifically include the following steps S1521-S1524:
[0125] S1521. Determine the geological conditions of the void to be filled.
[0126] S1522. Determine the weights of different ages based on the geological conditions described.
[0127] S1523. Weight the data differences corresponding to different age groups to obtain the target value.
[0128] S1524. The additive corresponding to the smallest target value is taken as the target additive.
[0129] In practice, computer equipment can determine the geological conditions of the void to be filled, which can be obtained through geological exploration of the void. Based on the geological conditions, the computer equipment can determine the weights for different ages. The weights for different ages can be the same or different. For example, the weights for the strength of the filling material at 3 days, 7 days, 14 days, 21 days, and 28 days of age can be the same, with each age having a weight of 20%; or, the weights for the strength of the filling material at 3 days, 7 days, 14 days, 21 days, and 28 days of age can be different, with longer ages having a larger weight. For example, the weights for 3 days and 7 days of age can both be 10%, the weight for 14 days of age can be 20%, the weight for 21 days of age can be 25%, and the weight for 28 days of age can be 35%.
[0130] After determining the weights for different age groups, the data differences corresponding to different age groups can be weighted to obtain a target value. This target value can represent the magnitude of the difference between the expected intensity data and the experimental intensity data. Therefore, the computer equipment can select the additive corresponding to the minimum value among multiple target values as the target additive.
[0131] In this embodiment, the computer device can first acquire selection test data for various types of additives. This selection test data may include test strength data for each type of filler obtained by adding each type of additive to the filler sample material. Based on this, by determining the planned filling operation time, actual filling operation data matching the target filling operation time can be obtained. This target filling operation time and the planned filling operation time belong to the same season. Then, the computer device can determine the expected strength data for each type of filler based on the actual filling operation data. After obtaining the test strength data and expected strength data, the computer device can select a target additive from various types of additives that is more suitable for the current season and matches the actual needs of the void to be filled, based on the test strength data and expected strength data for each type of filler. This embodiment, considering the actual filling operation time and the influence of additives on the strength of the filler formed under different seasonal factors, facilitates the determination of more suitable additives for the filling operation, helps ensure that the strength of the filler obtained from the actual filling operation meets safety requirements, and reduces the amount of filling material used.
[0132] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.
[0133] Reference Figure 7The diagram illustrates an additive selection device according to an embodiment of this application. Specifically, it may include a selection test data acquisition module 701, a planned filling operation time determination module 702, a real filling operation data acquisition module 703, a desired intensity data determination module 704, and a target additive selection module 705, wherein:
[0134] The optional test data acquisition module 701 is used to acquire optional test data of various types of additives. The optional test data includes test strength data of each type of filler obtained by adding each type of additive to the filling sample material.
[0135] The planned filling operation time determination module 702 is used to determine the planned filling operation time;
[0136] The actual filling operation data acquisition module 703 is used to acquire actual filling operation data matching the target filling operation time according to the planned filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season;
[0137] The expected strength data determination module 704 is used to determine the expected strength data of each type of filling body based on the actual filling operation data.
[0138] The target additive selection module 705 is used to select a target additive from a variety of additives based on the test strength data and the expected strength data for each type of filling material.
[0139] In this embodiment of the application, the real filling operation data acquisition module 703 can be specifically used for:
[0140] Determine the target season to which the planned filling operation time belongs;
[0141] Inquire about the actual filling operations carried out during the target season;
[0142] Obtain the actual filling operation data of the actual filling operation.
[0143] In one possible implementation of this application embodiment, the number of actual filling operations may include multiple items, and the actual filling operation data acquisition module 703 may also be used for:
[0144] Determine the volume of the void to be filled;
[0145] Determine the volume of the filled void corresponding to each of the actual filling operations;
[0146] Based on the volume of the void to be filled and the volumes of the multiple filled voids, the target filling operation is determined from the multiple actual filling operation items;
[0147] Obtain the actual filling operation data for the target filling operation.
[0148] In one possible implementation of this application embodiment, the real filling operation data acquisition module 703 can also be used for:
[0149] Calculate the ratio of the volume of the void to be filled to the volume of each of the filled voids;
[0150] The actual filling operation item corresponding to the minimum difference between the ratio and the value 1 is taken as the target filling operation item.
[0151] In this embodiment of the application, the expected intensity data determination module 704 can specifically be used for:
[0152] Obtain the detection data of the actual filling operation items corresponding to the actual filling operation data;
[0153] The actual filling operation data is corrected based on the detection data to obtain the expected strength data.
[0154] In this embodiment of the application, the target additive selection module 705 can be specifically used for:
[0155] Determine the data difference between the test strength data and the expected strength data for each type of filling material at different ages;
[0156] Based on the data difference, a target additive is selected from a variety of additive models.
[0157] In one possible implementation of this application embodiment, the target additive selection module 705 may also be used for:
[0158] Determine the geological conditions of the void to be filled;
[0159] The weights for different ages are determined based on the geological conditions described.
[0160] The target value is obtained by weighting the data differences corresponding to different age groups;
[0161] The additive corresponding to the smallest target value is taken as the target additive.
[0162] This application also provides an additive selection device, which can be used to implement the steps in the aforementioned method embodiments.
[0163] As the apparatus embodiments are basically similar to the method embodiments, they are described in a relatively simple manner. For relevant details, please refer to the description in the method embodiment section.
[0164] Reference Figure 8 The diagram illustrates a computer device provided in an embodiment of this application. Figure 8 As shown, the computer device 800 in this embodiment includes: a processor 810, a memory 820, and a computer program 821 stored in the memory 820 and executable on the processor 810. When the processor 810 executes the computer program 821, it implements the steps in the various embodiments of the additive selection method described above, for example... Figure 1 Steps S101 to S105 are shown. Alternatively, when the processor 810 executes the computer program 821, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 6 The functions of modules 601 to 605 are shown.
[0165] For example, the computer program 821 can be divided into one or more modules / units, which are stored in the memory 820 and executed by the processor 810 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which can be used to describe the execution process of the computer program 821 in the computer device 800. For example, the computer program 821 can be divided into an optional test data acquisition module, a planned filling operation time determination module, a real filling operation data acquisition module, a desired intensity data determination module, and a target additive selection module, with the specific functions of each module as follows:
[0166] The optional test data acquisition module is used to acquire optional test data of various types of additives. The optional test data includes test strength data of each type of filler obtained by adding each type of additive to the filler sample material.
[0167] The module for determining the planned filling operation time is used to determine the planned filling operation time.
[0168] The actual filling operation data acquisition module is used to acquire actual filling operation data matching the target filling operation time based on the planned filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season;
[0169] The expected strength data determination module is used to determine the expected strength data of each type of filling body based on the actual filling operation data.
[0170] A target additive selection module is used to select a target additive from a variety of additives based on the test strength data and the expected strength data for each type of filling material.
[0171] The computer device 800 may be a computer device that implements the steps in the foregoing method embodiments, and may be a desktop computer, cloud server, or other computing device. The computer device 800 may include, but is not limited to, a processor 810 and a memory 820. Those skilled in the art will understand that... Figure 8 This is merely one example of a computer device 800 and does not constitute a limitation on the computer device 800. It may include more or fewer components than shown, or combine certain components, or different components. For example, the computer device 800 may also include input / output devices, network access devices, buses, etc.
[0172] The processor 810 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.
[0173] The memory 820 can be an internal storage unit of the computer device 800, such as a hard disk or memory of the computer device 800. The memory 820 can also be an external storage device of the computer device 800, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the computer device 800. Furthermore, the memory 820 can include both internal and external storage units of the computer device 800. The memory 820 is used to store the computer program 821 and other programs and data required by the computer device 800. The memory 820 can also be used to temporarily store data that has been output or will be output.
[0174] This application also discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the additive selection method as described in the foregoing embodiments.
[0175] This application also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the additive selection method as described in the foregoing embodiments.
[0176] This application also discloses a computer program product that, when run on a computer, causes the computer to execute the additive selection method described in the foregoing embodiments.
[0177] The embodiments described above are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for selecting and formulating additives, characterized in that, include: Obtain test data for the selection of various types of additives, including test strength data for each type of filler obtained by adding each type of additive to the filler sample material; Determine the planned filling operation time; Based on the planned filling operation time, obtain the actual filling operation data for the matching target filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season; Based on the actual filling operation data, determine the expected strength data for each type of filling body; Based on the test strength data and the expected strength data for each of the filling materials, a target additive is selected from a variety of additives. The step of obtaining the actual filling operation data matching the target filling operation time based on the planned filling operation time includes: Determine the target season to which the planned filling operation time belongs; Inquire about the actual filling operations carried out during the target season; Obtain the actual filling operation data for the actual filling operation item; The number of actual filling operations includes multiple items, and obtaining the actual filling operation data for the actual filling operation items includes: Determine the volume of the void to be filled; Determine the volume of the filled void corresponding to each of the actual filling operations; Based on the volume of the void to be filled and the volumes of the multiple filled voids, the target filling operation is determined from the multiple actual filling operation items; Obtain the actual filling operation data for the target filling operation; The expected strength data is the strength data of the filling body that is actually expected to be obtained before the filled void is filled. The step of determining the target filling operation from multiple actual filling operation items based on the volume of the void to be filled and the volumes of multiple filled voids includes: Calculate the ratio of the volume of the void to be filled to the volume of each of the filled voids; The actual filling operation item corresponding to the minimum difference between the ratio and the value 1 is taken as the target filling operation item.
2. The method according to claim 1, characterized in that, The step of determining the expected strength data for each type of filling body based on the actual filling operation data includes: Obtain the detection data of the actual filling operation items corresponding to the actual filling operation data; The actual filling operation data is corrected based on the detection data to obtain the expected strength data.
3. The method according to any one of claims 1-2, characterized in that, The selection of target additives from a variety of additives based on the test strength data and the expected strength data for each type of filling material includes: Determine the data difference between the test strength data and the expected strength data for each type of filling material at different ages; Based on the data difference, a target additive is selected from a variety of additive models.
4. The method according to claim 3, characterized in that, The step of selecting a target additive from a variety of additive models based on the data difference includes: Determine the geological conditions of the void to be filled; The weights for different ages are determined based on the geological conditions described. The target value is obtained by weighting the data differences corresponding to different age groups; The additive corresponding to the smallest target value is taken as the target additive.
5. An additive selection device, characterized in that, include: The optional test data acquisition module is used to acquire optional test data of various types of additives. The optional test data includes test strength data of each type of filler obtained by adding each type of additive to the filler sample material. The module for determining the planned filling operation time is used to determine the planned filling operation time. The actual filling operation data acquisition module is used to acquire actual filling operation data matching the target filling operation time based on the planned filling operation time, wherein the target filling operation time and the planned filling operation time belong to the same season; The expected strength data determination module is used to determine the expected strength data of each type of filling body based on the actual filling operation data. A target additive selection module is used to select a target additive from a variety of additives based on the test strength data and the expected strength data of each type of filling material. The actual filling operation data acquisition module includes: The target season determination submodule is used to determine the target season to which the planned filling operation time belongs; The Actual Filling Operation Items Query Submodule is used to query actual filling operations carried out in the target season. The actual filling operation data acquisition submodule is used to acquire the actual filling operation data of the actual filling operation item; The number of actual filling operations includes multiple items, and the actual filling operation data acquisition submodule includes: The unit for determining the volume of the void to be filled is used to determine the volume of the void to be filled. The filled void volume determination unit is used to determine the volume of the filled void corresponding to each of the actual filling operations. The target filling operation item determination unit is used to determine the target filling operation item from multiple actual filling operation items based on the volume of the void to be filled and the volumes of multiple filled voids. The actual filling operation data acquisition unit is used to acquire the actual filling operation data of the target filling operation item; The expected strength data is the strength data of the filling body that is actually expected to be obtained before the filled void is filled. The target filling operation determination unit includes: The volume ratio calculation subunit is used to calculate the ratio of the volume of the void to be filled to the volume of each of the filled voids; The target filling operation item determination subunit is used to take the actual filling operation item corresponding to the minimum value of the difference between the ratio and the value 1 as the target filling operation item.
6. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the additive selection method as described in any one of claims 1-4.
7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the additive selection method as described in any one of claims 1-4.