Method and device for calibrating water content of sand and gravel material, and storage medium

Abstract

The application discloses a sandstone material moisture content calibration method, a calibration device and a storage medium. The calibration method comprises the following steps: constructing a spectrum coefficient library, the spectrum coefficient library comprising a plurality of correlation coefficients; obtaining a plurality of groups of sandstone material moisture content and microwave spectrum; for each group of sandstone material, respectively determining a predicted moisture content set of each group of sandstone material according to the plurality of correlation coefficients and the microwave spectrum of each group of sandstone material; comparing the moisture content of each group of sandstone material with the predicted moisture content set to obtain a moisture content error sum of each group of sandstone material; and determining a target correlation coefficient in the plurality of correlation coefficients according to the moisture content error sum of the plurality of groups of sandstone material to complete the calibration of the sandstone material moisture content. The application can reduce the calibration time of the sandstone material moisture content and improve the calibration accuracy of the sandstone material moisture content.

Description

Technical Field

[0001] This application relates to the field of concrete technology, and specifically to a method, calibration device, and storage medium for calibrating the moisture content of sand and gravel materials. Background Technology

[0002] Concrete is a composite material made by mixing cement, sand and gravel, water, admixtures, and additives in a specific ratio. As one of the most widely used materials in the construction industry, the amount of water used in concrete preparation needs to be precisely weighed according to the formula to ensure production quality. However, during concrete production, the moisture content of each batch of sand and gravel fluctuates due to factors such as the manufacturer's cleaning process and the accumulation of rainwater during on-site storage. Therefore, accurate testing of the moisture content of each batch of sand and gravel is necessary to produce concrete that meets quality requirements.

[0003] In daily production at a concrete mixing plant, the moisture content of sand and gravel is generally between 5% and 10%, and the data selected during calibration also falls within this range. However, due to the overly concentrated calibration data, the moisture content error between the actual and theoretical calibration curves will be proportionally amplified in both the high and low moisture content ranges. If the moisture content of the sand and gravel increases due to factors such as rain, exceeding its typical range, this calibration method will produce significant errors, which is detrimental to on-site concrete production quality control. Therefore, existing technology suffers from a significant calibration error in the moisture content of sand and gravel. Summary of the Invention

[0004] The purpose of this application is to provide a method, device and storage medium for calibrating the moisture content of sand and gravel materials, so as to solve the problem of large calibration error of moisture content of sand and gravel materials in the prior art.

[0005] To achieve the above objectives, the first aspect of this application provides a method for calibrating the moisture content of sand and gravel materials, applicable to a device for calibrating the moisture content of sand and gravel materials. The calibration method includes:

[0006] Construct a spectrum coefficient library, which includes multiple correlation coefficients;

[0007] Obtain the moisture content and microwave spectrum of multiple sets of sand and gravel materials;

[0008] For each group of sand and gravel materials, the predicted moisture content set for each group of sand and gravel materials is determined based on multiple correlation coefficients and the microwave spectrum of each group of sand and gravel materials.

[0009] Compare the moisture content of each group of sand and gravel materials with the predicted moisture content set to obtain the total moisture content error of each group of sand and gravel materials;

[0010] The target correlation coefficient is determined from multiple correlation coefficients based on the sum of the moisture content errors of multiple groups of sand and gravel materials, so as to complete the calibration of the moisture content of sand and gravel materials.

[0011] In this embodiment, the calibration device includes a microwave moisture sensor and a sprinkler, and the construction of the spectral coefficient library includes:

[0012] Obtain multiple types of sample sand and gravel materials;

[0013] Each type of sample sand and gravel material is divided into a preset number of sample sand and gravel materials;

[0014] For any type of sample sand and gravel material, the moisture content of any type of sample sand and gravel material is adjusted by a water sprinkler to obtain a preset number of target sample sand and gravel materials.

[0015] The microwave spectrum of each group of target sample sand and gravel materials is obtained by using a microwave moisture sensor to obtain the microwave spectrum of the target sample sand and gravel materials of a preset number of groups.

[0016] Linear fitting was performed on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups to determine multiple correlation coefficients of sand and gravel materials of any type.

[0017] A spectral coefficient library was constructed based on multiple correlation coefficients of various types of sample sand and gravel materials.

[0018] In this embodiment of the application, linear fitting is performed on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups, including:

[0019] The gradient descent algorithm was used to perform linear fitting on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups.

[0020] In this embodiment of the application, the moisture content of any type of sample sand and gravel material is adjusted to obtain a preset number of target sample sand and gravel materials, including:

[0021] Obtain multiple preset moisture contents;

[0022] For any type of sample sand and gravel material, adjust the moisture content of a preset number of sample sand and gravel materials according to multiple preset moisture contents to obtain the preset number of target sample sand and gravel materials.

[0023] In this embodiment of the application, for each group of sand and gravel materials, the predicted moisture content set for each group of sand and gravel materials is determined based on multiple correlation coefficients and the microwave spectrum of each group of sand and gravel materials, including:

[0024] Multiple correlation coefficients of various types of sample sand and gravel materials were obtained from the spectrum coefficient library;

[0025] According to the type of sand and gravel material in the samples, multiple correlation coefficients are grouped to obtain multiple sets of correlation coefficients;

[0026] The predicted moisture content set of each group of sand and gravel materials was determined based on multiple sets of correlation coefficients and the microwave spectrum of each group of sand and gravel materials.

[0027] In this embodiment of the application, the calibration device includes an oven, and obtaining the moisture content of multiple sets of sand and gravel materials includes:

[0028] Obtain the weight of each group of sand and gravel materials;

[0029] Multiple groups of sand and gravel materials are dried in an oven to obtain multiple groups of dried sand and gravel materials.

[0030] Obtain the weight of each group of dried sand and gravel materials;

[0031] The moisture content of each group of sand and gravel is determined based on the weight of each group of sand and gravel and the weight of each group of dried sand and gravel, so as to obtain the moisture content of multiple groups of sand and gravel.

[0032] In this embodiment, the moisture content of each group of sand and gravel materials satisfies formula (1):

[0033]

[0034] Among them, W w m1 represents the moisture content of each group of sand and gravel materials, m2 represents the weight of each group of sand and gravel materials, and m3 represents the weight of each group of dried sand and gravel materials.

[0035] A second aspect of this application provides a device for calibrating the moisture content of sand and gravel materials, comprising:

[0036] The memory is configured to store instructions; and

[0037] The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the aforementioned method for calibrating the moisture content of sand and gravel materials.

[0038] In this embodiment of the application, the calibration device further includes:

[0039] The sprinkler communicates with the processor and is configured to adjust the moisture content of the sand and gravel materials;

[0040] The microwave moisture sensor, which communicates with the processor, is configured to collect the microwave spectrum of sand and gravel materials.

[0041] The oven, which communicates with the processor, is configured to dry sand and gravel materials.

[0042] A third aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to perform the above-described method for calibrating the moisture content of sand and gravel materials.

[0043] This application constructs a spectral coefficient library and obtains the moisture content and microwave spectrum of multiple groups of sand and gravel materials. Then, for each group of sand and gravel materials, a predicted moisture content set is determined based on multiple correlation coefficients in the spectral coefficient library and the microwave spectrum of each group. The moisture content of each group of sand and gravel materials is then compared with the predicted moisture content set to obtain the total moisture content error for each group. Finally, a target correlation coefficient is determined from multiple correlation coefficients based on the total moisture content error of multiple groups of sand and gravel materials to complete the calibration of the sand and gravel material moisture content. This application, by determining the target correlation coefficient from multiple correlation coefficients based on the total moisture content error of multiple groups of sand and gravel materials, can reduce the calibration time for sand and gravel material moisture content and improve the calibration accuracy.

[0044] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0046] Figure 1 The flowchart illustrates a method for calibrating the moisture content of sand and gravel materials according to an embodiment of this application.

[0047] Figure 2 The flowchart illustrates a method for calibrating the moisture content of sand and gravel materials according to a specific embodiment of this application.

[0048] Figure 3 The diagram illustrates the structure of a device for calibrating the moisture content of sand and gravel materials according to an embodiment of this application. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0050] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0051] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0052] Figure 1 A flowchart illustrating a method for calibrating the moisture content of sand and gravel materials according to an embodiment of this application is shown schematically. Figure 1 As shown in the figure, this application provides a method for calibrating the moisture content of sand and gravel materials, which is applied to a device for calibrating the moisture content of sand and gravel materials. The calibration method may include the following steps:

[0053] Step 101: Construct a spectrum coefficient library, which includes multiple correlation coefficients;

[0054] Step 102: Obtain the moisture content and microwave spectrum of multiple sets of sand and gravel materials;

[0055] Step 103: For each group of sand and gravel materials, determine the predicted moisture content set for each group of sand and gravel materials based on multiple correlation coefficients and the microwave spectrum of each group of sand and gravel materials.

[0056] Step 104: Compare the moisture content of each group of sand and gravel materials with the predicted moisture content set to obtain the total moisture content error of each group of sand and gravel materials;

[0057] Step 105: Determine the target correlation coefficient among multiple correlation coefficients based on the sum of moisture content errors of multiple groups of sand and gravel materials, so as to complete the calibration of moisture content of sand and gravel materials.

[0058] In this embodiment, the calibration device can calibrate the moisture content of sand and gravel materials based on multiple correlation coefficients in a spectral coefficient library and the sum of moisture content errors for each group of sand and gravel materials. First, the calibration device can pre-construct a spectral coefficient library. Sand and gravel materials typically come in multiple types, such as river sand and manufactured sand. To meet the need for calibrating the moisture content of multiple types of sand and gravel materials during actual calibration, the spectral coefficient library includes multiple correlation coefficients for sample sand and gravel materials of multiple types. Thus, after constructing the spectral coefficient library, the calibration device can obtain the moisture content and microwave spectrum of multiple groups of sand and gravel materials. The number of groups of sand and gravel materials can be adjusted according to actual conditions. In one example, the number of groups of sand and gravel materials can be 15.

[0059] Since the moisture content of sand and gravel materials is linearly correlated with the microwave spectrum, the calibration device can determine the predicted moisture content set for each group of sand and gravel materials based on multiple correlation coefficients and the microwave spectrum of each group. The predicted moisture content set includes multiple predicted moisture contents determined based on the correlation coefficients and the microwave spectrum. With the predicted moisture content set determined, the calibration device can compare the moisture content of each group of sand and gravel materials with the predicted moisture content set to obtain the sum of moisture content errors between the two groups. After determining the sum of moisture content errors for each group of sand and gravel materials, for each correlation coefficient, the calibration device can obtain the sum of moisture content errors for multiple groups of sand and gravel materials corresponding to each correlation coefficient. Furthermore, based on the sum of moisture content errors for multiple groups of sand and gravel materials corresponding to each correlation coefficient, the calibration device can determine the correlation coefficient that minimizes the sum of moisture content errors for multiple groups of sand and gravel materials as the target correlation coefficient, thereby completing the calibration of the sand and gravel material moisture content. This reduces the calibration time for the moisture content of sand and gravel materials and improves the calibration accuracy of the moisture content of sand and gravel materials.

[0060] This application constructs a spectral coefficient library and obtains the moisture content and microwave spectrum of multiple groups of sand and gravel materials. Then, for each group of sand and gravel materials, a predicted moisture content set is determined based on multiple correlation coefficients in the spectral coefficient library and the microwave spectrum of each group. The moisture content of each group of sand and gravel materials is then compared with the predicted moisture content set to obtain the total moisture content error for each group. Finally, a target correlation coefficient is determined from multiple correlation coefficients based on the total moisture content error of multiple groups of sand and gravel materials to complete the calibration of the sand and gravel material moisture content. This application, by determining the target correlation coefficient from multiple correlation coefficients based on the total moisture content error of multiple groups of sand and gravel materials, can reduce the calibration time for sand and gravel material moisture content and improve the calibration accuracy.

[0061] In this embodiment, the calibration device includes a microwave moisture sensor and a sprinkler, and constructing the spectral coefficient library may include:

[0062] Obtain multiple types of sample sand and gravel materials;

[0063] Each type of sample sand and gravel material is divided into a preset number of sample sand and gravel materials;

[0064] For any type of sample sand and gravel material, the moisture content of any type of sample sand and gravel material is adjusted by a water sprinkler to obtain a preset number of target sample sand and gravel materials.

[0065] The microwave spectrum of each group of target sample sand and gravel materials is obtained by using a microwave moisture sensor to obtain the microwave spectrum of the target sample sand and gravel materials of a preset number of groups.

[0066] Linear fitting was performed on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups to determine multiple correlation coefficients of sand and gravel materials of any type.

[0067] A spectral coefficient library was constructed based on multiple correlation coefficients of various types of sample sand and gravel materials.

[0068] In this embodiment, the calibration device can pre-build a spectral coefficient library. First, the calibration device can acquire multiple types of sample sand and gravel materials and divide each type into a preset number of sample sand and gravel materials. The calibration device includes an oven, a microwave moisture sensor, and a sprinkler. Using the oven, the calibration device can dehydrate the sample sand and gravel materials to obtain sample sand and gravel materials with a moisture content of 0%. Further, for any type of sample sand and gravel material, the calibration device can adjust the moisture content of any type of sample sand and gravel material using the sprinkler to obtain a preset number of target sample sand and gravel materials. Typically, the moisture content of sand and gravel materials does not exceed 16%. Therefore, in one example, for any type of sample sand and gravel material, within the range of 0% to 16% moisture content, the calibration device can adjust the moisture content of any type of sample sand and gravel material at 0.5% moisture content intervals to obtain 32 groups of target sample sand and gravel materials.

[0069] After obtaining a preset number of target sample sand and gravel materials, the calibration device can acquire the microwave spectrum of each group of target sample sand and gravel materials using a microwave moisture sensor to obtain the microwave spectrum of the preset number of target sample sand and gravel materials. The microwave moisture sensor can be a MOSS MS-590 microwave moisture sensor. In one example, the distance between the upper and lower probes of the MOSS MS-590 microwave moisture sensor is set to 60 cm. The calibration device can place each group of target sample sand and gravel materials at the midpoint between the upper and lower probes to acquire the microwave spectrum of each group. Subsequently, the calibration device can perform linear fitting on the moisture content and microwave spectrum of the preset number of target sample sand and gravel materials to determine multiple correlation coefficients for any type of sample sand and gravel material. Based on these multiple correlation coefficients for multiple types of sample sand and gravel materials, a spectrum coefficient library is constructed. This facilitates subsequent calibration of the moisture content of the sand and gravel materials based on multiple correlation coefficients in the spectrum coefficient library.

[0070] In this embodiment of the application, adjusting the moisture content of any type of sample sand and gravel material to obtain a preset number of target sample sand and gravel materials may include:

[0071] Obtain multiple preset moisture contents;

[0072] For any type of sample sand and gravel material, adjust the moisture content of a preset number of sample sand and gravel materials according to multiple preset moisture contents to obtain the preset number of target sample sand and gravel materials.

[0073] In this embodiment, the calibration device can adjust the moisture content of any type of sample sand and gravel material to obtain a preset number of target sample sand and gravel materials. For any type of sample sand and gravel material, the calibration device can obtain multiple preset moisture contents. The preset moisture contents can be adjusted according to actual conditions. In one example, within the range of 0% to 16% moisture content, the calibration device can determine 32 preset moisture contents at 0.5% intervals. Furthermore, using a sprinkler, the calibration device can adjust the moisture content of any type of sample sand and gravel material according to multiple preset moisture contents, to obtain a preset number of target sample sand and gravel materials. In this way, the moisture content of a preset number of sample sand and gravel materials can be adjusted, facilitating the construction of a spectral coefficient library.

[0074] In this embodiment of the application, linear fitting of the moisture content and microwave spectrum of a preset number of target sample sand and gravel materials may include:

[0075] The gradient descent algorithm was used to perform linear fitting on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups.

[0076] In this embodiment, the calibration device can perform linear fitting on the moisture content and microwave spectrum of a preset number of target sample sand and gravel materials, thereby obtaining multiple correlation coefficients for any type of sample sand and gravel materials. Specifically, the calibration device can use the gradient descent algorithm to perform linear fitting on the moisture content and microwave spectrum of a preset number of target sample sand and gravel materials. Using the gradient descent algorithm for linear fitting allows for different fitting effects to be obtained by modifying the iteration step size, number of iterations, convergence conditions, etc., making it more flexible than algorithms such as least squares method and linear regression.

[0077] In this embodiment of the application, step 103, determining the predicted moisture content set for each group of sand and gravel materials based on multiple correlation coefficients and the microwave spectrum of each group of sand and gravel materials, may include:

[0078] Multiple correlation coefficients of various types of sample sand and gravel materials were obtained from the spectrum coefficient library;

[0079] According to the type of sand and gravel material in the samples, multiple correlation coefficients are grouped to obtain multiple sets of correlation coefficients;

[0080] The predicted moisture content set of each group of sand and gravel materials was determined based on multiple sets of correlation coefficients and the microwave spectrum of each group of sand and gravel materials.

[0081] In this embodiment, the calibration device can obtain multiple correlation coefficients for various types of sample sand and gravel materials from a spectral coefficient library. Furthermore, the calibration device can group these correlation coefficients according to the type of sample sand and gravel material, thereby obtaining multiple sets of correlation coefficients. Since the moisture content of sand and gravel materials is linearly correlated with the microwave spectrum, after obtaining multiple sets of correlation coefficients, the calibration device can determine the predicted moisture content set for each group of sand and gravel materials based on the multiple sets of correlation coefficients and the microwave spectrum of each group.

[0082] In this embodiment of the application, the calibration device includes an oven, and obtaining the moisture content of multiple sets of sand and gravel materials may include:

[0083] Obtain the weight of each group of sand and gravel materials;

[0084] Multiple groups of sand and gravel materials are dried in an oven to obtain multiple groups of dried sand and gravel materials.

[0085] Obtain the weight of each group of dried sand and gravel materials;

[0086] The moisture content of each group of sand and gravel is determined based on the weight of each group of sand and gravel and the weight of each group of dried sand and gravel, so as to obtain the moisture content of multiple groups of sand and gravel.

[0087] In this embodiment, the calibration device can obtain the moisture content of multiple groups of sand and gravel materials in practical application. Specifically, the calibration device can obtain the weight of each group of sand and gravel materials and dry them in an oven to obtain multiple groups of dried sand and gravel materials. Subsequently, the calibration device can obtain the weight of each group of dried sand and gravel materials. Then, the calibration device can determine the moisture content of each group of sand and gravel materials based on the weight of each group of sand and gravel materials and the weight of each group of dried sand and gravel materials. After determining the moisture content of each group of sand and gravel materials, the calibration device can obtain the moisture content of multiple groups of sand and gravel materials.

[0088] In this embodiment, the moisture content of each group of sand and gravel materials can satisfy formula (1):

[0089]

[0090] Among them, W w m1 represents the moisture content of each group of sand and gravel materials, m2 represents the weight of each group of sand and gravel materials, and m3 represents the weight of each group of dried sand and gravel materials.

[0091] In this embodiment, the calibration device can obtain the weight of each group of sand and gravel materials and dry multiple groups of sand and gravel materials in an oven to obtain multiple groups of dried sand and gravel materials. Subsequently, the calibration device can obtain the weight of each group of dried sand and gravel materials. Since each group of sand and gravel materials needs to be placed on a tray, the weight of the tray should be taken into account when determining the moisture content of each group of sand and gravel materials. Therefore, the calibration device can determine the moisture content of each group of sand and gravel materials based on the tray weight, the weight of each group of sand and gravel materials, and the weight of each group of dried sand and gravel materials.

[0092] Figure 2 A flowchart illustrating a method for calibrating the moisture content of sand and gravel materials according to a specific embodiment of this application is shown. Figure 2 As shown in a specific embodiment of this application, the method for determining the moisture content of sand and gravel materials may include:

[0093] S1. Collect microwave spectrum and moisture content of multiple types of sand and gravel materials within the full moisture content range, and establish a spectrum coefficient library;

[0094] S2. Collect the microwave spectrum and moisture content of sand and gravel materials at the mixing plant site;

[0095] S3. Determine the target correlation coefficient in the spectrum coefficient library that best matches the microwave spectrum and moisture content of the sand and gravel material, and complete the calibration.

[0096] In one specific embodiment of this application, the calibration device can collect microwave spectra and moisture contents of multiple types of sample sand and gravel materials across the entire moisture content range, thereby establishing a spectrum coefficient library. After establishing the spectrum coefficient library, the device collects microwave spectra and moisture contents of sand and gravel materials from the mixing plant site. Based on the spectrum coefficient library, the microwave spectra, and moisture contents of the sand and gravel materials, the calibration device can determine the target correlation coefficient in the spectrum coefficient library that best matches the microwave spectra and moisture contents of the sand and gravel materials. In this way, the calibration device can complete the calibration process for the moisture content of the sand and gravel materials.

[0097] Figure 3 The diagram schematically illustrates a structural block diagram of a device for calibrating the moisture content of sand and gravel materials according to an embodiment of this application. Figure 3 As shown in the figure, this application provides a device for calibrating the moisture content of sand and gravel materials, which may include:

[0098] Memory 310 is configured to store instructions; and

[0099] The processor 320 is configured to retrieve instructions from the memory 310 and, when executing the instructions, to implement the aforementioned method for calibrating the moisture content of sand and gravel materials.

[0100] Specifically, in this embodiment of the application, the processor 320 can be configured to:

[0101] Construct a spectrum coefficient library, which includes multiple correlation coefficients;

[0102] Obtain the moisture content and microwave spectrum of multiple sets of sand and gravel materials;

[0103] For each group of sand and gravel materials, the predicted moisture content set for each group of sand and gravel materials is determined based on multiple correlation coefficients and the microwave spectrum of each group of sand and gravel materials.

[0104] Compare the moisture content of each group of sand and gravel materials with the predicted moisture content set to obtain the total moisture content error of each group of sand and gravel materials;

[0105] The target correlation coefficient is determined from multiple correlation coefficients based on the sum of the moisture content errors of multiple groups of sand and gravel materials, so as to complete the calibration of the moisture content of sand and gravel materials.

[0106] Furthermore, the processor 320 can also be configured as follows:

[0107] Obtain multiple types of sample sand and gravel materials;

[0108] Each type of sample sand and gravel material is divided into a preset number of sample sand and gravel materials;

[0109] For any type of sample sand and gravel material, the moisture content of any type of sample sand and gravel material is adjusted by a water sprinkler to obtain a preset number of target sample sand and gravel materials.

[0110] The microwave spectrum of each group of target sample sand and gravel materials is obtained by using a microwave moisture sensor to obtain the microwave spectrum of the target sample sand and gravel materials of a preset number of groups.

[0111] Linear fitting was performed on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups to determine multiple correlation coefficients of sand and gravel materials of any type.

[0112] A spectral coefficient library was constructed based on multiple correlation coefficients of various types of sample sand and gravel materials.

[0113] Furthermore, the processor 320 can also be configured as follows:

[0114] The gradient descent algorithm was used to perform linear fitting on the moisture content and microwave spectrum of the target sample sand and gravel materials of a preset number of groups.

[0115] Furthermore, the processor 320 can also be configured as follows:

[0116] Obtain multiple preset moisture contents;

[0117] For any type of sample sand and gravel material, adjust the moisture content of a preset number of sample sand and gravel materials according to multiple preset moisture contents to obtain the preset number of target sample sand and gravel materials.

[0118] Furthermore, the processor 320 can also be configured as follows:

[0119] Multiple correlation coefficients of various types of sample sand and gravel materials were obtained from the spectrum coefficient library;

[0120] According to the type of sand and gravel material in the samples, multiple correlation coefficients are grouped to obtain multiple sets of correlation coefficients;

[0121] The predicted moisture content set of each group of sand and gravel materials was determined based on multiple sets of correlation coefficients and the microwave spectrum of each group of sand and gravel materials.

[0122] Furthermore, the processor 320 can also be configured as follows:

[0123] Obtain the weight of each group of sand and gravel materials;

[0124] Multiple groups of sand and gravel materials are dried in an oven to obtain multiple groups of dried sand and gravel materials.

[0125] Obtain the weight of each group of dried sand and gravel materials;

[0126] The moisture content of each group of sand and gravel is determined based on the weight of each group of sand and gravel and the weight of each group of dried sand and gravel, so as to obtain the moisture content of multiple groups of sand and gravel.

[0127] In this embodiment, the moisture content of each group of sand and gravel materials satisfies formula (1):

[0128]

[0129] Among them, W w m1 represents the moisture content of each group of sand and gravel materials, m2 represents the weight of each group of sand and gravel materials, and m3 represents the weight of each group of dried sand and gravel materials.

[0130] This application constructs a spectral coefficient library and obtains the moisture content and microwave spectrum of multiple groups of sand and gravel materials. Then, for each group of sand and gravel materials, a predicted moisture content set is determined based on multiple correlation coefficients in the spectral coefficient library and the microwave spectrum of each group. The moisture content of each group of sand and gravel materials is then compared with the predicted moisture content set to obtain the total moisture content error for each group. Finally, a target correlation coefficient is determined from multiple correlation coefficients based on the total moisture content error of multiple groups of sand and gravel materials to complete the calibration of the sand and gravel material moisture content. This application, by determining the target correlation coefficient from multiple correlation coefficients based on the total moisture content error of multiple groups of sand and gravel materials, can reduce the calibration time for sand and gravel material moisture content and improve the calibration accuracy.

[0131] In this embodiment of the application, the calibration device may further include:

[0132] The sprinkler communicates with the processor and is configured to adjust the moisture content of the sand and gravel materials;

[0133] The microwave moisture sensor, which communicates with the processor, is configured to collect the microwave spectrum of sand and gravel materials.

[0134] The oven, which communicates with the processor, is configured to dry sand and gravel materials.

[0135] In this embodiment, the calibration device may further include a sprinkler, a microwave moisture sensor, and an oven. The sprinkler, microwave moisture sensor, and oven all communicate with the processor. The sprinkler can be used to adjust the moisture content of the sand and gravel material. The microwave moisture sensor can be used to collect the microwave spectrum of the sand and gravel material. The oven can be used to dry the sand and gravel material. Thus, through the sprinkler, microwave moisture sensor, and oven, the calibration device can complete the calibration process for the moisture content of the sand and gravel material.

[0136] This application also provides a machine-readable storage medium storing instructions for causing a machine to perform the above-described method for calibrating the moisture content of sand and gravel materials.

[0137] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0138] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0139] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0140] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0141] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0142] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0143] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0144] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0145] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for calibrating the moisture content of a sand and gravel material, characterized by, The calibration method comprises the following steps: A spectrum coefficient library is constructed, and the spectrum coefficient library comprises a plurality of correlation coefficients; Obtain the moisture content and microwave spectrum of a plurality of groups of sand and stone materials; For each group of sand and stone materials, a predicted moisture content set of each group of sand and stone materials is determined according to the plurality of correlation coefficients and the microwave spectrum of each group of sand and stone materials respectively; Compare the moisture content and the predicted moisture content set of each group of sand and stone materials to obtain the moisture content error sum of each group of sand and stone materials; Determine a target correlation coefficient in the plurality of correlation coefficients according to the minimum moisture content error sum of the plurality of groups of sand and stone materials, so as to complete the calibration of the moisture content of the sand and stone materials; The calibration device comprises a microwave moisture sensor and a water sprayer, and the construction of the spectrum coefficient library comprises the following steps: Obtain a plurality of types of sample sand and stone materials; Divide each type of sample sand and stone material into a preset number of groups of sample sand and stone materials respectively; For any type of sample sand and stone material, adjust the moisture content of the any type of sample sand and stone material by the water sprayer to obtain a preset number of target sample sand and stone materials; Obtain the microwave spectrum of each group of target sample sand and stone materials by the microwave moisture sensor to obtain the microwave spectrum of the preset number of target sample sand and stone materials; Linearly fit the moisture content and the microwave spectrum of the preset number of target sample sand and stone materials respectively to determine a plurality of correlation coefficients of the any type of sample sand and stone material; Based on the plurality of correlation coefficients of the plurality of types of sample sand and stone materials, the spectrum coefficient library is constructed.

2. The calibration method of claim 1, wherein The linear fitting of the moisture content and the microwave spectrum of the preset number of target sample sand and stone materials respectively comprises the following steps: Linearly fit the moisture content and the microwave spectrum of the preset number of target sample sand and stone materials respectively by a gradient descent algorithm.

3. The calibration method of claim 1, wherein The adjustment of the moisture content of the any type of sample sand and stone material to obtain the preset number of target sample sand and stone materials comprises the following steps: Obtain a plurality of preset moisture contents; For the any type of sample sand and stone material, adjust the moisture content of the preset number of sample sand and stone materials according to the plurality of preset moisture contents to obtain the preset number of target sample sand and stone materials.

4. The calibration method of claim 1, wherein The determination of the predicted moisture content set of each group of sand and stone materials according to the plurality of correlation coefficients and the microwave spectrum of each group of sand and stone materials comprises the following steps: Obtain a plurality of correlation coefficients of a plurality of types of sample sand and stone materials from the spectrum coefficient library; Group the plurality of correlation coefficients according to the types of sample sand and stone materials to obtain a plurality of groups of correlation coefficients; Determine the predicted moisture content set of each group of sand and stone materials according to the plurality of groups of correlation coefficients and the microwave spectrum of each group of sand and stone materials respectively.

5. The calibration method of claim 1, wherein The calibration device comprises an oven, and the obtaining of the moisture content of a plurality of groups of sand and stone materials comprises the following steps: Obtain the weight of each group of sand and stone materials respectively; Dry a plurality of groups of sand and stone materials by the oven to obtain a plurality of groups of dried sand and stone materials; Obtain the weight of each group of dried sand and stone materials respectively; The water content of each group of sand and stone materials is determined according to the weight of each group of sand and stone materials and the weight of each group of dried sand and stone materials, so as to obtain the water contents of the groups of sand and stone materials.

6. The calibration method of claim 5, wherein, The water content of each group of sand and stone materials satisfies formula (1): ； （1） wherein, is the moisture content of the each group of sand and gravel material, is the weight of the tray, is the weight of the each group of sand and gravel material, is the weight of the each group of dried sand and gravel material.

7. A device for calibrating the water content of a sand and gravel material, characterized in that The method comprises the steps of: a memory configured to store instructions; and a processor configured to call the instructions from the memory and enable the calibration method of the water content of sand and stone materials according to any one of claims 1 to 6 when the instructions are executed.

8. The calibration device of claim 7, wherein The calibration device further comprises: a water sprayer in communication with the processor and configured to adjust the water content of sand and stone materials; a microwave moisture sensor in communication with the processor and configured to collect the microwave spectrum of the sand and stone materials; an oven in communication with the processor and configured to dry the sand and stone materials.

9. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing a machine to execute the calibration method of the water content of sand and stone materials according to any one of claims 1 to 6.

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