Multi-stage intelligent energy-saving temperature control drying system and method for kelp based on dynamic partitioning

Abstract

The present invention relates to the technical field of kelp drying control, and discloses a multi-stage intelligent energy-saving temperature-controlled drying system and method for kelp based on dynamic partitioning. The system comprises a kelp drying partition module, a kelp drying parameter analysis module, and a kelp drying adjustment module; a kelp partition three-dimensional model for kelp partition drying is intelligently constructed based on kelp three-dimensional model segmentation sample strip thickness partition parameters and kelp three-dimensional model segmentation sample parameters; intelligent screening of partition heat pump drying control parameters for kelp partition drying is performed based on kelp partition drying strip thickness mean parameters, kelp heat pump drying stage feature text parameters combined with an intelligent search algorithm and kelp standard heat pump drying control parameters corresponding to different kelp partition thicknesses in different drying stages based on big data storage, thereby realizing intelligent drying regulation of kelp drying in zones and stages.

Description

Technical Field

[0001] The present invention relates to the technical field of kelp drying control, and in particular to a multi-stage intelligent energy-saving temperature-controlled drying system and method for kelp based on dynamic partitioning. Background Art

[0002] Kelp heat pump drying rooms are commonly used in kelp drying processing. They are used for drying kelp and can also be used for drying other aquatic products. They have the advantages of high drying efficiency, excellent drying quality, low energy consumption, and environmental protection. The process flow of kelp heat pump drying technology includes a heating drying stage, a constant speed dehumidification drying stage, and a shaping drying stage. The existing kelp heat pump drying process cannot perform intelligent zoning drying based on kelp thickness and drying stage, which reduces the quality of kelp drying.

[0003] The Chinese invention patent with announcement number CN109442753B and announcement date 2021.10.01 discloses a precise temperature control type heat pump hot air furnace control system and control method; through the control system, through the collaboration of the temperature detection unit and the constant temperature adjustment unit, hot air matching the set temperature is supplied into the air supply unit; through the innovative design and intelligent control logic of the system, a multi-level selection of different heating capacities and a precisely controlled DC frequency conversion adjustment system are realized, so that when the heat pump is operating normally, the outlet air temperature of the heat pump is controlled to be maintained within ±0.3 degrees with the set temperature, thereby ensuring the quality and drying amount of the dried material; however, the above technical solution cannot realize zoned temperature control of the temperature adjustment object. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In order to solve the problem that some kelp heat pump drying processes cannot perform intelligent zoning and drying based on kelp thickness and drying stage, which reduces the quality of kelp drying, the above purpose is to realize the intelligent division of kelp drying areas, accurately control the heat pump drying parameters of different drying areas in different drying stages of kelp, and realize the intelligent control operation of kelp drying in different zones and stages.

[0006] (2) Technical solution

[0007] The present invention is achieved through the following technical solution: a multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning, the method comprising the following steps:

[0008] S1, collecting kelp three-dimensional model data;

[0009] S2. Segmenting the kelp 3D model samples according to the kelp 3D model data to generate kelp 3D model segmentation sample data and collecting the spatial coordinates of the kelp 3D model segmentation samples to generate kelp 3D model segmentation sample coordinate data;

[0010] S3, measuring the thickness of the kelp three-dimensional model segmented sample according to the kelp three-dimensional model segmented sample data and the kelp three-dimensional model segmented sample coordinate data, generating kelp three-dimensional model segmented sample strip thickness data and performing numerical partitioning processing on the kelp three-dimensional model segmented sample strip thickness, and constructing the kelp three-dimensional model segmented sample strip thickness interval;

[0011] S4, performing strip thickness parameter partitioning processing of the kelp 3D model segmented sample based on the strip thickness data of the kelp 3D model segmented sample and the strip thickness interval of the kelp 3D model segmented sample to generate kelp 3D model segmented sample strip thickness partition data; and performing kelp partition drying kelp partition three-dimensional model identification processing based on the kelp 3D model segmented sample data to generate kelp partition drying identification three-dimensional model data;

[0012] S5, performing statistical processing on the mean thickness of the dried kelp strips in the kelp zones according to the kelp three-dimensional model segmentation sample strip thickness zone data, to generate mean thickness data of the dried kelp strips in the kelp zones;

[0013] S6. Collecting characteristic text data of the kelp heat pump drying stage;

[0014] S7, performing zoned heat pump drying control parameter matching processing for kelp zone drying based on the kelp zone drying strip thickness mean data, the kelp heat pump drying stage characteristic text data, and the kelp standard heat pump drying control data corresponding to different kelp zone thicknesses at different drying stages, and generating kelp zone drying heat pump drying control data;

[0015] S8. Construct the kelp partition drying adjustment data and execute the kelp partition drying adjustment operation.

[0016] Preferably, the steps of collecting kelp three-dimensional model data are as follows:

[0017] S11, collect the 3D solid model information of the dried kelp online through a 3D laser scanner, and generate kelp 3D model data .

[0018] Preferably, the kelp 3D model sample segmentation processing is performed based on the kelp 3D model data to generate kelp 3D model segmentation sample data and perform spatial coordinate collection processing on the kelp 3D model segmentation sample. The operation steps for generating the kelp 3D model segmentation sample coordinate data are as follows:

[0019] S21, using the MarchingCubes three-dimensional grid division algorithm to divide the kelp three-dimensional model data The corresponding kelp 3D model upper surface is segmented and processed into a triangular mesh to generate a kelp 3D model segmentation sample data set , ;in Indicates the The kelp 3D model segmentation sample data corresponding to the kelp segmentation samples, Indicates the maximum number of kelp segmentation samples; the kelp three-dimensional model segmentation sample data represents the three-dimensional solid model data of the kelp segmentation sample formed after triangular mesh division;

[0020] S22, establishing a spatial rectangular coordinate system with the lower surface of the kelp three-dimensional model in step S21 as the base surface, and measuring the kelp three-dimensional model segmentation sample data set in order according to the kelp three-dimensional model segmentation sample number Sample data of kelp 3D model segmentation The corresponding spatial coordinate parameters of the center point of the kelp segmentation sample three-dimensional model, and generate the kelp three-dimensional model segmentation sample coordinate data set ,in Indicates the The kelp three-dimensional model segmentation sample coordinate data corresponding to the kelp segmentation samples represents the horizontal coordinate, vertical coordinate and vertical coordinate of the center point of the kelp segmentation sample three-dimensional model in the spatial rectangular coordinate system.

[0021] Preferably, the steps of measuring the strip thickness of the kelp 3D model segmentation sample according to the kelp 3D model segmentation sample data and the kelp 3D model segmentation sample coordinate data, generating the kelp 3D model segmentation sample strip thickness data and performing numerical partitioning processing on the kelp 3D model segmentation sample strip thickness, and constructing the kelp 3D model segmentation sample strip thickness interval are as follows:

[0022] S31, segmenting the generated kelp three-dimensional model into a sample data set Import into the mechanical 3D design software and run it, the mechanical 3D design software will segment the sample coordinate data set through the kelp 3D model Coordinate data of sample segments of the kelp 3D model Combined with the measurement tool to segment the sample data set of the kelp three-dimensional model Sample data of kelp 3D model segmentation The thickness of the corresponding kelp segmentation sample strip at the center point of the three-dimensional model is measured, and a data set of the kelp three-dimensional model segmentation sample strip thickness is generated. ,in Indicates the The thickness data of the kelp three-dimensional model segmentation sample corresponding to the kelp segmentation sample, The unit is millimeter, and the mechanical three-dimensional design software includes any one of SolidWorks, Creo, and AutoCAD;

[0023] S32, using a unified cost search algorithm to segment the kelp three-dimensional model sample strip thickness data set Thickness data of the kelp sample strip segmented by the three-dimensional model Compare the strip thickness values and search for the strip thickness data of the kelp three-dimensional model segmentation sample with the largest strip thickness value. and the kelp three-dimensional model segmentation sample strip thickness data with the smallest strip thickness value , and generate the maximum thickness of the kelp three-dimensional model segmentation sample after data identification The minimum thickness of the kelp 3D model segmentation sample ,in and The unit is millimeter;

[0024] S33, segmenting the sample strip thickness data set based on the kelp three-dimensional model Thickness data of the kelp sample strip segmented by the three-dimensional model Perform statistical processing on the mean thickness of the strip to generate the mean thickness of the strip of the kelp three-dimensional model segmentation sample ,in ,in The unit is millimeter;

[0025] S34, dividing the maximum thickness of the sample strip according to the three-dimensional model of the kelp , the minimum thickness of the kelp three-dimensional model segmented sample strip , the average thickness of the kelp three-dimensional model segmented sample strip Perform the value interval partitioning of the kelp three-dimensional model segmentation sample strip thickness, and construct the kelp three-dimensional model segmentation sample strip thickness interval set ,in Indicates the The thickness interval of the kelp sample body corresponding to the kelp drying partition is segmented by the 3D model. ; Indicates the thickness interval of the kelp three-dimensional model segmentation sample corresponding to the second kelp drying partition, .

[0026] Preferably, based on the kelp three-dimensional model segmentation sample strip body thickness data and the kelp three-dimensional model segmentation sample strip body thickness interval, the kelp three-dimensional model segmentation sample strip body thickness parameter partitioning processing is performed to generate the kelp three-dimensional model segmentation sample strip body thickness partition data and the kelp three-dimensional model segmentation sample data is combined with the kelp three-dimensional model segmentation sample data to perform kelp partition drying kelp partition three-dimensional model identification processing, and the operating steps of generating the kelp partition drying identification three-dimensional model data are as follows:

[0027] S41, dividing the kelp three-dimensional model into sample strip thickness data sets All the kelp 3D model segmentation sample strip thickness data Thickness interval set of the sample strip segmented with the kelp three-dimensional model The thickness interval of the kelp three-dimensional model segmentation sample strip The minimum thickness of the kelp three-dimensional model segmentation sample , the average thickness of the kelp three-dimensional model segmented sample strip , and the thickness interval of the sample strip body segmented by the three-dimensional model of kelp The mean thickness of the kelp 3D model segmented sample and the maximum thickness of the kelp three-dimensional model segmented sample strip Perform a comparison of the strip thickness values, and segment the strip thickness data set of the kelp three-dimensional model according to the strip thickness value comparison result. All the kelp 3D model segmentation sample strip thickness data Segment the sample strip thickness interval set according to the kelp three-dimensional model The thickness interval of the kelp three-dimensional model segmentation sample strip and the three-dimensional model of kelp to segment the sample strip thickness interval Performing the zoning and screening of the strip thickness parameters of the kelp three-dimensional model segmentation sample, and generating the kelp three-dimensional model segmentation sample strip thickness partition data set matrix ,in Indicates that the kelp three-dimensional model is segmented into sample strip thickness data sets Thickness data of the kelp sample strip segmented by the three-dimensional model The thickness range of the kelp three-dimensional model segmentation sample is selected according to the comparison of the thickness values of the kelp Thickness data of the kelp sample strip segmented in the 3D model The formation of The kelp three-dimensional model segmentation sample belt thickness partition data set corresponding to the kelp drying partition; Indicates that the kelp three-dimensional model is segmented into sample strip thickness data sets Thickness data of the kelp sample strip segmented by the three-dimensional model The thickness range of the kelp three-dimensional model segmentation sample is selected according to the comparison of the thickness values of the kelp Thickness data of the kelp sample strip segmented in the 3D model The formed kelp three-dimensional model segmentation sample strip thickness partition data set corresponding to the second kelp drying partition;

[0028] S42, using a bidirectional iterative search algorithm to segment the sample strip thickness partition data set matrix according to the kelp three-dimensional model The kelp three-dimensional model segmentation sample strip thickness partition data set and the kelp three-dimensional model segmentation sample strip thickness partition data set The kelp three-dimensional model segmentation sample belt thickness partition data corresponding to the kelp segmentation sample number is the kelp three-dimensional model segmentation sample data set Sample data of kelp 3D model segmentation The corresponding kelp segmentation sample 3D model is partitioned and screened, and the two kelp segmentation sample 3D model sets after partitioning are colored with different colors by combining the coloring tool in the mechanical 3D design software, and a kelp partition drying mark 3D model data set is generated. ,in Represents the kelp three-dimensional model segmentation sample data set Sample data of kelp 3D model segmentation Segment the sample strip thickness partition data set according to the kelp three-dimensional model The kelp segmentation sample number corresponding to the kelp three-dimensional model segmentation sample body thickness partition data is subjected to kelp segmentation sample three-dimensional model partition screening and coloring processing to form kelp partition drying identification three-dimensional model data corresponding to the first kelp drying partition; Represents the kelp three-dimensional model segmentation sample data set Sample data of kelp 3D model segmentation Segment the sample strip thickness partition data set according to the kelp three-dimensional model The kelp segmentation sample number corresponding to the kelp body thickness partition data of the kelp 3D model segmentation sample is subjected to kelp segmentation sample 3D model partition screening and coloring processing to form kelp partition drying identification 3D model data corresponding to the second kelp drying partition.

[0029] Preferably, the steps of performing statistical processing on the mean thickness of the dried kelp strips in the partitioned kelp strips according to the kelp three-dimensional model segmentation sample strip thickness partition data to generate the mean thickness data of the dried kelp strips in the partitioned kelp strips are as follows:

[0030] S51, segmenting the kelp three-dimensional model into a sample strip thickness partition data set matrix The kelp three-dimensional model segmentation sample belt thickness partition data set The three-dimensional model of kelp segmentation sample strip body thickness partition data, and the three-dimensional model of kelp segmentation sample strip body thickness partition data set The three-dimensional model segmentation sample strip thickness partition data of the kelp is respectively measured according to the mean measurement formula in step S33 to obtain the three-dimensional model segmentation sample strip thickness partition data set. The three-dimensional model of the kelp is segmented into sample strip body thickness partition data, and the three-dimensional model of the kelp is segmented into sample strip body thickness partition data set The kelp three-dimensional model segmentation sample strip thickness partition data corresponding to the kelp three-dimensional model segmentation sample strip thickness parameter partition mean strip thickness, and generate the kelp partition drying strip thickness mean data set ,in Represents the kelp three-dimensional model segmentation sample strip thickness partition data set The corresponding mean thickness data of the kelp drying zone in the first kelp drying zone, Represents the kelp three-dimensional model segmentation sample strip thickness partition data set The corresponding mean thickness data of the kelp drying zone of the second kelp drying zone, where and The units are all millimeters.

[0031] Preferably, the steps of collecting characteristic text data of the kelp heat pump drying stage are as follows:

[0032] S61. Collect the characteristic information of the heat pump drying stage of the kelp being dried online through the kelp drying management platform, and generate the characteristic text data of the kelp heat pump drying stage. The kelp heat pump drying stage characteristic text data represents characteristic information of the heat pump drying stage in which the dried kelp is currently located. The heat pump drying stage includes any one of a heating drying stage, a constant speed dehumidification drying stage, and a shaping drying stage.

[0033] Preferably, the following steps are performed to match the zoned heat pump drying control parameters of kelp zone drying based on the mean value data of kelp zone drying strip thickness, the characteristic text data of the kelp heat pump drying stage, and the kelp standard heat pump drying control data corresponding to different kelp zone thicknesses in different drying stages, and to generate the kelp zone drying heat pump drying control data:

[0034] S71. Establishing a standard heat pump drying control data set for kelp at different drying stages and corresponding to different kelp partition thicknesses , ;in Indicates the The different drying stages and different kelp partition thicknesses corresponding to the kelp drying characteristic combination types correspond to the kelp standard heat pump drying control data. Indicates the maximum number of kelp segmentation samples; the kelp drying feature combination type represents an index data type mainly formed by the combination of kelp heat pump drying stage information and kelp partition drying strip body thickness mean parameter for searching for kelp standard heat pump drying control parameters; the kelp standard heat pump drying control data corresponding to different kelp partition thicknesses in different drying stages represents the optimal heat pump drying control parameters set for the kelp drying feature combination type of the kelp drying partition, and the heat pump drying control parameters include drying airflow temperature and airflow velocity;

[0035] S72, using the Aho-Corasick search algorithm to partition the kelp drying strip thickness mean data set The average thickness data of kelp dried by different zones And the mean thickness data of the kelp drying strip body in different zones Combined with the characteristic text data of the kelp heat pump drying stage Standard heat pump drying control data set for kelp corresponding to different kelp partition thicknesses at different drying stages The different kelp partition thicknesses at different drying stages described in the standard heat pump drying control data for kelp Perform character matching of the kelp heat pump drying stage and the kelp zone drying belt thickness mean value, and search for the kelp zone drying belt thickness mean value data respectively and the characteristic text data of the kelp heat pump drying stage , and the mean thickness data of the kelp drying strips in different zones and the characteristic text data of the kelp heat pump drying stage The corresponding kelp standard heat pump drying control data for the different kelp partition thicknesses in the different drying stages , and generate kelp partition drying heat pump drying control data set through data identification ,in Represents the three-dimensional model data of the kelp partition drying mark The corresponding kelp drying zone heat pump drying control data of the first kelp drying zone; wherein Represents the three-dimensional model data of the kelp partition drying mark The corresponding kelp zone drying heat pump drying control data of the second kelp drying zone, the kelp zone drying heat pump drying control data represents the optimal heat pump drying control parameters screened for the kelp drying zone.

[0036] Preferably, the steps of constructing the kelp zone drying adjustment data and executing the kelp zone drying adjustment operation are as follows:

[0037] S81, drying the kelp in different areas and marking the three-dimensional model data set 3D model data of kelp partition drying identification to and the kelp partition drying heat pump drying control data set Kelp zone drying heat pump drying control data to Data combination identification is performed according to the kelp drying partition number to construct the kelp partition drying adjustment data set ,in Indicates the kelp drying adjustment data corresponding to the first kelp drying zone. ; Indicates the kelp drying adjustment data corresponding to the second kelp drying zone. ;

[0038] S82, the kelp drying management platform adjusts the data set according to the kelp partition drying Kelp zone drying adjustment data described in to The heat pump drying control parameters of the corresponding kelp drying zones adjust the air flow temperature and air flow velocity of the heat pump drying system, and perform the kelp drying operation in zones based on the three-dimensional model information of the kelp drying zones.

[0039] A multi-stage intelligent energy-saving temperature-controlled drying system for kelp based on dynamic partitioning is used to implement the multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning. The system includes a kelp drying partition module, a kelp drying parameter analysis module, and a kelp drying adjustment module;

[0040] The kelp drying partition module includes a kelp three-dimensional model acquisition unit, a kelp three-dimensional model segmentation unit, a kelp three-dimensional model segmentation sample coordinate measurement unit, a kelp three-dimensional model segmentation sample thickness measurement unit, a kelp three-dimensional model segmentation sample thickness parameter partition unit, a kelp three-dimensional model segmentation sample partition unit, and a kelp drying partition thickness mean value statistics unit;

[0041] The kelp 3D model acquisition unit acquires kelp 3D model data through a 3D laser scanner; the kelp 3D model segmentation unit performs kelp 3D model sample segmentation processing based on the kelp 3D model data to generate kelp 3D model segmentation sample data; the kelp 3D model segmentation sample coordinate measurement unit performs spatial coordinate acquisition processing of kelp 3D model segmentation samples based on the kelp 3D model segmentation sample data to generate kelp 3D model segmentation sample coordinate data; the kelp 3D model segmentation sample thickness measurement unit performs strip body thickness measurement processing of kelp 3D model segmentation samples based on the kelp 3D model segmentation sample data, the kelp 3D model segmentation sample coordinate data and in combination with the measurement tool in the mechanical 3D design software to generate the kelp 3D model segmentation sample Strip thickness data; the kelp three-dimensional model segmentation sample thickness parameter partitioning unit performs numerical partitioning processing of the kelp three-dimensional model segmentation sample strip thickness according to the kelp three-dimensional model segmentation sample strip thickness data, and constructs the kelp three-dimensional model segmentation sample strip thickness interval; the kelp three-dimensional model segmentation sample partitioning unit performs kelp partition three-dimensional model identification processing of the kelp partition drying according to the kelp three-dimensional model segmentation sample strip thickness partition data and the kelp three-dimensional model segmentation sample data, and generates kelp partition drying identification three-dimensional model data; the kelp drying partition thickness mean value statistical unit performs statistical processing of the kelp partition strip thickness mean value of the kelp partition drying according to the kelp three-dimensional model segmentation sample strip thickness partition data, and generates kelp partition drying strip thickness mean value data;

[0042] The kelp drying parameter analysis module includes a kelp heat pump drying stage characteristic information collection unit, a kelp standard heat pump drying parameter storage unit corresponding to different kelp partition thicknesses at different drying stages, and a kelp partition drying heat pump drying parameter matching unit;

[0043] The kelp heat pump drying stage characteristic information collection unit collects kelp heat pump drying stage characteristic text data through the kelp drying management platform; the kelp standard heat pump drying parameter storage unit corresponding to different kelp partition thicknesses in different drying stages is used to store kelp standard heat pump drying control data corresponding to different kelp partition thicknesses in different drying stages; the kelp partition drying heat pump drying parameter matching unit performs partition heat pump drying control parameter matching processing for kelp partition drying based on the kelp partition drying strip body thickness mean data, the kelp heat pump drying stage characteristic text data and the kelp standard heat pump drying control data corresponding to different kelp partition thicknesses in different drying stages, and generates kelp partition drying heat pump drying control data;

[0044] The kelp drying adjustment module includes a kelp partition drying adjustment parameter construction unit and a kelp partition drying adjustment unit;

[0045] The kelp zone drying adjustment parameter construction unit constructs kelp zone drying adjustment data based on the heat pump drying control parameters of the kelp drying zone and the three-dimensional model information of the kelp drying zone combined with data processing; the kelp zone drying adjustment unit performs the kelp zone drying adjustment operation based on the kelp zone drying adjustment data combined with the kelp drying management platform.

[0046] (3) Beneficial effects

[0047] The present invention provides a multi-stage intelligent energy-saving temperature-controlled drying system and method for kelp based on dynamic zoning. It has the following beneficial effects:

[0048] 1. Accurately and efficiently collect kelp three-dimensional model information through 3D laser scanner, and combine it with model sample segmentation processing to scientifically and finely generate kelp three-dimensional model segmentation sample information, providing real data support for kelp zoning drying; scientifically establish kelp three-dimensional model segmentation sample coordinate parameters based on data analysis, and combine the measurement tools in mechanical three-dimensional design software to accurately measure the strip thickness of kelp three-dimensional model segmentation samples, realize scientific evaluation of kelp zoning drying, and improve the accuracy of kelp drying; digitally construct the strip thickness zoning intervals of kelp zoning drying based on the strip thickness parameters of kelp three-dimensional model segmentation samples, and realize accurate division of kelp zoning drying areas based on kelp thickness characteristics; intelligently build kelp zoning three-dimensional models of kelp zoning drying based on the strip thickness zoning parameters of kelp three-dimensional model segmentation samples and kelp three-dimensional model segmentation sample parameters, and realize intelligent division of kelp drying areas; autonomously and efficiently count the mean strip thickness of kelp zoning drying based on the strip thickness zoning parameters of kelp three-dimensional model segmentation samples, realize scientific statistics of strip thickness of kelp zoning drying, and improve the quality of kelp drying.

[0049] 2. Collect the characteristic information of kelp heat pump drying stages online through the kelp drying management platform to provide reliable data support for the scientific adjustment of heat pump drying control parameters; intelligent screening of zoned heat pump drying control parameters for kelp zone drying is carried out based on the mean thickness parameter of kelp zone drying strips, characteristic text parameters of kelp heat pump drying stages, combined with intelligent search algorithm and standard heat pump drying control parameters of kelp zone drying corresponding to different kelp zone thicknesses in different drying stages based on big data storage, to achieve scientific selection and matching of heat pump drying control parameters based on kelp strip thickness and drying stage classification, to achieve intelligent drying regulation of kelp drying in zones and stages, and to improve the applicability of kelp drying.

[0050] 3. By combining data processing with the heat pump drying control parameters of the kelp drying zones and the three-dimensional model information of the kelp drying zones, the kelp zone drying adjustment parameters are efficiently and scientifically constructed to realize the timely collection of the kelp drying adjustment parameters. Based on the kelp zone drying adjustment parameters and the kelp drying management platform, the kelp zone drying adjustment operation is efficiently and autonomously performed to improve the efficiency and output of kelp drying. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 A schematic diagram of a module for a multi-stage intelligent energy-saving temperature-controlled drying system for kelp based on dynamic partitioning provided by the present invention;

[0052] Figure 2 This is a flow chart of the multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic zoning provided by the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0054] The embodiments of the multi-stage intelligent energy-saving temperature-controlled drying system and method for kelp based on dynamic partitioning are as follows:

[0055] Example 1:

[0056] See also Figure 1-Figure 2 A multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning comprises the following steps:

[0057] S1, collecting kelp three-dimensional model data;

[0058] S2. Segmenting the kelp 3D model samples according to the kelp 3D model data to generate kelp 3D model segmentation sample data and collecting the spatial coordinates of the kelp 3D model segmentation samples to generate kelp 3D model segmentation sample coordinate data;

[0059] S3, performing a measurement process on the strip body thickness of the kelp 3D model segmentation sample according to the kelp 3D model segmentation sample data and the kelp 3D model segmentation sample coordinate data, generating the kelp 3D model segmentation sample strip body thickness data and performing a numerical partitioning process on the kelp 3D model segmentation sample strip body thickness, and constructing the kelp 3D model segmentation sample strip body thickness interval;

[0060] S4, based on the kelp three-dimensional model segmentation sample strip body thickness data and the kelp three-dimensional model segmentation sample strip body thickness interval, the kelp three-dimensional model segmentation sample strip body thickness parameter partitioning processing is performed to generate the kelp three-dimensional model segmentation sample strip body thickness partition data; and the kelp three-dimensional model segmentation sample data is combined with the kelp three-dimensional model segmentation sample data to perform kelp partition drying kelp partition three-dimensional model identification processing to generate kelp partition drying identification three-dimensional model data;

[0061] S5, performing statistical processing on the mean thickness of the kelp zone dried in the kelp zone according to the kelp three-dimensional model segmentation sample zone thickness data, and generating the mean thickness data of the kelp zone dried;

[0062] S6. Collecting characteristic text data of the kelp heat pump drying stage;

[0063] S7, performing zoned heat pump drying control parameter matching processing for kelp zone drying based on the kelp zone drying strip thickness mean data, the kelp heat pump drying stage characteristic text data, and the kelp standard heat pump drying control data corresponding to different kelp zone thicknesses at different drying stages, and generating kelp zone drying heat pump drying control data;

[0064] S8. Construct the kelp partition drying adjustment data and execute the kelp partition drying adjustment operation.

[0065] For further information, see Figure 1-Figure 2 ,The steps for collecting kelp 3D model data are as follows:

[0066] S11, collect the 3D solid model information of the dried kelp online through a 3D laser scanner, and generate kelp 3D model data .

[0067] The kelp 3D model sample segmentation processing is performed based on the kelp 3D model data to generate the kelp 3D model segmentation sample data and perform spatial coordinate collection processing on the kelp 3D model segmentation sample. The operation steps for generating the kelp 3D model segmentation sample coordinate data are as follows:

[0068] S21. Use MarchingCubes 3D meshing algorithm to 3D model data of kelp The corresponding kelp 3D model upper surface is segmented and processed into a triangular mesh to generate a kelp 3D model segmentation sample data set , ;in Indicates the The kelp 3D model segmentation sample data corresponding to the kelp segmentation samples, Indicates the maximum number of kelp segmentation samples; kelp three-dimensional model segmentation sample data indicates the three-dimensional solid model data of the kelp segmentation sample formed after triangular mesh division;

[0069] S22, using the lower surface of the kelp 3D model in step S21 as the base surface to establish a spatial rectangular coordinate system, and measuring the kelp 3D model segmentation sample data set in order according to the kelp 3D model segmentation sample number Sample data of 3D model segmentation of the middle seaweed The corresponding spatial coordinate parameters of the center point of the kelp segmentation sample three-dimensional model, and generate the kelp three-dimensional model segmentation sample coordinate data set ,in Indicates the The kelp three-dimensional model segmentation sample coordinate data corresponding to the kelp segmentation samples represents the horizontal coordinate, vertical coordinate and vertical coordinate of the center point of the kelp segmentation sample three-dimensional model in the spatial rectangular coordinate system.

[0070] The steps for measuring the thickness of the kelp 3D model segmentation sample strips according to the kelp 3D model segmentation sample data and the kelp 3D model segmentation sample coordinate data, generating the kelp 3D model segmentation sample strip thickness data, performing numerical partitioning processing on the kelp 3D model segmentation sample strip thickness, and constructing the kelp 3D model segmentation sample strip thickness intervals are as follows:

[0071] S31, segmenting the generated kelp three-dimensional model into a sample data set Import it into the mechanical 3D design software and run it. The mechanical 3D design software will segment the sample coordinate data set through the kelp 3D model. Coordinate data of the sample segmentation of the 3D model of the middle seaweed Combined with measurement tools to segment the sample data set of kelp 3D model Sample data of 3D model segmentation of the middle seaweed The thickness of the corresponding kelp segmentation sample strip at the center point of the three-dimensional model is measured, and a data set of the kelp three-dimensional model segmentation sample strip thickness is generated. ,in Indicates the The thickness data of the kelp three-dimensional model segmentation sample corresponding to the kelp segmentation sample, The unit is millimeter. The mechanical 3D design software includes any one of SolidWorks, Creo, and AutoCAD;

[0072] S32. Use unified cost search algorithm to segment the sample strip thickness data set of kelp three-dimensional model Thickness data of the sample strip body of the 3D model of the middle sea zone Compare the strip thickness values and search for the strip thickness data of the kelp three-dimensional model segmentation sample with the largest strip thickness value. The thickness data of the kelp sample segmented by the 3D model with the smallest thickness value , and generate the maximum thickness of the kelp three-dimensional model segmentation sample after data identification The minimum thickness of the kelp 3D model segmentation sample ,in and The unit is millimeter;

[0073] S33. Segmentation of sample strip thickness data sets based on kelp three-dimensional model Thickness data of the sample strip body of the 3D model of the middle sea zone Perform statistical processing on the mean thickness of the strip to generate the mean thickness of the strip of the kelp three-dimensional model segmentation sample ,in ,in The unit is millimeter;

[0074] S34. Segment the maximum thickness of the sample strip based on the kelp three-dimensional model , Minimum thickness of kelp 3D model segmentation sample , the average thickness of the kelp 3D model segmentation sample Perform the value interval partitioning of the kelp three-dimensional model segmentation sample strip thickness, and construct the kelp three-dimensional model segmentation sample strip thickness interval set ,in Indicates the The thickness interval of the kelp sample body corresponding to the kelp drying partition is segmented by the 3D model. ; Indicates the thickness interval of the kelp three-dimensional model segmentation sample corresponding to the second kelp drying partition, .

[0075] Based on the kelp 3D model segmentation sample strip thickness data and the kelp 3D model segmentation sample strip thickness interval, the kelp 3D model segmentation sample strip thickness parameter partitioning processing is performed to generate the kelp 3D model segmentation sample strip thickness partition data and the kelp 3D model segmentation sample data is combined with the kelp 3D model segmentation sample data to perform kelp partition drying kelp partition 3D model identification processing. The operation steps for generating the kelp partition drying identification 3D model data are as follows:

[0076] S41, dividing the kelp three-dimensional model into sample strip thickness data sets All the kelp 3D model segmentation sample strip thickness data Thickness interval set of sample strips segmented with kelp 3D model The thickness interval of the internal kelp three-dimensional model segmentation sample Minimum thickness of the kelp 3D model segmentation sample , the average thickness of the kelp 3D model segmentation sample , and the thickness interval of the kelp three-dimensional model segmentation sample strip The average thickness of the kelp 3D model segmentation sample The maximum thickness of the kelp 3D model segmentation sample Compare the thickness values of the strips and segment the kelp three-dimensional model into sample strip thickness data sets based on the comparison results. All the kelp 3D model segmentation sample strip thickness data Segment the sample strip thickness interval set according to the kelp three-dimensional model Thickness interval of the sample strip body segmented by the three-dimensional model of the middle sea zone Thickness interval of the sample strip segmented by kelp three-dimensional model Performing the zoning and screening of the strip thickness parameters of the kelp three-dimensional model segmentation sample, and generating the kelp three-dimensional model segmentation sample strip thickness partition data set matrix ,in Indicates the data set of the thickness of the sample strips of the kelp 3D model segmentation Thickness data of the sample strip body of the 3D model of the middle sea zone According to the comparison of the strip thickness values, the strip thickness range of the kelp three-dimensional model segmentation sample was selected. Thickness data of kelp 3D model segmentation sample strip The formation of The kelp three-dimensional model segmentation sample belt thickness partition data set corresponding to the kelp drying partition; Indicates the data set of the thickness of the sample strips of the kelp 3D model segmentation Thickness data of the sample strip body of the 3D model of the middle sea zone According to the comparison of the strip thickness values, the strip thickness range of the kelp three-dimensional model segmentation sample was selected. Thickness data of kelp 3D model segmentation sample strip The formed kelp three-dimensional model segmentation sample strip thickness partition data set corresponding to the second kelp drying partition;

[0077] S42, using a bidirectional iterative search algorithm to segment the sample strip thickness partition data set matrix according to the kelp three-dimensional model Data set of the thickness partition of the 3D model of the mid-sea belt segmentation sample and the data set of kelp 3D model segmentation sample strip thickness partition The kelp three-dimensional model segmentation sample belt thickness partition data corresponding to the kelp segmentation sample number is the kelp three-dimensional model segmentation sample data set Sample data of 3D model segmentation of the middle seaweed The corresponding kelp segmentation sample 3D model is partitioned and screened, and the two kelp segmentation sample 3D model sets after partitioning are colored with different colors by combining the coloring tool in the mechanical 3D design software, and a kelp partition drying mark 3D model data set is generated. ,in Represents a sample data set of kelp 3D model segmentation Sample data of 3D model segmentation of the middle seaweed Segmentation of sample strip thickness partition data sets based on kelp 3D model The kelp segmentation sample number corresponding to the kelp body thickness partition data of the kelp 3D model segmentation sample is subjected to kelp segmentation sample 3D model partition screening and coloring processing to form kelp partition drying identification 3D model data corresponding to the first kelp drying partition; Represents a sample data set of kelp 3D model segmentation Sample data of 3D model segmentation of the middle seaweed Segmentation of sample strip thickness partition data sets based on kelp 3D model The kelp segmentation sample number corresponding to the kelp body thickness partition data of the kelp 3D model segmentation sample is subjected to kelp segmentation sample 3D model partition screening and coloring processing to form the kelp partition drying identification 3D model data corresponding to the second kelp drying partition.

[0078] The steps for generating the mean strip thickness data of the dried kelp strips by the 3D kelp model are as follows:

[0079] S51, segmenting the sample strip thickness partition data set matrix of the kelp three-dimensional model The data set of kelp 3D model segmentation sample strip thickness partition Thickness partition data of the 3D model segmentation sample of kelp, and the data set of thickness partition data of the 3D model segmentation sample of kelp The 3D model segmentation sample strip thickness partition data of the kelp is respectively measured according to the mean measurement formula in step S33 to obtain the 3D model segmentation sample strip thickness partition data set. Thickness partition data of the 3D model segmentation sample of kelp, and the data set of thickness partition data of the 3D model segmentation sample of kelp The mean value of the thickness of the kelp three-dimensional model segmentation sample strip thickness parameter partition corresponding to the kelp three-dimensional model segmentation sample strip thickness partition data, and generate the kelp partition drying strip thickness mean data set ,in Represents the data set of kelp 3D model segmentation sample strip thickness partition The corresponding mean thickness data of the kelp drying zone in the first kelp drying zone, Represents the data set of kelp 3D model segmentation sample strip thickness partition The corresponding mean thickness data of the kelp drying zone of the second kelp drying zone, where and The units are all millimeters.

[0080] Through the cooperation of the kelp 3D model acquisition unit and the kelp 3D model segmentation unit, a 3D laser scanner is used to accurately and efficiently collect kelp 3D model information, and combined with the model sample segmentation processing, the kelp 3D model segmentation sample information is scientifically and finely generated to provide real data support for kelp partition drying; the kelp 3D model segmentation sample coordinate measurement unit and the kelp 3D model segmentation sample thickness measurement unit cooperate with each other, and the kelp 3D model segmentation sample coordinate parameters are scientifically established based on data analysis. At the same time, the measurement tools in the mechanical 3D design software are combined to accurately measure the thickness of the kelp 3D model segmentation sample, so as to realize the scientific evaluation of kelp partition drying and improve the accuracy of kelp drying; the kelp 3D model segmentation sample thickness parameters are scientifically established based on data analysis. The partitioning unit digitally constructs the kelp strip thickness partition intervals for kelp zone drying based on the strip thickness parameters of the kelp three-dimensional model segmentation sample, and realizes the accurate division of kelp zone drying areas based on kelp thickness characteristics; the kelp three-dimensional model segmentation sample partitioning unit intelligently constructs the kelp zone three-dimensional model for kelp zone drying based on the strip thickness partition parameters of the kelp three-dimensional model segmentation sample and the kelp three-dimensional model segmentation sample parameters, and realizes the intelligent division of kelp drying areas; the kelp drying zone thickness mean statistical unit independently and efficiently calculates the mean strip thickness of the kelp zone drying based on the strip thickness partition parameters of the kelp three-dimensional model segmentation sample, and realizes the scientific statistics of the strip thickness of the kelp zone drying, and improves the quality of kelp drying.

[0081] For further information, see Figure 1-Figure 2 The steps for collecting the characteristic text data of the kelp heat pump drying stage are as follows:

[0082] S61. Collect the characteristic information of the heat pump drying stage of the kelp being dried online through the kelp drying management platform, and generate the characteristic text data of the kelp heat pump drying stage. The kelp heat pump drying stage characteristic text data represents characteristic information of the heat pump drying stage in which the dried kelp is currently located. The heat pump drying stage includes any one of a heating drying stage, a constant speed dehumidification drying stage, and a shaping drying stage.

[0083] The following steps are used to match the zoned heat pump drying control parameters of kelp zoned drying based on the mean kelp zoned drying thickness data, the kelp heat pump drying stage characteristic text data, and the kelp standard heat pump drying control data corresponding to different kelp zone thicknesses at different drying stages, and to generate the kelp zoned drying heat pump drying control data:

[0084] S71. Establishing a standard heat pump drying control data set for kelp at different drying stages and corresponding to different kelp partition thicknesses , ;in Indicates the The different drying stages and different kelp partition thicknesses corresponding to the kelp drying characteristic combination types correspond to the kelp standard heat pump drying control data. Indicates the maximum number of kelp segmentation samples; the kelp drying feature combination type indicates the index data type used to search for kelp standard heat pump drying control parameters, which is mainly formed by the combination of kelp heat pump drying stage information and the mean parameter of kelp partition drying strip thickness; the kelp standard heat pump drying control data corresponding to different kelp partition thicknesses at different drying stages indicates the optimal heat pump drying control parameters set for the kelp drying feature combination type of the kelp drying partition, and the heat pump drying control parameters include the drying airflow temperature and airflow velocity;

[0085] S72, using the Aho-Corasick search algorithm to partition the kelp drying strip thickness mean data set Average thickness data of the dried belt in different zones in the middle sea Average thickness data of kelp dried by different zones Combined with the characteristic text data of kelp heat pump drying stage Standard heat pump drying control data set for kelp at different drying stages and different kelp partition thicknesses Standard heat pump drying control data of kelp corresponding to different kelp partition thicknesses in different drying stages Perform character matching on the mean thickness of kelp heat pump drying stage and kelp zone drying strip, and search for the mean thickness data of kelp zone drying strip respectively. Characteristic text data of kelp heat pump drying stage , and the average thickness data of kelp drying strips in different zones Characteristic text data of kelp heat pump drying stage The corresponding different drying stages and different kelp partition thicknesses correspond to the standard heat pump drying control data of kelp , and generate kelp partition drying heat pump drying control data set through data identification ,in 3D model data showing kelp drying zone identification The corresponding kelp drying zone heat pump drying control data of the first kelp drying zone; wherein 3D model data showing kelp drying zone identification The corresponding kelp zone drying heat pump drying control data of the second kelp drying zone, the kelp zone drying heat pump drying control data represents the optimal heat pump drying control parameters screened for the kelp drying zone.

[0086] Through the kelp heat pump drying stage characteristic information collection unit, the kelp drying management platform is used to collect the kelp heat pump drying stage characteristic information online, providing reliable data support for the scientific adjustment of heat pump drying control parameters; the kelp zone drying heat pump drying parameter matching unit, based on the kelp zone drying strip body thickness mean parameter, kelp heat pump drying stage characteristic text parameter combined with intelligent search algorithm and different drying stages and different kelp zone thickness corresponding to kelp standard heat pump drying control parameters based on big data storage, intelligent screening of zone heat pump drying control parameters for kelp zone drying, realize scientific selection and matching of heat pump drying control parameters based on kelp strip body thickness and drying stage classification, realize intelligent drying regulation of kelp drying in zones and stages, and improve the applicability of kelp drying.

[0087] For further information, see Figure 1-Figure 2 The steps for constructing kelp zone drying adjustment data and executing kelp zone drying adjustment operations are as follows:

[0088] S81, drying the kelp in sections and labeling the three-dimensional model data set 3D model data of the zone drying mark of Zhonghai kelp to Kelp zone drying heat pump drying control data collection Zhonghai belt zone drying heat pump drying control data to Data combination identification is performed according to the kelp drying partition number to construct the kelp partition drying adjustment data set ,in Indicates the kelp drying adjustment data corresponding to the first kelp drying zone. ; Indicates the kelp drying adjustment data corresponding to the second kelp drying zone. ;

[0089] S82, kelp drying management platform adjusts data collection based on kelp drying zones Zhonghai Belt Zone Drying Adjustment Data to The heat pump drying control parameters of the corresponding kelp drying zones adjust the air flow temperature and air flow velocity of the heat pump drying system, and perform the kelp drying operation in zones based on the three-dimensional model information of the kelp drying zones.

[0090] Through the kelp zone drying adjustment parameter construction unit, the kelp zone drying adjustment parameters are constructed efficiently and scientifically based on the heat pump drying control parameters of the kelp drying zone and the kelp drying zone three-dimensional model information combined with data processing, so as to realize the timely collection of kelp drying adjustment parameters. The kelp zone drying adjustment unit, based on the kelp zone drying adjustment parameters combined with the kelp drying management platform, efficiently and autonomously performs the kelp zone drying adjustment operation, thereby improving the efficiency and output of kelp drying.

[0091] Example 2:

[0092] See also Figure 1-Figure 2 , a multi-stage intelligent energy-saving temperature control drying system for kelp based on dynamic partitioning is used to implement a multi-stage intelligent energy-saving temperature control drying method for kelp based on dynamic partitioning. The system includes a kelp drying partition module, a kelp drying parameter analysis module, and a kelp drying adjustment module;

[0093] The kelp drying partition module includes a kelp three-dimensional model acquisition unit, a kelp three-dimensional model segmentation unit, a kelp three-dimensional model segmentation sample coordinate measurement unit, a kelp three-dimensional model segmentation sample thickness measurement unit, a kelp three-dimensional model segmentation sample thickness parameter partition unit, a kelp three-dimensional model segmentation sample partition unit, and a kelp drying partition thickness mean value statistics unit;

[0094] The kelp 3D model acquisition unit acquires kelp 3D model data through a 3D laser scanner; the kelp 3D model segmentation unit performs kelp 3D model sample segmentation processing based on the kelp 3D model data to generate kelp 3D model segmentation sample data; the kelp 3D model segmentation sample coordinate measurement unit performs spatial coordinate acquisition processing of kelp 3D model segmentation samples based on the kelp 3D model segmentation sample data to generate kelp 3D model segmentation sample coordinate data; the kelp 3D model segmentation sample thickness measurement unit performs belt body thickness measurement processing of kelp 3D model segmentation samples based on the kelp 3D model segmentation sample data, the kelp 3D model segmentation sample coordinate data and the measurement tool in the mechanical 3D design software to generate the kelp 3D model segmentation sample belt body thickness measurement. body thickness data; a kelp three-dimensional model segmentation sample thickness parameter partitioning unit, which performs numerical partitioning processing of the kelp three-dimensional model segmentation sample strip body thickness according to the kelp three-dimensional model segmentation sample strip body thickness data, and constructs a kelp three-dimensional model segmentation sample strip body thickness interval; a kelp three-dimensional model segmentation sample partitioning unit, which performs kelp partition three-dimensional model identification processing of the kelp partition drying according to the kelp three-dimensional model segmentation sample strip body thickness partition data and the kelp three-dimensional model segmentation sample data, and generates kelp partition drying identification three-dimensional model data; a kelp drying partition thickness mean value statistical unit, which performs statistical processing of the kelp partition body thickness mean of the kelp partition drying according to the kelp three-dimensional model segmentation sample strip body thickness partition data, and generates kelp partition drying strip body thickness mean data;

[0095] The kelp drying parameter analysis module includes a kelp heat pump drying stage characteristic information collection unit, a kelp standard heat pump drying parameter storage unit corresponding to different kelp partition thicknesses at different drying stages, and a kelp partition drying heat pump drying parameter matching unit;

[0096] a kelp heat pump drying stage characteristic information collection unit, which collects kelp heat pump drying stage characteristic text data through the kelp drying management platform; a kelp standard heat pump drying parameter storage unit corresponding to different kelp partition thicknesses at different drying stages, which is used to store kelp standard heat pump drying control data corresponding to different kelp partition thicknesses at different drying stages; a kelp partition drying heat pump drying parameter matching unit, which matches the zoned heat pump drying control parameters of kelp partition drying based on the mean value data of kelp partition drying strip thickness, the kelp heat pump drying stage characteristic text data, and the kelp standard heat pump drying control data corresponding to different kelp partition thicknesses at different drying stages, and generates kelp zone drying heat pump drying control data;

[0097] The kelp drying adjustment module includes a kelp partition drying adjustment parameter construction unit and a kelp partition drying adjustment unit;

[0098] The kelp zone drying adjustment parameter construction unit constructs the kelp zone drying adjustment data based on the heat pump drying control parameters of the kelp drying zone and the three-dimensional model information of the kelp drying zone combined with data processing; the kelp zone drying adjustment unit performs the kelp zone drying adjustment operation based on the kelp zone drying adjustment data combined with the kelp drying management platform.

[0099] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning, characterized in that: The method comprises the following steps: S1, collecting kelp three-dimensional model data; S2, performing kelp three-dimensional model sample segmentation processing to generate kelp three-dimensional model segmentation sample data and performing kelp three-dimensional model segmentation sample spatial coordinate collection processing to generate kelp three-dimensional model segmentation sample coordinate data; S3, measuring the thickness of the kelp three-dimensional model segmented sample, generating kelp three-dimensional model segmented sample strip thickness data and performing numerical partitioning processing on the kelp three-dimensional model segmented sample strip thickness, and constructing the kelp three-dimensional model segmented sample strip thickness interval; S4, performing zoning processing of the strip thickness parameter of the kelp three-dimensional model segmentation sample to generate kelp three-dimensional model segmentation sample strip thickness zoning data and performing kelp partition drying kelp partition 3D model identification processing based on the kelp three-dimensional model segmentation sample data to generate kelp partition drying identification 3D model data; S5, performing statistical processing on the mean values of the thickness of the kelp strips dried by the kelp zones to generate mean values of the thickness of the kelp strips dried by the kelp zones; S6. Collecting characteristic text data of the kelp heat pump drying stage; S7, performing zone heat pump drying control parameter matching processing for kelp zone drying, and generating kelp zone drying heat pump drying control data; S8. Construct the kelp partition drying adjustment data and execute the kelp partition drying adjustment operation.

2. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 1 is characterized in that: Said S1 comprises the following steps: S11, collect the 3D solid model information of the dried kelp online through a 3D laser scanner, and generate kelp 3D model data .

3. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 2 is characterized in that: The S2 comprises the following steps: S21, using the MarchingCubes three-dimensional grid partitioning algorithm to The corresponding kelp 3D model upper surface is segmented and processed into a triangular mesh to generate a kelp 3D model segmentation sample data set , wherein include ,in Indicates the kelp three-dimensional model segmentation sample data corresponding to kelp segmentation samples; S22, using the lower surface of the kelp three-dimensional model in step S21 as the base surface to establish a spatial rectangular coordinate system, and measuring the sample numbers in order according to the segmentation of the kelp three-dimensional model. As stated in The corresponding spatial coordinate parameters of the center point of the kelp segmentation sample three-dimensional model, and generate the kelp three-dimensional model segmentation sample coordinate data set , wherein include ,in Indicates the The coordinate data of the kelp three-dimensional model segmentation samples corresponding to the kelp segmentation samples.

4. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 3 is characterized in that: The S3 includes the following steps: S31, the generated Import into the mechanical 3D design software and run it. The mechanical 3D design software will As stated in Combined with measurement tools As stated in The thickness of the corresponding kelp segmentation sample strip at the center point of the three-dimensional model is measured, and a data set of the kelp three-dimensional model segmentation sample strip thickness is generated. , include ,in Indicates the The thickness data of the kelp three-dimensional model segmentation sample corresponding to the kelp segmentation sample, The unit is millimeter; S32, using a unified cost search algorithm to As stated in Compare the belt thickness values and search for the one with the largest belt thickness value. and the minimum value of the belt thickness , and generate the maximum thickness of the kelp three-dimensional model segmentation sample after data identification Minimum thickness of the kelp 3D model segmentation sample ,in and The unit is millimeter; S33, based on the As stated in Perform statistical processing on the mean thickness of the strip to generate the mean thickness of the strip of the kelp three-dimensional model segmentation sample ,in The unit is millimeter; S34, according to 、 、 Perform the value interval partitioning of the kelp three-dimensional model segmentation sample strip thickness, and construct the kelp three-dimensional model segmentation sample strip thickness interval set ,in Indicates the thickness interval of the kelp three-dimensional model segmentation sample corresponding to the first kelp drying partition, ; Indicates the thickness interval of the kelp three-dimensional model segmentation sample corresponding to the second kelp drying partition, .

5. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 4 is characterized in that: The S4 comprises the following steps: S41, the All of the above With the Internal description As stated in 、 , and the As stated in and stated Compare the thickness of the strip and compare the thickness of the strip. All of the above As described As stated in and stated Performing the zoning and screening of the strip thickness parameters of the kelp three-dimensional model segmentation sample, and generating the kelp three-dimensional model segmentation sample strip thickness partition data set matrix ,in Indicates that the As stated in According to the thickness of the belt, the following values are selected: As stated in The formation of The kelp three-dimensional model segmentation sample belt thickness partition data set corresponding to the kelp drying partition; Indicates that the As stated in According to the thickness of the belt, the following values are selected: As stated in The formed kelp three-dimensional model segmentation sample strip thickness partition data set corresponding to the second kelp drying partition; S42, using a bidirectional iterative search algorithm according to the As stated in and stated The kelp segmentation sample number corresponding to the kelp three-dimensional model segmentation sample belt thickness partition data is As stated in The corresponding kelp segmentation sample 3D model is partitioned and screened, and the two kelp segmentation sample 3D model sets after partitioning are colored with different colors by combining the coloring tool in the mechanical 3D design software, and a kelp partition drying mark 3D model data set is generated. ,in Indicates the As stated in As described The kelp segmentation sample number corresponding to the kelp three-dimensional model segmentation sample body thickness partition data is subjected to kelp segmentation sample three-dimensional model partition screening and coloring processing to form kelp partition drying identification three-dimensional model data corresponding to the first kelp drying partition; Indicates the As stated in As described The kelp segmentation sample number corresponding to the kelp body thickness partition data of the kelp 3D model segmentation sample is subjected to kelp segmentation sample 3D model partition screening and coloring processing to form kelp partition drying identification 3D model data corresponding to the second kelp drying partition.

6. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 5 is characterized in that: The S5 comprises the following steps: S51, the As stated in The three-dimensional model of kelp is segmented into sample strip thickness partition data, and the The three-dimensional model of the kelp sample strip thickness partition data is respectively measured according to the mean measurement formula in step S33 to obtain the The three-dimensional model of kelp is segmented into sample strip thickness partition data, and the The kelp three-dimensional model segmentation sample strip thickness partition data corresponding to the kelp three-dimensional model segmentation sample strip thickness parameter partition mean strip thickness, and generate the kelp partition drying strip thickness mean data set ,in Indicates the The corresponding mean thickness data of the kelp drying zone in the first kelp drying zone, Indicates the The corresponding mean thickness data of the kelp drying zone of the second kelp drying zone, where and The units are all millimeters.

7. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 6 is characterized in that: The S6 comprises the following steps: S61. Collect the characteristic information of the heat pump drying stage of the kelp being dried online through the kelp drying management platform, and generate the characteristic text data of the kelp heat pump drying stage. .

8. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 7 is characterized in that: The S7 comprises the following steps: S71. Establishing a standard heat pump drying control data set for kelp at different drying stages and corresponding to different kelp partition thicknesses , include ,in Indicates the The different drying stages and different kelp partition thicknesses corresponding to the kelp drying characteristic combination types correspond to the standard heat pump drying control data of kelp; S72, using the Aho-Corasick search algorithm to As stated in and stated Combined with the above With the As stated in Carry out the character matching of the mean thickness of the kelp heat pump drying stage and the kelp partition drying belt body, and search for the and stated , and the and stated The corresponding , and generate kelp partition drying heat pump drying control data set through data identification ,in Indicates the The corresponding kelp drying zone heat pump drying control data of the first kelp drying zone; wherein Indicates the The corresponding kelp zone drying heat pump drying control data of the second kelp drying zone.

9. The multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to claim 8, characterized in that: The S8 comprises the following steps: S81, the As stated in to and stated As stated in to Data combination identification is performed according to the kelp drying partition number to construct the kelp partition drying adjustment data set ,in Indicates the kelp drying adjustment data corresponding to the first kelp drying zone. ; Indicates the kelp drying adjustment data corresponding to the second kelp drying zone. ; S82, kelp drying management platform according to As stated in to The heat pump drying control parameters of the corresponding kelp drying zones adjust the air flow temperature and air flow velocity of the heat pump drying system, and perform the kelp drying operation in zones based on the three-dimensional model information of the kelp drying zones.

10. A multi-stage intelligent energy-saving temperature-controlled drying system for kelp based on dynamic partitioning, used to implement the multi-stage intelligent energy-saving temperature-controlled drying method for kelp based on dynamic partitioning according to any one of claims 1 to 9, characterized in that: The system includes a kelp drying zoning module, a kelp drying parameter analysis module, and a kelp drying adjustment module.

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